Clinical characteristics and outcomes of hospital-manifested COVID-19 among Brazilians

OBJECTIVES

To analyze the clinical characteristics and outcomes of admitted patients with the hospital- versus community-manifested COVID-19 and to evaluate the risk factors related to mortality in the first population.

METHODS

This retrospective cohort included consecutive adult patients with COVID-19, hospitalized between March and September 2020. The demographic data, clinical characteristics, and outcomes were extracted from medical records. Patients with hospital-manifested COVID-19 (study group) and those with community-manifested COVID-19 (control group) were matched by the propensity score model. Logistic regression models were used to verify the risk factors for mortality in the study group.

RESULTS

Among 7,710 hospitalized patients who had COVID-19, 7.2% developed symptoms while admitted for other reasons. Patients with hospital-manifested COVID-19 had a higher prevalence of cancer (19.2% vs 10.8%) and alcoholism (8.8% vs 2.8%) than patients with community-manifested COVID-19 and also had a higher rate of intensive care unit requirement (45.1% vs 35.2%), sepsis (23.8% vs 14.5%), and death (35.8% vs 22.5%) (P <0.05 for all). The factors independently associated with increased mortality in the study group were increasing age, male sex, number of comorbidities, and cancer.

CONCLUSION

Hospital-manifested COVID-19 was associated with increased mortality. Increasing age, male sex, number of comorbidities, and cancer were independent predictors of mortality among those with hospital-manifested COVID-19 disease.

Frequency and burden of neurological manifestations upon hospital presentation in COVID-19 patients: Findings from a large Brazilian cohort

BACKGROUND

Scientific data regarding the prevalence of COVID-19 neurological manifestations and prognosis in Latin America countries is still lacking. Therefore, the study aims to understand neurological manifestations of SARS-CoV 2 infection and outcomes in the Brazilian population.

METHODS

This study is part of the Brazilian COVID-19 Registry, a multicentric cohort, including data from 37 hospitals. For the present analysis, patients were grouped according to the presence of reported symptoms (i.e., headache; anosmia and ageusia; syncope and dizziness) vs. clinically-diagnosed neurological manifestations (clinically-defined neurological syndrome: neurological signs or diagnoses captured by clinical evaluation) and matched with patients without neurological manifestations by age, sex, number of comorbidities, hospital of admission, and whether or not patients had underlying neurological disease.

RESULTS

From 6,635 hospitalized patients with COVID-19, 30.8% presented reported neurological manifestations, 10.3% were diagnosed with a neurological syndrome and 60.1% did not show any neurological manifestations. In patients with reported symptoms, the most common ones were headache (20.7%), ageusia (11.1%) and anosmia (8.0%). In patients with neurological syndromes, acute encephalopathy was the most common diagnosis (9.7%). In the matched analysis, patients with neurological syndromes presented more cases of septic shock (17.0 vs. 13.0%, p = 0.045), intensive care unit admission (45.3 vs. 38.9%, p = 0.023), and mortality (38.7 vs. 32.6%, p = 0.026; and 39.2 vs. 30.3%, p < 0.001) when compared to controls.

CONCLUSION

COVID-19 in-hospital patients with clinically defined neurological syndromes presented a higher incidence of septic shock, ICU admission and death when compared to controls.

Cohort study protocol of the Brazilian collaborative research network on COVID-19: strengthening WHO global data

INTRODUCTION

With the COVID-19 pandemic, hospitals in low-income countries were faced with a triple challenge. First, a large number of patients required hospitalisation because of the infection's more severe symptoms. Second, there was a lack of systematic and broad testing policies for early identification of cases. Third, there were weaknesses in the integration of information systems, which led to the need to search for available information from the hospital information systems. Accordingly, it is also important to state that relevant aspects of COVID-19's natural history had not yet been fully clarified. The aim of this research protocol is to present the strategies of a Brazilian network of hospitals to perform systematised data collection on COVID-19 through the WHO platform.

METHODS AND ANALYSIS

This is a multicentre project among Brazilian hospitals to provide data on COVID-19 through the WHO global platform, which integrates patient care information from different countries. From October 2020 to March 2021, a committee worked on defining a flowchart for this platform, specifying the variables of interest, data extraction standardisation and analysis.

ETHICS AND DISSEMINATION

This protocol was approved by the Research Ethics Committee (CEP) of the Research Coordinating Center of Brazil (CEP of the Hospital Nossa Senhora da Conceicao), on 29 January 2021, under approval No. 4.515.519 and by the National Research Ethics Commission (CONEP), on 5 February 2021, under approval No. 4.526.456. The project results will be explained in WHO reports and published in international peer-reviewed journals, and summaries will be provided to the funders of the study.

Hospital characteristics associated with COVID-19 mortality: data from the multicenter cohort Brazilian Registry

The COVID-19 pandemic caused unprecedented pressure over health care systems worldwide. Hospital-level data that may influence the prognosis in COVID-19 patients still needs to be better investigated. Therefore, this study analyzed regional socioeconomic, hospital, and intensive care units (ICU) characteristics associated with in-hospital mortality in COVID-19 patients admitted to Brazilian institutions. This multicenter retrospective cohort study is part of the Brazilian COVID-19 Registry. We enrolled patients ≥ 18 years old with laboratory-confirmed COVID-19 admitted to the participating hospitals from March to September 2020. Patients' data were obtained through hospital records. Hospitals' data were collected through forms filled in loco and through open national databases. Generalized linear mixed models with logit link function were used for pooling mortality and to assess the association between hospital characteristics and mortality estimates. We built two models, one tested general hospital characteristics while the other tested ICU characteristics. All analyses were adjusted for the proportion of high-risk patients at admission. Thirty-one hospitals were included. The mean number of beds was 320.4 ± 186.6. These hospitals had eligible 6556 COVID-19 admissions during the study period. Estimated in-hospital mortality ranged from 9.0 to 48.0%. The first model included all 31 hospitals and showed that a private source of funding (β = - 0.37; 95% CI - 0.71 to - 0.04; p = 0.029) and location in areas with a high gross domestic product (GDP) per capita (β = - 0.40; 95% CI - 0.72 to - 0.08; p = 0.014) were independently associated with a lower mortality. The second model included 23 hospitals and showed that hospitals with an ICU work shift composed of more than 50% of intensivists (β = - 0.59; 95% CI - 0.98 to - 0.20; p = 0.003) had lower mortality while hospitals with a higher proportion of less experienced medical professionals had higher mortality (β = 0.40; 95% CI 0.11-0.68; p = 0.006). The impact of those association increased according to the proportion of high-risk patients at admission. In-hospital mortality varied significantly among Brazilian hospitals. Private-funded hospitals and those located in municipalities with a high GDP had a lower mortality. When analyzing ICU-specific characteristics, hospitals with more experienced ICU teams had a reduced mortality.

Predictors of venous thromboembolism in COVID-19 patients: results of the COVID-19 Brazilian Registry

Previous studies that assessed risk factors for venous thromboembolism (VTE) in COVID-19 patients have shown inconsistent results. Our aim was to investigate VTE predictors by both logistic regression (LR) and machine learning (ML) approaches, due to their potential complementarity. This cohort study of a large Brazilian COVID-19 Registry included 4120 COVID-19 adult patients from 16 hospitals. Symptomatic VTE was confirmed by objective imaging. LR analysis, tree-based boosting, and bagging were used to investigate the association of variables upon hospital presentation with VTE. Among 4,120 patients (55.5% men, 39.3% critical patients), VTE was confirmed in 6.7%. In multivariate LR analysis, obesity (OR 1.50, 95% CI 1.11-2.02); being an ex-smoker (OR 1.44, 95% CI 1.03-2.01); surgery ≤ 90 days (OR 2.20, 95% CI 1.14-4.23); axillary temperature (OR 1.41, 95% CI 1.22-1.63); D-dimer ≥ 4 times above the upper limit of reference value (OR 2.16, 95% CI 1.26-3.67), lactate (OR 1.10, 95% CI 1.02-1.19), C-reactive protein levels (CRP, OR 1.09, 95% CI 1.01-1.18); and neutrophil count (OR 1.04, 95% CI 1.005-1.075) were independent predictors of VTE. Atrial fibrillation, peripheral oxygen saturation/inspired oxygen fraction (SF) ratio and prophylactic use of anticoagulants were protective. Temperature at admission, SF ratio, neutrophil count, D-dimer, CRP and lactate levels were also identified as predictors by ML methods. By using ML and LR analyses, we showed that D-dimer, axillary temperature, neutrophil count, CRP and lactate levels are risk factors for VTE in COVID-19 patients.

Hypothyroidism does not lead to worse prognosis in COVID-19: findings from the Brazilian COVID-19 registry

Background

It is not clear whether previous thyroid diseases influence the course and outcomes of COVID-19.

Methods

The study is a part of a multicentric cohort of patients with confirmed COVID-19 diagnosis from 37 hospitals. Matching for age, sex, number of comorbidities, and hospital was performed for the paired analysis.

Results

Of 7,762 patients with COVID-19, 526 had previously diagnosed hypothyroidism and 526 were matched controls. The median age was 70 years, and 68.3% were females. The prevalence of comorbidities was similar, except for coronary and chronic kidney diseases that were higher in the hypothyroidism group (p=0.015 and p=0.001). D-dimer levels were lower in patients with hypothyroid (p=0.037). In-hospital management was similar, but hospital length-of-stay (p=0.029) and mechanical ventilation requirement (p=0.006) were lower for patients with hypothyroidism. There was a trend of lower in-hospital mortality in patients with hypothyroidism (22.1% vs 27.0%; p=0.062).

Conclusion

Patients with hypothyroidism had a lower requirement of mechanical ventilation and showed a trend of lower in-hospital mortality. Therefore, hypothyroidism does not seem to be associated with a worse prognosis.

Smart Check - COVID-19 triage system: Evaluation of the impact on the screening time and identification of clinical manifestations of SARS-CoV-2 infection in a public health service

INTRODUCTION

Most patients with COVID-19 have mild or moderate manifestations; however, there is a wide spectrum of clinical presentations and even more severe repercussions that require high diagnostic suspicion. Vital sign acquisition and monitoring are crucial for detecting and responding to patients with COVID-19.

OBJECTIVE

Thus, we conducted this study to demonstrate the impact of using a tool called Smart Check on the triage time of patients with suspected COVID-19 and to identify the main initial clinical manifestations in these patients.

METHODOLOGY

We assessed triage times before and after the use of Smart Check in 11 466 patients at Hospital Nossa Senhora da Conceição in Porto Alegre, Brazil, from 1 June to 31 July 2020. In this group, we identified 220 patients for the identification of COVID-19 clinical manifestations in a case-control analysis.

RESULTS

Smart Check was able to decrease the triage time by 33 seconds on average (P < .001), with 75% of the exams being performed within 5 minutes, whereas with the usual protocol these steps were performed within 6 minutes. A range of clinical presentations made up the COVID-19 initial manifestations. Those with the highest frequency were dry cough (46.4%), fever (41.3%), dyspnoea (35.8%), and headache (31.8%). Loss of appetite was the manifestation that had a statistically significant association with the SARS-CoV-2 presence (univariate analysis). When analysed together, loss of appetite associated with dyspnoea and/or ageusia and/or fever was related to the diagnosis of COVID-19.

CONCLUSIONS

Smart Check, a simple clinical evaluation tool, along with the targeted use of rapid PCR testing, can optimise triage time for patients with and without COVID-19. In triage centres, a number of initial signs and symptoms should be cause for SARS-CoV-2 infection suspicion, in particular the association of respiratory, neurological, and gastrointestinal manifestations.