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Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

Background Atrial fibrillation (AF) is a common arrhythmia classified as paroxysmal and non-paroxysmal. Non-paroxysmal AF is associated with an increased risk of complications. Diabetes contributes to AF initiation, yet its role in AF maintenance is unclear. We conducted a systematic review and meta-analysis to summarize the evidence regarding the association of diabetes with AF types. Methods We searched 5 databases for observational studies investigating the association of diabetes with the likelihood of an AF type (vs another type) in humans. Study quality was evaluated using the Newcastle–Ottawa Scale. Studies classifying AF types as paroxysmal (reference) and non-paroxysmal were pooled in a meta-analysis using random effects models. Results Of 1997 articles we identified, 20 were included in our systematic review. The population sample size ranged from 64 to 9816 participants with mean age ranging from 40 to 75 years and percentage of women from 24.8 to 100%. The quality of studies varied from poor (60%) to fair (5%) to good (35%). In the systematic review, 8 studies among patients with AF investigated the cross-sectional association of diabetes with non-paroxysmal AF (vs paroxysmal) of which 6 showed a positive association and 2 showed no association. Fourteen studies investigated the longitudinal association of diabetes with “more sustained” AF types (vs “less sustained”) of which 2 showed a positive association and 12 showed no association. In the meta-analysis of cross-sectional studies, patients with AF and diabetes were 1.31-times more likely to have non-paroxysmal AF than those without diabetes [8 studies; pooled OR (95% CI), 1.31 (1.13–1.51), I2 = 82.6%]. The meta-analysis of longitudinal studies showed that for patients with paroxysmal AF, diabetes is associated with 1.32-times increased likelihood of progression to non-paroxysmal AF [five studies; pooled OR (95% CI), 1.32 (1.07–1.62); I2 = 0%]. Conclusions Our findings suggest that diabetes is associated with an increased likelihood of non-paroxysmal AF rather than paroxysmal AF. However, further high quality studies are needed to replicate these findings, adjust for potential confounders, elucidate mechanisms linking diabetes to non-paroxysmal AF, and assess the impact of antidiabetic medications on AF types. These strategies could eventually help decrease the risk of non-paroxysmal AF among patients with diabetes.

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BackgroundLevels of N-terminal pro B-type natriuretic peptide (NT-proBNP), a marker of heart failure and cardiovascular risk, are generally higher in women than men. We explored whether iron biomarkers mediate sex differences in NT-proBNP levels.MethodsWe included 5,343 community-dwelling individuals from the Prevention of Renal and Vascular Endstage Disease study. With linear regression analyses, we investigated the association of sex and iron biomarkers with NT-proBNP levels, independent of adjustment for potential confounders. The assessed iron biomarkers included ferritin, transferrin saturation (TSAT), hepcidin, and soluble transferrin receptor (sTfR). Next, we performed mediation analyses to investigate to which extent iron biomarkers influence the association between sex and NT-proBNP.ResultsOf the included 5,343 participants, the mean standard deviation age was 52.2 ± 11.6 years and 52% were females. After adjustment for potential confounders, women compared to men, had higher NT-proBNP (β = 0.31; 95%CI = 0.29, 0.34), but lower ferritin (β = –0.37; 95%CI = –0.39, –0.35), hepcidin (β = –0.22, 95%CI = –0.24, –0.20), and TSAT (β = –0.07, 95% CI = –0.08, –0.06). Lower ferritin (β = –0.05, 95%CI = –0.08, –0.02), lower hepcidin (β = –0.04, 95%CI = –0.07, –0.006), and higher TSAT (β = 0.07; 95%CI = 0.01, 0.13) were associated with higher NT-proBNP. In mediation analyses, ferritin and hepcidin explained 6.5 and 3.1% of the association between sex and NT-proBNP, respectively, while TSAT minimally suppressed (1.9%) this association.ConclusionOur findings suggest that iron biomarkers marginally explain sex differences in levels of NT-proBNP. Future studies are needed to explore causality and potential mechanisms underlying these pathways.

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