Background Age and comorbidities increase COVID-19 related in-hospital mortality risk, but the extent by which comorbidities mediate the impact of age remains unknown. Methods In this multicenter retrospective cohort study with data from 45 Dutch hospitals, 4806 proven COVID-19 patients hospitalized in Dutch hospitals (between February and July 2020) from the CAPACITY-COVID registry were included (age 69[58–77]years, 64% men). The primary outcome was defined as a combination of in-hospital mortality or discharge with palliative care. Logistic regression analysis was performed to analyze the associations between sex, age, and comorbidities with the primary outcome. The effect of comorbidities on the relation of age with the primary outcome was evaluated using mediation analysis. Results In-hospital COVID-19 related mortality occurred in 1108 (23%) patients, 836 (76%) were aged ≥70 years (70+). Both age 70+ and female sex were univariably associated with outcome (odds ratio [OR]4.68, 95%confidence interval [4.02–5.45], OR0.68[0.59–0.79], respectively;both p<  0.001). All comorbidities were univariably associated with outcome (p<0.001), and all but dyslipidemia remained significant after adjustment for age70+ and sex. The impact of comorbidities was attenuated after age-spline adjustment, only leaving female sex, diabetes mellitus (DM), chronic kidney disease (CKD), and chronic pulmonary obstructive disease (COPD) significantly associated (female OR0.65[0.55–0.75], DM OR1.47[1.26–1.72], CKD OR1.61[1.32–1.97], COPD OR1.30[1.07–1.59]). Pre-existing comorbidities in older patients negligibly (<6% in all comorbidities) mediated the association between higher age and outcome. Conclusions Age is the main determinant of COVID-19 related in-hospital mortality, with negligible mediation effect of pre-existing comorbidities. Trial registration CAPACITY-COVID (NCT04325412)

Aims Patients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality. Methods and results We used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existing heart disease and in-hospital mortality. A total of 16 511 patients with COVID-19 were included (21.1% aged 66–75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male, and often had other comorbid conditions when compared with those without. Mortality was higher in patients with cardiac disease (29.7%; n = 1545 vs. 15.9%; n = 1797). However, following multivariable adjustment, this difference was not significant [adjusted risk ratio (aRR) 1.08, 95% confidence interval (CI) 1.02–1.15; P = 0.12 (corrected for multiple testing)]. Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure (aRR 1.19, 95% CI 1.10–1.30; P &lt; 0.018) particularly for severe (New York Heart Association class III/IV) heart failure (aRR 1.41, 95% CI 1.20–1.64; P &lt; 0.018). None of the other heart disease subtypes, including ischaemic heart disease, remained significant after multivariable adjustment. Serious cardiac complications were diagnosed in &lt;1% of patients. Conclusion Considerable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare during hospitalization.

Aims Patients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality. Method and results We used data from the CAPACITY-COVID registry and LEOSS study. Multivariable modified Poisson regression models were fitted to assess the association between different types of pre-existent heart disease and in-hospital mortality. 10,481 patients with COVID-19 were included (22.4% aged 66-75 years; 38.7% female) of which 30.5% had a history of cardiac disease. Patients with heart disease were older, predominantly male and more likely to have other comorbid conditions when compared to those without. COVID-19 symptoms at presentation did not differ between these groups. Mortality was higher in patients with cardiac disease (30.3%; n=968 versus 15.7%; n=1143). However, following multivariable adjustment this difference was not significant (adjusted risk ratio (aRR) 1.06 [95% CI 0.98-1.15, p-value 0.13]). Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for NYHA III/IV heart failure (aRR 1.43 [95% CI 1.22-1.68, p-value <0.001]) and atrial fibrillation (aRR 1.14 [95% CI 1.04-1.24, p-value 0.01]). None of the other heart disease subtypes, including ischemic heart disease, remained significant after multivariable adjustment. Conclusion There is considerable heterogeneity in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with severe heart failure are at greatest risk of death when hospitalized with COVID-19.

Background The best available imaging technique for the detection of prior myocardial infarction (MI) is cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE). Although the electrocardiogram (ECG) still plays a major role in the diagnosis of prior MI, the diagnostic value of the ECG remains uncertain. This study evaluates the diagnostic value of the ECG in the assessment of prior MI. Methods In this retrospective study, data from electronic patient files were collected of 1033 patients who had undergone CMR with LGE between January 2014 and December 2017. After the exclusion of 59 patients, the data of 974 patients were analysed. Twelve-lead ECGs were blinded and evaluated for signs of prior MI by two cardiologists separately. Disagreement in interpretation was resolved by the judgement of a third cardiologist. Outcomes of CMR with LGE were used as the gold standard. Results The sensitivity of the ECG in the detection of MI was 38.0% with a 95% confidence interval (CI) of 31.6–44.8%. The specificity was 86.9% (95% CI 84.4–89.1%). The positive and negative predictive value were 43.6% (95% CI 36.4–50.9%) and 84.0% (95% CI 81.4–86.5%) respectively. In 170 ECGs (17.5%), the two cardiologists disagreed on the presence or absence of MI. Inter-rater variability was moderate (κ 0.51, 95% CI 0.45–0.58, p < 0.001). Conclusion The ECG has a low diagnostic value in the detection of prior MI. However, if the ECG shows no signs of prior MI, the absence of MI is likely. This study confirms that a history of MI should not be based solely on an ECG.

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