Applying two approaches to detect unmeasured confounding due to time-varying variables in a self-controlled risk interval design evaluating COVID-19 vaccine safety signals, using myocarditis as a case example.

We test the robustness of the self-controlled risk interval (SCRI) design in a setting where time between doses may introduce time-varying confounding, using both negative control outcomes (NCOs) and quantitative bias analysis (QBA). All vaccinated cases identified from 5 European databases between 1 September 2020 and end of data availability were included. Exposures were doses 1-3 of the Pfizer, Moderna, AstraZeneca, and Janssen COVID-19 vaccines; outcomes were myocarditis and otitis externa (NCO). The SCRI used a 60-day control window and dose-specific 28-day risk windows, stratified by vaccine brand and adjusted for calendar time. The QBA included two scenarios: (i) baseline probability of the confounder was higher in the control window and (ii) vice versa. The NCO was not associated with any of the COVID-19 vaccine types or doses except Moderna dose 1 (IRR = 1.09, 95%CI 1.01-1.09). The QBA suggested even the strongest literature-reported confounder (COVID-19; RRmyocarditis = 18.3) could only explain away part of the observed effect from IRR = 3 to IRR = 1.40. The SCRI seems robust to unmeasured confounding in the COVID-19 setting, although a strong unmeasured confounder could bias the observed effect upward. Replication of our findings for other safety signals would strengthen this conclusion.

Transfusion of ever-pregnant donor red blood cells and mortality of male patients.

Previous studies found exposure to red blood cell transfusions from female donors who have been pregnant reduces survival in male patients compared to exposure to male donor products, but evidence is not consistent. We postulate the previously observed association is modified by offspring sex, with an expected increased mortality risk for male patients receiving units from female donors with sons. Here, marginal structural models were used to assess the association between exposure to units from ever-pregnant donors, ever-pregnant donors with sons and ever-pregnant donors with daughters, and mortality. Clinical data were collected on first-ever transfusion recipients in the Netherlands and donor data were supplemented with information about offspring sex and date of birth. In this analysis, 56,825 patients were included, of whom 8,288 died during follow-up. Exposure to red blood cell units from everpregnant donors with sons was not associated with increased all-cause mortality risk among male transfusion recipients (hazard ratio [HR] 0.91, 95% confidence interval 0.83-1.01). Exposure to ever-pregnant donors, irrespective of offspring sex, was associated with mortality in male patients aged between 18 and 50 years (ever-pregnant donors: HR 1.81, 95% CI 1.31-2.51) compared to male donor units, but was protective in female patients. This study suggests that the observed increased mortality risk for exposure to red blood cell units from parous female donors does not depend on offspring sex. The increased risk of mortality seen in younger adult male patients is consistent with previous observations, but the underlying biological mechanism could not be identified in this study.

"Catheter replacement in catheter-associated urinary tract infection: current state of evidence ".

PURPOSE: Catheter associated urinary tract infection (CAUTI) is the most common healthcare associated infection. A significant knowledge gap exists regarding the necessity of catheter replacement as part of CAUTI treatment. Current guidelines recommend replacement for faster recovery and to prevent recurrences, but adherence is low. In this systematic review, we aimed to assess the available evidence regarding catheter replacement for CAUTI. MATERIALS AND METHODS: Eligible studies investigated the effect of catheter replacement in CAUTI on clinical outcomes and/or recurrence rates, irrespective of catheter type or setting. We searched electronic literature databases from inception to October 15th, 2023. Information was extracted regarding setting, eligibility criteria, definition of CAUTI, timing of replacement, and outcomes. RESULTS: Of the 257 identified studies, four were considered relevant and included. Two were randomized controlled trials (RCT) and two were observational studies. One RCT showed higher rates of clinical recovery and lower recurrence rates in the replacement group, while results of the other RCT favoured retainment, with a lower recurrence rate in the retainment group, although longer antimicrobial treatment in this group. Two observational studies were inconclusive. CONCLUSIONS: Current guidelines rely heavily on recommendations from a single study, emphasizing the need for further research. The burden of catheter replacement, including patient discomfort and resource impact, warrants careful consideration. A randomized trial is essential to provide more evidence on the effect of catheter replacement on clinical outcomes including CAUTI recurrence.

Assessing Heterogeneity of Treatment Effect in Real-World Data.

Increasing availability of real-world data (RWD) generated from patient care enables the generation of evidence to inform clinical decisions for subpopulations of patients and perhaps even individuals. There is growing opportunity to identify important heterogeneity of treatment effects (HTE) in these subgroups. Thus, HTE is relevant to all with interest in patients' responses to interventions, including regulators who must make decisions about products when signals of harms arise postapproval and payers who make coverage decisions based on expected net benefit to their beneficiaries. Prior work discussed HTE in randomized studies. Here, we address methodological considerations when investigating HTE in observational studies. We propose 4 primary goals of HTE analyses and the corresponding approaches in the context of RWD: to confirm subgroup effects, to describe the magnitude of HTE, to discover clinically important subgroups, and to predict individual effects. We discuss other possible goals including exploring prognostic score- and propensity score-based treatment effects, and testing the transportability of trial results to populations different from trial participants. Finally, we outline methodological needs for enhancing real-world HTE analysis.

Applicability of European Society of Cardiology guidelines according to gross national income.

AIMS: To assess the feasibility to comply with the recommended actions of ESC guidelines on general cardiology areas in 102 countries and assess how compliance relates to the country's income level. METHODS AND RESULTS: All recommendations from seven ESC guidelines on general cardiology areas were extracted and labelled on recommended actions. A survey was sent to all 102 ESC national and affiliated cardiac societies (NCSs). Respondents were asked to score recommended actions on their availability in clinical practice on a four-point Likert scale (fully available, mostly/often available, mostly/often unavailable, fully unavailable), and select the top three barriers perceived as being responsible for limiting their national availability. Applicability was assessed overall, per World Bank gross national income (GNI) level, and per guideline.A total of 875 guideline recommendations on general cardiology was extracted. Responses were received from 64 of 102 (62.7%) NCSs. On average, 71·6% [95% confidence interval (CI): 68.6-74.6] of the actions were fully available, 9.9% (95% CI: 8.7-11.1) mostly/often available, 6.7% (95% CI: 5.4-8.0) mostly/often unavailable, and 11·8% (95% CI: 9.5-14.1) fully unavailable. In low-income countries (LICs), substantially more actions were fully unavailable [29·4% (95% CI: 22.6-36.3)] compared with high-income countries [HICs, countries 2.4% (95% CI: 1.2-3.7); P < 0.05]. Nevertheless, a proportion of actions with the lowest availability scores were often fully or mostly unavailable independent of GNIs. Actions were most often not available due to lack of reimbursement and other financial barriers. CONCLUSION: Local implementation of ESC guidelines on general cardiology is high in HICs and low in LICs , being inversely correlated with country gross national incomes.

Comparison of likelihood penalization and variance decomposition approaches for clinical prediction models: A simulation study.

Logistic regression is one of the most commonly used approaches to develop clinical risk prediction models. Developers of such models often rely on approaches that aim to minimize the risk of overfitting and improve predictive performance of the logistic model, such as through likelihood penalization and variance decomposition techniques. We present an extensive simulation study that compares the out-of-sample predictive performance of risk prediction models derived using the elastic net, with Lasso and ridge as special cases, and variance decomposition techniques, namely, incomplete principal component regression and incomplete partial least squares regression. We varied the expected events per variable, event fraction, number of candidate predictors, presence of noise predictors, and the presence of sparse predictors in a full-factorial design. Predictive performance was compared on measures of discrimination, calibration, and prediction error. Simulation metamodels were derived to explain the performance differences within model derivation approaches. Our results indicate that, on average, prediction models developed using penalization and variance decomposition approaches outperform models developed using ordinary maximum likelihood estimation, with penalization approaches being consistently superior over the variance decomposition approaches. Differences in performance were most pronounced on the calibration of the model. Performance differences regarding prediction error and concordance statistic outcomes were often small between approaches. The use of likelihood penalization and variance decomposition techniques methods was illustrated in the context of peripheral arterial disease.

Unintended impact of pharmacovigilance regulatory interventions: A systematic review.

AIMS: Studies assessing the impact of pharmacovigilance regulatory interventions often focus on the expected (or intended) outcomes, while any possible unintended impact may be overlooked. The update of the Good Pharmacovigilance Practice guideline in 2017 elaborated on impact assessment, emphasizing the need also to assess possible unintended impact. This systematic literature review investigated how often the unintended impact of regulatory interventions was considered in publications of studies investigating pharmacovigilance regulatory interventions in Europe. METHODS: We conducted a systematic review of the literature on MEDLINE and EMBASE from 1 January 2012 to 28 February 2022 to identify publications that investigated the impact of regulatory interventions in Europe. The primary outcome of the study was the number of publications reporting assessments of unintended impact. In addition, we studied the characteristics of these publications, including the type of outcomes assessed, the analytical methods applied and the type of data used. RESULTS: In total, 96 publications were included in the analysis. The unintended impact of pharmacovigilance regulatory interventions was investigated in 23 of 96 publications (24%). The drug classes most frequently studied in the publications assessing unintended impact of regulatory interventions were oral glucose-lowering drugs (n = 6, 26%), opioids (n = 4, 17%), antidepressants (n = 4, 17%) and antipsychotics (n = 3, 13%). The reported methods to assess the unintended impact were interrupted time series (n = 10, 43%) and descriptive statistics with or without significance testing (n = 2 [9%] and n = 9 [39%], respectively). The outcomes selected for unintended impact assessments included the use of other drugs (n = 16, 70%), health outcomes (n = 8, 35%) and behavioural changes (n = 4, 17%). Most of the publications reported on the use of electronic health record databases (n = 13, 57%) or claims databases (n = 13, 57%), while registries were used in 4 publications (17%). CONCLUSION: The unintended impact of pharmacovigilance regulatory interventions was reported in only a quarter of identified publications. There was no apparent increase in attention to unintended impact assessments after the update of the Good Pharmacovigilance Practice guidelines.

Primary nonadherence to drugs prescribed by general practitioners: A Dutch database study.

AIM: Primary nonadherence (PNA) is defined as not filling the first prescription for a drug treatment. PNA can lead not only to poor patient outcomes but also to exposure misclassification in written prescription databases. This study aims to estimate PNA in primary care in the Netherlands and to investigate associated factors. METHODS: Patients from the Nivel Primary Care Database (Nivel-PCD) who received a new prescription (>1 year not prescribed) from a general practitioner in 2012 were linked to pharmacy dispensing information of consenting pharmacies based on sex, year of birth, four-digit postal code and at least 50% matching Anatomical Therapeutic Classification codes. PNA was defined as not having a prescription dispensed within 30 days from the prescribing date. PNA was assessed overall and per drug class. The associations between PNA and several patient- and prescription-related characteristics were assessed using mixed-effects logistic regression models. RESULTS: After matching 86 361 of 396 251 subjects (21.8%) in the Nivel-PCD records to the pharmacy records, this study included 65 877 subjects who received 181 939 new drug prescriptions. Overall, PNA was 11.5%. PNA was lowest for thyroid hormones (5.5%) and highest for proton pump inhibitors (12.8%). Several factors were associated with PNA, such as having comorbidities (odds ratio [OR] 1.46, 95% confidence interval [CI] 1.37-1.56 for >3 active diagnoses, compared to no active diagnoses) or reimbursement status (OR 2.78, 95% CI 2.65-2.92 for not reimbursed drugs compared to fully reimbursed drugs). CONCLUSIONS: A total of 11.5% of newly prescribed drugs were not dispensed. This can lead to overestimation of the actual drug exposure status when using written prescription databases.

Quantitative bias analysis in practice: review of software for regression with unmeasured confounding.

BACKGROUND: Failure to appropriately account for unmeasured confounding may lead to erroneous conclusions. Quantitative bias analysis (QBA) can be used to quantify the potential impact of unmeasured confounding or how much unmeasured confounding would be needed to change a study's conclusions. Currently, QBA methods are not routinely implemented, partly due to a lack of knowledge about accessible software. Also, comparisons of QBA methods have focused on analyses with a binary outcome. METHODS: We conducted a systematic review of the latest developments in QBA software published between 2011 and 2021. Our inclusion criteria were software that did not require adaption (i.e., code changes) before application, was still available in 2022, and accompanied by documentation. Key properties of each software tool were identified. We provide a detailed description of programs applicable for a linear regression analysis, illustrate their application using two data examples and provide code to assist researchers in future use of these programs. RESULTS: Our review identified 21 programs with [Formula: see text] created post 2016. All are implementations of a deterministic QBA with [Formula: see text] available in the free software R. There are programs applicable when the analysis of interest is a regression of binary, continuous or survival outcomes, and for matched and mediation analyses. We identified five programs implementing differing QBAs for a continuous outcome: treatSens, causalsens, sensemakr, EValue, and konfound. When applied to one of our illustrative examples, causalsens incorrectly indicated sensitivity to unmeasured confounding whereas the other four programs indicated robustness. sensemakr performs the most detailed QBA and includes a benchmarking feature for multiple unmeasured confounders. CONCLUSIONS: Software is now available to implement a QBA for a range of different analyses. However, the diversity of methods, even for the same analysis of interest, presents challenges to their widespread uptake. Provision of detailed QBA guidelines would be highly beneficial.

Mobile health vs. standard care after cardiac surgery: results of The Box 2.0 study.

AIMS: Postoperative atrial fibrillation (POAF) is a common complication of cardiac surgery, yet difficult to detect in ambulatory patients. The primary aim of this study is to investigate the effect of a mobile health (mHealth) intervention on POAF detection after cardiac surgery. METHODS AND RESULTS: We performed an observational cohort study among 730 adult patients who underwent cardiac surgery at a tertiary care hospital in The Netherlands. Of these patients, 365 patients received standard care and were included as a historical control group, undergoing surgery between December 2017 and September 2018, and 365 patients were prospectively included from November 2018 and November 2020, undergoing an mHealth intervention which consisted of blood pressure, temperature, weight, and electrocardiogram (ECG) monitoring. One physical outpatient follow-up moment was replaced by an electronic visit. All patients were requested to fill out a satisfaction and quality of life questionnaire. Mean age in the intervention group was 62 years, 275 (70.4%) patients were males. A total of 4136 12-lead ECGs were registered. In the intervention group, 61 (16.7%) patients were diagnosed with POAF vs. 25 (6.8%) patients in the control group [adjusted risk ratio (RR) of POAF detection: 2.15; 95% confidence interval (CI): 1.55-3.97]. De novo atrial fibrillation was found in 13 patients using mHealth (6.5%) vs. 4 control group patients (1.8%; adjusted RR 3.94, 95% CI: 1.50-11.27). CONCLUSION: Scheduled self-measurements with mHealth devices could increase the probability of detecting POAF within 3 months after cardiac surgery. The effect of an increase in POAF detection on clinical outcomes needs to be addressed in future research.

Tell me what you want, what you really really want: Estimands in observational pharmacoepidemiologic comparative effectiveness and safety studies.

PURPOSE: Ideally, the objectives of a pharmacoepidemiologic comparative effectiveness or safety study should dictate its design and data analysis. This paper discusses how defining an estimand is instrumental to this process. METHODS: We applied the ICH-E9 (Statistical Principles for Clinical Trials) R1 addendum on estimands - which originally focused on randomized trials - to three examples of observational pharmacoepidemiologic comparative effectiveness and safety studies. Five key elements specify the estimand: the population, contrasted treatments, endpoint, intercurrent events, and population-level summary measure. RESULTS: Different estimands were defined for case studies representing three types of pharmacological treatments: (1) single-dose treatments using a case study about the effect of influenza vaccination versus no vaccination on mortality risk in an adult population of ≥60 years of age; (2) sustained-treatments using a case study about the effect of dipeptidyl peptidase 4 inhibitor versus glucagon-like peptide-1 agonist on hypoglycemia risk in treatment of uncontrolled diabetes; and (3) as needed treatments using a case study on the effect of nitroglycerin spray as-needed versus no nitroglycerin on syncope risk in treatment of stabile angina pectoris. CONCLUSIONS: The case studies illustrated that a seemingly clear research question can still be open to multiple interpretations. Defining an estimand ensures that the study targets a treatment effect that aligns with the treatment decision the study aims to inform. Estimand definitions further help to inform choices regarding study design and data-analysis and clarify how to interpret study findings.

Bias in observational studies on the effectiveness of in hospital use of hydroxychloroquine in COVID-19.

PURPOSE: During the first waves of the coronavirus pandemic, evidence on potential effective treatments was urgently needed. Results from observational studies on the effectiveness of hydroxychloroquine (HCQ) were conflicting, potentially due to biases. We aimed to assess the quality of observational studies on HCQ and its relation to effect sizes. METHODS: PubMed was searched on 15 March 2021 for observational studies on the effectiveness of in-hospital use of HCQ in COVID-19 patients, published between 01/01/2020 and 01/03/2021 on. Study quality was assessed using the ROBINS-I tool. Association between study quality and study characteristics (journal ranking, publication date, and time between submission and publication) and differences between effects sizes found in observational studies compared to those found in RCTs, were assessed using Spearman's correlation. RESULTS: Eighteen of the 33 (55%) included observational studies were scored as critical risk of bias, eleven (33%) as serious risk and only four (12%) as moderate risk of bias. Biases were most often scored as critical in the domains related to selection of participants (n = 13, 39%) and bias due to confounding (n = 8, 24%). There were no significant associations found between the study quality and the characteristics nor between the study quality and the effect estimates. DISCUSSION: Overall, the quality of observational HCQ studies was heterogeneous. Synthesis of evidence of effectiveness of HCQ in COVID-19 should focus on RCTs and carefully consider the added value and quality of observational evidence.

Improving accuracy in diagnosing aortic stenosis severity: An in-depth analysis of echocardiographic measurement error through literature review and simulation study.

AIMS: The present guidelines advise replacing the aortic valve for individuals with severe aortic stenosis (AS) based on various echocardiographic parameters. Accurate measurements are essential to avoid misclassification and unnecessary interventions. The objective of this study was to evaluate the influence of measurement error on the echocardiographic evaluation of the severity of AS. METHODS AND RESULTS: A systematic review was performed to examine whether measurement errors are reported in studies focusing on the prognostic value of peak aortic jet velocity (Vmax ), mean pressure gradient (MPG), and effective orifice area (EOA) in asymptomatic patients with AS. Out of the 37 studies reviewed, 17 (46%) acknowledged the existence of measurement errors, but none of them utilized methods to address them. Secondly, the magnitude of potential errors was collected from available literature for use in clinical simulations. Interobserver variability ranged between 0.9% and 8.3% for Vmax and MPG but was higher for EOA (range 7.7%-12.7%), indicating lower reliability. Assuming a circular left ventricular outflow tract area led to a median underestimation of EOA by 23% compared to planimetry by other modalities. A clinical simulation resulted in the reclassification of 42% of patients, shifting them from a diagnosis of severe AS to moderate AS. CONCLUSIONS: Measurement errors are underreported in studies on echocardiographic assessment of AS severity. These errors can lead to misclassification and misdiagnosis. Clinicians and scientists should be aware of the implications for accurate clinical decision-making and assuring research validity.

Improved prehospital triage for acute cardiac care: results from HART-c, a multicentre prospective study.

BACKGROUND: Cardiac symptoms are one of the most prevalent reasons for emergency department visits. However, over 80% of patients with such symptoms are sent home after acute cardiovascular disease has been ruled out. OBJECTIVE: The Hollands-Midden Acute Regional Triage-cardiology (HART-c) study aimed to investigate whether a novel prehospital triage method, combining prehospital and hospital data with expert consultation, could increase the number of patients who could safely stay at home after emergency medical service (EMS) consultation. METHODS: The triage method combined prehospital EMS data, such as electrocardiographic and vital parameters in real time, and data from regional hospitals (including previous medical records and admission capacity) with expert consultation. During the 6­month intervention and control periods 1536 and 1376 patients, respectively, were consulted by the EMS. The primary endpoint was the percentage change of patients who could stay at home after EMS consultation. RESULTS: The novel triage method led to a significant increase in patients who could safely stay at home, 11.8% in the intervention group versus 5.9% in the control group: odds ratio 2.31 (95% confidence interval (CI) 1.74-3.05). Of 181 patients staying at home, only 1 (< 1%) was later diagnosed with ACS; no patients died. Furthermore the number of interhospital transfers decreased: relative risk 0.81 (95% CI 0.67-0.97). CONCLUSION: The HART­c triage method led to a significant decrease in interhospital transfers and an increase in patients with cardiac symptoms who could safely stay at home. The presented method thereby reduced overcrowding and, if implemented throughout the country and for other medical specialties, could potentially reduce the number of cardiac and non-cardiac hospital visits even further.

Evaluation of the Value of Waist Circumference and Metabolomics in the Estimation of Visceral Adipose Tissue.

Visceral adipose tissue (VAT) is a strong prognostic factor for cardiovascular disease and a potential target for cardiovascular risk stratification. Because VAT is difficult to measure in clinical practice, we estimated prediction models with predictors routinely measured in general practice and VAT as outcome using ridge regression in 2,501 middle-aged participants from the Netherlands Epidemiology of Obesity study, 2008-2012. Adding waist circumference and other anthropometric measurements on top of the routinely measured variables improved the optimism-adjusted R2 from 0.50 to 0.58 with a decrease in the root-mean-square error (RMSE) from 45.6 to 41.5 cm2 and with overall good calibration. Further addition of predominantly lipoprotein-related metabolites from the Nightingale platform did not improve the optimism-corrected R2 and RMSE. The models were externally validated in 370 participants from the Prospective Investigation of Vasculature in Uppsala Seniors (PIVUS, 2006-2009) and 1,901 participants from the Multi-Ethnic Study of Atherosclerosis (MESA, 2000-2007). Performance was comparable to the development setting in PIVUS (R2 = 0.63, RMSE = 42.4 cm2, calibration slope = 0.94) but lower in MESA (R2 = 0.44, RMSE = 60.7 cm2, calibration slope = 0.75). Our findings indicate that the estimation of VAT with routine clinical measurements can be substantially improved by incorporating waist circumference but not by metabolite measurements.

A first step towards best practice recommendations for the design and statistical analyses of pragmatic clinical trials: A modified Delphi approach.

AIM: Pragmatic clinical trials (PCTs) are randomized trials implemented through routine clinical practice, where design parameters of traditional randomized controlled trials are modified to increase generalizability. However, this may introduce statistical challenges. We aimed to identify these challenges and discuss possible solutions leading to best practice recommendations for the design and analysis of PCTs. METHODS: A modified Delphi method was used to reach consensus among a panel of 11 experts in clinical trials and statistics. Statistical issues were identified in a focused literature review and aggregated with insights and possible solutions from experts collected through a series of survey iterations. Issues were ranked according to their importance. RESULTS: Twenty-seven articles were included and combined with experts' insight to generate a list of issues categorized into participants, recruiting sites, randomization, blinding and intervention, outcome (selection and measurement) and data analysis. Consensus was reached about the most important issues: risk of participants' attrition, heterogeneity of "usual care" across sites, absence of blinding, use of a subjective endpoint and data analysis aligned with the trial estimand. Potential issues should be anticipated and preferably be addressed in the trial protocol. The experts provided solutions regarding data collection and data analysis, which were considered of equal importance. DISCUSSION: A set of important statistical issues in PCTs was identified and approaches were suggested to anticipate and/or minimize these through data analysis. Any impact of choosing a pragmatic design feature should be gauged in the light of the trial estimand.

Identification of causal effects in case-control studies.

BACKGROUND: Case-control designs are an important yet commonly misunderstood tool in the epidemiologist's arsenal for causal inference. We reconsider classical concepts, assumptions and principles and explore when the results of case-control studies can be endowed a causal interpretation. RESULTS: We establish how, and under which conditions, various causal estimands relating to intention-to-treat or per-protocol effects can be identified based on the data that are collected under popular sampling schemes (case-base, survivor, and risk-set sampling, with or without matching). We present a concise summary of our identification results that link the estimands to the (distribution of the) available data and articulate under which conditions these links hold. CONCLUSION: The modern epidemiologist's arsenal for causal inference is well-suited to make transparent for case-control designs what assumptions are necessary or sufficient to endow the respective study results with a causal interpretation and, in turn, help resolve or prevent misunderstanding. Our approach may inform future research on different estimands, other variations of the case-control design or settings with additional complexities.

Comprehensive comparison of stroke risk score performance: a systematic review and meta-analysis among 6 267 728 patients with atrial fibrillation.

AIMS: Multiple risk scores to predict ischaemic stroke (IS) in patients with atrial fibrillation (AF) have been developed. This study aims to systematically review these scores, their validations and updates, assess their methodological quality, and calculate pooled estimates of the predictive performance. METHODS AND RESULTS: We searched PubMed and Web of Science for studies developing, validating, or updating risk scores for IS in AF patients. Methodological quality was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). To assess discrimination, pooled c-statistics were calculated using random-effects meta-analysis. We identified 19 scores, which were validated and updated once or more in 70 and 40 studies, respectively, including 329 validations and 76 updates-nearly all on the CHA2DS2-VASc and CHADS2. Pooled c-statistics were calculated among 6 267 728 patients and 359 373 events of IS. For the CHA2DS2-VASc and CHADS2, pooled c-statistics were 0.644 [95% confidence interval (CI) 0.635-0.653] and 0.658 (0.644-0.672), respectively. Better discriminatory abilities were found in the newer risk scores, with the modified-CHADS2 demonstrating the best discrimination [c-statistic 0.715 (0.674-0.754)]. Updates were found for the CHA2DS2-VASc and CHADS2 only, showing improved discrimination. Calibration was reasonable but available for only 17 studies. The PROBAST indicated a risk of methodological bias in all studies. CONCLUSION: Nineteen risk scores and 76 updates are available to predict IS in patients with AF. The guideline-endorsed CHA2DS2-VASc shows inferior discriminative abilities compared with newer scores. Additional external validations and data on calibration are required before considering the newer scores in clinical practice. CLINICAL TRIAL REGISTRATION: ID CRD4202161247 (PROSPERO).

Bias of time-varying exposure effects due to time-varying covariate measurement strategies.

PURPOSE: In studies of effects of time-varying drug exposures, adequate adjustment for time-varying covariates is often necessary to properly control for confounding. However, the granularity of the available covariate data may not be sufficiently fine, for example when covariates are measured for participants only when their exposure levels change. METHODS: To illustrate the impact of choices regarding the frequency of measuring time-varying covariates, we simulated data for a large target trial and for large observational studies, varying in covariate measurement design. Covariates were measured never, on a fixed-interval basis, or each time the exposure level switched. For the analysis, it was assumed that covariates remain constant in periods of no measurement. Cumulative survival probabilities for continuous exposure and non-exposure were estimated using inverse probability weighting to adjust for time-varying confounding, with special emphasis on the difference between 5-year event risks. RESULTS: With monthly covariate measurements, estimates based on observational data coincided with trial-based estimates, with 5-year risk differences being zero. Without measurement of baseline or post-baseline covariates, this risk difference was estimated to be 49% based on the available observational data. With measurements on a fixed-interval basis only, 5-year risk differences deviated from the null, to 29% for 6-monthly measurements, and with magnitude increasing up to 35% as the interval length increased. Risk difference estimates diverged from the null to as low as -18% when covariates were measured depending on exposure level switching. CONCLUSION: Our simulations highlight the need for careful consideration of time-varying covariates in designing studies on time-varying exposures. We caution against implementing designs with long intervals between measurements. The maximum length required will depend on the rates at which treatments and covariates change, with higher rates requiring shorter measurement intervals.

Declining daily functioning as a prelude to a hip fracture in older persons-an individual patient data meta-analysis.

BACKGROUND: Daily functioning is known to decline after a hip fracture, but studies of self-reported functioning before the fracture suggest this decline begins before the fracture. OBJECTIVE: Determine whether change in functioning in the year before a hip fracture in very old (80+) differs from change in those without a hip fracture. DESIGN: Two-stage individual patient data meta-analysis including data from the Towards Understanding Longitudinal International older People Studies (TULIPS)-consortium. SETTING: Four population-based longitudinal cohorts from the Netherlands, New Zealand and the UK. SUBJECTS: Participants aged 80+ years. METHODS: Participants were followed for 5 years, during which (instrumental) activities of daily living [(I)ADL] scores and incident hip fractures were registered at regular intervals. Z-scores of the last (I)ADL score and the change in (I)ADL in the year before a hip fracture were compared to the scores of controls, adjusted for age and sex. RESULTS: Of the 2,357 participants at baseline, the 161 who sustained a hip fracture during follow-up had a worse (I)ADL score before the fracture (0.40 standard deviations, 95% CI 0.19 to 0.61, P = 0.0002) and a larger decline in (I)ADL in the year before fracture (-0.11 standard deviations, 95% CI -0.22 to 0.004, P = 0.06) compared to those who did not sustain a hip fracture. CONCLUSIONS: In the very old a decline in daily functioning already starts before a hip fracture. Therefore, a hip fracture is a sign of ongoing decline and what full recovery is should be seen in light of the pre-fracture decline.