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Objective To develop in vitro fertilization (IVF) prediction models to estimate the individualized chance of cumulative live birth at two time points: pretreatment (i.e., before starting the first complete cycle of IVF) and posttreatment (i.e., before starting the second complete cycle of IVF in those couples whose first complete cycle was unsuccessful). Design Population-based cohort study. Setting National data from the Society for Assisted Reproductive Technology (SART) Clinic Outcome Reporting System. Patient(s) Based on 88,614 women who commenced IVF treatment using their own eggs and partner’s sperm in SART member clinics. Intervention(s) Not applicable. Main Outcome Measure(s) The pretreatment model estimated the cumulative chance of a live birth over a maximum of three complete cycles of IVF, whereas the posttreatment model did so over the second and third complete cycles. One complete cycle included all fresh and frozen embryo transfers resulting from one episode of ovarian stimulation. We considered the first live birth episode, including singletons and multiple births. Result(s) Pretreatment predictors included woman’s age (35 years vs. 25 years, adjusted odds ratio 0.69, 95% confidence interval 0.66–0.73) and body mass index (35 kg/m2 vs. 25 kg/m2, adjusted odds ratio 0.75, 95% confidence interval 0.72–0.78). The posttreatment model additionally included the number of eggs from the first complete cycle (15 vs. 9 eggs, adjusted odds ratio 1.10, 95% confidence interval 1.03–1.18). According to the pretreatment model, a nulliparous woman aged 34 years with a body mass index of 23.3 kg/m2, male partner infertility, and an antimullerian hormone level of 3 ng/mL has a 61.7% chance of having a live birth over her first complete cycle of IVF (and a cumulative chance over three complete cycles of 88.8%). If a live birth is not achieved, according to the posttreatment model, her chance of having a live birth over the second complete cycle 1 year later (age 35 years, number of eggs 7) is 42.9%. The C-statistic for all models was between 0.71 and 0.73. Conclusion(s) The focus of previous IVF prediction models based on US data has been cumulative live birth excluding cycles involving frozen embryos. These novel prediction models provide clinically relevant estimates that could help clinicians and couples plan IVF treatment at different points in time.

STUDY QUESTIONAre perinatal outcomes following fresh blastocyst versus fresh cleavage stage embryo transfer (ET) different in singletons, twins, and between singleton siblings?SUMMARY ANSWERSingleton babies conceived following fresh blastocyst, versus cleavage stage, ET are less likely to be small for gestational age (SGA) or to have a congenital anomaly (a result confirmed by comparing singleton siblings), while singletons born following fresh blastocyst ET were at a higher risk of being large for gestational age (LGA) than their sibling born following fresh cleavage stage ET.WHAT IS KNOWN ALREADYBlastocyst stage transfer is now the preferred strategy in most IVF units. Previous studies have suggested that babies conceived through blastocyst transfer are at increased risk of preterm birth and LGA.STUDY DESIGN, SIZE, DURATIONA national population-based retrospective cohort study was performed using linked Human Fertilisation and Embryology Authority (HFEA) data on 130 516 IVF and ICSI livebirths occurring from 103 062 women between 2000 and 2017.PARTICIPANTS/MATERIALS, SETTING, METHODSWe included women who had at least one singleton livebirth resulting from IVF/ICSI fresh embryo treatment, using their own eggs and partner’s sperm. A linked HFEA dataset was analysed using a multilevel framework, which accommodated repeated IVF cycles resulting in livebirths in the same woman. A population-averaged robust Poisson model was used for binary outcomes and a multinomial logistic regression model was used for categorical outcomes. Unadjusted and adjusted risk ratios (aRRs) (95% CI) were calculated.MAIN RESULTS AND THE ROLE OF CHANCEThere were 130 516 livebirths in 103 062 women, including 86 630 singletons, 43 886 twin births, and 5384 pairs of singleton siblings. In comparison with fresh cleavage stage ET, fresh blastocyst stage transfer in singletons was associated with a lower risk of low birthweight (aRR = 0.92; 95% CI 0.86, 0.99), lower risk of being SGA (0.83; 0.78, 0.89), and lower risk of congenital anomaly (0.79; 0.71, 0.89). This analysis did not show an increase in risk associated with preterm birth (1.00; 0.94, 1.06), high birthweight (0.99; 0.93, 1.06), LGA (0.99; 0.93, 1.05), and the chance of healthy singleton baby (1.00; 1.00, 1.02). Twins resulting from fresh blastocyst stage ET were at slightly higher risk of preterm birth (1.05; 1.02, 1.10) compared with twins conceived following fresh cleavage stage ET. There was insufficient evidence for an association with the other perinatal outcomes. Singleton siblings born following fresh blastocyst stage ET were at a higher risk of being LGA (1.57; 1.01, 2.46) and at lower risk of having a congenital anomaly (0.52; 0.28, 0.97) compared to their singleton siblings born following cleavage stage ET. There was some evidence of excess risk of preterm birth (1.42; 0.97, 2.23) associated with blastocyst stage transfer. However, we could not confirm an association between blastocyst stage ET and low birthweight (1.35; 0.81, 2.27), high birthweight (1.19; 0.80, 1.77), and the chance of being a healthy baby (0.97; 0.86, 1.09).LIMITATIONS, REASONS FOR CAUTIONThis was an observational study where we were unable to adjust for some key confounders, such as maternal smoking status and BMI, which may change from one pregnancy to another and are not recorded in the HFEA dataset.WIDER IMPLICATIONS OF THE FINDINGSIn the largest study of its kind, our analysis of singleton siblings, corrected for unmeasured, non-time varying maternal factors, confirms the previously reported association between blastocyst transfer and LGA babies, and shows a reduced risk of congenital anomaly following blastocyst transfer. Our sibling analysis did not confirm a decreased risk of low birthweight following blastocyst transfer. Overall, absolute risks are low and there is insufficient evidence to challenge the practice of extended culture of embryos.STUDY FUNDING/COMPETING INTEREST(S)This project is financed by an NHS Grampian Endowment Research Grant, project number 17/052. One of the authors, S.B., was the Editor in Chief of HROpen until 31 December 2022 and would have been in that role when the paper was first submitted. As an invited speaker, S.B. has received travel expenses, accommodation and honoraria from Merck, Organon, and Ferring. A.M. has received travel expenses, accommodation, and honoraria from Merck Serono, Cook Medical, Pharmasure, Gedeon Richter, and Ferring. D.J.M. is currently a HROpen Associate Editor.TRIAL REGISTRATION NUMBERN/A.

Purpose Existing research hints that people living with and beyond cancer are at an increased risk of stroke. However, there is insufficient evidence to appropriately inform guidelines for specific stroke prevention or management for cancer patients. We conducted a systematic review and meta-analysis to describe and quantify stroke incidence in people living with and beyond cancer. Methods Medline, CINAHL, and EMBASE were searched for epidemiological studies comparing stroke incidence between cancer and non-cancer patients. Reviewers independently extracted data; random-effects meta-analyses and quality assessment were performed. Results Thirty-six studies were narratively synthesised. Meta-analysis was conducted using seven studies. Methodological quality was high for most studies. Study populations were heterogeneous, and the length of follow-up and risk factors varied. There was a variation in risk between different cancer types and according to stroke type: pancreatic (HR 2.85 (95% CI 2.43–3.36), ischaemic) (HR 2.28 (95% CI 1.43–3.63), haemorrhagic); lung (HR 2.33 (95% CI 1.63–3.35), ischaemic) (HR 2.14 (95% CI 1.45–3.15), haemorrhagic); and head and neck (HR 1.54 (95% CI 1.40–1.69), haemorrhagic) cancers were associated with significantly increased incidence of stroke. Risk is highest within the first 6 months of diagnosis. Narrative synthesis indicated that several studies also showed significantly increased incidence of stroke in individuals with colorectal cancer, breast cancer, ovarian cancer, nasopharyngeal cancer, leukaemia, and myeloma, and those who have received radiotherapy for head and neck cancers and platinum-based chemotherapy may also have higher stroke incidence. Conclusions Stroke incidence is significantly increased after diagnosis of certain cancers. Implications for Cancer Survivors Cardiovascular risk should be assessed during cancer survivorship care, with attention to modifying shared cancer/cardiovascular risk factors.

Introduction With increasing caesarean section (c-section) rates, personalized communication of risk has become paramount. A reliable tool to predict complications would support evidence-based discussions around planned mode of birth. This systematic review aimed to identify, synthesize and quality appraise prognostic models of maternal complications of elective c-section. Methods MEDLINE, Embase, Web of Science, CINAHL and the Cochrane Library were searched on 27 January using terms relating to ‘c-section’, ‘prognostic models’ and complications such as ‘infection’. Any study developing and/or validating a prognostic model for a maternal complication of elective c-section in the English language after January 1995 was selected for analysis. Data were extracted using a predetermined checklist: source of data; participants; outcome to be predicted; candidate predictors; sample size; missing data; model development; model performance; model evaluation; results; and interpretation. Quality was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST) tool. Results In total, 7752 studies were identified; of these, 16 full papers were reviewed and three eligible studies were identified, containing three prognostic models derived from hospitals in Japan, South Africa and the UK. The models predicted risk of blood transfusion, spinal hypotension and postpartum haemorrhage. The study authors deemed their studies to be exploratory, exploratory and confirmatory, respectively. From the three studies, a total of 29 unique candidate predictors were identified, with 15 predictors in the final models. Maternal age (n = 3), previous c-section (n = 2), placenta praevia (n = 2) and pre-operative haemoglobin (n = 2) were found to be common predictors amongst the included studies. None of the studies were externally validated and all had a high risk of bias due to the analysis technique used. Conclusion Few models have been developed to predict complications of elective c-section. Existing models predicting blood transfusion, spinal hypotension and postpartum haemorrhage cannot be recommended for clinical practice. Future research should focus on identifying predictors known before surgery and validating the resulting models.

Rationale & Objective There is limited evidence to guide follow-up after acute kidney injury (AKI). Knowledge gaps include which patients to prioritize, at what time point, and for mitigation of which outcomes. In this study, we sought to compare the net benefit of risk model–based clinical decisions following AKI. Study Design External validation of 2 risk models of AKI outcomes: the Grampian -Aberdeen (United Kingdom) AKI readmissions model and the Alberta (Canada) kidney disease risk model of chronic kidney disease (CKD) glomerular (G) filtration rate categories 4 and 5 (CKD G4 and G5). Process mining to delineate existing care pathways. Setting & Participants Validation was based on data from adult hospital survivors of AKI from Grampian, 2011-2013. Predictors KDIGO-based measures of AKI severity and comorbidities specified in the original models. Outcomes Death or readmission within 90 days for all hospital survivors. Progression to new CKD G4-G5 for patients surviving at least 90 days after AKI. Analytical Approach Decision curve analysis to assess the “net benefit” of use of risk models to guide clinical care compared to alternative approaches (eg, prioritizing all AKI, severe AKI, or only those without kidney recovery). Results 26,575 of 105,461 hospital survivors in Grampian (mean age, 60.9 ± 19.8 [SD] years) were included for validation of the death or readmission model, and 9,382 patients (mean age, 60.9 ± 19.8 years) for the CKD G4-G5 model. Both models discriminated well (area under the curve [AUC], 0.77 and 0.86, respectively). Decision curve analysis showed greater net benefit for follow up of all AKI than only severe AKI in most cases. Both original and refitted models provided net benefit superior to any other decision strategy. In process mining of all hospital discharges, 41% of readmissions and deaths occurred among people recovering after AKI. 1,464 of 3,776 people (39%) readmitted after AKI had received no intervening monitoring. Limitations Both original models overstated risks, indicating a need for regular updating. Conclusions Follow up after AKI has potential net benefit for preempting readmissions, death, and subsequent CKD progression. Decisions could be improved by using risk models and by focusing on AKI across a full spectrum of severity. The current lack of monitoring among many with poor outcomes indicates possible opportunities for implementation of decision support.

STUDY QUESTION Can we develop an IVF prediction model to estimate individualized chances of a live birth over multiple complete cycles of IVF in couples embarking on their second complete cycle of treatment? SUMMARY ANSWER Yes, our prediction model can estimate individualized chances of cumulative live birth over three additional complete cycles of IVF. WHAT IS KNOWN ALREADY After the completion of a first complete cycle of IVF, couples who are unsuccessful may choose to undergo further treatment to have their first child, while those who have had a live birth may decide to have more children. Existing prediction models can estimate the overall chances of success in couples before commencing IVF but are unable to revise these chances on the basis of the couple’s response to a first treatment cycle in terms of the number of eggs retrieved and pregnancy outcome. This makes it difficult for couples to plan and prepare emotionally and financially for the next step in their treatment. STUDY DESIGN, SIZE, DURATION For model development, a population-based cohort was used of 49 314 women who started their second cycle of IVF including ICSI in the UK from 1999 to 2008 using their own oocytes and their partners’ sperm. External validation was performed on data from 39 442 women who underwent their second cycle from 2010 to 2016. PARTICIPANTS/MATERIALS, SETTING, METHODS Data about all UK IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA) database. Using a discrete time logistic regression model, we predicted the cumulative probability of live birth from the second up to and including the fourth complete cycles of IVF. Inverse probability weighting was used to account for treatment discontinuation. Discrimination was assessed using c-statistic and calibration was assessed using calibration-in-the-large and calibration slope. MAIN RESULTS AND THE ROLE OF CHANCE Following exclusions, 49 314 women with 73 053 complete cycles were included. 12 408 (25.2%) had a live birth resulting from their second complete cycle. Cumulatively, 17 394 (35.3%) had a live birth over complete cycles two to four. The model showed moderate discriminative ability (c-statistic: 0.65, 95% CI: 0.64 to 0.65) and evidence of overprediction (calibration-in-the-large = −0.08) and overfitting (calibration slope 0.85, 95% CI: 0.81 to 0.88) in the validation cohort. However, after recalibration the fit was much improved. The recalibrated model identified the following key predictors of live birth: female age (38 versus 32 years—adjusted odds ratio: 0.59, 95% CI: 0.57 to 0.62), number of eggs retrieved in the first complete cycle (12 versus 4 eggs; 1.34, 1.30 to 1.37) and outcome of the first complete cycle (live birth versus no pregnancy; 1.78, 1.66 to 1.91; live birth versus pregnancy loss; 1.29, 1.23 to 1.36). As an example, a 32-year-old with 2 years of non-tubal infertility who had 12 eggs retrieved from her first stimulation and had a live birth during her first complete cycle has a 46% chance of having a further live birth from the second complete cycle of IVF and an 81% chance over a further three cycles. LIMITATIONS, REASONS FOR CAUTION The developed model was updated using validation data that was 6 to 12 years old. IVF practice continues to evolve over time, which may affect the accuracy of predictions from the model. We were unable to adjust for some potentially important predictors, e.g. BMI, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count. These were not available in the linked HFEA dataset. WIDER IMPLICATIONS OF THE FINDINGS By appropriately adjusting for couples who discontinue treatment, our novel prediction model will provide more realistic chances of live birth in couples starting a second complete cycle of IVF. Clinicians can use these predictions to inform discussion with couples who wish to plan ahead. This prediction tool will enable couples to prepare emotionally, financially and logistically for IVF treatment. STUDY FUNDING/COMPETING INTEREST(S) This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. The authors have no conflict of interest. TRIAL REGISTRATION NUMBER N/A.

IntroductionExisting randomised controlled trials (RCTs) comparing a freeze-all embryo transfer strategy and a fresh embryo transfer strategy have shown conflicting results. A freeze-all or a fresh transfer policy may be preferable for some couples undergoing in-vitro fertilisation (IVF), but it is unclear which couples would benefit most from each policy, how and under which protocols. Therefore, we plan a systematic review and individual participant data meta-analysis of RCTs comparing a freeze-all and a fresh transfer policy.Methods and analysisWe will search electronic databases (Medline, Embase, PsycINFO and CENTRAL) and trial registries (ClinicalTrials.gov and the International Clinical Trials Registry Platform) from their inception to present to identify eligible RCTs. We will also check reference lists of relevant papers. The search was performed on 23 September 2020 and will be updated. We will include RCTs comparing a freeze-all embryo transfer strategy and a fresh embryo transfer strategy in couples undergoing IVF. The primary outcome will be live birth resulting from the first embryo transfer. All outcomes listed in the core outcome set for infertility research will be reported. We will invite the lead investigators of eligible trials to join the Individual participant data meta-analysis of trials comparing frozen versus fresh embryo transfer strategy (INFORM) collaboration and share the deidentified individual participant data (IPD) of their trials. We will harmonise the IPD and perform a two-stage meta-analysis and examine treatment–covariate interactions for important baseline characteristics.Ethics and disseminationThe study ethics have been granted by the Monash University Human Research Ethics Committee (Project ID: 30391). The findings will be disseminated via presentations at international conferences and publication in peer-reviewed journals.PROSPERO registration numberCRD42021296566.

STUDY QUESTION Can we use prediction modelling to estimate the impact of coronavirus disease 2019 (COVID 19) related delay in starting IVF or ICSI in different groups of women? SUMMARY ANSWER Yes, using a combination of three different models we can predict the impact of delaying access to treatment by 6 and 12 months on the probability of conception leading to live birth in women of different age groups with different categories of infertility. WHAT IS KNOWN ALREADY Increased age and duration of infertility can prejudice the chances of success following IVF, but couples with unexplained infertility have a chance of conceiving naturally without treatment whilst waiting for IVF. The worldwide suspension of IVF could lead to worse outcomes in couples awaiting treatment, but it is unclear to what extent this could affect individual couples based on age and cause of infertility. STUDY DESIGN, SIZE, DURATION A population-based cohort study based on national data from all licensed clinics in the UK obtained from the Human Fertilisation and Embryology Authority Register. Linked data from 9589 women who underwent their first IVF or ICSI treatment in 2017 and consented to the use of their data for research were used to predict livebirth. PARTICIPANTS/MATERIALS, SETTING, METHODS Three prediction models were used to estimate the chances of livebirth associated with immediate treatment versus a delay of 6 and 12 months in couples about to embark on IVF or ICSI. MAIN RESULTS AND THE ROLE OF CHANCE We estimated that a 6-month delay would reduce IVF livebirths by 0.4%, 2.4%, 5.6%, 9.5% and 11.8% in women aged LIMITATIONS, REASONS FOR CAUTION Major sources of uncertainty include the use of prediction models generated in different populations and the need for a number of assumptions. Although the models are validated and the bases for the assumptions are robust, it is impossible to eliminate the possibility of imprecision in our predictions. Therefore, our predicted live birth rates need to be validated in prospective studies to confirm their accuracy. WIDER IMPLICATIONS OF THE FINDINGS A delay in starting IVF reduces success rates in all couples. For the first time, we have shown that while this results in fewer babies in older women and those with a known cause of infertility, it has a less detrimental effect on couples with unexplained infertility, some of whom conceive naturally whilst waiting for treatment. Post-COVID 19, clinics planning a phased return to normal clinical services should prioritize older women and those with a known cause of infertility. STUDY FUNDING/COMPETING INTEREST(S) No external funding was received for this study. B.W.M. is supported by an NHMRC Practitioner Fellowship (GNT1082548) and reports consultancy work for ObsEva, Merck, Merck KGaA, Guerbet and iGenomics. S.B. is Editor-in-Chief of Human Reproduction Open. None of the other authors declare any conflicts of interest. TRIAL REGISTRATION NUMBER N/A.

Purpose: This study aimed to evaluate the outcomes of juxtapapillary choroidal melanomas treated with notched ruthenium-106 plaques. Methods: Juxtapapillary choroidal melanomas (tumours within 2 disc diameters from the optic disc) treated with notched ruthenium-106 plaques (Eckert & Ziegler, BEBIG, Berlin, Germany) at the Scottish Ocular Oncology Service between 2009 and 2015 were retrospectively reviewed. The data were analysed with respect to various outcome measures including recurrence, complications, vision, and eye preservation. Results: We reviewed 40 patients with a median tumour diameter of 8.4 mm (range 5–17 mm) and a median thickness of 2.5 mm (range 1.1–6 mm). AJCC tumour category distribution was 62.5% T1, 32.5% T2, and 5% T3 tumours. The mean presenting vision was 0.3 logMAR, and the mean final vision was 0.7 logMAR, with 62.5% retaining >1.0 logMAR and 50% retaining >0.3 logMAR at the final follow-up. The median follow-up was 51 months (14–100 months). Over the maximum follow-up time, 13 tumours (32.5%) recurred. Six of these were treated with salvage proton beam therapy (PBT), 2 with transpupillary thermotherapy followed by PBT, and 5 with enucleation. The final eye retention rate was 87.5%. Complications included maculopathy (10%), retinal detachment (5%), neovascular glaucoma (2.5%), and diplopia (2.5%). The observed risk of recurrence over 5 years was 31% (95% CI: 14.1%, 47.8%), and the risk of enucleation over 5 years was 11.5% (95% CI: 0.9%, 21.8%). Conclusion: Juxtapapillary choroidal melanomas treated with notched ruthenium plaques have a high recurrence rate and frequently need salvage treatment with PBT for tumour control. This has led to a change in our practice toward offering PBT as the first-line treatment for these patients.

Background Postpartum haemorrhage (PPH) causes substantial morbidity and mortality worldwide. A reliable prognostic tool for PPH has potential to aid prevention efforts. Objective Systematically to identify and appraise prognostic modelling studies for prediction of PPH. Search strategy MEDLINE, Embase, CINAHL and the Cochrane Library were searched using a combination of terms and synonyms including 'prediction tool', 'risk score' and 'postpartum haemorrhage'. Selection criteria Any observational or experimental study developing a prognostic model for women's risk of PPH. English language publications. Data collection and analysis Predesigned data extraction form to record: data source; participant criteria; outcome; candidate predictors; actual predictors; sample size; missing data; model development; model performance; model evaluation; interpretation. Main results Of 2146 citations screened, 14 studies were eligible for inclusion. Studies addressed populations of women who experienced placenta praevia, placenta accreta spectrum, vaginal birth, caesarean birth (CS) and the general obstetric population. All studies were at high risk of bias due to low sample size, no internal validation, suboptimal or no external validation or no reporting or handling of missing data. Five studies raised applicability concerns. Three externally validated and three internally validated studies show potential for robust external validation. Conclusion Of 14 prognostic models for PPH risk, three have some potential for clinical use: in CS, in placenta accreta spectrum disorders with MRI placental Evaluation and in placenta praevia. Future research requires robust internal and external validation of existing tools and development of a model for use in the general obstetric population. Tweetable abstract Current PPH prediction tools need external validation: one for CS, one for placenta praevia and one for placenta accreta. Tools are needed for labouring women.

STUDY QUESTION What is the rate of natural conception leading to ongoing pregnancy or livebirth over 6–12 months for infertile women of age ≥35 years? SUMMARY ANSWER Natural conception rates were still clinically relevant in women aged 35 years and above and were significantly higher in women with unexplained infertility compared to those with other diagnoses. WHAT IS KNOWN ALREADY In recent years, increasing numbers of women have attempted to conceive at a later age, resulting in a commensurate increase in the need for ART. However, there is a lack of data on natural fertility outcomes (i.e. no interventions) in women with increasing age. STUDY DESIGN, SIZE, DURATION A systematic review with individual participant data (IPD) meta-analysis was carried out. PubMed, MEDLINE, EMBASE, the Cochrane Library, clinicaltrials.gov were searched until 1 July 2018 including search terms ‘fertility service’, ‘waiting list’, ‘treatment-independent’ and ‘spontaneous conception’. Language restrictions were not imposed. PARTICIPANTS/MATERIALS, SETTING, METHODS Inclusion criteria were studies (at least partly) reporting on infertile couples with female partner of age ≥35 years who attended fertility services, underwent fertility workup (e.g. history, semen analysis, tubal status and ovulation status) and were exposed to natural conception (e.g. independent of treatment such as IVF, ovulation induction and tubal surgery). Studies that exclusively studied only one infertility diagnosis, without including other women presenting to infertility services for other causes of infertility, were excluded. For studies that met the inclusion criteria, study authors were contacted to provide IPD, after which fertility outcomes for women of age ≥35 years were retrieved. Time to pregnancy or livebirth and the effect of increasing age on fertility outcomes after adjustment for other prognostic factors were analysed. Quality of studies was graded with the Newcastle–Ottawa Scale (non-randomised controlled trials (RCTs)) or the Cochrane Risk of Bias tool (for RCTs). MAIN RESULTS AND THE ROLE OF CHANCE We included nine studies (seven cohort studies and two RCTs) (n = 4379 women of at least age 35 years), with the observed composite primary outcome of ongoing pregnancy or livebirth occurring in 429 women (9.8%) over a median follow-up of 5 months (25th to 75th percentile: 2.5–8.5 months). Studies were of moderate to high quality. The probability of natural conception significantly decreased with any diagnosis of infertility, when compared with unexplained infertility. We found non-linear effects of female age and duration of infertility on ongoing pregnancy and tabulated the predicted probabilities for unexplained infertile women aged 35–42 years with either primary or secondary infertility and with a duration of infertility from 1 to 6 years. For a 35-year-old woman with 2 years of primary unexplained infertility, the predicted probability of natural conception leading to ongoing pregnancy or livebirth was 0.15 (95% CI 0.11–0.19) after 6 months and 0.24 (95% CI 0.17–0.30) after 12 months. For a 42-year-old woman, this decreased to 0.08 (95% CI 0.04–0.11) after 6 months and 0.13 (95% CI 0.07–0.18) after 12 months. LIMITATIONS, REASONS FOR CAUTION In the studies selected, there were different study designs, recruitment strategies in different centres, protocols and countries and different methods of assessment of infertility. Data were limited for women above the age of 40 years. WIDER IMPLICATIONS OF THE FINDINGS Women attending fertility services should be encouraged to pursue natural conception while waiting for treatment to commence and after treatment if it is unsuccessful. Our results may aid in counselling women, and, in particular, for those with unexplained infertility. STUDY FUNDING/COMPETING INTEREST(S) S.J.C. received funding from the University of Adelaide Summer Research Scholarship. B.W.M. is supported by a NHMRC Investigator grant (GNT1176437), B.W.M. reports consultancy for ObsEva, Merck, Merck KGaA, iGenomix and Guerbet. B.W.M. reports research support by Merck and Guerbet. PROSPERO REGISTRATION NUMBER CRD42018096552.

The treatment of unexplained infertility is a contentious topic that continues to attract a great deal of interest amongst clinicians, patients and policy makers. The inability to identify an underlying pathology makes it difficult to devise effective treatments for this condition. Couples with unexplained infertility can conceive on their own and any proposed intervention needs to offer a better chance of having a baby. Over the years, several prognostic and prediction models based on routinely collected clinical data have been developed, but these are not widely used by clinicians and patients. In this opinion paper, we propose a prognosis-based approach such that a decision to access treatment is based on the estimated chances of natural and treatment-related conception, which, in the same couple, can change over time. This approach avoids treating all couples as a homogeneous group and minimizes unnecessary treatment whilst ensuring access to those who need it early.

To study the association of donor sperm on perinatal outcomes of livebirths conceived via in vitro fertilization (IVF) when compared with partner sperm.Retrospective cohort study SETTING: National Human Fertilisation and Embryology Authority assisted reproductive technology registry PATIENTS: All live born singletons and twins conceived through IVF with or without intracytoplasmic sperm injection in the United Kingdom between 1991 and 2016 INTERVENTION(S): Donor sperm compared to partner sperm MAIN OUTCOME MEASURE(S): Perinatal outcomes were assessed. The primary outcomes were preterm and very preterm birth; low, very low, high, and very high birthweight; Secondary outcomes were congenital anomaly and health baby. These were assessed for singletons and twins separately.For singleton livebirths, compared to partner sperm, those conceived with donor sperm were at reduced odds of very preterm (odds ratio [OR], 0.76; 95% confidence interval [CI], 0.63-0.91; adjusted OR [aOR], 0.80; 95% CI, 0.66-0.96), and preterm (OR, 0.90; 95% CI, 0.83-0.98; aOR, 0.93; 95% CI, 0.85-1.01) birth. For birthweight outcomes, donor sperm showed a reduced odds of low (OR, 0.83; 95% CI, 0.76-0.91; aOR, 0.86; 95% CI, 0.78-0.94) and an increased odds of high (OR, 1.15; 95% CI, 1.07-1.23; aOR, 1.09; 95% CI, 1.01-1.17) birthweight. There was no confirmed difference in the odds ratios of very low (OR, 0.88; 95% CI, 0.74-1.06; aOR, 0.94; 95% CI, 0.78-1.13) or very high (OR, 1.21; 95% CI, 1.04-1.40; aOR, 1.15; 95% CI, 0.98-1.34) birthweight. Liveborn twins conceived with donor sperm, compared to partner sperm, were at reduced odds of very low (OR, 0.76; 95% CI, 0.66-0.88; aOR, 0.83; 95% CI, 0.72-0.96) and low (OR, 0.87; 95% CI, 0.81-0.93; aOR, 0.91; 95% CI, 0.85-0.98) birthweight. There was a suggestion of a reduced odds of very preterm (OR, 0.81; 95% CI, 0.70-0.95; aOR, 0.86; 95% CI, 0.74-1.01) and preterm (OR, 0.93; 95% CI, 0.86-1.01; aOR, 0.96; 95% CI, 0.88-1.04) birth. There was considerable uncertainty around the ORs for high (OR, 0.73; 95% CI, 0.31-1.72; aOR, 0.72; 95% CI, 0.29-1.80) and very high (OR, 1.02; 95% CI, 0.39-2.67; aOR, 1.34; 95% CI, 0.50-3.60) birthweight.Although unmeasured confounding remains a possibility, as paternal age, body mass index, and smoking status were unavailable for analysis, women, couples, service providers can be reassured that IVF livebirths conceived with donor sperm have no greater chance of adverse outcomes when compared to partner sperm.

STUDY QUESTIONWhat are the best-quality clinical prediction models in IVF (including ICSI) treatment to inform clinicians and their patients of their chance of success?SUMMARY ANSWERThe review recommends the McLernon post-treatment model for predicting the cumulative chance of live birth over and up to six complete cycles of IVF.WHAT IS KNOWN ALREADYPrediction models in IVF have not found widespread use in routine clinical practice. This could be due to their limited predictive accuracy and clinical utility. A previous systematic review of IVF prediction models, published a decade ago and which has never been updated, did not assess the methodological quality of existing models nor provided recommendations for the best-quality models for use in clinical practice.STUDY DESIGN, SIZE, DURATIONThe electronic databases OVID MEDLINE, OVID EMBASE and Cochrane library were searched systematically for primary articles published from 1978 to January 2019 using search terms on the development and/or validation (internal and external) of models in predicting pregnancy or live birth. No language or any other restrictions were applied.PARTICIPANTS/MATERIALS, SETTING, METHODSThe PRISMA flowchart was used for the inclusion of studies after screening. All studies reporting on the development and/or validation of IVF prediction models were included. Articles reporting on women who had any treatment elements involving donor eggs or sperm and surrogacy were excluded. The CHARMS checklist was used to extract and critically appraise the methodological quality of the included articles. We evaluated models’ performance by assessing their c-statistics and plots of calibration in studies and assessed correct reporting by calculating the percentage of the TRIPOD 22 checklist items met in each study.MAIN RESULTS AND THE ROLE OF CHANCEWe identified 33 publications reporting on 35 prediction models. Seventeen articles had been published since the last systematic review. The quality of models has improved over time with regard to clinical relevance, methodological rigour and utility. The percentage of TRIPOD score for all included studies ranged from 29 to 95%, and the c-statistics of all externally validated studies ranged between 0.55 and 0.77. Most of the models predicted the chance of pregnancy/live birth for a single fresh cycle. Six models aimed to predict the chance of pregnancy/live birth per individual treatment cycle, and three predicted more clinically relevant outcomes such as cumulative pregnancy/live birth. The McLernon (pre- and post-treatment) models predict the cumulative chance of live birth over multiple complete cycles of IVF per woman where a complete cycle includes all fresh and frozen embryo transfers from the same episode of ovarian stimulation. McLernon models were developed using national UK data and had the highest TRIPOD score, and the post-treatment model performed best on external validation.LIMITATIONS, REASONS FOR CAUTIONTo assess the reporting quality of all included studies, we used the TRIPOD checklist, but many of the earlier IVF prediction models were developed and validated before the formal TRIPOD reporting was published in 2015. It should also be noted that two of the authors of this systematic review are authors of the McLernon model article. However, we feel we have conducted our review and made our recommendations using a fair and transparent systematic approach.WIDER IMPLICATIONS OF THE FINDINGSThis study provides a comprehensive picture of the evolving quality of IVF prediction models. Clinicians should use the most appropriate model to suit their patients’ needs. We recommend the McLernon post-treatment model as a counselling tool to inform couples of their predicted chance of success over and up to six complete cycles. However, it requires further external validation to assess applicability in countries with different IVF practices and policies.STUDY FUNDING/COMPETING INTEREST(S)The study was funded by the Elphinstone Scholarship Scheme and the Assisted Reproduction Unit, University of Aberdeen. Both D.J.M. and S.B. are authors of the McLernon model article and S.B. is Editor in Chief of Human Reproduction Open. They have completed and submitted the ICMJE forms for Disclosure of potential Conflicts of Interest. The other co-authors have no conflicts of interest to declare.REGISTRATION NUMBERN/A

Background and Purpose— We aimed to determine individual and combined effects of atrial fibrillation (AF) and heart failure (HF) on acute ischemic stroke outcomes: in-hospital mortality, length-of-stay, and poststroke disability; long-term mortality and stroke recurrence. Methods— Prospective cohort study of patients with acute ischemic stroke admitted to a UK center with a catchment population of ≈900 000 between 2004 and 2016. Exposure groups were patients with neither AF nor HF (reference group), those with AF but without HF, those with HF but without AF, and those with AF+HF. Logistic and Cox regressions were used to model in-hospital and long-term outcomes, respectively. Results— A total of 10 816 patients with a mean age±SD =77.9±12.1 years, 48% male were included. Only 30 (4.9%) of the patients with HF but not AF were anticoagulated at discharge. Both AF (odds ratio, 1.24 [95% CI, 1.07–1.43]), HF (odds ratio, 1.40 [1.10–1.79]), and their combination (odds ratio, 2.23 [1.83–2.72]) were associated with increased odds of in-hospital mortality. All 3 exposure groups were associated with increased length-of-stay, while only AF predicted increased disability (1.36 [1.12–1.64]). Patients were followed for a median of 5.5 and 3.7 years for mortality and recurrence, respectively. Long-term mortality was associated with AF (hazard ratio, 1.45 [95% CI, 1.33–1.59]), HF (2.07 [1.83–2.36]), and their combination (2.20 [1.96–2.46]). Recurrent stroke was associated with AF 1.50 (1.26–1.78), HF (1.33 [1.01–1.75]), and AF with HF (1.62 [1.28–2.07]). Conclusions— The AF-associated excess risk of stroke recurrence was independent of comorbid HF. HF without AF was also associated with a significant risk of recurrence. Anticoagulation for secondary stroke prevention in patients with HF without AF may require further evaluation in a clinical trial setting.

STUDY QUESTION Which couples with unexplained subfertility can expect increased chances of ongoing pregnancy with IVF compared to expectant management? SUMMARY ANSWER For couples in which the woman is under 40 years of age, IVF is associated with higher chances of conception than expectant management. WHAT IS KNOWN ALREADY The clinical indications for IVF have expanded over time from bilateral tubal blockage to include unexplained subfertility in which there is no identifiable barrier to conception. Yet, there is little evidence from randomized controlled trials that IVF is effective in these couples. STUDY DESIGN, SIZE, DURATION We compared outcomes in British couples with unexplained subfertility undergoing IVF (n = 40 921) from registry data to couples with the same type of subfertility on expectant management. Those couples on expectant management (defined as no intervention aside from the advice to have intercourse) comprised a prospective nation-wide Dutch cohort (n = 4875) and a retrospective regional cohort from Aberdeen, Scotland (n = 975). We excluded couples who had tried for PARTICIPANTS/MATERIALS, SETTING, METHODS We matched couples who received IVF and couples on expectant management based on their characteristics to control for confounding. We fitted a Cox proportional hazards model including patient characteristics, IVF treatment and their interactions to estimate the individualized chance of conception over 1 year—either following IVF or expectant management for all combinations of patient characteristics. The endpoint was conception leading to ongoing pregnancy, defined as a foetus reaching a gestational age of at least 12 weeks. MAIN RESULTS AND THE ROLE OF CHANCE The adjusted 1-year chance of conception was 47.9% (95% CI: 45.0–50.9) after IVF and 26.1% (95% CI: 24.2–28.0) after expectant management. The absolute difference in the average adjusted 1-year chances of conception was 21.8% (95%CI: 18.3–25.3) in favour of IVF. The effectiveness of IVF was influenced by female age, duration of subfertility and previous pregnancy. IVF was effective in women under 40 years, but the 1-year chance of an IVF conception declined sharply in women over 34 years. In contrast, in woman over 40 years of age, IVF was less effective, with an absolute difference in chance compared to expectant management of 10% or lower. Regardless of female age, IVF was also less effective in couples with a short period of secondary subfertility (1 year) who had chances of natural conception of 30% or above. LIMITATIONS, REASONS FOR CAUTION The 1-year chances of conception were based on three cohorts with different sampling mechanisms. Despite adjustment for the three most important prognostic patient characteristics, namely female age, duration of subfertility and primary or secondary subfertility, our estimates might not be free from residual confounding. WIDER IMPLICATIONS OF THE FINDINGS IVF should be used selectively based on judgements on gain compared to continuing expectant management for a given couple. Our results can be used by clinicians to counsel couples with unexplained subfertility, to inform their expectations and facilitate evidence-based, shared decision making. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by Tenovus Scotland [grant G17.04]. Travel for RvE was supported by the Amsterdam Reproduction & Development Research Group [grant V.000296]. SB reports acting as editor-in-chief of HROpen. Other authors have no conflicts.

To determine whether perinatal outcomes following frozen vs. fresh embryo transfer (ET) differ within singletons, within sets of twins, and between siblings.Population-based retrospective cohort study.Academic Medical School PATIENT(S): 200,075 live births in 151,561 women who underwent in vitro fertilization with frozen or fresh ET between 1992 and 2017.Gestational age at birth, birthweight, congenital anomaly, and healthy baby (≥37 weeks of gestation, birthweight 2,500-4,000 g, no congenital malformations).There were 200,075 live births in 151,561 women including 132,679 singletons, 33,698 sets of twins, and 5,723 pairs of singleton siblings. In singletons, frozen ET was associated with a lower risk of very preterm birth (adjusted relative risk [aRR], 0.83; 95% confidence interval [CI], 0.73, 0.94), preterm birth (aRR, 0.93; 95% CI, 0.88, 0.97), low birthweight (2,500 g) (aRR, 0.72; 95% CI, 0.68, 0.77), small for gestational age (aRR, 0.66; 95% CI, 0.62, 0.70) and congenital anomaly (aRR, 0.85; 95% CI, 0.78, 0.94), but higher risk of high birthweight (4,000 g) (aRR, 1.64; 95% CI, 1.58, 1.72) and large for gestational age (aRR, 1.62; 95% CI, 1.55, 1.70) in comparison with fresh ET. In twins, frozen ET was associated with lower risk of very preterm birth (aRR, 0.84; 95% CI, 0.73, 0.97), and low birthweight (aRR, 0.72; 95% CI, 0.68, 0.77), but with a higher chance of a healthy baby (aRR, 1.11; 95% CI, 1.06, 1.16) compared to fresh ET. Singletons conceived following frozen ET had a lower risk of low birthweight (aRR, 0.56; 95% CI, 0.44, 0.74) and being small for gestational age (aRR, 0.54; 95% CI, 0.42, 0.68) than a singleton sibling born after a fresh ET. Frozen ET also was associated with higher risk of high birthweight (aRR, 1.85; 95% CI, 1.54, 2.24) and being large for gestational age (aRR, 1.81; 95% CI, 1.50, 2.20), and also were less likely to be preterm (aRR, 0.81; 95% CI, 0.67, 0.99).Our key finding is that singletons born following a frozen ET are less likely to be small for gestational age than a singleton sibling born following fresh ET but are more likely to be large for gestational age.

Introduction With increasing caesarean section (c-section) rates, personalised communication of risk has become paramount. A reliable tool to predict complications would support evidence-based discussion around planned mode of birth. Method MEDLINE, Embase, Web of Science, CINAHL, and the Cochrane Library were searched on 27th January with the terms relating to c-section, prognostic models, and complications such as infection. Any study developing and/or validating a prognostic model for maternal complications of c-section in the English language after January 1995 was included. Data extracted encompassed: source of data, participant criteria, outcome to be predicted, candidate predictors, actual predictors, sample size, model development, and model performance. PROBAST (Prediction model Risk Of Bias Assessment Tool) was utilised for risk of bias analysis and applicability concern in the prognostic model studies. Result 7,752 studies were identified, of which 16 were reviewed producing 3 studies where 3 prognostic models were identified which predicted risk of: blood transfusion, spinal hypotension, and postpartum haemorrhage. From the 3 studies, a total of 29 unique candidate predictors were identified and 15 predictors in the final model. Study authors deemed their studies to be exploratory, exploratory, and confirmatory respectively. None were externally validated and all had a high risk of bias due to analysis technique. Conclusion Few models have been developed to predict complications of elective c-section. Existing models predicting blood transfusion, spinal hypotension, and postpartum haemorrhage cannot be recommended for clinical practice. Future research should focus on identifying predictors known before surgery and validating resulting models. Take-home Message Systematic review of prediction models for planned C-section complications found none suitable for practice.

Study question Are perinatal outcomes different in pregnancies conceived using donor sperm compared with those with partner sperm? Summary answer The perinatal outcomes of singleton and twin pregnancies conceived with donor sperm are better when compared to those conceived with partner sperm What is known already There has been a substantial increase in the use of donor sperm in the last 15 years across the world. A recent systematic review and meta-analysis has suggested that there is an increased risk of hypertensive disorders of pregnancy and small for gestational age babies from ART treatment using donor sperm compared to partner`s sperm. This meta-analysis was limited due to poor quality of primary studies often with small sample sizes. Study design, size, duration This is a retrospective cohort study on 196,293 singleton and 46,275 twin pregnancies from the Human Fertilisation and Embryology Authority (HFEA) anonymised dataset including all live births from 1991 to 2016. Outcomes were preterm birth ( < 37 weeks); very preterm birth ( < 32 weeks); very low, low, high and very high birth weight ( < 1500g, < 2500g, >4000g and >4500g respectively); congenital anomaly and healthy baby (term live birth with appropriate weight and no congenital anomaly). Participants/materials, setting, methods All pregnancies resulting in singleton or twin livebirth were included. Any cycle involving donor oocytes, PGD, gamete intra-fallopian transfer, ectopic pregnancy, miscarriage, stillbirth, or termination was excluded. Logistic regression and generalised estimating equations were used for analysis of singletons and twins, respectively. Odds ratios (aOR) with 95% confidence intervals (CI) for donor versus partner sperm were adjusted for maternal age, previous pregnancy, cause of infertility and year for all outcomes plus gestational age for birthweight. Main results and the role of chance Baseline characteristics for donor and partner sperm pregnancies were assessed for singleton and twin livebirths separately. In both analyses there were significant differences between donor and partner sperm pregnancies in terms of maternal age, previous pregnancy status and cause of infertility. Analysis of singleton births demonstrated an increased odds (aOR, 95% CI) of having a healthy baby (1.09, 1.05 - 1.12) and reduced odds of congenital anomaly (0.34, 0.29 - 0.39), very preterm birth (0.66, 0.58-0.75), preterm birth (0.81, 0.76-0.86), low birthweight 0.89 (0.83 - 0.96) in singleton births using donor sperm compared with those using partner sperm. There was, however, an increased odds of high birthweight (1.10, 1.05 - 1.16) and very high birthweight (1.16, 1.05-1.29) with donor sperm pregnancies. Analysis of twin births conceived with donor sperm also showed higher odds of having a healthy baby (1.07, 1.01 - 1.15) and lower odds of congenital anomaly (0.52, 0.39 - 0.68) compared with partner sperm. There were no statistically significant differences between the birthweight or birth gestation outcomes for twin pregnancies. Sensitivity analysis of only cases with complete outcome data showed no significant differences when compared to the primary analysis. Limitations, reasons for caution This is a retrospective study of a single nation’s routinely collected data. We could not adjust for confounders such as smoking, BMI and pregnancy complications such as pre-eclampsia, as they are not recorded in HFEA’s dataset. Wider implications of the findings Patients and clinicians can be reassured that donor sperm pregnancies are not at higher risk of adverse perinatal outcomes. In fact, they are more likely to result in a healthy baby. Worldwide registries should consider including maternal data to enable a better assessment of outcomes. Trial registration number Not applicable

Predicting long-term stroke mortality is a clinically important and unmet need. We aimed to develop and internally validate a 10-year ischaemic stroke mortality prediction score. In this UK cohort study, 10,366 patients with first-ever ischaemic stroke between January 2003 and December 2016 were followed up for a median (interquartile range) of 5.47 (2.96–9.15) years. A Cox proportional-hazards model was used to predict 10-year post-admission mortality. The predictors associated with 10-year mortality included age, sex, Oxfordshire Community Stroke Project classification, estimated glomerular filtration rate (eGFR), pre-stroke modified Rankin Score, admission haemoglobin, sodium, white blood cell count and comorbidities (atrial fibrillation, coronary heart disease, heart failure, cancer, hypertension, chronic obstructive pulmonary disease, liver disease and peripheral vascular disease). The model was internally validated using bootstrap resampling to assess optimism in discrimination and calibration. A nomogram was created to facilitate application of the score at the point of care. Mean age (SD) was 78.5 ± 10.9 years, 52% female. Most strokes were partial anterior circulation syndromes (38%). 10-year mortality predictors were: total anterior circulation stroke (hazard ratio, 95% confidence intervals) (2.87, 2.62–3.14), eGFR

Childhood obesity has become a serious global healthcare challenge. No UK data currently define its anaesthetic and perioperative implications. We aimed to determine obesity prevalence amongst UK children undergoing general anaesthesia and the incidence of predefined adverse perioperative events, and to compare perioperative obesity rates with National Child Measurement Programme (NCMP) data.During a site-selected consecutive 7-day study period, all children (2-16 yr) undergoing general anaesthesia were included. Anonymised hospital, surgical, and procedural details; demographic data; and adverse perioperative events were collected prospectively by Paediatric Anaesthesia Trainee Research Network (PATRN) collaborators.For this study, 102 UK hospitals participated and 4232 cases were included in the final analysis; 76% of hospitals did not routinely calculate BMI. In addition, 3030 (71.6%; 95% confidence interval [CI]: 70.2-73.0%) children of healthy weight were compared with 537 (12.7%; 11.7-13.7%) children who were overweight and 478 (11.3%; 10.3-12.2%) children with obesity. Children with obesity (n=71; 14.9%) more commonly underwent (adeno)tonsillectomy than children of healthy weight (n=282; 9.3%; P0.001; odds ratio [OR] 2.15; 95% CI: 1.58-2.92). Fewer children with obesity (n=365; 77% vs n=2552; 85%) were anaesthetised by consultant anaesthetists (OR 0.62; 95% CI: 0.48-0.79). Mask ventilation was difficult for 3.7% of children with obesity vs 0.6% of children of healthy weight (difference 3.0%; 95% CI: 1.3-4.7%; P0.001). Comparison with NCMP data demonstrated an over-representation of obesity amongst the paediatric surgical population.This large multicentre cohort study suggests a concerning prevalence of children with obesity presenting for anaesthesia. These results should be used to inform optimal provision of care for this population and support perioperative healthcare initiatives to address the burden of childhood obesity.ClinicalTrials.gov Identifier: NCT03994419.

Nursing home placement after stroke indicates a poor outcome but numbers placed vary between hospitals. The aim of this study is to determine whether between-hospital variations in new nursing home placements post-stroke are reliant solely on case-mix differences or whether service heterogeneity plays a role. A prospective, multi-center cohort study of acute stroke patients admitted to eight National Health Service acute hospitals within the Anglia Stroke and Heart Clinical Network between 2009 and 2011 was conducted. We modeled the association between hospitals (as a fixed-effect) and rates of new discharges to nursing homes using multiple logistic regression, adjusting for important patient risk factors. Descriptive and graphical data analyses were undertaken to explore the role of hospital characteristics. Of 1335 stroke admissions, 135 (10%) were discharged to a nursing home but rates varied considerably from 6% to 19% between hospitals. The hospital with the highest adjusted odds ratio of nursing home discharges (OR 4.26, 95% CI 1.69 to 10.73), was the only hospital that did not provide rehabilitation beds in the stroke unit. Increasing hospital size appeared to be related to an increased odds of nursing home placement, although attenuated by the number of hospital stroke admissions. Our results highlight the potential influence of hospital characteristics on this important outcome, independently of patient-level factors.

Background and Aims There is limited evidence to inform which people should receive follow up after AKI and for what reasons. Here we report the external validation (geographical and temporal) and potential clinical utility of two complementary models for predicting different post-discharge outcomes after AKI. We used decision curve analysis, a technique that enables visualisation of the trade-off (net benefit) between identifying true positives and avoiding false positives across a range of potential risk thresholds for a risk model. Based on decision curve analysis we compared model guided approaches to follow up after AKI with alternative strategies of standardised follow up – e.g. follow up of all people with AKI, severe AKI, or a discharge eGFR Method The Alberta AKI risk model predicts the risk of stage G4 CKD at one year after AKI among those with a baseline GFR>=45 and at least 90 days survival (2004-2014, n=9973). A trial is now underway using this tool at a 10% threshold to identify high risk people who may benefit from specialist nephrology follow up. The Aberdeen AKI risk model provides complementary predictions of early mortality or unplanned readmissions within 90 days of discharge (2003, n=16453), aimed at supporting non-specialists in discharge planning, with a threshold of 20-40% considered clinically appropriate in the study. For the Alberta model we externally validated using Grampian residents with hospital AKI in 2011-2013 (n=9382). For the Aberdeen model we externally validated using all people admitted to hospital in Grampian in 2012 (n=26575). Analysis code was shared between the sites to maximise reproducibility. Results Both models discriminated well in the external validation cohorts (AUC 0.855 for CKD G4, and AUC 0.774 for death and readmissions model), but as both models overpredicted risks, recalibration was performed. For both models, decision curve analysis showed that prioritisation of patients based on the presence or severity of AKI would be inferior to a model guided approach. For predicting CKD G4 progression at one year, a strategy guided by discharge eGFR Conclusion In conclusion, prioritising AKI follow up is complex and standardised recommendations for all people may be an inefficient and inadequate way of guiding clinical follow-up. Guidelines for AKI follow up should consider suggesting an individualised approach both with respect to purpose and prioritisation.

Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital or dying with the disease.Design Living systematic review and critical appraisal by the covid-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group.Data sources PubMed and Embase through Ovid, up to 17 February 2021, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020.Study selection Studies that developed or validated a multivariable covid-19 related prediction model.Data extraction At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool).Results 126 978 titles were screened, and 412 studies describing 731 new prediction models or validations were included. Of these 731, 125 were diagnostic models (including 75 based on medical imaging) and the remaining 606 were prognostic models for either identifying those at risk of covid-19 in the general population (13 models) or predicting diverse outcomes in those individuals with confirmed covid-19 (593 models). Owing to the widespread availability of diagnostic testing capacity after the summer of 2020, this living review has now focused on the prognostic models. Of these, 29 had low risk of bias, 32 had unclear risk of bias, and 545 had high risk of bias. The most common causes for high risk of bias were inadequate sample sizes (n=408, 67%) and inappropriate or incomplete evaluation of model performance (n=338, 56%). 381 models were newly developed, and 225 were external validations of existing models. The reported C indexes varied between 0.77 and 0.93 in development studies with low risk of bias, and between 0.56 and 0.78 in external validations with low risk of bias. The Qcovid models, the PRIEST score, Carr’s model, the ISARIC4C Deterioration model, and the Xie model showed adequate predictive performance in studies at low risk of bias. Details on all reviewed models are publicly available at https://www.covprecise.org/.Conclusion Prediction models for covid-19 entered the academic literature to support medical decision making at unprecedented speed and in large numbers. Most published prediction model studies were poorly reported and at high risk of bias such that their reported predictive performances are probably optimistic. Models with low risk of bias should be validated before clinical implementation, preferably through collaborative efforts to also allow an investigation of the heterogeneity in their performance across various populations and settings. Methodological guidance, as provided in this paper, should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction modellers should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline.Systematic review registration Protocol https://osf.io/ehc47/, registration https://osf.io/wy245.Readers’ note This article is the final version of a living systematic review that has been updated over the past two years to reflect emerging evidence. This version is update 4 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

STUDY QUESTION: How well does a previously developed dynamic prediction model perform in an external, geographical validation in terms of predicting the chances of natural conception at various points in time?SUMMARY ANSWER: The dynamic prediction model performs well in an external validation on a Scottish cohort.WHAT IS KNOWN ALREADY: Prediction models provide information that can aid evidence-based management of unexplained subfertile couples. We developed a dynamic prediction model for natural conception (van Eekelen model) that is able to update predictions of natural conception when couples return to their clinician after a period of unsuccessful expectant management. It is not known how well this model performs in an external population.STUDY DESIGN, SIZE, DURATION: A record-linked registry study including the long-term follow-up of all couples who were considered unexplained subfertile following a fertility workup at a Scottish fertility clinic between 1998 and 2011. Couples with anovulation, uni/bilateral tubal occlusion, mild/severe endometriosis or impaired semen quality according to World Health Organization criteria were excluded.PARTICIPANTS/MATERIALS, SETTING, METHODS: The endpoint was time to natural conception, leading to an ongoing pregnancy (defined as reaching a gestational age of at least 12 weeks). Follow-up was censored at the start of treatment, at the change of partner or at the end of study (31 March 2012). The performance of the van Eekelen model was evaluated in terms of calibration and discrimination at various points in time. Additionally, we assessed the clinical utility of the model in terms of the range of the calculated predictions.MAIN RESULTS AND THE ROLE OF CHANCE: Of a total of 1203 couples with a median follow-up of 1 year and 3 months after the fertility workup, 398 (33%) couples conceived naturally leading to an ongoing pregnancy. Using the dynamic prediction model, the mean probability of natural conception over the course of the first year after the fertility workup was estimated at 25% (observed: 23%). After 0.5, 1 and 1.5 years of expectant management after the completion of the fertility workup, the average probability of conceiving naturally over the next year was estimated at 18% (observed: 15%), 14% (observed: 14%) and 12% (observed: 12%). Calibration plots showed good agreement between predicted chances and the observed fraction of ongoing pregnancy within risk groups. Discrimination was moderate with c statistics similar to those in the internal validation, ranging from 0.60 to 0.64. The range of predicted chances was sufficiently wide to distinguish between couples having a good and poor prognosis with a minimum of zero at all times and a maximum of 55% over the first year after the workup, which decreased to maxima of 43% after 0.5 years, 34% after 1 year and 29% after 1.5 years after the fertility workup.LIMITATIONS, REASONS FOR CAUTION: The model slightly overestimated the chances of conception by ~2-3% points on group level in the first-year post-fertility workup and after 0.5 years of expectant management, respectively. This is likely attributable to the fact that the exact dates of completion of the fertility workup for couples were missing and had to be estimated.WIDER IMPLICATIONS OF THE FINDINGS: The van Eekelen model is a valid and robust tool that is ready to use in clinical practice to counsel couples with unexplained subfertility on their individualized chances of natural conception at various points in time, notably when couples return to the clinic after a period of unsuccessful expectant management.STUDY FUNDING/COMPETING INTEREST(S): This work was supported by a Chief Scientist Office postdoctoral training fellowship in health services research and health of the public research (ref PDF/12/06). There are no conflicts of interest.

The current definition of infertility acknowledges the importance of duration of pregnancy seeking but fails to recognize the prevalent negative impact of female age. In fact, the diagnosis of unexplained infertility increases with women's age because of our incapacity to discern between age-related infertility and real unexplained infertility. Physicians' response to the pressures of increased female age has been to take prompt refuge in assisted reproduction despite the lack of robust evidence and the inherent risks and costs of these procedures. Moreover, the prioritization of immediate health gains over those in the future, preference for accessing active treatment rapidly and reluctance to wait for spontaneous pregnancy expose patients to additional risks of overtreatment. Solutions are not simple to find but an alternative and innovative vision of infertility based on prognosis may be a valid solution. The availability of validated dynamic models based on real-life data that could predict both natural and ART-mediated conceptions may be of benefit. They could facilitate patients' counselling and could optimize the chances of success without exposing patients to unnecessary, expensive and demanding treatments.

Background Clinical prediction models are useful in estimating a patient’s risk of having a certain disease or experiencing an event in the future based on their current characteristics. Defining an appropriate risk threshold to recommend intervention is a key challenge in bringing a risk prediction model to clinical application; such risk thresholds are often defined in an ad hoc way. This is problematic because tacitly assumed costs of false positive and false negative classifications may not be clinically sensible. For example, when choosing the risk threshold that maximizes the proportion of patients correctly classified, false positives and false negatives are assumed equally costly. Furthermore, small to moderate sample sizes may lead to unstable optimal thresholds, which requires a particularly cautious interpretation of results. Main text We discuss how three common myths about risk thresholds often lead to inappropriate risk stratification of patients. First, we point out the contexts of counseling and shared decision-making in which a continuous risk estimate is more useful than risk stratification. Second, we argue that threshold selection should reflect the consequences of the decisions made following risk stratification. Third, we emphasize that there is usually no universally optimal threshold but rather that a plausible risk threshold depends on the clinical context. Consequently, we recommend to present results for multiple risk thresholds when developing or validating a prediction model. Conclusion Bearing in mind these three considerations can avoid inappropriate allocation (and non-allocation) of interventions. Using discriminating and well-calibrated models will generate better clinical outcomes if context-dependent thresholds are used.

Background and purpose: Urinary tract infection (UTI) is one of the most common complications following stroke and has prognostic significance. UTI rates have been shown to vary between hospitals, but it is unclear whether this is due to case-mix differences or heterogeneities in care among hospitals. Methods: A prospective multi-center cohort study of acute stroke patients admitted to eight National Health Service (NHS) acute hospital trusts within the Anglia Stroke & Heart Clinical Network between 2009 and 2011 was conducted. We modeled the association between hospital (as a fixed-effect) and inpatient UTI using a multivariable logistic regression model, adjusting for established patient-level risk factors. We graphically and descriptively analyzed heterogeneities in hospital-level characteristics. Results: We included 2,241 stroke admissions in our analysis; 171 (7.6%) acquired UTI as an inpatient. UTI rates varied significantly between the eight hospitals, ranging from 3 to 11%. The hospital that had the lowest odds of UTI [odds ratio (OR) = 0.50 (95% confidence interval (CI) 0.22-.11)] in adjusted analysis, had the highest number of junior doctors and occupational therapists per five beds of all hospitals. The hospital with the highest adjusted UTI rate [OR=2.69 (1.56-4.64)] was tertiary, the largest and had the highest volume of stroke patients, lowest number of stroke unit beds per 100 admissions, and the highest number of hospital beds per CT scanner. Conclusions: There is hospital-level variation in post-stroke UTI. Our results suggest the potential influence of service characteristics independently of patient-level factors which may be amenable to be addressed to improve the ultimate stroke outcome.

BACKGROUND Registry data from the Human Fertilisation and Embryology Authority (HFEA) show an increase of 40% in IUI and 377% in IVF cases using donor sperm between 2006 and 2016. OBJECTIVE AND RATIONALE The objective of this study was to establish whether pregnancies conceived using donor sperm are at higher risk of obstetric and perinatal complications than those conceived with partner sperm. As more treatments are being carried out using donor sperm, attention is being given to obstetric and perinatal outcomes, as events in utero and at delivery have implications for long-term health. There is a need to know if there is any difference in the outcomes of pregnancies between those conceived using donor versus partner sperm in order to adequately inform and counsel couples. SEARCH METHODS We performed a systematic review and meta-analysis of the outcomes of pregnancies conceived using donor sperm compared with partner sperm. Searches were performed in the OVID MEDLINE, OVID Embase, CENTRAL and CINAHL databases, including all studies published before 11 February 2019. The search strategy involved search terms for pregnancy, infant, donor sperm, heterologous artificial insemination, donor gametes, pregnancy outcomes and perinatal outcomes. Studies were included if they assessed pregnancies conceived by any method using, or infants born from, donor sperm compared with partner sperm and described early pregnancy, obstetric or perinatal outcomes. The Downs and Black tool was used for quality and bias assessment of studies. OUTCOMES Of 3391 studies identified from the search, 37 studies were included in the review and 36 were included in the meta-analysis. For pregnancies conceived with donor sperm, versus partner sperm, there was an increase in the relative risk (RR) (95% CI) of combined hypertensive disorders of pregnancy: 1.44 (1.17–1.78), pre-eclampsia: 1.49 (1.05–2.09) and small for gestational age (SGA): 1.42 (1.17–1.79) but a reduced risk of ectopic pregnancy: 0.69 (0.48–0.98). There was no difference in the overall RR (95% CI) of miscarriage: 0.94 (0.80–1.11), gestational diabetes: 1.49 (0.62–3.59), pregnancy-induced hypertension (PIH): 1.24 (0.87–1.76), placental abruption: 0.65 (0.04–10.37), placenta praevia: 1.19 (0.64–2.21), preterm birth: 0.98 (0.88–1.08), low birth weight: 0.97 (0.82–1.15), high birthweight: 1.28 (0.94–1.73): large for gestational age (LGA): 1.01 (0.84–1.22), stillbirth: 1.23 (0.97–1.57), neonatal death: 0.79 (0.36–1.73) and congenital anomaly: 1.15 (0.86–1.53). WIDER IMPLICATIONS The majority of our findings are reassuring, except for the mild increased risk of hypertensive disorders of pregnancy and SGA in pregnancies resulting from donor sperm. However, the evidence for this is limited and should be interpreted with caution because the evidence was based on observational studies which varied in their quality and risk of bias. Further high-quality population-based studies reporting obstetric outcomes in detail are required to confirm these findings.

STUDY QUESTION What is the chance of a treatment-independent live birth following IVF (including ICSI) treatment? SUMMARY ANSWER Over 5 years of follow-up, the treatment-independent live birth rate was 17% in unsuccessfully treated women and 15% in those who had a live birth after IVF. WHAT IS KNOWN ALREADY A limited number of studies have investigated the chance of treatment-independent conception following completion of IVF, but most of them have been based on surveys with poor response rates and limited sample sizes. STUDY DESIGN, SIZE, DURATION This is a population-based, retrospective cohort study of 2133 women who received IVF treatment between 1998 and 2011 at a single regional IVF Unit and were followed for a minimum of 1 year and maximum of 15 years after their last IVF or ICSI treatment cycle. PARTICIPANTS/MATERIALS, SETTING, METHODS This study included all women, residing in the north-east of the UK, who attended the Aberdeen Fertility Clinic and received IVF treatment between 1998 and 2011. Clinical and diagnostic information of all women was linked with treatment and pregnancy outcome data. A total of 2133 women were divided into two groups: (i) those who achieved a live birth following successful IVF or ICSI treatment (n = 1060) and (ii) those in whom treatment was unsuccessful i.e. resulted in either no pregnancy or pregnancy loss (n = 1073). The two groups were followed from the date of the last embryo transfer until the first treatment-independent live birth or 31 December 2012, whichever came first. The primary outcome was the treatment-independent live birth rate at 1, 2.5, 5 and 10 years of follow-up. Cox regression was used to determine factors associated with treatment-independent live birth in each group. MAIN RESULTS AND THE ROLE OF CHANCE Within 5 years of follow-up, the treatment-independent live birth rate was 17% (95% CI, 15–19%) among women whose IVF or ICSI treatment was unsuccessful and 15% (95% CI, 12–17%) among women whose treatment resulted in live birth. In both groups, shorter duration of infertility, younger female age and IVF as compared to ICSI were associated with a higher chance of achieving treatment-independent live birth. Among unsuccessfully treated women, the chance of post-IVF live birth was reduced in those with tubal factor infertility. Three or more previous IVF or ICSI embryo transfers were associated with a lower chance of treatment-independent live birth among successfully treated women. LIMITATIONS, REASONS FOR CAUTION The study was conducted in a single fertility centre, which could compromise the generalizability of the findings. Moreover, data were unavailable on the women’s use of contraception or active attempts to get pregnant, both of which could influence treatment-independent live birth rates. WIDER IMPLICATIONS OF THE FINDINGS This study provides a better understanding of the long-term prognosis for treatment-independent live birth after completion of IVF or ICSI treatment. The results will inform women of their chances of a treatment-independent live birth following failed or successful treatment and the factors that are associated with it. STUDY FUNDING/COMPETING INTEREST(S) This work was funded by a Chief Scientist Office Postdoctoral Training Fellowship in Health Services Research and Health of the Public Research (Ref PDF/12/06). The views expressed here are those of the authors and not necessarily those of the Chief Scientist Office. The authors have no competing interests. TRIAL REGISTRATION NUMBER Not applicable.

STUDY QUESTION Is there a difference in the odds of a live birth following blastocyst- versus cleavage-stage embryo transfer in the first complete cycle of IVF? SUMMARY ANSWER After adjusting for indication bias, there was not enough evidence to suggest a difference in the odds of live birth following blastocyst- versus cleavage-stage embryo transfer in the first complete cycle of IVF. WHAT IS KNOWN ALREADY Replacement of blastocyst-stage embryos has become the dominant practice in IVF but there is uncertainty about whether this technique offers an improved chance of cumulative live birth over all fresh and frozen-thawed embryo transfer attempts associated with a single oocyte retrieval. STUDY DESIGN, SIZE, DURATION National population-based retrospective cohort study of 100 610 couples who began their first IVF/ICSI treatment at a licenced UK clinic between 1 January 1999 and 30 July 2010. PARTICIPANTS/MATERIALS, SETTING, METHODS Data from the Human Fertilisation and Embryology Authority (HFEA) register on IVF/ICSI treatments using autologous gametes between 1999 and 2010 were analysed. The primary outcome was the live birth rate over the first complete cycle of IVF. Cumulative live birth rates (CLBR) were compared for couples who underwent blastocyst and cleavage transfer, and the adjusted odds of live birth over the first complete cycle were estimated for each group using binary logistic regression. This analysis was repeated within groups of female age, oocytes collected and primary versus secondary infertility. Inverse probability of treatment weighting was used to account for the imbalance in couple characteristics between treatment groups. MAIN RESULTS AND THE ROLE OF CHANCE In total, 94 294 (93.7%) couples had a cleavage-stage embryo transfer while 6316 (6.3%) received blastocysts. Over the first complete cycle of IVF/ICSI (incorporating all fresh and frozen-thawed embryo transfers associated with the first oocyte retrieval), the CLBR was increased in those who underwent blastocyst transfer (56.5%) compared to cleavage-stage embryo transfer (34.8%). However, after accounting for the imbalance between exposures, blastocyst transfer did not significantly influence the odds of live birth over the first complete cycle (adjusted odds ratio: 1.03 (0.96, 1.10)). LIMITATIONS, REASONS FOR CAUTION Limitations of our study include the retrospective nature of the HFEA dataset and availability of linked data up until 2010. We were unable to adjust for some confounders, such as smoking status, BMI and embryo quality, as these data are not collected at national level by the HFEA. Similarly, there may be unknown couple, treatment or clinic variables that may influence our results. We were unable to assess the intended stage of embryo transfer for women who did not have an embryo replaced, and therefore excluded them from our study. Perinatal outcomes were not included in our analyses and would be a useful basis for future study. WIDER IMPLICATIONS OF THE FINDINGS Our findings show that blastocyst-stage embryo transfer may offer an improved chance of live birth in both the first fresh and the first complete cycle of IVF/ICSI compared to cleavage-stage transfer, even in couples with typically poorer prognoses. Where possible, offering blastocyst transfer to a wider range of couples may increase cumulative success rates. STUDY FUNDING/COMPETING INTEREST(S) N.J.C. received a Wolfson Foundation Intercalated Degree Research Fellowship funded by the Wolfson Foundation, through the Royal College of Physicians. This work was supported by a Chief Scientist Office Postdoctoral Training Fellowship in Health Services Research and Health of the Public Research (Ref PDF/12/06) held by D.J.M. The views expressed here are those of the authors and not necessarily those of the Chief Scientist Office or the Wolfson Foundation. The funders did not have any role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; nor in the decision to submit the paper for publication. None of the authors has any conflicts of interest to declare. TRIAL REGISTRATION NUMBER N/A

Background and Purpose- We aimed to determine individual and combined effects of atrial fibrillation (AF) and heart failure (HF) on acute ischemic stroke outcomes: in-hospital mortality, length-of-stay, and poststroke disability; long-term mortality and stroke recurrence. Methods- Prospective cohort study of patients with acute ischemic stroke admitted to a UK center with a catchment population of ≈900 000 between 2004 and 2016. Exposure groups were patients with neither AF nor HF (reference group), those with AF but without HF, those with HF but without AF, and those with AF+HF. Logistic and Cox regressions were used to model in-hospital and long-term outcomes, respectively. Results- A total of 10 816 patients with a mean age±SD =77.9±12.1 years, 48% male were included. Only 30 (4.9%) of the patients with HF but not AF were anticoagulated at discharge. Both AF (odds ratio, 1.24 [95% CI, 1.07-1.43]), HF (odds ratio, 1.40 [1.10-1.79]), and their combination (odds ratio, 2.23 [1.83-2.72]) were associated with increased odds of in-hospital mortality. All 3 exposure groups were associated with increased length-of-stay, while only AF predicted increased disability (1.36 [1.12-1.64]). Patients were followed for a median of 5.5 and 3.7 years for mortality and recurrence, respectively. Long-term mortality was associated with AF (hazard ratio, 1.45 [95% CI, 1.33-1.59]), HF (2.07 [1.83-2.36]), and their combination (2.20 [1.96-2.46]). Recurrent stroke was associated with AF 1.50 (1.26-1.78), HF (1.33 [1.01-1.75]), and AF with HF (1.62 [1.28-2.07]). Conclusions- The AF-associated excess risk of stroke recurrence was independent of comorbid HF. HF without AF was also associated with a significant risk of recurrence. Anticoagulation for secondary stroke prevention in patients with HF without AF may require further evaluation in a clinical trial setting.

STUDY QUESTION Can we develop a prediction model that can estimate the chances of conception leading to live birth with and without treatment at different points in time in couples with unexplained subfertility? SUMMARY ANSWER Yes, a dynamic model was developed that predicted the probability of conceiving under expectant management and following active treatments (in vitro fertilisation (IVF), intrauterine insemination with ovarian stimulation (IUI + SO), clomiphene) at different points in time since diagnosis. WHAT IS KNOWN ALREADY Couples with no identified cause for their subfertility continue to have a realistic chance of conceiving naturally, which makes it difficult for clinicians to decide when to intervene. Previous fertility prediction models have attempted to address this by separately estimating either the chances of natural conception or the chances of conception following certain treatments. These models only make predictions at a single point in time and are therefore inadequate for informing continued decision-making at subsequent consultations. STUDY DESIGN, SIZE, DURATION A population-based study of 1316 couples with unexplained subfertility attending a regional clinic between 1998 and 2011. PARTICIPANTS/MATERIALS, SETTING, METHODS A dynamic prediction model was developed that estimates the chances of conception within 6 months from the point when a diagnosis of unexplained subfertility was made. These predictions were recomputed each month to provide a dynamic assessment of the individualised chances of conception while taking account of treatment status in each month. Conception must have led to live birth and treatments included clomiphene, IUI + SO, and IVF. Predictions for natural conception were externally validated using a prospective cohort from The Netherlands. MAIN RESULTS AND THE ROLE OF CHANCE A total of 554 (42%) couples started fertility treatment within 2 years of their first fertility consultation. The natural conception leading to live birth rate was 0.24 natural conceptions per couple per year. Active treatment had a higher chance of conception compared to those who remained under expectant management. This association ranged from weak with clomiphene to strong with IVF [clomiphene, hazard ratio (HR) = 1.42 (95% confidence interval, 1.05 to 1.91); IUI + SO, HR = 2.90 (2.06 to 4.08); IVF, HR = 5.09 (4.04 to 6.40)]. Female age and duration of subfertility were significant predictors, without clear interaction with the relative effect of treatment. LIMITATIONS, REASONS FOR CAUTION We were unable to adjust for other potentially important predictors, e.g. measures of ovarian reserve, which were not available in the linked Grampian dataset that may have made predictions more specific. This study was conducted using single centre data meaning that it may not be generalizable to other centres. However, the model performed as well as previous models in reproductive medicine when externally validated using the Dutch cohort. WIDER IMPLICATIONS OF THE FINDINGS For the first time, it is possible to estimate the chances of conception following expectant management and different fertility treatments over time in couples with unexplained subfertility. This information will help inform couples and their clinicians of their likely chances of success, which may help manage expectations, not only at diagnostic workup completion but also throughout their fertility journey. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by a Chief Scientist Office postdoctoral training fellowship in health services research and health of the public research (ref PDF/12/06). B.W.M. is supported by an NHMRC Practitioner Fellowship (GNT1082548). B.W.M. reports consultancy for ObsEva, Merck, and Guerbet. None of the other authors declare any conflicts of interest.

ObjectivesTo determine whether stroke patients’ acute hospital length of stay (AHLOS) varies between hospitals, over and above case mix differences and to investigate the hospital-level explanatory factors.DesignA multicentre prospective cohort study.SettingEight National Health Service acute hospital trusts within the Anglia Stroke & Heart Clinical Network in the East of England, UK.ParticipantsThe study sample was systematically selected to include all consecutive patients admitted within a month to any of the eight hospitals, diagnosed with stroke by an accredited stroke physician every third month between October 2009 and September 2011.Primary and secondary outcome measuresAHLOS was defined as the number of days between date of hospital admission and discharge or death, whichever came first. We used a multiple linear regression model to investigate the association between hospital (as a fixed-effect) and AHLOS, adjusting for several important patient covariates, such as age, sex, stroke type, modified Rankin Scale score (mRS), comorbidities and inpatient complications. Exploratory data analysis was used to examine the hospital-level characteristics which may contribute to variance between hospitals. These included hospital type, stroke monthly case volume, service provisions (ie, onsite rehabilitation) and staffing levels.ResultsA total of 2233 stroke admissions (52% female, median age (IQR) 79 (70 to 86) years, 83% ischaemic stroke) were included. The overall median AHLOS (IQR) was 9 (4 to 21) days. After adjusting for patient covariates, AHLOS still differed significantly between hospitals (pConclusionsWe have clearly demonstrated that AHLOS varies between different hospitals, and that the most important patient-level explanatory variables are discharge mRS, dementia and inpatient complications. We highlight the potential importance of stroke volume in influencing these differences but cannot discount the potential effect of unmeasured confounders.

Objectives: To determine the risk factor profiles associated with post-acute ischaemic stroke (AIS) myocardial infarction (MI) over long-term follow-up. Methods: This observational study includes prospectively identified AIS patients (n=9840) admitted to a UK regional centre between January 2003-December 2016 (median follow-up: 4.72 years). Predictors of post-stroke MI during follow up were examined using logistic and Cox regression models for in-hospital and post-discharge events, respectively. MI incidence was determined using a competing risk non-parametric estimator. The influence of post-stroke MI on mortality was examined using Cox regressions. Results: Mean age (SD) of study participants was 77.3(12.2) years (48% males). Factors associated with in-hospital MI (OR(95%CI)) were increasing blood glucose (1.80(1.17-2.77) per 10mmol/L), total leukocyte count (1.25(1.01-1.54) per 10x109/L), and CRP (1.05(1.02-1.08) per 10mg/L increase). Age (HR(95%CI) =1.03(1.01-1.06)), coronary heart disease (1.59(1.01-2.50)), chronic kidney disease (2.58(1.44-4.63)), and cancers (1.76(1.08-2.89)) were associated with incident MI between discharge and one year follow-up. Age ((1.02(1.00-1.03)), diabetes (1.96(1.38-2.65)), congestive heart failure (2.07(1.44-2.99), coronary heart disease (1.81(1.31-2.50)), hypertension (1.86(1.24-2.79)), and peripheral vascular disease (2.25(1.40-3.63)) were associated with incident MI between 1-5 years after discharge. Diabetes (2.01(1.09-3.72)), hypertension (3.69(1.44-9.45)), and peripheral vascular disease (2.46(1.02-5.98)) were associated with incident MI between 5-10 years after discharge. Cumulative MI incidence over 10 years was 5.4%. MI during all follow-up periods (discharge-1 year, 1-5 years, 5-10 years) was associated with increased risk of death (respective HR(95%CI)=3.26(2.51-4.15), 1.96(1.58-2.42) and 1.92(1.26-2.93)). Conclusions: In conclusion, prognosis is poor in post-stroke MI. We highlight a range of potential areas to focus preventative efforts.

STUDY QUESTION: Are the published pre-treatment and post-treatment McLernon models, predicting cumulative live birth rates (LBR) over multiple complete IVF cycles, valid in a different context? SUMMARY ANSWER: With minor recalibration of the pre-treatment model, both McLernon models accurately predict cumulative LBR in a different geographical context and a more recent time period. WHAT IS KNOWN ALREADY: Previous IVF prediction models have estimated the chance of a live birth after a single fresh embryo transfer, thereby excluding the important contribution of embryo cryopreservation and subsequent IVF cycles to cumulative LBR. In contrast, the recently developed McLernon models predict the cumulative chance of a live birth over multiple complete IVF cycles at two certain time points: (i) before initiating treatment using baseline characteristics (pre-treatment model) and (ii) after the first IVF cycle adding treatment related information to update predictions (post-treatment model). Before implementation of these models in clinical practice, their predictive performance needs to be validated in an independent cohort. STUDY DESIGN, SIZE, DURATION: External validation study in an independent prospective cohort of 1515 Dutch women who participated in the OPTIMIST study (NTR2657) and underwent their first IVF treatment between 2011 and 2014. Participants underwent a total of 2881 complete treatment cycles, with a complete cycle defined as all fresh and frozen thawed embryo transfers resulting from one episode of ovarian stimulation. The follow up duration was 18 months after inclusion, and the primary outcome was ongoing pregnancy leading to live birth. PARTICIPANTS/MATERIALS, SETTING, METHODS: Model performance was externally validated up to three complete treatment cycles, using the linear predictor as described by McLernon et al. to calculate the probability of a live birth. Discrimination was expressed by the c-statistic and calibration was depicted graphically in a calibration plot. In contrast to the original model development cohort, anti-Müllerian hormone (AMH), antral follicle count (AFC) and body weight were available in the OPTIMIST cohort, and evaluated as potential additional predictors for model improvement. MAIN RESULTS AND THE ROLE OF CHANCE: Applying the McLernon models to the OPTIMIST cohort, the c-statistic of the pretreatment model was 0.62 (95% CI: 0.59-0.64) and of the post-treatment model 0.71 (95% CI: 0.69-0.74). The calibration plot of the pretreatment model indicated a slight overestimation of the cumulative LBR. To improve calibration, the pre-treatment model was recalibrated by subtracting 0.35 from the intercept. The post-treatment model calibration plot revealed accurate cumulative LBR predictions. After addition of AMH, AFC and body weight to the McLernon models, the c-statistic of the updated pre-treatment model improved slightly to 0.66 (95% CI: 0.64-0.68), and of the updated post-treatment model remained at the previous level of 0.71 (95% CI: 0.69-0.73). Using the recalibrated pre-treatment model, a woman aged 30 years with 2 years of primary infertility who starts ICSI treatment for male factor infertility has a chance of 40% of a live birth from the first complete cycle, increasing to 72% over three complete cycles. If this woman weighs 70 kg, has an AMH of 1.5 ng/mL and an AFC of 10 measured at the beginning of her treatment, the updated pre-treatment model revises the estimated chance of a live birth to 30% in the first complete cycle and 59% over three complete cycles. If this woman then has five retrieved oocytes, no embryos cryopreserved and a single fresh cleavage stage embryo transfer in her first ICSI cycle, the post-treatment model estimates the chances of a live birth at 28 and 58%, respectively. LIMITATIONS, REASONS FOR CAUTION: Two randomized controlled trials (RCT) evaluating the effectiveness of gonadotropin dose individualization on basis of the AFC were nested within the OPTIMIST study. The strict dosing regimens, the RCT in- and exclusion criteria and the limited follow up time of 18 months might have influenced model performance in this independent cohort. Also, consistent with the original model development study, external validation was performed using the optimistic assumption that the cumulative LBR in couples who discontinue treatment without a live birth would have been equal to that of those who continue treatment. WIDER IMPLICATIONS OF THE FINDINGS: After national recalibration to account for geographical differences in IVF treatment, the McLernon prediction models can be introduced as new counselling tools in clinical practice to inform patients and to complement clinical reasoning. These models are the first to offer an objective and personalized estimate of the cumulative probability of a live birth over multiple complete IVF cycles. STUDY FUNDING/COMPETING INTEREST(S): No external funds were obtained for this study. M.J.C.E., D.J.M. and S.B. have nothing to disclose. J.A.L, S.C.O, T.C.v.T. and H.LT. received an unrestricted personal grant from Merck BV. B.W.M. is supported by a NHMRC Practitioner Fellowship (GNT1082548) and reports consultancy for ObsEva, Merck and Guerbet. F.J.M.B. receives monetary compensation as a member of the external advisory board for Merck BV (the Netherlands) and Ferring pharmaceutics BV (the Netherlands), for consultancy work for Gedeon Richter (Belgium) and Roche Diagnostics on automated AMH assay development, and for a research cooperation with Ansh Labs (USA).

Our paper presents two clinical prediction models that estimate the chance of having a baby over multiple complete cycles of in vitro fertilisation (IVF)—that is, cumulative live birth.1 The pretreatment model predicts the chance of cumulative live birth before treatment starts, and the post-treatment model predicts the chance of cumulative live birth just after the first embryo transfer. Through a collaboration with researchers from the University of Utrecht, who have externally validated these models, we have decided to revise the method used to assess the discriminatory ability of our models in the original study. In time to event models, such as ours, discrimination indicates the proportion of all pairs of women who can be ordered such that the woman with the lower predicted chance of live birth is the one who either did not have a live birth or had more complete cycles of IVF to have a live …

Couples in whom the results of an initial fertility workup fail to identify the presence of any obvious barriers to conception are diagnosed with unexplained subfertility. Couples who have tried to conceive for a relatively short time have a good chance of natural conception and thus may not benefit from immediate access to ART. As fertility decreases over time, the main dilemma that clinicians and couples face is when to abandon an expectant approach in favour of active treatment. Several prognostic or predictive models have been used to try to discriminate between couples with high and low chances of conception but have been unable to compare individualized chances of conception associated with ART relative to chances of natural conception at various time points. These models are also unable to recalculate the chances of pregnancy at subsequent time points in those who return after a period of unsuccessful expectant management. In this paper, we discuss currently available models. We conclude that in order to provide accurate, individualized and dynamic fertility prognoses associated with and without treatment at different points in time, we need to develop, validate and update clinical prediction models which are fit for purpose. We suggest several steps to move the field forwards.

In women undergoing IVF/ICSI who miscarry in their first complete cycle, what is the chance of a live birth in subsequent complete cycles, and how does this compare with those whose first complete cycle ends with live birth or without a pregnancy?After two further complete cycles of IVF/ICSI, women who had miscarried or had a live birth in their first complete cycle had a higher chance of live birth (40.9 and 49.0%, respectively) than those who had no pregnancies (30.1%).Cumulative live birth rates (CLBRs) after one or more complete cycles of IVF have been reported previously, as have some of the risk factors associated with miscarriage, both in general populations and in those undergoing IVF. Chances of cumulative live birth after a number of complete IVF cycles involving replacement of fresh followed by frozen embryos after an initial miscarriage in a population undergoing IVF treatment have not been reported previously.National population-based cohort study of 112 549 women who started their first IVF treatment between 1999 and 2008.Data from the UK Human Fertilisation and Embryology Authority (HFEA) register on IVF/ICSI treatments, using autologous gametes were analysed. CLBRs were estimated in women who (i) had miscarriage (and no live birth), (ii) at least one live birth or (iii) no pregnancy in their first complete cycle of IVF/ICSI (including fresh and frozen embryo transfers following a single oocyte retrieval episode). A multivariable analysis was performed to assess the effect of first complete cycle outcome on subsequent CLBRs after adjusting for confounding factors such as female age, duration of infertility and cause of infertility.In their first complete cycle, 9321 (8.3%) women had at least one miscarriage (and no live birth); 33 152 (29.5%) had at least one live birth and 70 076 (62.3%) had no pregnancies. After two further complete cycles, conservative CLBRs (which assume that women who discontinued treatment subsequently never had a live birth) were 40.9, 49.0 and 30.1%, while optimal CLBRs (which assume that women who discontinue have the same chance of live birth as those treated) were 49.5, 57.9 and 38.4% in the miscarriage, live birth and no pregnancy groups respectively. Odds of cumulative live birth for women who miscarried in their first complete cycle were 42% higher than those who had no pregnancy [odds ratio (95% CI) = 1.42 (1.34, 1.50)], and twice as high for live birth versus no pregnancy [2.04 (1.89, 2.20)]. Negative predictors for live birth in all women included tubal infertility [0.88 (0.82, 0.94)] and increasing age [18-40 years = 0.94 (0.94, 0.95);40 years = 0.63 (0.59, 0.66) per year].CLBRs could not be estimated for treatments occurring after September 2008 due to potentially incomplete data following regulatory changes regarding consent for data use in research. Additionally, covariates not included in the HFEA database (including BMI, smoking, previous history of miscarriage and gestational age at miscarriage) could not be adjusted for in our analysis.Miscarriage following IVF can be devastating for couples who are uncertain about their ultimate prognosis. Our findings will provide reassurance to these couples as they consider their options for continuing treatment.N.J.C. received an Aberdeen Summer Research Scholarship funded by the Institute of Applied Health Sciences (University of Aberdeen), through the Aberdeen Clinical Academic Training Scheme. This work was supported by a Chief Scientist Office Postdoctoral Training Fellowship in Health Services Research and Health of the Public Research (Ref PDF/12/06). The views expressed here are those of the authors and not necessarily those of the Chief Scientist Office or the University of Aberdeen. The funders did not have any role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; nor in the decision to submit the paper for publication. None of the authors has any conflicts of interest to declare.

ObjectivesTo distinguish between variation in referral threshold and variation in accurate selection of patients for referral in fast-track referrals for possible cancer. To examine factors associated with threshold and accuracy and model the effects of changing thresholds.DesignAnalysis of national data on cancer referrals from general practices in England over a 5-year period. We developed a new method to estimate specificity of referral to complement existing sensitivity. We used bivariate meta-analysis to produce summary measures and described practices in relation to these.Setting5479 general practitioner (GP) practices with data relating to more than 50 cancer cases diagnosed over the 5 years.OutcomesNumber of practices whose 95% confidence regions for sensitivity and specificity indicated that they were outliers in terms of either referral threshold or decision accuracy.Results2019 practices (36.8%) were outliers in relation to referral threshold compared with 1205 practices (22%) in relation to decision accuracy. Practice age profile, cancer incidence and deprivation showed a modest association with decision accuracy but not with thresholds. If all practices shared the referral behaviour of those in the highest quintile of age-standardised referral rate, there would be a 3.3% increase in cancers detected through fast-track pathways at the cost of a 36.9% increase in urgent referrals.ConclusionThis new method permits variation in referral to be described more precisely and quality improvement activities to be targeted. Changing referral thresholds without increasing accuracy will result in modest effects on detection rates and a large increase in demand on diagnostic services.

Infertility is defined as failure to conceive after 1 year of unprotected intercourse. This dichotomization into fertile versus infertile, based on lack of conception over 12-month period, is fundamentally flawed. Time to conception is strongly influenced by factors such as female age and whilst a minority of couples have absolute infertility (sterility), many are able to conceive without intervention but may take longer to do so, reflecting the degree of subfertility. This natural variability in time to conception means that subfertility reflects a prognosis rather than a diagnosis. Current clinical prediction models in fertility only provide individualized estimates of the probability of either treatment-independent pregnancy or treatment-dependent pregnancy, but do not take account of both. Together, prognostic factors which are able to predict natural pregnancy and predictive factors of response to treatment would be required to estimate the absolute increase in pregnancy chances with treatment. This stratified medicine approach would be appropriate for facilitating personalized decision-making concerning whether or not to treat subfertile patients. Published models are thus far of little value for decisions regarding when to initiate treatment in patients who undergo a period of, ultimately unsuccessful, expectant management. We submit that a dynamic prediction approach, which estimates the change in subfertility prognosis over the course of follow-up, would be ideally suited to inform when the commencement of treatment would be most beneficial in those undergoing expectant management. Further research needs to be undertaken to identify treatment predictive factors and to identify or create databases to allow these approaches to be explored. In the interim, the most feasible approach is to use a combination of previously published clinical prediction models.