Long-term prognostic impact of subclinical myocardial dysfunction in patients recovered from COVID-19.

BACKGROUND: Cardiovascular sequelae may occur in patients recovered from coronavirus disease 2019 (COVID-19). Recent studies have detected a considerable incidence of subclinical myocardial dysfunction-assessed with speckle-tracking echocardiography-and of long-COVID symptoms in these patients. This study aimed to define the long-term prognostic role of subclinical myocardial dysfunction and long-COVID condition in patients recovered from COVID-19 pneumonia. METHODS: We prospectively followed up 110 patients hospitalized at our institution due to COVID-19 pneumonia in April 2020 and then recovered from SARS-CoV-2 infection. A 7-month clinical and echocardiographic evaluation was performed, followed by a 21-month clinical follow-up. The primary outcome was major adverse cardiovascular events (MACE), a composite of myocardial infarction, stroke, heart failure hospitalization, and all-cause mortality. RESULTS: A subclinical myocardial dysfunction-defined as an impairment of left ventricular global longitudinal strain (≥-18%)-was identified at a 7-month follow-up in 37 patients (34%), was associated with an increased risk of long-term MACE with a good discriminative power (area under the curve: .73) and resulted in a strong independent predictor of extended MACE in multivariate regression analyses. Long-COVID condition was not associated with a worse long-term prognosis, instead. CONCLUSIONS: In patients recovered from COVID-19 pneumonia, a subclinical myocardial dysfunction is present in one-third of the whole population at 7-month follow-up and is associated with a higher risk of MACE at long-term follow-up. Speckle-tracking echocardiography is a promising tool to optimize the risk-stratification in patients recovered from COVID-19 pneumonia, while the definition of a long-COVID condition has no prognostic relevance.

Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis.

BACKGROUND: Identification of reliable outcome predictors in coronavirus disease 2019 (COVID-19) is of paramount importance for improving patient's management. METHODS: A systematic review of literature was conducted until 24 April 2020. From 6843 articles, 49 studies were selected for a pooled assessment; cumulative statistics for age and sex were retrieved in 587 790 and 602 234 cases. Two endpoints were defined: (a) a composite outcome including death, severe presentation, hospitalization in the intensive care unit (ICU) and/or mechanical ventilation; and (b) in-hospital mortality. We extracted numeric data on patients' characteristics and cases with adverse outcomes and employed inverse variance random-effects models to derive pooled estimates. RESULTS: We identified 18 and 12 factors associated with the composite endpoint and death, respectively. Among those, a history of CVD (odds ratio (OR) = 3.15, 95% confidence intervals (CIs) 2.26-4.41), acute cardiac (OR = 10.58, 5.00-22.40) or kidney (OR = 5.13, 1.78-14.83) injury, increased procalcitonin (OR = 4.8, 2.034-11.31) or D-dimer (OR = 3.7, 1.74-7.89), and thrombocytopenia (OR = 6.23, 1.031-37.67) conveyed the highest odds for the adverse composite endpoint. Advanced age, male sex, cardiovascular comorbidities, acute cardiac or kidney injury, lymphocytopenia and D-dimer conferred an increased risk of in-hospital death. With respect to the treatment of the acute phase, therapy with steroids was associated with the adverse composite endpoint (OR = 3.61, 95% CI 1.934-6.73), but not with mortality. CONCLUSIONS: Advanced age, comorbidities, abnormal inflammatory and organ injury circulating biomarkers captured patients with an adverse clinical outcome. Clinical history and laboratory profile may then help identify patients with a higher risk of in-hospital mortality.