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BackgroundMultimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs in excess of ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised.AimTo examine variation in prevalence using different definitions of multimorbidity.Design and settingCross-sectional study of 1 168 620 people in England.MethodComparison of multimorbidity (MM) prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 International Classification of Diseases, 10th revision chapters), and mental–physical MM (≥2 LTCs where ≥1 mental health LTC and ≥1 physical health LTC are recorded). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions.ResultsMM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental–physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (adjusted odds ratio [aOR] 58.09, 95% confidence interval [CI] = 56.13 to 60.14; aOR 77.69, 95% CI = 75.33 to 80.12; and aOR 102.06, 95% CI = 98.61 to 105.65; respectively), but mental–physical MM was much less strongly associated (aOR 4.32, 95% CI = 4.21 to 4.43). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived decile. This was most marked in mental–physical MM at 40–45 years younger, followed by MM2+ at 15–20 years younger, and MM3+ and MM3+ from 3+ at 10–15 years younger. Females had higher prevalence of multimorbidity under all definitions, which was most marked for mental–physical MM.ConclusionEstimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies.

Background: Patients with anterior cruciate ligament (ACL) revision report lower outcome scores on validated knee questionnaires postoperatively compared to cohorts with primary ACL reconstruction. In a previously active population, it is unclear if patient-reported outcomes (PROs) are associated with a return to activity (RTA) or vary by sports participation level (higher level vs. recreational athletes). Hypotheses: Individual RTA would be associated with improved outcomes (ie, decreased knee symptoms, pain, function) as measured using validated PROs. Recreational participants would report lower PROs compared with higher level athletes and be less likely to RTA. Study Design: Cohort study; Level of evidence, 2. Methods: There were 862 patients who underwent a revision ACL reconstruction (rACLR) and self-reported physical activity at any level preoperatively. Those who did not RTA reported no activity 2 years after revision. Baseline data included patient characteristics, surgical history and characteristics, and PROs: International Knee Documentation Committee questionnaire, Marx Activity Rating Scale, Knee injury and Osteoarthritis Outcome Score, and the Western Ontario and McMaster Universities Osteoarthritis Index. A binary indicator was used to identify patients with same/better PROs versus worse outcomes compared with baseline, quantifying the magnitude of change in each direction, respectively. Multivariable regression models were used to evaluate risk factors for not returning to activity, the association of 2-year PROs after rACLR surgery by RTA status, and whether each PRO and RTA status differed by participation level. Results: At 2 years postoperatively, approximately 15% did not RTA, with current smokers (adjusted odds ratio [aOR] = 3.3; P = .001), female patients (aOR = 2.9; P < .001), recreational participants (aOR = 2.0; P = .016), and those with a previous medial meniscal excision (aOR = 1.9; P = .013) having higher odds of not returning. In multivariate models, not returning to activity was significantly associated with having worse PROs at 2 years; however, no clinically meaningful differences in PROs at 2 years were seen between participation levels. Conclusion: Recreational-level participants were twice as likely to not RTA compared with those participating at higher levels. Within a previously active cohort, no RTA was a significant predictor of lower PROs after rACLR. However, among patients who did RTA after rACLR, approximately 20% reported lower outcome scores. Most patients with rACLR who were active at baseline improved over time; however, patients who reported worse outcomes at 2 years had a clinically meaningful decline across all PROs.

To evaluate the time-varying cardio-protective effect of glucagon-like peptide-1 receptor agonists (GLP-1RAs) using pooled data from eight contemporary cardiovascular outcome trials using the difference in the restricted mean survival time (ΔRMST) as the effect estimate.Data from eight multinational cardiovascular outcome randomized controlled trials of GLP-1RAs for type 2 diabetes mellitus were pooled. Flexible parametric survival models were fit from published Kaplan-Meier plots. The differences between arms in RMST (ΔRMST) were calculated at 12, 24, 36 and 48 months. ΔRMST values were pooled using an inverse variance-weighted random-effects model; heterogeneity was tested with Cochran's Q statistic. The endpoints studied were: three-point major adverse cardiovascular events (MACE), all-cause mortality, stroke, cardiovascular mortality and myocardial infarction.We included eight large (3183-14 752 participants, total = 60 080; median follow-up range: 1.5 to 5.4 years) GLP-1RA trials. Among GLP-1RA recipients, we observed an average delay in three-point MACE of 0.03, 0.15, 0.37 and 0.63 months at 12, 24, 36 and 48 months, respectively. At 48 months, while cardiovascular mortality was comparable in both arms (pooled ΔRMST 0.163 [-0.112, 0.437]; P = 0.24), overall survival was higher (ΔRMST = 0.261 [0.08-0.43] months) and stroke was delayed (ΔRMST 0.22 [0.15-0.33]) in patients receiving GLP-1RAs.Glucagon-like peptide-1 receptor agonists may delay the occurrence of MACE by an average of 0.6 months at 48 months, with meaningfully larger gains in patients with cardiovascular disease. This metric may be easier for clinicians and patients to interpret than hazard ratios, which assume a knowledge of absolute risk in the absence of treatment.

ObjectivesTrials often do not represent their target populations, threatening external validity. The aim was to assess whether age, sex, comorbidity count and/or race/ethnicity are associated with likelihood of screen failure (i.e., failure to be randomised to the trial for any reason) among potential trial participants.DesignBayesian meta-analysis of individual participant-level data (IPD).SettingIndustry-funded phase 3/4 trials in chronic medical conditions. Participants were identified as “randomised” or “screen failure” using trial IPD.ParticipantsData were available for 52 trials involving 72,178 screened individuals of whom 24,733 (34%) failed screening.Main outcome measuresFor each trial, logistic regression models were constructed to assess likelihood of screen failure, regressed on age (per 10-year increment), sex (male versus female), comorbidity count (per one additional comorbidity) and race/ethnicity. Trial-level analyses were combined in Bayesian hierarchical models with pooling across condition.ResultsIn age- and sex-adjusted models, neither age nor sex was associated with increased odds of screen failure, though weak associations were detected after additionally adjusting for comorbidity (age, per 10-year increment: odds ratio [OR] 1.02; 95% credibility interval [CI] 1.01 to 1.04 and male sex: OR 0.95; 95% CI 0.91 to 1.00). Comorbidity count was weakly associated with screen failure, but in an unexpected direction (OR 0.97 per additional comorbidity, 95% CI 0.94 to 1.00, adjusted for age and sex). Those who self-reported as Black were slightly more likely to fail screening (OR 1.04; 95% CI 0.99 to 1.09); an effect which persisted after adjustment for age, sex and comorbidity count (OR 1.05; 95% CI 0.98 to 1.12).ConclusionsAge, sex, comorbidity count and Black race/ethnicity were not strongly associated with increased likelihood of screen failure. Proportionate increases in screening these underserved populations may improve representation in trials.Trial registrationRelevant trials in chronic medical conditions were identified according to pre-specified criteria (PROSPERO CRD42018048202).

BackgroundMultimorbidity prevalence rates vary considerably depending on the conditions considered in the morbidity count, but there is no standardised approach to the number or selection of conditions to include.Methods and FindingsWe conducted a cross-sectional study using English primary care data for 1168260 participants who were all people alive and permanently registered with 149 included general practices. Outcome measures of the study were prevalence estimates of multimorbidity when varying the number and selection of conditions considered (≥two conditions) for 80 conditions. Included conditions featured in ≥one of the nine published lists of conditions examined in the study and/or phenotyping algorithms in the Health Data Research UK Phenotype Library. First, multimorbidity prevalence was calculated when considering the individually most common two conditions, three conditions, etc, up to 80 conditions. Second, prevalence was calculated using nine condition-lists from published studies. Analyses were stratified by dependent variables age, socioeconomic position, and sex. Prevalence when only the two commonest conditions were considered was 4.6% (95%CI [4.6,4.6] p 99% of that measured when considering all 80 conditions was 52 for the whole population but was lower in older people (29 in >80 years) and higher in younger people (71 in 0–9-year-olds). Nine published condition-lists were examined; these were either recommended for measuring multimorbidity, used in previous highly cited studies of multimorbidity prevalence, or widely applied measures of ‘comorbidity’. Multimorbidity prevalence using these lists varied from 11.1% to 36.4%. A limitation of the study is that conditions were not always replicated using the same ascertainment rules as previous studies to improve comparability across condition lists, but this highlights further variability in prevalence estimates across studies.ConclusionsIn this study we observed that varying the number and selection of conditions results in very large differences in multimorbidity prevalence, and different numbers of conditions are needed to reach ceiling rates of multimorbidity prevalence in certain groups of people. These findings imply that there is a need for a standardised approach to defining multimorbidity, and to facilitate this, researchers can use existing condition-lists associated with highest multimorbidity prevalence.Author summaryWhy was this study done?There is wide variety in the conditions considered by researchers when measuring multimorbidity prevalence.A systematic review of 566 studies, published in 2021, found lack of consensus in the selection of conditions considered.In half of studies only eight conditions (diabetes, stroke, cancer, chronic obstructive pulmonary disease, hypertension, coronary heart disease, chronic kidney disease, and heart failure) were consistently considered; and the number of conditions considered varied from 2 to 285 (median 17).A more consistent approach to measuring multimorbidity is needed to facilitate comparability and generalisability across studies.What did the researchers do and find?This study investigated the relationship between the number and selection of conditions considered and the impact on multimorbidity prevalence.There are large differences in prevalence, a range of 4.6% to 40.5%, when different numbers and selections of conditions are considered.Nine published condition-lists were examined; including those recommended for measuring multimorbidity, previously used to measure multimorbidity prevalence, or measures of ‘comorbidity’.Highest multimorbidity prevalence was found when using Ho always + usually (a list derived from a recent Delphi consensus study), Barnett (widely used to measure multimorbidity prevalence), and Fortin (a list recommended for use in measuring multimorbidity).People who are the oldest, living in the most deprived areas, and men require fewer conditions to be considered to reach close to multimorbidity prevalence when considering all 80 conditions (the ceiling effect, where the prevalence approaches the upper limit of prevalence possible in the study).What do these findings mean?All conditions were counted in the same way (the presence of the condition ever recorded) to improve comparability, however in previous studies conditions were counted according to varying rules, highlighting that further variability in prevalence estimates across studies will happen because of variation in how each condition is measured.There is a need for standardisation when measuring multimorbidity prevalence so that results across studies are comparable and population subgroups are accurately represented.To address this, researchers can consider using the Ho always + usually, Barnett, or Fortin condition lists.

Background Important disparities in the treatment and outcomes of women and men with atrial fibrillation (AF) are well recognized. Whether introduction of direct oral anticoagulants has reduced disparities in treatment is uncertain. Methods and Results All patients who had an incident hospitalization from 2010 to 2019 with nonvalvular AF in Scotland were included in the present cohort study. Community drug dispensing data were used to determine prescribed oral anticoagulation therapy and comorbidity status. Logistic regression modeling was used to evaluate patient factors associated with treatment with vitamin K antagonists and direct oral anticoagulants. A total of 172 989 patients (48% women [82 833 of 172 989]) had an incident hospitalization with nonvalvular AF in Scotland between 2010 and 2019. By 2019, factor Xa inhibitors accounted for 83.6% of all oral anticoagulants prescribed, while treatment with vitamin K antagonists and direct thrombin inhibitors declined to 15.9% and 0.6%, respectively. Women were less likely to be prescribed any oral anticoagulation therapy compared with men (adjusted odds ratio [aOR], 0.68 [95% CI, 0.67–0.70]). This disparity was mainly attributed to vitamin K antagonists (aOR, 0.68 [95% CI, 0.66–0.70]), while there was less disparity in the use of factor Xa inhibitors between women and men (aOR, 0.92 [95% CI, 0.90–0.95]). Conclusions Women with nonvalvular AF were significantly less likely to be prescribed vitamin K antagonists compared with men. Most patients admitted to the hospital in Scotland with incident nonvalvular AF are now treated with factor Xa inhibitors and this is associated with fewer treatment disparities between women and men.

BackgroundPeople with comorbidities are under-represented in clinical trials. Empirical estimates of treatment effect modification by comorbidity are lacking leading to uncertainty in treatment recommendations. We aimed to produce estimates of treatment effect modification by comorbidity using individual participant data (IPD).Methods and ResultsUsing 126 industry-sponsored phase 3/4 trials across 23 index conditions, we performed a two-stage IPD meta-analysis to estimate modification of treatment effect by comorbidity. We estimated the effect of comorbidity measured in 3 ways: (i) the number of comorbidities (in addition to the index condition), (ii) presence or absence of the six commonest comorbid diseases for each index condition, and (iii) using continuous markers of underlying conditions (e.g., estimated glomerular function).Comorbidities were under-represented in trial participants and few had >2 comorbidities. We found no evidence of modification of treatment efficacy by comorbidity, for any of the 3 measures of comorbidity. This was the case for 20 conditions for which the outcome variable was continuous (e.g., change in glycosylated haemoglobin in diabetes) and for three conditions in which the outcomes were discrete events (e.g., number of headaches in migraine). Although all were null, estimates of treatment effect modification were more precise in some cases (e.g., Sodium-glucose co-transporter inhibitors for type 2 diabetes – interaction term for comorbidity count 0.004, 95% CI - 0.01 to 0.02) while for others credible intervals were wide (e.g., corticosteroids for asthma – interaction term -0.22, 95% CI -1.07 to 0.54).ConclusionFor trials included in this analysis, there was no empirical evidence of treatment effect modification by comorbidity. Our findings support the assumption that estimates of treatment efficacy are constant, at least across modest levels of comorbidity.

ObjectivesTo investigate the association of primary acute cerebral venous thrombosis (CVT) with COVID-19 vaccination through complete ascertainment of all diagnosed CVT in the population of Scotland.DesignCase-crossover study comparing recent (1-14 days after vaccination) with less recent exposure to vaccination among cases of CVT.SettingNational data for Scotland from 1 December 2020, with diagnosed CVT case ascertainment through neuroimaging studies up to 17 May 2021 and diagnostic coding of hospital discharges up to 28 April 2021 and with linkage to vaccination records.Main outcome measurePrimary acute cerebral venous thrombosisResultsOf 50 primary acute CVT cases, 29 were ascertained only from neuroimaging studies, 2 were ascertained only from hospital discharges, and 19 were ascertained from both sources. Of these 50 cases, 14 had received the Astra-Zeneca ChAdOx1 vaccine and 3 the Pfizer BNT162b2 vaccine. The incidence of CVT per million doses in the first 14 days after vaccination was 2.2 (95% credible interval 0.9 to 4.1) for ChAdOx1 and 1 (95% credible interval 0.1 to 2.9) for BNT162b2. The rate ratio for CVT associated with exposure to ChAdOx1 in the first 14 days compared with exposure 15-84 days after vaccination was 3.2 (95% credible interval 1.1 to 9.5). The 95% credible interval for the rate ratio associated with recent versus less recent exposure to BNT162b2 (0.6 to 95.8) was too wide for useful inference.ConclusionsThese findings support a causal association between CVT and the AstraZeneca vaccine. The absolute risk of post-vaccination CVT in this population-wide study in Scotland was lower than has been reported for populations in Scandinavia and Germany; the explanation for this is not clear.What is already known on this topicThe risk of cerebral venous thrombosis (CVT) within 28 days of receiving the AstraZeneca ChAdOx1 vaccine has been estimated as 18 to 25 per million doses in Germany and Scandinavia, but only 5 per million doses in the UK based on the Yellow Card reporting scheme. Risk estimates based on adverse event reporting systems are subject to under-ascertainment and other biases.What this study addsAll diagnosed cases of CVT in Scotland were ascertained by searching neuroimaging studies from December 2020 to May 2021 and linked to national vaccination records. The risk of CVT within 28 days of vaccination with ChAdOx1 was estimated as 3.5 per million doses with an upper bound of 6 per million doses, against a background incidence of about 12 per million adults per year. This indicates that the Yellow Card system has not seriously underestimated the risk in the UK; the explanation for higher risk in other European countries is not clear.

Eczema and asthma are allergic diseases and two of the commonest chronic conditions in high-income countries. Their co-existence with other allergic conditions is common, but little research exists on wider multimorbidity with these conditions. We set out to identify and compare clusters of multimorbidity in people with eczema or asthma and people without. Using routinely-collected primary care data from the U.K. Clinical Research Practice Datalink GOLD, we identified adults ever having eczema (or asthma), and comparison groups never having eczema (or asthma). We derived clusters of multimorbidity from hierarchical cluster analysis of Jaccard distances between pairs of diagnostic categories estimated from mixed-effects logistic regressions. We analysed 434,422 individuals with eczema (58% female, median age 47 years) and 1,333,281 individuals without (55% female, 47 years), and 517,712 individuals with asthma (53% female, 44 years) and 1,601,210 individuals without (53% female, 45 years). Age at first morbidity, sex and having eczema/asthma affected the scope of multimorbidity, with women, older age and eczema/asthma being associated with larger morbidity clusters. Injuries, digestive, nervous system and mental health disorders were more commonly seen in eczema and asthma than control clusters. People with eczema and asthma of all ages and both sexes may experience greater multimorbidity than people without eczema and asthma, including conditions not previously recognised as contributing to their disease burden. This work highlights areas where there is a critical need for research addressing the burden and drivers of multimorbidity in order to inform strategies to reduce poor health outcomes.

Introduction: Patients with type 2 diabetes mellitus (T2DM) undergoing coronary artery bypass grafting (CABG) are at risk of cardiovascular events. SGLT2i and GLP-1RA are effective cardio-protective agents, however, their prescription among CABG patients is uncertain. Methods: We analyzed the nationwide Veteran Affairs database (2016 – 2019) to report trends and factors associated with SGLT2i or GLP1RA prescription after CABG. Results: Among 5,109 patients operated at 40 different VA medical centers, 525/5109 (10.4%), 352/5109 (6.8%) and 91/5109 (1.8%) were prescribed SGLT2i, GLP-1RA and both respectively. Substantial increase in the quarterly SGLPT2i prescription rates (1.6% (2016Q1), 33% (2019Q4)) was present; less so for GLP-1RA (0.8% (2016Q1), 11.2% (2019Q4)). SGLT2i use was less likely with pre-existing vascular disease (OR 0.75-95%CI-[0.75,0.94]) or kidney disease (OR 0.72-95%CI-[0.58,0.88]), while GLP-1RA use was associated with obesity (OR 1.91-95%CI-[1.50,2.46]). Conclusion: The overall utilization of SGLT2i or GLP-1RA drugs in US Veterans with T2DM undergoing CABG is low, with SGLT2i preferred over GLP-1RA.

Background Multimorbidity (the presence of two or more chronic conditions) is common amongst people with chronic kidney disease, but it is unclear which conditions cluster together and if this changes as kidney function declines. We explored which clusters of conditions are associated with different estimated glomerular filtration rates (eGFRs) and studied associations between these clusters and adverse outcomes. Methods Two population-based cohort studies were used: the Stockholm Creatinine Measurements project (SCREAM, Sweden, 2006–2018) and the Secure Anonymised Information Linkage Databank (SAIL, Wales, 2006–2021). We studied participants in SCREAM (404,681 adults) and SAIL (533,362) whose eGFR declined lower than thresholds (90, 75, 60, 45, 30 and 15 mL/min/1.73m2). Clusters based on 27 chronic conditions were identified. We described the most common chronic condition(s) in each cluster and studied their association with adverse outcomes using Cox proportional hazards models (all-cause mortality (ACM) and major adverse cardiovascular events (MACE)). Results Chronic conditions became more common and clustered differently across lower eGFR categories. At eGFR 90, 75, and 60 mL/min/1.73m2, most participants were in large clusters with no prominent conditions. At eGFR 15 and 30 mL/min/1.73m2, clusters involving cardiovascular conditions were larger and were at the highest risk of adverse outcomes. At eGFR 30 mL/min/1.73m2, in the heart failure, peripheral vascular disease and diabetes cluster in SCREAM, ACM hazard ratio (HR) is 2.66 (95% confidence interval (CI) 2.31–3.07) and MACE HR is 4.18 (CI 3.65–4.78); in the heart failure and atrial fibrillation cluster in SAIL, ACM HR is 2.23 (CI 2.04 to 2.44) and MACE HR is 3.43 (CI 3.22–3.64). Chronic pain and depression were common and associated with adverse outcomes when combined with physical conditions. At eGFR 30 mL/min/1.73m2, in the chronic pain, heart failure and myocardial infarction cluster in SCREAM, ACM HR is 2.00 (CI 1.62–2.46) and MACE HR is 4.09 (CI 3.39–4.93); in the depression, chronic pain and stroke cluster in SAIL, ACM HR is 1.38 (CI 1.18–1.61) and MACE HR is 1.58 (CI 1.42–1.76). Conclusions Patterns of multimorbidity and corresponding risk of adverse outcomes varied with declining eGFR. While diabetes and cardiovascular disease are known high-risk conditions, chronic pain and depression emerged as important conditions and associated with adverse outcomes when combined with physical conditions.

Given the advantages in transparency, reproducibility, adaptability and computational efficiency in R, there is a growing interest in converting existing spreadsheet-based models into an R script for model re-use and upskilling training among health economic modellers. The objective of this exercise was to convert the Scottish Cardiovascular Disease (CVD) Policy Model from Excel to R and discuss the lessons learnt throughout this process. The CVD model is a competing risk state transition cohort model. Four health economists, with varied experience of R, attempted to replicate an identical model structure in R based on the model in Excel and reproduce the intermediate and final results. Replications varied in their use of specialist health economics packages in addition to standard data management packages. Two versions of the CVD model were created in R along with a Shiny app. Version 1 was developed without health economics specialist packages and produced identical results to the Excel version. Version 2 used the heemod package and did not achieve the same results, possibly due to the non-standard elements of the model and limited time to adapt the functions. The R model requires less than half the computational time than the Excel model. Conversion of the spreadsheet models to script models is feasible for health economists. A step-by-step guide for the conversion process is provided and modellers' experience is discussed. Coding without specialist packages allows full flexibility, while specialist packages may add convenience if the model structure is suitable. Whichever approach is taken, transparency and replicability remain the key criteria in model programming. Model conversions must maintain standards in these areas regardless of the choice of software.

Background The applicability of randomised controlled trials of pharmacological agents to older people with frailty/multimorbidity is often uncertain, due to concerns that trials are not representative. However, assessing trial representativeness is challenging and complex. We explore an approach assessing trial representativeness by comparing rates of trial serious adverse events (SAE) to rates of hospitalisation/death in routine care. Methods This was an observational analysis of individual (125 trials, n=122,069) and aggregate-level drug trial data (483 trials, n=636,267) for 21 index conditions compared to population-based routine healthcare data (routine care). Trials were identified from ClinicalTrials.gov. Routine care comparison from linked primary care and hospital data from Wales, UK (n=2.3M). Our outcome of interest was SAEs (routinely reported in trials). In routine care, SAEs were based on hospitalisations and deaths (which are SAEs by definition). We compared trial SAEs in trials to expected SAEs based on age/sex standardised routine care populations with the same index condition. Using IPD, we assessed the relationship between multimorbidity count and SAEs in both trials and routine care and assessed the impact on the observed/expected SAE ratio additionally accounting for multimorbidity. Results For 12/21 index conditions, the pooled observed/expected SAE ratio was Conclusions Trial participants experience fewer SAEs than expected based on age/sex/condition hospitalisation and death rates in routine care, confirming the predicted lack of representativeness. This difference is only partially explained by differences in multimorbidity. Assessing observed/expected SAE may help assess the applicability of trial findings to older populations in whom multimorbidity and frailty are common.

Objective: \ud To review comparative effectiveness research (CER) using physician’s prescribing preference as an instrumental variable (PPP IV) in pharmacoepidemiology, and to review methodological studies that use simulation to evaluate the performance PPP IV in CER.\ud \ud Study design and setting: \ud We conducted a review of CER using PPP IV as well as studies evaluating the use of PPP IV by using simulation methods. We searched Ovid, PubMed, and Google Scholar databases from 2005 to 2020.\ud \ud Results: \ud We identified 6 simulation studies and 18 CER studies. The simulation studies explored the most suitable ways for using PPP IV in different settings (outcome types, sample size, the prevalence of outcomes) which can be useful guidance for using PPP IV in CER. The CERs studies identified show heterogeneity in terms of validation assumptions, estimation methods and sample size. Not all applied studies utilised the methodological insights from the simulation studies. However, they all concluded that PPP is a valid instrumental variable.\ud \ud Conclusion: \ud Future CER should consider a range of methodological issues to improve the validity of findings when using PPP IV. Specifically, studies should consider the impact of different choice of statistical methods, forms of proxy for measuring preference, time-varying exposures, and the type of outcome.

Background: Although graft choice may be limited in the revision setting based on previously used grafts, most surgeons believe that graft choice for anterior cruciate ligament (ACL) reconstruction is an important factor related to outcome. Hypothesis: In the ACL revision setting, there would be no difference between autograft and allograft in rerupture rate and patient-reported outcomes (PROs) at 6-year follow-up. Study Design: Cohort study; Level of evidence, 2. Methods: Patients who had revision surgery were identified and prospectively enrolled in this cohort study by 83 surgeons over 52 sites. Data collected included baseline characteristics, surgical technique and pathology, and a series of validated PRO measures. Patients were followed up at 6 years and asked to complete the identical set of PRO instruments. Incidence of additional surgery and reoperation because of graft failure were also recorded. Multivariable regression models were used to determine the predictors (risk factors) of PROs, graft rerupture, and reoperation at 6 years after revision surgery. Results: A total of 1234 patients including 716 (58%) men were enrolled. A total of 325 (26%) underwent revision using a bone-patellar tendon-bone (BTB) autograft; 251 (20%), soft tissue autograft; 289 (23%), BTB allograft; 302 (25%), soft tissue allograft; and 67 (5%), other graft. Questionnaires and telephone follow-up for subsequent surgery information were obtained for 809 (66%) patients, while telephone follow-up was only obtained for an additional 128 patients for the total follow-up on 949 (77%) patients. Graft choice was a significant predictor of 6-year Marx Activity Rating Scale scores ( P = .024). Specifically, patients who received a BTB autograft for revision reconstruction had higher activity levels than did patients who received a BTB allograft (odds ratio [OR], 1.92; 95% CI, 1.25-2.94). Graft rerupture was reported in 5.8% (55/949) of patients by their 6-year follow-up: 3.5% (16/455) of patients with autografts and 8.4% (37/441) of patients with allografts. Use of a BTB autograft for revision resulted in patients being 4.2 times less likely to sustain a subsequent graft rupture than if a BTB allograft were utilized ( P = .011; 95% CI, 1.56-11.27). No significant differences were found in graft rerupture rates between BTB autograft and soft tissue autografts ( P = .87) or between BTB autografts and soft tissue allografts ( P = .36). Use of an autograft was found to be a significant predictor of having fewer reoperations within 6 years compared with using an allograft ( P = .010; OR, 0.56; 95% CI, 0.36-0.87). Conclusion: BTB and soft tissue autografts had a decreased risk in graft rerupture compared with BTB allografts. BTB autografts were associated with higher activity level than were BTB allografts at 6 years after revision reconstruction. Surgeons and patients should consider this information when choosing a graft for revision ACL reconstruction.

Aims The Global Registry of Acute Coronary Events (GRACE) score was developed to evaluate risk in patients with myocardial infarction. However, its performance in type 2 myocardial infarction is uncertain. Methods and results In two cohorts of consecutive patients with suspected acute coronary syndrome from 10 hospitals in Scotland (n = 48 282) and a tertiary care hospital in Sweden (n = 22 589), we calculated the GRACE 2.0 score to estimate death at 1 year. Discrimination was evaluated by the area under the receiver operating curve (AUC), and compared for those with an adjudicated diagnosis of type 1 and type 2 myocardial infarction using DeLong’s test. Type 1 myocardial infarction was diagnosed in 4981 (10%) and 1080 (5%) patients in Scotland and Sweden, respectively. At 1 year, 720 (15%) and 112 (10%) patients died with an AUC for the GRACE 2.0 score of 0.83 [95% confidence interval (CI) 0.82–0.85] and 0.85 (95% CI 0.81–0.89). Type 2 myocardial infarction occurred in 1121 (2%) and 247 (1%) patients in Scotland and Sweden, respectively, with 258 (23%) and 57 (23%) deaths at 1 year. The AUC was 0.73 (95% CI 0.70–0.77) and 0.73 (95% CI 0.66–0.81) in type 2 myocardial infarction, which was lower than for type 1 myocardial infarction in both cohorts (P Conclusion The GRACE 2.0 score provided good discrimination for all-cause death at 1 year in patients with type 1 myocardial infarction, and moderate discrimination for those with type 2 myocardial infarction. Trial registration ClinicalTrials.gov number, NCT01852123.

Introduction Frailty and multimorbidity are common in type 2 diabetes (T2D), including people Methods Analysis of UK Biobank participants (n = 20,566) with T2D aged 40-72 years comparing two frailty measures (frailty phenotype and frailty index) and two multimorbidity measures (Charlson comorbidity index and a simply count of 40 long-term conditions (LTCs)). Outomes: mortality (all-cause, cardiovascular- and cancer-related mortality), Major Adverse Cardiovascular Event (MACE), hospitalization with hypoglycaemia or fall/fracture. Results Measure choice influenced the population identified: 42% of participants were identified as frail/multimorbid by at least one measure; only 2.2% were identified by all four measures. Both frailty and multimorbidity, by all measures, were prevalent throughout the age range studied. Each measure was associated with mortality, MACE, hypoglycaemia and falls. The absolute 5-year mortality risk was higher in older versus younger participants with a given level of frailty (e.g. 1.9%, and 9.9% in men aged 45 and 65, respectively, using frailty phenotype) or multimorbidity (e.g. 1.3%, and 7.8% in men with 4 LTCs aged 45 and 65, respectively). Using frailty phenotype, the relationship between higher HbA1c and mortality was stronger in frail compared with pre-frail or robust participants. Conclusion Assessment of frailty/multimorbidity should be embedded within routine management of middle-aged and older people with T2D. Method of identification as well as features such as age impact baseline risk and should influence clinical decisions (e.g. glycaemic control).

OBJECTIVE Studies using claims databases reported that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection >30 days earlier was associated with an increase in the incidence of type 1 diabetes. Using exact dates of diabetes diagnosis from the national register in Scotland linked to virology laboratory data, we sought to replicate this finding. RESEARCH DESIGN AND METHODS A cohort of 1,849,411 individuals aged RESULTS There were 365,080 individuals who had at least one detected SARS-CoV-2 infection during follow-up and 1,074 who developed type 1 diabetes. The rate ratio for incident type 1 diabetes associated with first positive test for SARS-CoV-2 (reference category: no previous infection) was 0.86 (95% CI 0.62, 1.21) for infection >30 days earlier and 2.62 (95% CI 1.81, 3.78) for infection in the previous 30 days. However, negative and positive SARS-CoV-2 tests were more frequent in the days surrounding diabetes presentation. In those aged 0–14 years, incidence of type 1 diabetes during 2020–2021 was 20% higher than the 7-year average. CONCLUSIONS Type 1 diabetes incidence in children increased during the pandemic. However, the cohort analysis suggests that SARS-CoV-2 infection itself was not the cause of this increase.

Background: Lytic or malpositioned tunnels may require bone grafting during revision anterior cruciate ligament reconstruction (rACLR) surgery. Patient characteristics and effects of grafting on outcomes after rACLR are not well described. Purpose: To describe preoperative characteristics, intraoperative findings, and 2-year outcomes for patients with rACLR undergoing bone grafting procedures compared with patients with rACLR without grafting. Study Design: Cohort study; Level of evidence, 3. Methods: A total of 1234 patients who underwent rACLR were prospectively enrolled between 2006 and 2011. Baseline revision and 2-year characteristics, surgical technique, pathology, treatment, and patient-reported outcome instruments (International Knee Documentation Committee [IKDC], Knee injury and Osteoarthritis Outcome Score [KOOS], Western Ontario and McMaster Universities Osteoarthritis Index, and Marx Activity Rating Scale [Marx]) were collected, as well as subsequent surgery information, if applicable. The chi-square and analysis of variance tests were used to compare group characteristics. Results: A total of 159 patients (13%) underwent tunnel grafting—64 (5%) patients underwent 1-stage and 95 (8%) underwent 2-stage grafting. Grafting was isolated to the femur in 31 (2.5%) patients, the tibia in 40 (3%) patients, and combined in 88 patients (7%). Baseline KOOS Quality of Life (QoL) and Marx activity scores were significantly lower in the 2-stage group compared with the no bone grafting group ( P≤ .001). Patients who required 2-stage grafting had more previous ACLRs ( P < .001) and were less likely to have received a bone–patellar tendon–bone or a soft tissue autograft at primary ACLR procedure ( P≤ .021) compared with the no bone grafting group. For current rACLR, patients undergoing either 1-stage or 2-stage bone grafting were more likely to receive a bone–patellar tendon–bone allograft ( P≤ .008) and less likely to receive a soft tissue autograft ( P≤ .003) compared with the no bone grafting group. At 2-year follow-up of 1052 (85%) patients, we found inferior outcomes in the 2-stage bone grafting group (IKDC score = 68; KOOS QoL score = 44; KOOS Sport/Recreation score = 65; and Marx activity score = 3) compared with the no bone grafting group (IKDC score = 77; KOOS QoL score = 63; KOOS Sport/Recreation score = 75; and Marx activity score = 7) ( P≤ .01). The 1-stage bone graft group did not significantly differ compared with the no bone grafting group. Conclusion: Tunnel bone grafting was performed in 13% of our rACLR cohort, with 8% undergoing 2-stage surgery. Patients treated with 2-stage grafting had inferior baseline and 2-year patient-reported outcomes and activity levels compared with patients not undergoing bone grafting. Patients treated with 1-stage grafting had similar baseline and 2-year patient-reported outcomes and activity levels compared with patients not undergoing bone grafting.

IntroductionCOVID-19 deaths are commoner among care-home residents, but the mortality burden has not been quantified.MethodsCare-home residency was identified via a national primary care registration database linked to national mortality data. Life expectancy was estimated using Makeham-Gompertz models, to (i) describe yearly life expectancy from Nov 2015 to Oct 2020 (ii) compare life expectancy (during 2016-2018) between care-home residents and the wider Scottish population and (iii) apply care-home life expectancy estimates to COVID-19 death counts to estimate years of life lost (YLL).ResultsAmong care-home residents, life expectancy in 2015/16 to 2019/20 ranged from 2.7 to 2.3 years for women and 2.3 to 1.8 years for men. Life expectancy was lowest in 2019/20. Age-sex specific life expectancy in 2016-2018 in care-home residents was lower than in the Scottish population (10 and 2.5 years in those aged 70 and 90 respectively). Rather than using national life tables, applying care-home specific life expectancies to COVID-19 deaths yields, mean YLLs for care-home residents were 2.6 and 2.2 for women and men respectively, with total care-home resident YLLs of 3,560 years in women and 2,046 years in men. In people aged over-70, approximately half of deaths and a quarter of YLL attributed to COVID-19 were accounted for by the 5% of over-70s who were care-home residents.ConclusionPrioritising care-home residents for vaccination is justified not only in terms of total deaths, but also in terms of years of life lost.Research in contextEvidence before this studyWe searched PubMed to 1st December 2020, with the terms (“nursing home” OR “care-home” OR “long-term care” OR “residential care”) AND (“mortality” OR “life expectancy” OR “length of stay”). We also searched for studies specific to the impact of the COVID-19 pandemic on those living in care-homes. We restricted our search to publications in English. Usual care-home life expectancy, in a UK context, has not previously been defined. One systematic review of length of stay was identified, which found significant heterogeneity in factors and associations. The impact of COVID-19 on excess mortality among care-home residents was noted, but the impact on life expectancy was not reported. Studies evaluating life expectancy among older people in the COVID-19 pandemic have not taken account of residency in their estimates.Added value of this studyUsing Scottish national representative linked data we describe the usual life expectancy of older adults (aged ≥70 years) living in care-homes, compared to older people living elsewhere. Deaths among care-home residents account for a considerable proportion of all mortality in older adults, around 19% for men and 30% for women. Life expectancy in care-home residents during the pandemic fell by almost 6 months, from 2.7 to 2.3 years in men and 2.1 to 1.8 years in women. In total, over 5,600 Years of Life were Lost (YLL) by care-home residents in Scotland who died with COVID-19. Around half of COVID-19 deaths and a quarter of YLL in those aged 70 years and over occurred among care-home residents. During the COVID-19 pandemic a smaller proportion of deaths among care-home residents occurred in hospitals.Implications of all the available evidencePrioritising the 5% of older adults who are care-home residents for vaccination against COVID-19 is justified both in terms of total deaths and total years of life lost. Individual and societal planning for care needs in older age relies on understanding usual care-home life expectancy and patterns of mortality. Understanding life expectancy may help clinicians, residents and their families make decisions about their health care, facilitating more informed discussions around their priorities and wishes. Population-wide estimates of YLL and burden of disease should take account of residency status, given the significant differences between life expectancy of those living in care-homes from their peers in other settings.

Background Frailty, an age-related state of vulnerability to adverse health outcomes, is an important factor in the management of diabetes. This systematic review aims to summarise the observational data on prevalence of frailty in diabetes and the association between frailty and generic (e.g. mortality) and diabetes specific (e.g. hypoglycaemia) outcomes. Methods We searched three electronic databases for observational studies assessing frailty in adults (≥18 years) with diabetes (type 1, type 2, or unspecified). Eligible studies quantified the prevalence or incidence of frailty or the association between frailty and clinical outcomes in the context of diabetes. Results 118 studies included, using 18 different frailty measures. Frailty phenotype was the most used (n = 69) followed by frailty index (n = 16) and the FRAIL scale (n = 10). Studies were highly heterogenous in terms of setting (88 community, 18 outpatient, 10 inpatient, 2 residential care), population demographics, and inclusion criteria. The median frailty prevalence in community-based studies using the frailty phenotype was 13% (interquartile range 7-18%). Frailty was identified in “middle-aged” (9%) or low ( Conclusions Frailty in diabetes is common but inconsistently measured. Frailty is associated with a range of adverse outcomes. Research gaps include the relationship between frailty and glycaemia (particularly hypoglycaemia and the relationship between HbA1c and outcomes in the context of frailty), and the impact of frailty in specific groups such as middle-aged people and in low and low-middle income countries.

Introduction Frailty is common in clinical practice, but trials rarely report on participant frailty. Consequently, clinicians and guideline-developers assume frailty is largely absent from trials and have questioned the relevance of trial findings to frail people. Therefore, we examined frailty in phase 3/4 industry-sponsored clinical trials of pharmacological interventions for three exemplar conditions: type 2 diabetes mellitus (T2DM), rheumatoid arthritis (RA), and chronic obstructive pulmonary disease (COPD). Methods We constructed a 40-item frailty index (FI) in 19 clinical trials (7 T2DM, 8 RA, 4 COPD, mean age 42–65 years) using individual-level participant data. Participants with a FI >0.24 were considered “frail”. Baseline disease severity was assessed using HbA1c for T2DM, Disease Activity Score-28 (DAS28) for RA, and % predicted FEV1 for COPD. Using generalised gamma regression, we modelled FI on age, sex and disease severity. In negative binomial regression we modelled serious adverse event rates on FI, and combined results for each index condition in a random-effects meta-analysis. Results All trials included frail participants: prevalence 7–21% in T2DM trials, 33–73% in RA trials, and 15–22% in COPD trials. Increased disease severity and female sex were associated with higher FI in all trials. Frailty was associated with age in T2DM and RA trials, but not in COPD. Across all trials, and after adjusting for age, sex, and disease severity, higher FI predicted increased risk of serious adverse events; the pooled incidence rate ratios (per 0.1-point increase in FI scale) were 1.46 (95% CI 1.21–1.75), 1.45 (1.13–1.87) and 1.99 (1.43–2.76) for T2DM, RA and COPD, respectively. Conclusion Frailty is identifiable and prevalent among middle aged and older participants in phase 3/4 drug trials and has clinically important safety implications. Trial data may be harnessed to better understand chronic disease management in people living with frailty.

Introduction Fewer clinical trials are carried out in older people. It is unclear how representative and applicable clinical trials carried out exclusively in older people are. We compared clinical trials recruiting older people exclusively “older trials” to those recruiting adults of all ages “all age trials”, using anti-hypertensives acting on the renin-angiotensin aldosterone system (RAAS drugs) as an exemplar. Method We searched the US clinical trials register 1, to identify all trials carried out exclusively in those aged over 60. From these we selected trials of RAAS drugs. These were matched in a 2:1 ratio to trials carried out in adults of all ages. Data regarding baseline characteristics, adverse events and eligibility criteria were collected from clinical trial reports and clinicaltrials.gov. Estimated associations were calculated for age, sex and adverse events. Eligibility criteria were described and ICD- 10 coded, as appropriate. Results 71 clinical trials were carried out exclusively in older people.13 related to RAAS drugs. Participants in “Older trials” had higher mean age (73.1 and 55.9 respectively), mean difference 16.17 (CI 15.31–17.02). Older trials had fewer male participants. Participants in older trials had lower mean body mass index (BMI). A higher rate of participants in older trials experienced serious adverse events. (2.07, CI 1.55–2.75.) Few older trials had upper age limits (23.1% V 27% all age trials). All trials had exclusion criteria in multiple ICD blocks. Concurrent medications were a more common exclusion criterion in older trials (61.5% v 40.9%). Conclusions Clinical trials carried out exclusively in older people are representative in terms of age, serious adverse events and eligibility. Although there are multiple exclusion criteria for clinical trial participation in both groups, this is not prohibitive. This supports carrying out more trials exclusively in older people. References 1. NIH, US national library of medicine.ClinicalTrials.gov Available at https://clinicaltrials.gov/

Summary Background HIV enhances human papillomavirus (HPV)-induced carcinogenesis. However, the contribution of HIV to cervical cancer burden at a population level has not been quantified. We aimed to investigate cervical cancer risk among women living with HIV and to estimate the global cervical cancer burden associated with HIV. Methods We did a systematic literature search and meta-analysis of five databases (PubMed, Embase, Global Health [ CABI.org ], Web of Science, and Global Index Medicus) to identify studies analysing the association between HIV infection and cervical cancer. We estimated the pooled risk of cervical cancer among women living with HIV across four continents (Africa, Asia, Europe, and North America). The risk ratio (RR) was combined with country-specific UNAIDS estimates of HIV prevalence and GLOBOCAN 2018 estimates of cervical cancer to calculate the proportion of women living with HIV among women with cervical cancer and population attributable fractions and age-standardised incidence rates (ASIRs) of HIV-attributable cervical cancer. Findings 24 studies met our inclusion criteria, which included 236 127 women living with HIV. The pooled risk of cervical cancer was increased in women living with HIV (RR 6·07, 95% CI 4·40–8·37). Globally, 5·8% (95% CI 4·6–7·3) of new cervical cancer cases in 2018 (33 000 new cases, 95% CI 26 000–42 000) were diagnosed in women living with HIV and 4·9% (95% CI 3·6–6·4) were attributable to HIV infection (28 000 new cases, 20 000–36 000). The most affected regions were southern Africa and eastern Africa. In southern Africa, 63·8% (95% CI 58·9–68·1) of women with cervical cancer (9200 new cases, 95% CI 8500–9800) were living with HIV, as were 27·4% (23·7–31·7) of women in eastern Africa (14 000 new cases, 12 000–17 000). ASIRs of HIV-attributable cervical cancer were more than 20 per 100 000 in six countries, all in southern Africa and eastern Africa. Interpretation Women living with HIV have a significantly increased risk of cervical cancer. HPV vaccination and cervical cancer screening for women living with HIV are especially important for countries in southern Africa and eastern Africa, where a substantial HIV-attributable cervical cancer burden has added to the existing cervical cancer burden. Funding WHO, US Agency for International Development, and US President's Emergency Plan for AIDS Relief.

The ACCESS Study is a prospective, multicenter registry to evaluate the efficacy and safety of trans-subclavian and axillary transcatheter aortic valve replacement (TAx-TAVR) with the latest-genera...

Eczema and asthma are allergic diseases and two of the commonest chronic conditions in high-income countries. Their co-existence with other allergic conditions is common, but little research exists on wider multimorbidity with these conditions. We set out to identify and compare clusters of multimorbidity in people with eczema or asthma and people without. Using routinely-collected primary care data from the U.K. Clinical Research Practice Datalink GOLD, we identified adults ever having eczema (or asthma), and comparison groups never having eczema (or asthma). We derived clusters of multimorbidity from hierarchical cluster analysis of Jaccard distances between pairs of diagnostic categories estimated from mixed-effects logistic regressions. We analysed 434,422 individuals with eczema (58% female, median age 47 years) and 1,333,281 individuals without (55% female, 47 years), and 517,712 individuals with asthma (53% female, 44 years) and 1,601,210 individuals without (53% female, 45 years). Age at first morbidity, sex and having eczema/asthma affected the scope of multimorbidity, with women, older age and eczema/asthma being associated with larger morbidity clusters. Injuries, digestive, nervous system and mental health disorders were more commonly seen in eczema and asthma than control clusters. People with eczema and asthma of all ages and both sexes may experience greater multimorbidity than people without eczema and asthma, including conditions not previously recognised as contributing to their disease burden. This work highlights areas where there is a critical need for research addressing the burden and drivers of multimorbidity in order to inform strategies to reduce poor health outcomes.