ObjectiveThe biological age progression of the heart varies from person to person. We developed a deep learning model (DLM) to predict the biological age via ECG to explore its contribution to future cardiovascular diseases (CVDs).MethodsThere were 71,741 cases ranging from 20 to 80 years old recruited from the health examination center. The development set used 32,707 cases to train the DLM for estimating the ECG-age, and 8,295 cases were used as the tuning set. The validation set included 30,469 ECGs to follow the outcomes, including all-cause mortality, cardiovascular-cause mortality, heart failure (HF), diabetes mellitus (DM), chronic kidney disease (CKD), acute myocardial infarction (AMI), stroke (STK), coronary artery disease (CAD), atrial fibrillation (AF), and hypertension (HTN). Two independent external validation sets (SaMi-Trop and CODE15) were also used to validate our DLM.ResultsThe mean absolute errors of chronologic age and ECG-age was 6.899 years (r = 0.822). The higher difference between ECG-age and chronological age was related to more comorbidities and abnormal ECG rhythm. The cases with the difference of more than 7 years had higher risk on the all-cause mortality [hazard ratio (HR): 1.61, 95% CI: 1.23–2.12], CV-cause mortality (HR: 3.49, 95% CI: 1.74–7.01), HF (HR: 2.79, 95% CI: 2.25–3.45), DM (HR: 1.70, 95% CI: 1.53–1.89), CKD (HR: 1.67, 95% CI: 1.41–1.97), AMI (HR: 1.76, 95% CI: 1.20–2.57), STK (HR: 1.65, 95% CI: 1.42–1.92), CAD (HR: 1.24, 95% CI: 1.12–1.37), AF (HR: 2.38, 95% CI: 1.86–3.04), and HTN (HR: 1.67, 95% CI: 1.51–1.85). The external validation sets also validated that an ECG-age >7 years compare to chronologic age had 3.16-fold risk (95% CI: 1.72–5.78) and 1.59-fold risk (95% CI: 1.45–1.74) on all-cause mortality in SaMi-Trop and CODE15 cohorts. The ECG-age significantly contributed additional information on heart failure, stroke, coronary artery disease, and atrial fibrillation predictions after considering all the known risk factors.ConclusionsThe ECG-age estimated via DLM provides additional information for CVD incidence. Older ECG-age is correlated with not only on mortality but also on other CVDs compared with chronological age.
Background:High-volume hemofiltration (HVHF) is widely used for blood purification in critically ill patients with systemic inflammatory syndromes. The purpose of this study was to evaluate the effect of HVHF on mortality at different follow-up periods in critically ill patients.Methods:We systematically searched PubMed, Embase, and the Cochrane Library through April 2017 to identify trials that evaluated the effect of HVHF on mortality in critically ill patients. Summary relative risks (RRs) and 95% confidence intervals (CIs) were employed to calculate the treatment effect using a random effects model. Eleven trials involving 1048 critically ill patients were included in this study.Results:The summary results indicated no significant differences between HVHF and usual care for the incidence of 28-day mortality (RR: 0.93; 95%CI: 0.80–1.08; P = .321), 7-day mortality (RR: 0.72; 95%CI: 0.50–1.03; P = .072), 60-day mortality (RR: 1.00; 95%CI: 0.86–1.16; P = .997), and 90-day mortality (RR: 1.01; 95%CI: 0.88–1.16; P = .927). Subgroup analysis suggested HVHF significantly reduced the risk of 28-day mortality (RR: 0.64; 95%CI: 0.42–0.97; P = .035) if pooled the study sample size < 100.Conclusion:Our findings suggest HVHF significantly reduced the incidence of 28-day mortality when pooled the study sample size < 100. Further, HVHF had a marginal effect on the incidence of 7-day mortality.
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