Predictive Value of Echocardiographic Pulmonary to Left Atrial Ratio for In-Hospital Death in Patients with COVID-19.

Background: Echocardiographic Pulmonary to Left Atrial Ratio (ePLAR) represents an accurate and sensitive non-invasive tool to estimate the trans-pulmonary gradient. The prognostic value of ePLAR in hospitalized patients with COVID-19 remains unknown. We aimed to investigate the predictive value of ePLAR on in-hospital mortality in patients with COVID-19. Methods: One hundred consecutive patients admitted to two Italian institutions for COVID-19 undergoing early (<24 h) echocardiographic examination were included; ePLAR was determined from the maximum tricuspid regurgitation continuous wave Doppler velocity (m/s) divided by the transmitral E-wave: septal mitral annular Doppler Tissue Imaging e'-wave ratio (TRVmax/E:e'). The primary outcome measure was in-hospital death. Results: patients who died during hospitalization had at baseline a higher prevalence of tricuspid regurgitation, higher ePLAR, right-side pressures, lower Tricuspid Annular Plane Systolic Excursion (TAPSE)/ systolic Pulmonary Artery Pressure (sPAP) ratio and reduced inferior vena cava collapse than survivors. Patients with ePLAR > 0.28 m/s at baseline showed non-significant but markedly increased in-hospital mortality compared to those having ePLAR ≤ 0.28 m/s (27% vs. 10.8%, p = 0.055). Multivariate Cox regression showed that an ePLAR > 0.28 m/s was independently associated with an increased risk of death (HR 5.07, 95% CI 1.04−24.50, p = 0.043), particularly when associated with increased sPAP (p for interaction = 0.043). Conclusions: A high ePLAR value at baseline predicts in-hospital death in patients with COVID-19, especially in those with elevated pulmonary arterial pressure. These results support an early ePLAR assessment in patients admitted for COVID-19 to identify those at higher risk and potentially guide strategies of diagnosis and care.

Predictors of Mortality and Cardiovascular Outcome at 6 Months after Hospitalization for COVID-19.

Clinical outcome data of patients discharged after Coronavirus disease 2019 (COVID-19) are limited and no study has evaluated predictors of cardiovascular prognosis in this setting. Our aim was to assess short-term mortality and cardiovascular outcome after hospitalization for COVID-19. A prospective cohort of 296 consecutive patients discharged after COVID-19 from two Italian institutions during the first wave of the pandemic and followed up to 6 months was included. The primary endpoint was all-cause mortality. The co-primary endpoint was the incidence of the composite outcome of major adverse cardiac and cerebrovascular events (MACCE: cardiovascular death, myocardial infarction, stroke, pulmonary embolism, acute heart failure, or hospitalization for cardiovascular causes). The mean follow-up duration was 6 ± 2 months. The incidence of all-cause death was 4.7%. At multivariate analysis, age was the only independent predictor of mortality (aHR 1.08, 95% CI 1.01-1.16). MACCE occurred in 7.2% of patients. After adjustment, female sex (aHR 2.6, 95% CI 1.05-6.52), in-hospital acute heart failure during index hospitalization (aHR 3.45, 95% CI 1.19-10), and prevalent atrial fibrillation (aHR 3.05, 95% CI 1.13-8.24) significantly predicted the incident risk of MACCE. These findings may help to identify patients for whom a closer and more accurate surveillance after discharge for COVID-19 should be considered.

Simple Parameters from Complete Blood Count Predict In-Hospital Mortality in COVID-19.

INTRODUCTION: The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. MATERIALS AND METHODS: In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients (F 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. RESULTS: At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) (χ 2 10.4; p < 0.001), neutrophil-to-lymphocyte (NL) ratio (χ 2 7.6; p = 0.006), and platelet count (χ 2 5.39; p = 0.02), along with age (χ 2 87.6; p < 0.001) and gender (χ 2 17.3; p < 0.001), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a NL ratio > 4.68 was characterized by an odds ratio for in-hospital mortality (OR) = 3.40 (2.40-4.82), while the OR for a RDW > 13.7% was 4.09 (2.87-5.83); a platelet count > 166,000/µL was, conversely, protective (OR: 0.45 (0.32-0.63)). CONCLUSION: Our findings arise the opportunity of stratifying COVID-19 severity according to simple lab parameters, which may drive clinical decisions about monitoring and treatment.

Respiratory and Psychophysical Sequelae Among Patients With COVID-19 Four Months After Hospital Discharge.

Importance: Although plenty of data exist regarding clinical manifestations, course, case fatality rate, and risk factors associated with mortality in severe coronavirus disease 2019 (COVID-19), long-term respiratory and functional sequelae in survivors of COVID-19 are unknown. Objective: To evaluate the prevalence of lung function anomalies, exercise function impairment, and psychological sequelae among patients hospitalized for COVID-19, 4 months after discharge. Design, Setting, and Participants: This prospective cohort study at an academic hospital in Northern Italy was conducted among a consecutive series of patients aged 18 years and older (or their caregivers) who had received a confirmed diagnosis of severe acute respiratory coronavirus 2 (SARS-CoV-2) infection severe enough to require hospital admission from March 1 to June 29, 2020. SARS-CoV-2 infection was confirmed via reverse transcription-polymerase chain reaction testing, bronchial swab, serological testing, or suggestive computed tomography results. Exposure: Severe COVID-19 requiring hospitalization. Main Outcomes and Measures: The primary outcome of the study was to describe the proportion of patients with a diffusing lung capacity for carbon monoxide (Dlco) less than 80% of expected value. Secondary outcomes included proportion of patients with severe lung function impairment (defined as Dlco <60% expected value); proportion of patients with posttraumatic stress symptoms (measured using the Impact of Event Scale-Revised total score); proportion of patients with functional impairment (assessed using the Short Physical Performance Battery [SPPB] score and 2-minute walking test); and identification of factors associated with Dlco reduction and psychological or functional sequelae. Results: Among 767 patients hospitalized for severe COVID-19, 494 (64.4%) refused to participate, and 35 (4.6%) died during follow-up. A total of 238 patients (31.0%) (median [interquartile range] age, 61 [50-71] years; 142 [59.7%] men; median [interquartile range] comorbidities, 2 [1-3]) consented to participate to the study. Of these, 219 patients were able to complete both pulmonary function tests and Dlco measurement. Dlco was reduced to less than 80% of the estimated value in 113 patients (51.6%) and less than 60% in 34 patients (15.5%). The SPPB score was suggested limited mobility (score <11) in 53 patients (22.3%). Patients with SPPB scores within reference range underwent a 2-minute walk test, which was outside reference ranges of expected performance for age and sex in 75 patients (40.5%); thus, a total of 128 patients (53.8%) had functional impairment. Posttraumatic stress symptoms were reported in a total of 41 patients (17.2%). Conclusions and Relevance: These findings suggest that at 4 months after discharge, respiratory, physical, and psychological sequelae were common among patients who had been hospitalized for COVID-19.

Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients.

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.