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ObjectivesCurrently available COVID-19 prognostic models have focused on laboratory and radiological data obtained following admission. However, these tests are not available on initial assessment or in resource-limited settings. We aim to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of COVID-19, to identify patients at risk of critical outcomes. MethodsWe used data from the SEMI-COVID-19 Registry, a nationwide multicenter cohort of consecutive patients hospitalized for COVID-19 from 132 centers in Spain. Clinical signs and symptoms, demographic variables, and medical history ascertained at hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to construct a predictive model. We externally validated the final model in a separate cohort of patients admitted at less-complex hospitals (< 300 beds).We undertook decision curve analysis to assess the clinical usefulness of the predictive model. The primary outcome was a composite of in-hospital death, mechanical ventilation or admission to intensive care unit. ResultsThere were 10,433 patients, 7,850 (primary outcome 25.1%) in the development cohort and 2,583 (primary outcome 27.0%) in the validation cohort. Variables in the final model included: age, cardiovascular disease, chronic kidney disease, dyspnea, tachypnea, confusion, systolic blood pressure, and SpO2[≤]93% or oxygen requirement.The C-statistic in the development cohort was 0.823 (95% CI,0.813-0.834). On external validation, the C-statistic was 0.792 (95% CI,0.772-0.812). The model showed a positive net benefit for threshold probabilities between 3% and 79%. ConclusionsAmong patients presenting with COVID-19, the model based on easily-obtained clinical information had good discrimination and generalizability for identifying patients at risk of critical outcomes without the need of additional testing. The online calculator provided would facilitate triage of patients during the pandemic. This study could provide a useful tool for decision-making in health systems under pandemic pressure and resource-limited settings.
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ObjectivesA decrease in blood cell counts, especially lymphocytes and eosinophils, has been described in patients with severe SARS-CoV-2 (COVID-19), but there is no knowledge of the potential role of their recovery in these patients prognosis. This article aims to analyse the effect of blood cell depletion and blood cell recovery on mortality due to COVID-19. DesignThis work is a multicentre, retrospective, cohort study of 9,644 hospitalised patients with confirmed COVID-19 from the Spanish Society of Internal Medicines SEMI-COVID-19 Registry. SettingThis study examined patients hospitalised in 147 hospitals throughout Spain. ParticipantsThis work analysed 9,644 patients (57.12% male) out of a cohort of 12,826 patients [≥]18 years of age hospitalised with COVID-19 in Spain included in the SEMI-COVID-19 Registry as of 29 May 2020. Main outcome measuresThe main outcome measure of this work is the effect of blood cell depletion and blood cell recovery on mortality due to COVID-19. Univariate analysis was performed to determine possible predictors of death and then multivariate analysis was carried out to control for potential confounders. ResultsAn increase in the eosinophil count on the seventh day of hospitalisation was associated with a better prognosis, including lower mortality rates (5.2% vs 22.6% in non-recoverers, OR 0.234 [95% CI, 0.154 to 0.354]) and lower complication rates, especially regarding to development of acute respiratory distress syndrome (8% vs 20.1%, p=0.000) and ICU admission (5.4% vs 10.8%, p=0.000). Lymphocyte recovery was found to have no effect on prognosis. Treatment with inhaled or systemic glucocorticoids was not found to be a confounding factor. ConclusionEosinophil recovery in patients with COVID-19 is a reliable marker of a good prognosis that is independent of prior treatment. This finding could be used to guide discharge decisions.
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BackgroundSpain has been one of the countries most affected by the COVID-19 pandemic. ObjectiveTo create a registry of patients with COVID-19 hospitalized in Spain in order to improve our knowledge of the clinical, diagnostic, therapeutic, and prognostic aspects of this disease. MethodsA multicentre retrospective cohort study, including consecutive patients hospitalized with confirmed COVID-19 throughout Spain. Epidemiological and clinical data, additional tests at admission and at seven days, treatments administered, and progress at 30 days of hospitalization were collected from electronic medical records. ResultsUp to April 30th 2020, 6,424 patients from 109 hospitals were included. Their median age was 69.1 years (range: 18-102 years) and 56.9% were male. Prevalences of hypertension, dyslipidemia, and diabetes mellitus were 50.2%, 39.7%, and 18.7%, respectively. The most frequent symptoms were fever (86.2%) and cough (76.5%). High values of ferritin (72.4%), lactate dehydrogenase (70.2%), and D-dimer (61.5%), as well as lymphopenia (52.6%), were frequent. The most used antiviral drugs were hydroxychloroquine (85.7%) and lopinavir/ritonavir (62.4%). 31.5% developed respiratory distress. Overall mortality rate was 21.1%, with a marked increase with age (50-59 years: 4.2%, 60-69 years: 9.1%, 70-79 years: 21.4%, 80-89 years: 42.5%, [≥] 90 years: 51.1%). ConclusionsThe SEMI-COVID-19 Network provides data on the clinical characteristics of patients with COVID-19 hospitalized in Spain. Patients with COVID-19 hospitalized in Spain are mostly severe cases, as one in three patients developed respiratory distress and one in five patients died. These findings confirm a close relationship between advanced age and mortality.
