BackgroundIn non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline... Show moreBackgroundIn non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC). MethodsFor the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naive approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA. ResultsTen of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score. ConclusionANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly. Show less
Linschoten, M.; Peters, S.; Smeden, M. van; Jewbali, L.S.; Schaap, J.; Siebelink, H.M.; ... ; CAPACITY-COVID Collaborative Conso 2020
Aims:To determine the frequency and pattern of cardiac complications in patients hospitalised with coronavirus disease (COVID-19).Methods and results:CAPACITY-COVID is an international patient... Show moreAims:To determine the frequency and pattern of cardiac complications in patients hospitalised with coronavirus disease (COVID-19).Methods and results:CAPACITY-COVID is an international patient registry established to determine the role of cardiovascular disease in the COVID-19 pandemic. In this registry, data generated during routine clinical practice are collected in a standardised manner for patients with a (highly suspected) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection requiring hospitalisation. For the current analysis, consecutive patients with laboratory confirmed COVID-19 registered between 28 March and 3 July 2020 were included. Patients were followed for the occurrence of cardiac complications and pulmonary embolism from admission to discharge. In total, 3011 patients were included, of which 1890 (62.8%) were men. The median age was 67 years (interquartile range 56-76); 937 (31.0%) patients had a history of cardiac disease, with pre-existent coronary artery disease being most common (n=463, 15.4%). During hospitalisation, 595 (19.8%) patients died, including 16 patients (2.7%) with cardiac causes. Cardiac complications were diagnosed in 349 (11.6%) patients, with atrial fibrillation (n=142, 4.7%) being most common. The incidence of other cardiac complications was 1.8% for heart failure (n=55), 0.5% for acute coronary syndrome (n=15), 0.5% for ventricular arrhythmia (n=14), 0.1% for bacterial endocarditis (n=4) and myocarditis (n=3), respectively, and 0.03% for pericarditis (n=1). Pulmonary embolism was diagnosed in 198 (6.6%) patients.Conclusion:This large study among 3011 hospitalised patients with COVID-19 shows that the incidence of cardiac complications during hospital admission is low, despite a frequent history of cardiovascular disease. Long-term cardiac outcomes and the role of pre-existing cardiovascular disease in COVID-19 outcome warrants further investigation. Show less