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Abstract Introduction Despite increased interest in learning health systems (LHS), a paucity of guidance and tools for evaluating LHS implementation exists. To address this, we aim to undertake a scoping review on existing tools and evaluation of exemplars of LHS implementation. Methods We conducted a scoping review of peer-reviewed studies within Scopus, EMBASE, MEDLINE, and MEDLINE in-process that described (1) the evaluation of the implementation of an operating LHS or (2) the development of a framework or tool to facilitate this evaluation. Anima, basic research, abstracts, non-English language articles, and publications before 2018 were excluded. All study designs were considered. Findings From 1300 studies initially identified, 4 were eligible, revealing three tools with nine implementation evaluation examples. The identified tools shared constructs which were evaluated, including: Stakeholders, Data, Research Evidence, Implementation, and Sociotechnical Infrastructure. However, there was divergence in evaluation methodology. Tools ranged from a five-point numerical rating system for process maturity with a radar chart called the Network Maturity Grid (NMG); the Kaiser Permanente Washington (KPWA) LHS Logic Model, which provides a broad list of constructs and sample measures relevant to LHS operations; and finally LADDERS, a simple tool or form-based template designed for consistent evaluation over time. The NMG tool was the most mature in terms of adaptation and adoption. Notably, two (NMG and the KPWA LHS Logic Model) out of three tools conceptualized the LHS as a suite of processes and devised tools were processes that linked these constructs. Implications for toolkit development The evaluation of LHS implementation remains an under explored area of investigation, as this scoping review found only three tools for LHS implementation evaluation. Our findings indicate a need for further empirical research in this area and suggest early consensus in constructs that need to be considered during evaluation.

Abstract Background In the context of expanding digital health tools, the health system is ready for Learning Health System (LHS) models. These models, with proper governance and stakeholder engagement, enable the integration of digital infrastructure to provide feedback to all relevant parties including clinicians and consumers on performance against best practice standards, as well as fostering innovation and aligning healthcare with patient needs. The LHS literature primarily includes opinion or consensus-based frameworks and lacks validation or evidence of benefit. Our aim was to outline a rigorously codesigned, evidence-based LHS framework and present a national case study of an LHS-aligned national stroke program that has delivered clinical benefit. Main text Current core components of a LHS involve capturing evidence from communities and stakeholders (quadrant 1), integrating evidence from research findings (quadrant 2), leveraging evidence from data and practice (quadrant 3), and generating evidence from implementation (quadrant 4) for iterative system-level improvement. The Australian Stroke program was selected as the case study as it provides an exemplar of how an iterative LHS works in practice at a national level encompassing and integrating evidence from all four LHS quadrants. Using this case study, we demonstrate how to apply evidence-based processes to healthcare improvement and embed real-world research for optimising healthcare improvement. We emphasize the transition from research as an endpoint, to research as an enabler and a solution for impact in healthcare improvement. Conclusions The Australian Stroke program has nationally improved stroke care since 2007, showcasing the value of integrated LHS-aligned approaches for tangible impact on outcomes. This LHS case study is a practical example for other health conditions and settings to follow suit.

Background Polycystic ovary syndrome (PCOS) is the most prevalent female endocrinopathy. Although increased cardiovascular risk factors are well established for the syndrome, PCOS remains overlooked within the realm of cardiology. We conducted a systematic review and meta‐analysis on the risk of clinical cardiovascular disease (CVD) events in women with PCOS to inform the 2023 International Evidence‐Based PCOS Guideline. Methods and Results A systematic review and meta‐analysis was conducted comparing the risk of clinical CVD events in women with and without PCOS. Medline (Ovid), PsycInfo (Ovid), EMBASE, All EBM (Ovid), and CINAHL were searched from January 1, 2017, until March 1, 2023, to update the 2018 PCOS Guideline. Pooled odds ratios (ORs), incidence rate ratios (IRRs), and hazard ratios (HRs) were calculated. Twenty studies involving 1.06 million women (369 317 with PCOS and 692 963 without PCOS) were included. PCOS was associated with higher risk of composite CVD (OR, 1.68 [95% CI, 1.26–2.23]; I2 = 71.0%), composite ischemic heart disease (OR, 1.48 [95% CI, 1.07–2.05]; I2 = 81.0%), myocardial infarction (OR, 2.50 [95% CI, 1.43–4.38]; I2 = 83.3%), and stroke (OR, 1.71 [95% CI, 1.20–2.44]; I2 = 81.4%). The relationship with cardiovascular mortality was less clear (OR, 1.19 [95% CI, 0.53–2.69]; I2 = 0%). Meta‐analyses of IRRs support these findings. Results from pooled HRs were limited by the small number of studies and significant heterogeneity. Conclusions This review provides evidence and highlights the importance of recognizing PCOS as a significant risk factor for CVD morbidity. The 2023 International Evidence‐Based PCOS Guideline now recommends awareness of increased CVD risk and comprehensive risk assessment in PCOS to help mitigate the burden of CVD in this common and high‐risk condition.

Objective To predict birth weight at various potential gestational ages of delivery based on data routinely available at the first antenatal visit.Design Individual participant data meta-analysis.Data sources Individual participant data of four cohorts (237 228 pregnancies) from the International Prediction of Pregnancy Complications (IPPIC) network dataset.Eligibility criteria for selecting studies Studies in the IPPIC network were identified by searching major databases for studies reporting risk factors for adverse pregnancy outcomes, such as pre-eclampsia, fetal growth restriction, and stillbirth, from database inception to August 2019. Data of four IPPIC cohorts (237 228 pregnancies) from the US (National Institute of Child Health and Human Development, 2018; 233 483 pregnancies), UK (Allen et al, 2017; 1045 pregnancies), Norway (STORK Groruddalen research programme, 2010; 823 pregnancies), and Australia (Rumbold et al, 2006; 1877 pregnancies) were included in the development of the model.Results The IPPIC birth weight model was developed with random intercept regression models with backward elimination for variable selection. Internal-external cross validation was performed to assess the study specific and pooled performance of the model, reported as calibration slope, calibration-in-the-large, and observed versus expected average birth weight ratio. Meta-analysis showed that the apparent performance of the model had good calibration (calibration slope 0.99, 95% confidence interval (CI) 0.88 to 1.10; calibration-in-the-large 44.5 g, −18.4 to 107.3) with an observed versus expected average birth weight ratio of 1.02 (95% CI 0.97 to 1.07). The proportion of variation in birth weight explained by the model (R2) was 46.9% (range 32.7-56.1% in each cohort). On internal-external cross validation, the model showed good calibration and predictive performance when validated in three cohorts with a calibration slope of 0.90 (Allen cohort), 1.04 (STORK Groruddalen cohort), and 1.07 (Rumbold cohort), calibration-in-the-large of −22.3 g (Allen cohort), −33.42 (Rumbold cohort), and 86.4 g (STORK Groruddalen cohort), and observed versus expected ratio of 0.99 (Rumbold cohort), 1.00 (Allen cohort), and 1.03 (STORK Groruddalen cohort); respective pooled estimates were 1.00 (95% CI 0.78 to 1.23; calibration slope), 9.7 g (−154.3 to 173.8; calibration-in-the-large), and 1.00 (0.94 to 1.07; observed v expected ratio). The model predictions were more accurate (smaller mean square error) in the lower end of predicted birth weight, which is important in informing clinical decision making.Conclusions The IPPIC birth weight model allowed birth weight predictions for a range of possible gestational ages. The model explained about 50% of individual variation in birth weights, was well calibrated (especially in babies at high risk of fetal growth restriction and its complications), and showed promising performance in four different populations included in the individual participant data meta-analysis. Further research to examine the generalisability of performance in other countries, settings, and subgroups is required.Trial registration PROSPERO CRD42019135045

Background: Women with cardiometabolic pregnancy complications are at increased risk of future diabetes and heart disease which can be reduced through lifestyle management postpartum. Objectives: This study aimed to explore preferred intervention characteristics and behaviour change needs of women with or without prior cardiometabolic pregnancy complications for engaging in postpartum lifestyle interventions. Design: Quantitative cross-sectional study. Methods: Online survey. Results: Overall, 473 women were included, 207 (gestational diabetes (n = 105), gestational hypertension (n = 39), preeclampsia (n = 35), preterm birth (n = 65) and small for gestational age (n = 23)) with and 266 without prior cardiometabolic pregnancy complications. Women with and without complications had similar intervention preferences, with delivery ideally by a healthcare professional with expertise in women’s health, occurring during maternal child health nurse visits or online, commencing 7 weeks to 3 months post birth, with 15- to 30-min monthly sessions, lasting 1 year and including monitoring of progress and social support. Women with prior complications preferred intervention content on women’s health, mental health, exercise, mother’s diet and their children’s health and needed to know more about how to change behaviour, have more time to do it and feel they want to do it enough to participate. There were significant differences between groups, with more women with prior cardiometabolic pregnancy complications wanting content on women’s health (87.9% vs 80.8%, p = 0.037), mother’s diet (72.5% vs 60.5%, p = 0.007), preventing diabetes or heart disease (43.5% vs 27.4%, p

Abstract Background Both obesity and sleep disorders are common among women during pregnancy. Although prior research has identified a relationship between obesity and sleep disorders, those findings are from women later in pregnancy. Objective To explore the relationships between self‐reported sleep duration, insufficient sleep and snoring with body mass index (BMI) among multiethnic women at risk of gestational diabetes mellitus (GDM)in early pregnancy. Methods Cross‐sectional study of baseline data from women at risk of GDM enrolled in the Treatment of BOoking Gestational diabetes Mellitus (TOBOGM) multicentre trial across 12 Australian/Austrian sites. Participants completed a questionnaire before 20 weeks’ gestation to evaluate sleep. BMI 5 days/month was higher in class II and class III obesity (1.38 (1.03–1.85) and 1.34 (1.01–1.80), respectively), and the risk of snoring increased as BMI increased (1.59 (1.25–2.02), 2.68 (2.07–3.48), 4.35 (3.21–5.88) to 4.96 (3.65–6.74), respectively)). Conclusions Obesity is associated with insufficient sleep among pregnant women at risk of GDM. Snoring is more prevalent with increasing BMI.

Abstract Objectives To explore associations between type and number of abnormal glucose values on antenatal oral glucose tolerance test (OGTT) with postpartum diabetes in South Asian women diagnosed with gestational diabetes (GDM) using International Association of the Diabetes and Pregnancy Study Groups criteria. Methods This post‐hoc evaluation of the Lifestyle Intervention IN Gestational Diabetes (LIVING) study, a randomized controlled trial, was conducted among women with GDM in the index pregnancy, across 19 centers in Bangladesh, India, and Sri Lanka. Postpartum diabetes (outcome) was defined on OGTT, using American Diabetes Association (ADA) criteria. Results We report data on 1468 women with GDM, aged 30.9 (5.0) years, and with median (interquartile range) follow‐up period of 1.8 (1.4–2.4) years after childbirth following the index pregnancy. We found diabetes in 213 (14.5%) women with an incidence of 8.7 (7.6–10.0)/100 women‐years. The lowest incidence rate was 3.8/100 women years, in those with an isolated fasting plasma glucose (FPG) abnormality, and highest was 19.0/100 women years in participants with three abnormal values. The adjusted hazard ratios for two and three abnormal values compared to one abnormal value were 1.73 (95% confidence interval [CI], 1.18–2.54; p = .005) and 3.56 (95% CI, 2.46–5.16; p

Introduction Scaling up interventions targeting non-communicable diseases (NCDs) is a global health priority, and implementation research can contribute to that effort. In 2019, the Global Alliance for Chronic Diseases funded 27 implementation research studies to improve evidence for scaling up interventions targeting prevention and/or control of hypertension and/or diabetes in low-resource settings. We examined these studies to improve the understanding of the implementation factors, including challenges and facilitators, that influence the early implementation phase of scale-up research projects targeting NCDs.Methods This qualitative study was undertaken between August 2020 and July 2021. 43 semi-structured interviews were conducted with project investigators, implementers and policymakers, across 19 diverse scale-up projects, being implemented in 20 countries. The transcripts were inductively, open-coded using thematic analysis. Generated themes were mapped systematically to four out of five domain categorisations of the Consolidated Framework for Implementation Research (CFIR); the innovation domain fell outside the scope of this study.Results Highlighted findings using CFIR are: (i) outer setting: influence of politics, lack of coordination between government departments and differing agendas towards NCDs hindered implementation while reliable and trustworthy government connections proved useful; (ii) inner setting: commitment of resources for implementation was a challenge while research capacity, work culture and trustworthy networks facilitated implementation; (iii) individuals: high-level stakeholder support and leadership was essential; (iv) process: extensive time and efforts required for stakeholder engagement towards local contextualisation was challenging, while collaborating, joint reflection, effective communication and adaptation facilitated. COVID-19 provided both challenges and opportunities and these varied depending on the intervention characteristics and study objectives.Conclusion Researchers supporting the scale-up of complex interventions targeting NCDs need to leverage on existing trusting relationships and foster equitable stakeholder partnerships through research. Interpersonal skills and good communication are essential complements to research expertise and must be considered during capacity building.

BackgroundWomen with overweight and obesity are at higher risk of developing complications in pregnancy such as gestational diabetes and longer-term chronic conditions. Research concerning health behavior change interventions during pregnancy and postpartum shows promising effects, but implementation into routine services is sparsely investigated. Most interventions focus on the antenatal or postpartum life stages, failing to meet the needs of women. IMPACT DIABETES Bump2Baby is a multicenter project across 4 high-income countries developed to test the implementation of an antenatal and postpartum evidence-based mobile health (mHealth) coaching intervention called Bump2Baby and Me (B2B&Me) designed to sit alongside usual care in the perinatal period. ObjectiveWe aim to explore the feasibility and implementation of the B2B&Me intervention and investigate the effectiveness of this intervention in women at risk of gestational diabetes. MethodsIMPACT DIABETES Bump2Baby is a hybrid type 2 effectiveness-implementation study, which integrates an evidence-based mHealth coaching app that includes personalized health behavior change coaching provided by health care professionals alongside antenatal care from the first antenatal visit to 12 months postpartum. The mHealth app offers the possibility of synchronous calls, asynchronous contact (including coach-participant text and video messaging exchanges tailored to the participant’s needs), and ongoing access to an extensive library of bespoke intervention materials. Participants will interact asynchronously with their health coach throughout the intervention via the app. This randomized controlled trial across 4 clinical sites within Ireland, the United Kingdom, Spain, and Australia will recruit 800 women in early pregnancy to evaluate the effectiveness on postpartum weight. The Exploration, Preparation, Implementation, and Sustainment implementation framework is the theoretical underpinning of the study. The implementation evaluation will be assessed at the individual, hospital staff, and broader community levels using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework. Data sources for the RE-AIM evaluation will include app and platform analytics, screening and training records, participant medical records, key informant interviews, participant and partner exit interviews, cost data, study questionnaires, staff surveys, and blood sample analyses. ResultsThe study was approved and registered with the Australian New Zealand Clinical Trials Registry on November 19, 2020. Recruitment commenced on February 9, 2021, and data collection is ongoing. Publication of the results is expected in 2024. ConclusionsThis is the first hybrid effectiveness-implementation study of an 18-month mHealth coaching intervention in at-risk women that we are aware of. As research aims to move toward real-world implementable solutions, it is critical that hybrid studies are conducted. The data from this large multicenter study will be useful in planning the potential implementation and scale-up of evidence-based perinatal health behavior change interventions. Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12620001240932; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380020&isReview=true International Registered Report Identifier (IRRID)DERR1-10.2196/51431

Summary: Background: Anti-androgens and combined oral contraceptive pills (COCPs) may mitigate hyperandrogenism-related symptoms of polycystic ovary syndrome (PCOS). However, their efficacy and safety in PCOS remain unclear as previous reviews have focused on non-PCOS populations. To inform the 2023 International Evidence-based Guideline in PCOS, we conducted the first systematic review and meta-analysis investigating the efficacy and safety of anti-androgens in the management of hormonal and clinical features of PCOS. Methods: We systematically searched MEDLINE, Embase, PsycInfo, All EBM reviews, and CINAHL up to 28th June 2023 for randomised controlled trials (RCTs) examining oral anti-androgen use, alone or in combination with metformin, COCPs, lifestyle, or other interventions, in women of any age, with PCOS diagnosed by Rotterdam, National Institutes of Health or Androgen Excess & PCOS Society criteria, and using a form of contraception. Non-English studies and studies of less than 6 months duration or which used the same anti-androgen regimen in both/all groups were excluded in order to establish efficacy for the clinical outcomes of interest. Three authors screened articles against selection criteria and assessed risk of bias and quality using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. Critical outcomes (prioritised during guideline development for GRADE purposes) included weight, body mass index (BMI), irregular cycles, hirsutism, liver function, and quality of life. Random effects meta-analyses were conducted where appropriate. This study is registered with PROSPERO, CRD42022345640. Findings: From 1660 studies identified in the search, 27 articles comprising 20 unique studies were included. Of these, 13 studies (n = 961) were pooled in meta-analysis. Seven studies had a high risk of bias, nine moderate and four low. Anti-androgens included finasteride, flutamide, spironolactone, or bicalutamide. In meta-analysis, anti-androgens + lifestyle were superior to metformin + lifestyle for hirsutism (weighted mean difference [WMD] [95% CI]: −1.59 [−3.06, −0.12], p = 0.03; I2 = 74%), SHBG (7.70 nmol/l [0.75, 14.66], p = 0.03; I2 = 0%), fasting insulin and fasting insulin: glucose ratio (−2.11 μU/ml [−3.97, −0.26], p = 0.03; I2 = 0% and −1.12 [−1.44, −0.79], p

Abstract Background Process improvement in healthcare is informed by knowledge from the private sector. Skilled individuals may aid the adoption of this knowledge by frontline care delivery workers through knowledge brokering. However, the effectiveness of those who broker knowledge is limited when the context they work within proves unreceptive to their efforts. We therefore need greater insight into the contextual conditions that support individuals to broker process improvement knowledge to the frontline of care delivery, and how policy makers and organizations might generate such conditions. Methods Our research took place in a healthcare system within an Australian State. We undertook a qualitative, embedded single case study over the four year period of a process improvement intervention encompassing 57 semi-structured interviews (with knowledge brokers, policy makers, and executive sponsors), 12 focus groups, and 137 h of observation, which included the frontline implementation of actual process improvement initiatives, where knowledge brokering took place. Results We identified four phases of the process improvement intervention that moved towards a more mature collaboration within which knowledge brokering by improvement advisors began to emerge as effective. In the first phase knowledge brokering was not established. In the second phase, whilst knowledge brokering had been initiated, the knowledge being brokered lacked legitimacy amongst frontline practitioners, resulting in resistance. Only in the fourth and final phase of the intervention did the collective experience of policy makers result in reflections on how they might engender a more receptive context for knowledge brokering. Conclusion We highlight a number of suggested actions that policy makers might consider, if they wish to engender contextual conditions that support knowledge brokering. Policy makers might consider: ensuring they respect local context and experience, by pulling good ideas upward, rather than imposing foreign knowledge from on high; facilitating the lateral diffusion of knowledge by building cultural linkages between people and organizations; strengthening collaboration, not competition, so that trans-organisational flow of ideas might be encouraged; being friend, not foe, to healthcare organizations on their knowledge integration journey. In sum, we suggest that top-down approaches to facilitating the diffusion and adoption of new ideas ought to be reconsidered.

BackgroundUnwarranted extended length of stay (LOS) increases the risk of hospital-acquired complications, morbidity, and all-cause mortality and needs to be recognized and addressed proactively.ObjectiveThis systematic review aimed to identify validated prediction variables and methods used in tools that predict the risk of prolonged LOS in all hospital admissions and specifically General Medicine (GenMed) admissions.MethodLOS prediction tools published since 2010 were identified in five major research databases. The main outcomes were model performance metrics, prediction variables, and level of validation. Meta-analysis was completed for validated models. The risk of bias was assessed using the PROBAST checklist.ResultsOverall, 25 all admission studies and 14 GenMed studies were identified. Statistical and machine learning methods were used almost equally in both groups. Calibration metrics were reported infrequently, with only 2 of 39 studies performing external validation. Meta-analysis of all admissions validation studies revealed a 95% prediction interval for theta of 0.596 to 0.798 for the area under the curve. Important predictor categories were co-morbidity diagnoses and illness severity risk scores, demographics, and admission characteristics. Overall study quality was deemed low due to poor data processing and analysis reporting.ConclusionTo the best of our knowledge, this is the first systematic review assessing the quality of risk prediction models for hospital LOS in GenMed and all admissions groups. Notably, both machine learning and statistical modeling demonstrated good predictive performance, but models were infrequently externally validated and had poor overall study quality. Moving forward, a focus on quality methods by the adoption of existing guidelines and external validation is needed before clinical application.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42021272198.

IntroductionThe aim of the study was to identify available polycystic ovary syndrome (PCOS) models of care (MoCs) and describe their characteristics and alignment with the international PCOS guideline.MethodsOvid MEDLINE, All EBM, PsycINFO, Embase, and CINAHL were searched from inception until 11 July 2022. Any study with a description of a PCOS MoC was included. Non-evidence-based guidelines, abstracts, study protocols, and clinical trial registrations were excluded. We also excluded MoCs delivered in research settings to minimize care bias. Meta-analysis was not performed due to heterogeneity across MoCs. We describe and evaluate each MoC based on the recommendations made by the international evidence-based guideline for assessing and managing PCOS.ResultsOf 3,671 articles, six articles describing five MoCs were included in our systematic review. All MoCs described a multidisciplinary approach, including an endocrinologist, dietitian, gynecologist, psychologist, dermatologist, etc. Three MoCs described all aspects of PCOS care aligned with the international guideline recommendations. These include providing education on long-term risks, lifestyle interventions, screening and management of emotional well-being, cardiometabolic diseases, and the dermatological and reproductive elements of PCOS. Three MoCs evaluated patients’ and healthcare professionals’ satisfaction, with generally positive findings. Only one MoC explored the impact of their service on patients’ health outcomes and showed improvement in BMI.ConclusionThere is limited literature describing PCOS MoCs in routine practice. Future research should explore developing cost-effective co-created multidisciplinary PCOS MoCs globally. This may be facilitated by the exchange of best practices between institutions with an established MoC and those who are interested in setting one up.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346539, identifier CRD42022346539.

Objective: To develop and translate rigorous, comprehensive evidence-based guidelines for diagnosis, assessment, and treatment, to improve the lives of those with polycystic ovary syndrome (PCOS) worldwide. Here we will focus on diagnosis. Participants: Extensive health professional and consumer or patient engagement informed the guideline priority areas. International society-nominated panels included consumers, and experts in paediatrics, endocrinology, gynaecology, primary care, reproductive endocrinology, psychology, dietetics, exercise physiology, sleep, bariatric/metabolic surgery, public health, other co-opted experts, project management, evidence synthesis and translation. Evidence: Best practice, evidence-based guideline development involved extensive evidence synthesis and the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework covered evidence quality, feasibility, acceptability, cost, implementation and ultimately recommendation strength. Process: Governance included an international advisory board, project board and five guideline development groups with 52 members, consumer, and translation committees. The Centre for Research Excellence in Women’s Health in Reproductive Life, funded by the Australian National Health and Medical Research Council (NHMRC), and led by Monash University, partnered with the American Society for Reproductive Medicine, the Endocrine Society, the European Society of Endocrinology and the European Society of Human Reproduction and Embryology. Thirty-six organisations collaborated with international meetings over nine months. Fifty-five prioritised clinical questions involved 52 systematic and three narrative reviews, generating evidence-based and consensus recommendations with accompanying practice points. Committee members nominated by collaborating organisations provided international peer review, and evidence expert-reviewed methods and outputs were submitted to NHMRC for independent review. Recommendations: PCOS should be diagnosed using the revised consensus Rotterdam criteria, which are now updated to evidence-based criteria in the International Guideline. In adults this requires the presence of two of i) clinical/biochemical hyperandrogenism ii) ovulatory dysfunction and iii) polycystic ovaries on ultrasound or elevated anti-mullerian hormone (AMH) levels, after other causes of these features are excluded. Where irregular menstrual cycles and hyperandrogenism are present, ultrasound or AMH are not required for diagnosis. In adolescents, both hyperandrogenism and ovulatory dysfunction are required, with ultrasound and AMH not recommended, due to poor specificity. Conclusion: Overall, evidence in PCOS is low to moderate quality. Based on high prevalence and significant health impact, greater priority, funding, and research is recommended. Guideline translation will be extensive including multilingual education outputs and evidence-based resources for consumers (the ASKPCOS app), healthcare professionals and policy makers.

Objective Systematic review of length of stay (LOS) prediction models to assess the study methods (including prediction variables), study quality, and performance of predictive models (using area under receiver operating curve (AUROC)) for general surgery populations and total knee arthroplasty (TKA). Method LOS prediction models published since 2010 were identified in five major research databases. The main outcomes were model performance metrics including AUROC, prediction variables, and level of validation. Risk of bias was assessed using the PROBAST checklist. Results Five general surgery studies (15 models) and 10 TKA studies (24 models) were identified. All general surgery and 20 TKA models used statistical approaches; 4 TKA models used machine learning approaches. Risk scores, diagnosis, and procedure types were predominant predictors used. Risk of bias was ranked as moderate in 3/15 and high in 12/15 studies. Discrimination measures were reported in 14/15 and calibration measures in 3/15 studies, with only 4/39 externally validated models (3 general surgery and 1 TKA). Meta-analysis of externally validated models (3 general surgery) suggested the AUROC 95% prediction interval is excellent and ranges between 0.803 and 0.970. Conclusion This is the first systematic review assessing quality of risk prediction models for prolonged LOS in general surgery and TKA groups. We showed that these risk prediction models were infrequently externally validated with poor study quality, typically related to poor reporting. Both machine learning and statistical modelling methods, plus the meta-analysis, showed acceptable to good predictive performance, which are encouraging. Moving forward, a focus on quality methods and external validation is needed before clinical application.

Abstract Background Implementation science seeks to enable change, underpinned by theories and frameworks such as the Consolidated Framework for Implementation Research (CFIR). Yet academia and frontline healthcare improvement remain largely siloed, with limited integration of implementation science methods into frontline improvement where the drivers include pragmatic, rapid change. Using the CIFR lens, we aimed to explore how pragmatic and complex healthcare improvement and implementation science can be integrated. Methods Our research involved the investigation of a case study that was undertaking the implementation of an improvement intervention at a large public health service. Our research involved qualitative data collection methods of semi-structured interviews and non-participant observations of the implementation team delivering the intervention. Thematic analysis identified key themes from the qualitative data. We examined our themes through the lens of CFIR to gain in-depth understanding of how the CFIR components operated in a ‘real-world’ context. Results The key themes emerging from our research outlined that leadership, context and process are the key components that dominate and affect the implementation process. Leadership which cultivates connections with front line clinicians, fosters engagement and trust. Navigating context was facilitated by ‘bottom-up’ governance. Multi-disciplinary and cross-sector capability were key processes that supported pragmatic and agile responses in a changing complex environment. Process reflected the theoretically-informed, and iterative implementation approach. Mapping CFIR domains and constructs, with these themes demonstrated close alignment with the CFIR. The findings bring further depth to CFIR. Our research demonstrates that leadership which has a focus on patient need as a key motivator to engage clinicians, which applies and ensures iterative processes which leverage contextual factors can achieve successful, sustained implementation and healthcare improvement outcomes. Conclusions Our longitudinal study highlights insights that strengthen alignment between implementation science and pragmatic frontline healthcare improvement. We identify opportunities to enhance the relevance of CFIR in the ‘real-world’ setting through the interconnected nature of our themes. Our study demonstrates actionable knowledge to enhance the integration of implementation science in healthcare improvement.

IntroductionWomen with previous gestational diabetes mellitus (GDM) are at increased risk of type 2 diabetes (T2D). Guidelines recommend postnatal diabetes screening (oral glucose tolerance test or HbA1c) typically 6-12 weeks after birth, with screening maintained at regular intervals thereafter. Despite this, around half of women are not screened, representing a critical missed opportunity for early identification of prediabetes or type 2 diabetes. While policy and practice-level recommendations are comprehensive, those at the personal-level primarily focus on increasing screening knowledge and risk perception, potentially missing other influential behavioral determinants. We aimed to identify modifiable, personal-level factors impacting postpartum type 2 diabetes screening among Australian women with prior gestational diabetes and recommend intervention functions and behavior change techniques to underpin intervention content.Research design and methodsSemi-structured interviews with participants recruited via Australia’s National Gestational Diabetes Register, using a guide based on the Theoretical Domains Framework (TDF). Using an inductive-deductive approach, we coded data to TDF domains. We used established criteria to identify ‘important’ domains which we then mapped to the Capability, Opportunity, Motivation–Behavior (COM-B) model.ResultsNineteen women participated: 34 ± 4 years, 19 ± 4 months postpartum, 63% Australian-born, 90% metropolitan, 58% screened for T2D according to guidelines. Eight TDF domains were identified: ‘knowledge’, ‘memory, attention, and decision-making processes’, ‘environmental context and resources’, ‘social influences’, ‘emotion’, ‘beliefs about consequences’, ‘social role and identity’, and ‘beliefs about capabilities’. Study strengths include a methodologically rigorous design; limitations include low recruitment and homogenous sample.ConclusionsThis study identified numerous modifiable barriers and enablers to postpartum T2D screening for women with prior GDM. By mapping to the COM-B, we identified intervention functions and behavior change techniques to underpin intervention content. These findings provide a valuable evidence base for developing messaging and interventions that target the behavioral determinants most likely to optimize T2D screening uptake among women with prior GDM.

Abstract Background Gestational diabetes (GDM) impacts 8–18% of pregnancies and greatly increases both maternal and child risk of developing non-communicable diseases such as type 2 diabetes and obesity. Whilst lifestyle interventions in pregnancy and postpartum reduce this risk, a research translation gap remains around delivering implementable interventions with adequate population penetration and participation. Impact Diabetes Bump2Baby is an implementation project of an evidence-based system of care for the prevention of overweight and obesity. Bump2Baby and Me is the multicentre randomised controlled trial investigating the effectiveness of a mHealth coaching programme in pregnancy and postpartum for women at high risk of developing GDM. Methods Eight hundred women will be recruited in early pregnancy from 4 clinical sites within Ireland, the UK, Spain, and Australia. Women will be screened for eligibility using the validated Monash GDM screening tool. Participants will be enrolled from 12 to 24 weeks’ gestation and randomised on a 1:1 basis into the intervention or control arm. Alongside usual care, the intervention involves mHealth coaching via a smartphone application, which uses a combination of synchronous and asynchronous video and text messaging, and allows for personalised support and goal setting with a trained health coach. The control arm receives usual care. All women and their children will be followed from early pregnancy until 12 months postpartum. The primary outcome will be a difference in maternal body mass index (BMI) of 0.8 kg/m2 at 12 months postpartum. Secondary maternal and infant outcomes include the development of GDM, gestational weight gain, pregnancy outcomes, improvements in diet, physical activity, sleep, and neonatal weight and infant growth patterns. The 5-year project is funded by the EU Commission Horizon 2020 and the Australian National Health and Medical Research Council. Ethical approval has been received. Discussion Previous interventions have not moved beyond tightly controlled efficacy trials into routine service delivery. This project aims to provide evidence-based, sustainable support that could be incorporated into usual care for women during pregnancy and postpartum. This study will contribute evidence to inform the early prevention of non-communicable diseases like obesity and diabetes in mothers and the next generation. Trial registration Australian New Zealand Clinical Trials Registry ACTRN12620001240932 . Registered on 19 November 2020

ContextPre-clinical evidence suggests that prolactin has important metabolic functions in pregnancy and postpartum, in addition to lactogenic actions.ObjectiveTo explore the relationship between prolactin and maternal metabolic outcomes in human pregnancy and postpartum, particularly in relation to gestational diabetes mellitus (GDM).Data sourcesMEDLINE via OVID, CINAHL plus, Embase.Study selectionEligible studies included women who were pregnant or up to 12 months postpartum, reporting at least one maternal serum prolactin level in relation to key metabolic outcomes including GDM, glycaemic parameters, obesity, and gestational weight gain.Data extractionTwo independent reviewers extracted data.Data synthesisTwenty-six articles were included. Meta-analysis showed no relationship between maternal prolactin levels and GDM status, with a weighted mean difference of -2.14 ng/mL (95% CI -12.54 to 8.27 ng/mL, p=0.7) between GDM and controls in early pregnancy (n=3 studies) and -3.89 ng/mL (95% CI, -15.20 to 7.41 ng/mL, p=0.5) in late pregnancy (n=11 studies). In narrative synthesis of other outcomes (due to study heterogeneity and/or lack of data), prolactin levels were not associated with maternal glycaemic or weight-related parameters during pregnancy, but in the postpartum period (particularly with lactation) a high-prolactin environment was associated with low circulating insulin and beta-cell function, and increased insulin sensitivity.ConclusionsCurrent evidence from human studies does not clearly support a relationship between prolactin and metabolic parameters during pregnancy, including with GDM status. Elevated prolactin was associated with lower insulin and beta-cell function and higher insulin sensitivity in the post-partum period, but the direction of causality remains unclear.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier [CRD42021262771].

Aims: Increasing evidence for benefit of early detection of cystic fibrosis related diabetes (CFRD) coupled with limitations of current diagnostic investigations has led to interest and utilisation of continuous glucose monitoring (CGM). We conducted a systematic review to assess current evidence on CGM compared to reference standard oral glucose tolerance test for the detection of dysglycemia in people with cystic fibrosis without confirmed diabetes. Methods: MEDLINE, Embase, CENTRAL, Evidence-Based Medicine Reviews, grey literature and six relevant journals were searched for studies published after year 2000. Studies reporting contemporaneous CGM metrics and oral glucose tolerance test results were included. Outcomes on oral glucose tolerance tests were categorised into a) normal, b) abnormal (indeterminate and impaired) or c) diabetic as defined by American Diabetes Association criteria. CGM outcomes were defined as hyperglycemia (≥1 peak sensor glucose ≥ 200 mg/dL), dysglycemia (≥1 peak sensor glucose ≥ 140–199 mg/dL) or normoglycemia (all sensor glucose peaks 200 mg/dL on CGM is not appropriate for the diagnosis of CFRD. Prospective studies correlating CGM metrics to disease-specific outcomes are needed to determine appropriate cut-points.

Pregnancy is a high-risk period for excess gestational weight gain and subsequent obesity development. Antenatal lifestyle interventions are prioritised to optimise weight, with current evidence demonstrating efficacy and associated reduction in risk of adverse maternal and neonatal outcomes. Yet, evidence to guide the field from efficacy-based to implementation research within real-world settings is lacking, and several key challenges remain. Here, we discuss key considerations to support the implementation of accessible, relevant, effective, and low-cost lifestyle interventions in routine pregnancy care. This includes identifying what components of lifestyle interventions are most effective, with pragmatic guidance on how to conduct implementation research, improving rigour in reporting to ensure learnings from implementation are captured, and recognising and addressing the socioecological aspects of obesity prevention, including supporting women living with socioeconomic disadvantage and reducing weight stigma.

BackgroundReproductive-aged women are a high-risk population group for accelerated weight gain and obesity development, with pregnancy recognized as a critical contributory life-phase. Healthy lifestyle interventions during the antenatal period improve maternal and infant health outcomes, yet translation and implementation of such interventions into real-world health care settings remains limited. ObjectiveWe aim to generate key implementation learnings to inform the feasibility of future scale up and determine the effectiveness of intervention delivery methods on engagement, experience, acceptability, knowledge, risk perception, health literacy, and modifiable weight-related health behaviors in women during preconception, pregnancy, and postpartum periods. MethodsThis randomized hybrid implementation effectiveness study will evaluate the penetration, reach, feasibility, acceptability, adoption, and fidelity of a healthy lifestyle intervention (OptimalMe) implemented into, and in partnership with, private health care. Individual health outcomes associated with implementation delivery mode, including knowledge, risk perception, health literacy, self-management, and health behaviors, are secondary outcomes. A total of 300 women aged 18 to 44 years, who are not pregnant but wish to conceive within the next 12 months, and with access to the internet will be recruited. All participants will receive the same digital lifestyle intervention, OptimalMe, which is supported by health coaching and text messages during preconception, pregnancy, and postpartum periods. We will use a parallel 2-arm design to compare telephone with videoconference remote delivery methods for health coaching. Methods are theoretically underpinned by the Consolidated Framework for Implementation Research and outcomes based on the Reach, Engagement, Adaptation, Implementation and Maintenance framework. ResultsThe study was approved on August 16, 2019 and has been registered. Recruitment commenced in July 2020, and data collection is ongoing. Results are expected to be published in 2022. ConclusionsThe study’s design aligns with best practice implementation research. Results will inform translation of evidence from randomized controlled trials on healthy lifestyle interventions into practice targeting women across preconception, pregnancy, and postpartum periods. Learnings will target consumers, program facilitators, health professionals, services, and policy makers to inform future scale up to ultimately benefit the health of women across these life-phases. Trial RegistrationAustralian and New Zealand Clinical Trial Registry ACTRN12620001053910; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378243&isReview=true International Registered Report Identifier (IRRID)DERR1-10.2196/33625

PurposeTo examine Australian psychological distress trends from 2001 to 2017/18, including analysis by age, sex, location, and household income.MethodsSecondary analysis of the working age population (18–64 years) in six successive representative national health surveys. Measures were prevalence of psychological distress at very-high symptom level (defined by a Kessler Psychological Distress Scale (K10) score of 30 or more) and combined high/very-high level (K10 score of 22 or more). Very-high K10 scores are associated with mental health problems meeting diagnostic thresholds in past year.ResultsFrom 2001 to 2017/18 Australian rates of K10 very-high distress rose significantly from 3.8 to 5.1% and combined high/very-high from 13.2 to 14.8%. In women aged 55–64, very-high distress rose significantly and substantially from 3.5 to 7.2% and high/very-high distress from 12.4 to 18.7%. In men aged 25–34, very-high distress increased from 2.1 to 4.0% and high/very-high from 10.6 to 11.5%. Income was strongly and inversely associated with distress (lowest vs. highest quintile adjusted OR 11.4). An apparent association of increased distress with regional location disappeared with adjustment for income.ConclusionAustralia’s population level of psychological distress increased significantly from 2001–2017/18, with levels highest in women and with rates inversely associated with income. This is likely to be indicative of increased community rates of mental disorders. Given that this has occurred whilst mental healthcare expenditure has increased, there is an urgent need to reconsider how best to respond to mental illness, including targeting the most vulnerable based on social determinants such as age, gender, and lower incomes.

IntroductionUsing body mass index (BMI) as a proxy, previous Mendelian randomization (MR) studies found total causal effects of general obesity on polycystic ovarian syndrome (PCOS). Hitherto, total and direct causal effects of general- and central obesity on PCOS have not been comprehensively analyzed.ObjectivesTo investigate the causality of central- and general obesity on PCOS using surrogate anthropometric markers.MethodsSummary GWAS data of female-only, large-sample cohorts of European ancestry were retrieved for anthropometric markers of central obesity (waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR)) and general obesity (BMI and its constituent variables-weight and height), from the IEU Open GWAS Project. As the outcome, we acquired summary data from a large-sample GWAS (118870 samples; 642 cases and 118228 controls) within the FinnGen cohort. Total causal effects were assessed via univariable two-sample Mendelian randomization (2SMR). Genetic architectures underlying causal associations were explored. Direct causal effects were analyzed by multivariable MR modelling.ResultsInstrumental variables demonstrated no weak instrument bias (F > 10). Four anthropometric exposures, namely, weight (2.69-77.05), BMI (OR: 2.90-4.06), WC (OR: 6.22-20.27), and HC (OR: 6.22-20.27) demonstrated total causal effects as per univariable 2SMR models. We uncovered shared and non-shared genetic architectures underlying causal associations. Direct causal effects of WC and HC on PCOS were revealed by two multivariable MR models containing exclusively the anthropometric markers of central obesity. Other multivariable MR models containing anthropometric markers of both central- and general obesity showed no direct causal effects on PCOS.ConclusionsBoth and general- and central obesity yield total causal effects on PCOS. Findings also indicated potential direct causal effects of normal weight-central obesity and more complex causal mechanisms when both central- and general obesity are present. Results underscore the importance of addressing both central- and general obesity for optimizing PCOS care.