ABC2-SPH risk score for in-hospital mortality in COVID-19 patients: development, external validation and comparison with other available scores

Abstract

Objectives The majority of available scores to assess mortality risk of coronavirus disease 19 (COVID-19) patients in the emergency department have high risk of bias. Therefore, our aim was to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients, and to compare this score with other existing ones. Methods Consecutive patients (≥18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March-July, 2020. The model was validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Results Median (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO 2 /FiO 2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833 to 0.885]) and Spanish (0.894 [95% CI 0.870 to 0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions We designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19.

Usefulness of the C2HEST Score in Predicting the Clinical Outcomes of COVID-19 in Diabetic and Non-Diabetic Cohorts

“…The ROC analysis indicates that C 2 HEST poorly predicts in-hospital deaths, which indicates the need to use other scales for this purpose. To date, the ABC2-SPH risk score was validated for predicting in-hospital mortality in COVID-19 and displayed better discrimination ability compared to other existing scores [28]. However, its effectiveness and similarly other scales predicting the mortality and severe course of the disease in the diabetic cohort require further detailed analysis.…”

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

“…It is known that tachypnea is one of the alarming COVID-19 symptoms as it may be an indicator of COVID-19 pneumonia. 39 Despite the fact that SF ratio, a strong predictor of COVID-19 prognosis and mortality, 4,40 was slightly higher in hypothyroidism patients, the difference was not clinically relevant (428.6 vs. 423.8, p=0.034).…”

“…To adjust for potential confounding variables, patients who had underlying hypothyroidism were matched to patients who had not underlying hypothyroidism (controls) on the basis of propensity score. Propensity score model was estimated by logistic regression, and included gender, age, number of comorbidities (hypertension, diabetes mellitus, obesity, coronary artery disease, heart failure, atrial fibrillation or flutter, cirrhosis, chronic obstructive pulmonary disease, cancer and previous stroke) 4 and hospital. Patients from the control group were searched to find those who had the closest propensity score from the hypothyroidism group (within 0.17 standard deviations of the logit of the propensity score, on a scale from 0-1.00), using the MatchIt package in R software.…”

“…1 It is well known that individuals with some underlying medical conditions, such as cardiovascular diseases, cancer, obesity, diabetes and hypertension, are more likely to develop severe COVID-19, require hospitalization and intensive care, and have higher mortality rates. 2,3,4 Nevertheless, other conditions such as asthma and Chagas disease surprisingly have not been related to more severe cases of COVID-19. 5 However, many factors that interfere on COVID-19 clinical characteristics, symptoms and prognosis are still unknown and require further investigation to improve disease prevention and patient management.…”

Mechanical Ventilation and Death During Pregnancy Complicated by COVID-19: A Prognostic Analysis from the Brazilian COVID-19 Registry Score

“…This is a multicenter retrospective substudy of the Brazilian COVID-19 Registry, a multicenter cohort study of consecutive patients with laboratory-con rmed COVID-19 hospitalized between March and September 2020, in 37 Brazilian public and private hospitals, as previously described (11,12). It adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline (13).…”