Dataset Information

High risk coronavirus disease 2019: The primary results of the CoronaHeart multi-center cohort study.

ABSTRACT:

Background

Patients with Coronavirus Disease 2019 (COVID-19) may present high risk features during hospitalization, including cardiovascular manifestations. However, less is known about the factors that may further increase the risk of death in these patients.

Methods

We included patients with COVID-19 and high risk features according to clinical and/or laboratory criteria at 21 sites in Brazil from June 10th to October 23rd of 2020. All variables were collected until hospital discharge or in-hospital death.

Results

A total of 2546 participants were included (mean age 65 years; 60.3% male). Overall, 70.8% were admitted to intensive care units and 54.2% had elevated troponin levels. In-hospital mortality was 41.7%. An interaction among sex, age and mortality was found (p = 0.007). Younger women presented higher rates of death than men (30.0% vs 22.9%), while older men presented higher rates of death than women (57.6% vs 49.2%). The strongest factors associated with in-hospital mortality were need for mechanical ventilation (odds ratio [OR] 8.2, 95% confidence interval [CI] 5.4-12.7), elevated C-reactive protein (OR 2.3, 95% CI 1.7-2.9), cancer (OR 1.8, 95 %CI 1.2-2.9), and elevated troponin levels (OR 1.8, 95% CI 1.4-2.3). A risk score was developed for risk assessment of in-hospital mortality.

Conclusions

This cohort showed that patients with COVID-19 and high risk features have an elevated rate of in-hospital mortality with differences according to age and sex. These results highlight unique aspects of this population and might help identifying patients who may benefit from more careful initial surveillance and potential subsequent interventional therapies.

SUBMITTER: Guimaraes PO

PROVIDER: S-EPMC8321709 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Publications

High risk coronavirus disease 2019: The primary results of the CoronaHeart multi-center cohort study.

Guimarães Patrícia O PO de Souza Francis R FR Lopes Renato D RD Bittar Cristina C Cardozo Francisco A FA Caramelli Bruno B Calderaro Daniela D Albuquerque Cícero P CP Drager Luciano F LF Feres Fausto F Baracioli Luciano L Feitosa Filho Gilson G Barbosa Roberto R RR Ribeiro Henrique B HB Ribeiro Expedito E Alves Renato J RJ Soeiro Alexandre A Faillace Bruno B Figueiredo Estêvão E Damiani Lucas P LP do Val Renata M RM Huemer Natassja N Nicolai Lisiê G LG Hajjar Ludhmila A LA Abizaid Alexandre A Kalil Filho Roberto R

International journal of cardiology. Heart & vasculature 20210730

<h4>Background</h4>Patients with Coronavirus Disease 2019 (COVID-19) may present high risk features during hospitalization, including cardiovascular manifestations. However, less is known about the factors that may further increase the risk of death in these patients.<h4>Methods</h4>We included patients with COVID-19 and high risk features according to clinical and/or laboratory criteria at 21 sites in Brazil from June 10th to October 23rd of 2020. All variables were collected until hospital dis ...[more]

PMID: 34345648

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Project description:BackgroundKidney transplant (KT) recipients are considered a high-risk group for unfavorable outcomes in the course of coronavirus disease 2019 (COVID-19).AimTo describe the clinical aspects and outcomes of COVID-19 among KT recipients.MethodsThis multicenter cohort study enrolled 1,680 KT recipients diagnosed with COVID-19 between March and November 2020, from 35 Brazilian centers. The main outcome was the 90-day cumulative incidence of death, for the entire cohort and according to acute kidney injury (AKI) and renal replacement therapy (RRT) requirement. Fatality rates were analyzed according to hospitalization, intensive care unit (ICU) admission, and mechanical ventilation (MV) requirement. Multivariable analysis was performed by logistic regression for the probability of hospitalization and death.ResultsThe median age of the recipients was 51.3 years, 60.4% were men and 11.4% were Afro-Brazilian. Comorbidities were reported in 1,489 (88.6%), and the interval between transplantation and infection was 5.9 years. The most frequent symptoms were cough (54%), myalgia (40%), dyspnea (37%), and diarrhea (31%), whereas the clinical signs were fever (61%) and hypoxemia (13%). Hospitalization was required in 65.1%, and immunosuppressive drugs adjustments were made in 74.4% of in-hospital patients. ICU admission was required in 34.6% and MV in 24.9%. In the multivariable modeling, the variables related with the probability of hospitalization were age, hypertension, previous cardiovascular disease, recent use of high dose of steroid, and fever, dyspnea, diarrhea, and nausea or vomiting as COVID-19 symptoms. On the other hand, the variables that reduced the probability of hospitalization were time of COVID-19 symptoms, and nasal congestion, headache, arthralgia and anosmia as COVID-19 symptoms. The overall 90-day cumulative incidence of death was 21.0%. The fatality rates were 31.6%, 58.2%, and 75.5% in those who were hospitalized, admitted to the ICU, and required MV, respectively. At the time of infection, 23.2% had AKI and 23.4% required RRT in the follow-up. The cumulative incidence of death was significantly higher among recipients with AKI (36.0% vs. 19.1%, P < 0.0001) and in those who required RRT (70.8% vs. 10.1%, P < 0.0001). The variables related with the probability of death within 90 days after COVID-19 were age, time after transplantation, presence of hypertension, previous cardiovascular disease, use of tacrolimus and mycophenolate, recent use of high dose of steroids, and dyspnea as COVID-19 symptom. On the other hand, the variables that reduced the risk of death were time of symptoms, and headache and anosmia as COVID-19 symptoms.ConclusionThe patients diagnosed with COVID-19 were long-term KT recipients and most of them had some comorbidities. One in every five patients died, and the rate of death was significantly higher in those with AKI, mainly when RRT was required.

Project description:BackgroundCoronavirus disease 2019 (COVID-19) is sweeping the globe. Despite multiple case-series, actionable knowledge to tailor decision-making proactively is missing.Research questionCan a statistical model accurately predict infection with COVID-19?Study design and methodsWe developed a prospective registry of all patients tested for COVID-19 in Cleveland Clinic to create individualized risk prediction models. We focus here on the likelihood of a positive nasal or oropharyngeal COVID-19 test. A least absolute shrinkage and selection operator logistic regression algorithm was constructed that removed variables that were not contributing to the model's cross-validated concordance index. After external validation in a temporally and geographically distinct cohort, the statistical prediction model was illustrated as a nomogram and deployed in an online risk calculator.ResultsIn the development cohort, 11,672 patients fulfilled study criteria, including 818 patients (7.0%) who tested positive for COVID-19; in the validation cohort, 2295 patients fulfilled criteria, including 290 patients who tested positive for COVID-19. Male, African American, older patients, and those with known COVID-19 exposure were at higher risk of being positive for COVID-19. Risk was reduced in those who had pneumococcal polysaccharide or influenza vaccine or who were on melatonin, paroxetine, or carvedilol. Our model had favorable discrimination (c-statistic = 0.863 in the development cohort and 0.840 in the validation cohort) and calibration. We present sensitivity, specificity, negative predictive value, and positive predictive value at different prediction cutoff points. The calculator is freely available at https://riskcalc.org/COVID19.InterpretationPrediction of a COVID-19 positive test is possible and could help direct health-care resources. We demonstrate relevance of age, race, sex, and socioeconomic characteristics in COVID-19 susceptibility and suggest a potential modifying role of certain common vaccinations and drugs that have been identified in drug-repurposing studies.

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Dataset Information

High risk coronavirus disease 2019: The primary results of the CoronaHeart multi-center cohort study.

Background

Methods

Results

Conclusions

Publications

High risk coronavirus disease 2019: The primary results of the CoronaHeart multi-center cohort study.

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