key: cord-0698683-q4arbsw0 authors: Vieira, Marcelo Luiz Campos; Afonso, Tania Regina; Oliveira, Alessandra Joslin; Stangenhaus, Carolina; Dantas, Juliana Cardoso Dória; Santos, Luiz Otávio Arruda; de França, Lucas Arraes; do Prado, Rogério Ruscitto; Cordovil, Adriana; Monaco, Cláudia Gianini; Lira Filho, Edgar Bezerra; Rodrigues, Ana Clara Tude; Bacal, Fernando; de Matos, Gustavo Faissol Janot; Antunes, Telma; Camargo, Luis Fernando Aranha; Fischer, Cláudio Henrique; Morhy, Samira Saady title: A risk score for predicting death in COVID‐19 in‐hospital infection: A Brazilian single‐center study date: 2022-03-30 journal: J Clin Ultrasound DOI: 10.1002/jcu.23195 sha: dab41746a0ef95fd65aeb8029702d006ca3f3dcb doc_id: 698683 cord_uid: q4arbsw0 BACKGROUND: There is a paucity of information about Brazilian COVID‐19 in‐hospital mortality probability of death combining risk factors. OBJECTIVE: We aimed to correlate COVID‐19 Brazilian in‐hospital patients' mortality to demographic aspects, biomarkers, tomographic, echocardiographic findings, and clinical events. METHODS: A prospective study, single tertiary center in Brazil, consecutive patients hospitalized with COVID‐19. We analyzed the data from 111 patients from March to August 2020, performed a complete transthoracic echocardiogram, chest thoracic tomographic (CT) studies, collected biomarkers and correlated to in‐hospital mortality. RESULTS: Mean age of the patients: 67 ± 17 years old, 65 (58.5%) men, 29 (26%) presented with systemic arterial hypertension, 18 (16%) with diabetes, 11 (9.9%) with chronic obstructive pulmonary disease. There was need for intubation and mechanical ventilation of 48 (43%) patients, death occurred in 21/111 (18.9%) patients. Multiple logistic regression models correlated variables with mortality: age (OR: 1.07; 95% CI 1.02–1.12; p: 0.012; age >74 YO AUC ROC curve: 0.725), intubation need (OR: 23.35; 95% CI 4.39–124.36; p < 0.001), D dimer (OR: 1.39; 95% CI 1.02–1.89; p: 0.036; value >1928.5 ug/L AUC ROC curve: 0.731), C‐reactive protein (OR: 1.18; 95% CI 1.05–1.32; p < 0.005; value >29.35 mg/dl AUC ROC curve: 0.836). A risk score was created to predict intrahospital probability of death, by the equation: 3.6 (age >75 YO) + 66 (intubation need) + 28 (C‐reactive protein >29) + 2.2 (D dimer >1900). CONCLUSIONS: A novel and original risk score were developed to predict the probability of death in Covid 19 in‐hospital patients concerning combined risk factors. In December 2019, an infectious outbreak was observed in the center of China which would achieve global epidemic dimensions with exponential pandemic spread in the first few months of 2020. [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] Viral pneumonia cases were noted, along with the identification of a novel viral agent SARS-CoV 2 (COVID- 19) , previously called "2019 novel coronavirus" (2019-nCoV). 1,2 Its mortality rate was reported to be very variable concerning investigations throughout different continents (from 2.3% to 21%). 10, [13] [14] [15] It observed is an increase in cytokines in patients affected by the virus, [16] [17] [18] as well as in the natriuretic peptide pro BNP NT-proBNP, levels of ultra-sensitive troponin (cTnI), and D-dimer. 19, 20 Imaging approaches can lead to diagnostic information of COVID-19 complications and the extent of the disease and could also provide prognostic information. Echocardiography may be employed to diagnose myocardial dysfunction in order to demonstrate cardiac involvement of COVID 19. Few complete echocardiographic studies have been undertaken so far, but the most relevant findings correlate right ventricle dilatation with a troponin increase 21 and lower free wall longitudinal strain to a worse prognosis. 22 Thoracic computed tomography can aid in the possible diagnosis of COVID-19 infection and it can be used to detect the pulmonary infectious process and to estimate the extent of pulmonary involvement. 23, 24 There is a paucity of information concerning the Brazilian COVID-19 in-hospital mortality rate and its relationship to biomarkers, clinical data, and echocardiographic and tomographic findings. To our best knowledge, this is the first study to address the clinical, laboratory, and imaging data concerning Brazilian COVID-19 in-hospital mortality probability taking into consideration combined risk factors. Thus, we performed an investigation to study in-hospital mortality concerning demographic data, clinical events during the in-hospital period, biomarkers, and echocardiographic and tomographic findings. Echocardiography was performed following clinical needs. The echocardiographic examination was performed following current international recommendations for COVID 19 echocardiographic performance. 25 Thoracic computed tomography was performed upon the request of the attending physician responsible for the patient, based on the patient's clinical needs. Thoracic involvement of the parenchyma was considered as follows: >25%, 25%-50%, and >50%. The qualitative characteristics evaluated by absolute and relative frequencies; quantitative characteristics of the patients were described by summary measures (mean, SD, median, minimum, and maximum). 27, 28 Deaths were described according to the qualitative characteristics evaluated using absolute and relative frequencies, and the association was verified with the use of chi-square tests or exact tests (Fisher's exact test or likelihood ratio test). The quantitative characteristics were described according to the mortality of the patients using summary measures and were compared using Student's t-tests or Mann-Whitney tests according to the probability distribution of the variables. 27, 28 Multiple logistic regression models were adjusted, maintaining the variables age, need for intubation, diabetes, and heart disease and a laboratory or cardiological characteristic was inserted separately in each model due to the small number of cases of death in the sample, all characteristics being maintained in the final model "full model". 27, 28 To perform the analyses, IBM-SPSS for Windows version 20.0 software was used and Microsoft Excel 2003 software was used to tabulate the data. The tests were performed with a 5% significance level. Echocardiography, tomographic examinations, and laboratory investigation were performed according to the request of the attending physician responsible for the patient, in response to the clinical need during in-hospital stay. Patients and legal responsibles were aware of the report of the findings of the clinical investigation in medical journals. The demographic information, comorbidities, clinical in-hospital course, laboratory data, and the echocardiographic and thoracic computed tomography findings are presented in Tables 1, 2 Demographic, clinical evolution, laboratory, echocardiographic, and tomographic data analysis related to mortality among the COVID-19 in-hospital patients are presented in Table 5 (just the parameters with statistical significance plus the TAPSE with p = 0.064; all other studied parameters did not reach the statistical significance level). The multiple logistic regression model for predicting COVID-19 in-hospital mortality is presented in Table 6 . In-hospital mortality was related to age, need for intubation and mechanical ventilation, and the CRP and D dimer levels. The area under the receiver operating characteristic curves for predicting COVID-19 patients in-hospital mortality concerning age, D-dimer and C-reactive protein are shown in Table 7 and Graph 1. A risk score was created to predict intrahospital probability of death, by the equation: 3.6 (age >75 YO) + 66 (intubation need) + 28 (C-reactive protein >29) + 2.2 (D dimer >1900). To our best knowledge, this is the first investigation to study data including a complete transthoracic echocardiogram, computed thoracic tomographic (CT) studies, biomarkers, laboratory data, and clinical information in hospitalized patients with COVID-19 in a tertiary hospital in Brazil that aimed to predict the probability of in-hospital death combining risk factors. These data seem to be relevant, taking into consideration the number of Brazilian patients affected by models for patients with hypertension, diabetes, or obesity. We wonder if this could be related to the number of patients studied (111). In our study, we observed increased levels of C-reactive protein, D-dimer, BNP, troponin-I, ferritin, and interleukin 6 ( Table 2 ). The relevance of the increased biomarkers to in-hospital mortality was dem- under multiple logistic regression model analysis. We consider that although the OR is high for the need for intubation and mechanical ventilation need and mortality, it also has a very wide CI, which could lead to a certain concern about its accuracy and greater uncertainty in relation to the estimate. A study considering myocardial injury was observed that 1 in 5 patients presented myocardial involvement what could predict 30 day mortality. 29 The findings of the echocardiographic and thoracic tomographic studies were not associated with COVID-19 in-hospital mortality. Tomographic studies were performed in 54/111 (48.6) patients. Thoracic parenchyma involvement occurred between 25% and 50% in 26/30 (86.7%) patients who were submitted to computed thoracic tomography investigation, and mainly of them maintained the tomographic findings during the first weeks after hospital discharge. (intubation need) + 28 (C-reactive protein >29) + 2.2 (D dimer >1900). The data that support the findings of this study are available from the corresponding author upon reasonable request. 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