Predicting critical illness on initial diagnosis of COVID-19: Development and validation of the PRIORITY model for outpatient applicability. (preprint)

OBJECTIVE 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. DESIGN National multicenter cohort study. SETTING Data from the SEMI (Sociedad Espanola de Medicina Interna) COVID-19 Registry, a nationwide cohort of consecutive COVID-19 patients presenting in 132 centers between March 23 and May 21, 2020. Model development used data from hospitals with >300 beds, and validation used those from hospitals with <300 beds. PARTICIPANTS Adults (age [≥] 18 years) presenting with COVID-19 diagnosis. MAIN OUTCOME MEASURE Composite of in-hospital death, mechanical ventilation or admission to intensive care unit. RESULTS There were 10,433 patients, 7,850 (main outcome rate 25.1%) in the model development cohort and 2,583 (main outcome rate 27.0%) in the validation cohort. The clinical variables in the final model were: age, cardiovascular disease, moderate or severe chronic kidney disease, dyspnea, tachypnea, confusion, systolic blood pressure, and SpO2 [≤] 93% or supplementary oxygen requirement at presentation. The model developed had C-statistic of 0.823 (95% confidence interval [CI] 0.813 to 0.834) and calibration slope of 0.995. The external validation had C-statistic of 0.792 (95% CI, 0.772 to 0.812) and calibration slope of 0.872. The model showed positive net benefit in terms of hospitalizations avoided for the predicted probability thresholds between 3% and 79%. CONCLUSIONS Among patients presenting with COVID-19, easily-obtained basic clinical information had good discrimination for identifying patients at risk of critical outcomes, and the model showed good generalizability. A model-based online prediction calculator provided with this paper would facilitate triage of patients during the pandemic.

Healthcare workers hospitalized due to COVID-19 have no higher risk of death than general population. Data from the Spanish SEMI-COVID-19 Registry. (preprint)

Aim: To determine whether healthcare workers (HCW) hospitalized in Spain due to COVID-19 have a worse prognosis than non-healthcare workers (NHCW). Methods: Observational cohort study based on the SEMI-COVID-19 Registry, a nationwide registry that collects sociodemographic, clinical, laboratory, and treatment data on patients hospitalised with COVID-19 in Spain. Patients aged 20-65 years were selected. A multivariate logistic regression model was performed to identify factors associated with mortality. Results: As of 22 May 2020, 4393 patients were included, of whom 419 (9.5%) were HCW. Median (interquartile range) age of HCW was 52 (15) years and 62.4% were women. Prevalence of comorbidities and severe radiological findings upon admission were less frequent in HCW. There were no difference in need of respiratory support and admission to intensive care unit, but occurrence of sepsis and in-hospital mortality was lower in HCW (1.7% vs. 3.9%; p=0.024 and 0.7% vs. 4.8%; p<0.001 respectively). Age, male sex and comorbidity, were independently associated with higher in-hospital mortality and healthcare working with lower mortality (OR 0.219, 95%CI 0.069-0.693, p=0.01). 30-days survival was higher in HCW (0.968 vs. 0.851 p<0.001). Conclusions: Hospitalized COVID-19 HCW had fewer comorbidities and a better prognosis than NHCW. Our results suggest that professional exposure to COVID-19 in HCW does not carry more clinical severity nor mortality.

Severity scores in COVID-19 pneumonia: a multicenter, retrospective, cohort study (preprint)

BackgroundIdentification of patients on admission to hospital with Coronavirus infectious disease 2019 (COVID-19) pneumonia who can develop poor outcomes have not yet ben comprehensively assessed.ObjectiveTo compare severity scores used for community acquired pneumonia to identify high-risk patients.DesignPSI, CURB-65, qSOFA and MuLBSTA, a new score for viral pneumonia, were calculated on admission to hospital to identify high-risk patients for in-hospital mortality. Area under receiver operating characteristics curve (AUROC), sensitivity and specificity for each score were determined and AUROC were compared among them.ParticipantsPatients with COVID-19 pneumonia included in the SEMI-COVID-19 Network.Key resultsWe examined 10,238 patients with COVID-19. Mean age of patients was 66.6 years and 57.9% were males. The most common comorbidities were: hypertension (49.2%), diabetes (18.8%) and chronic obstructive pulmonary disease (12.8%). Acute respiratory distress syndrome (34.7%) and acute kidney injury (13.9%) were the most common complications. In-hospital mortality was 20.9%.  PSI and CURB-65 showed the highest AUROC (0.835 and0.825, respectively). qSOFA and MuLBSTA had a lower AUROC (0.728 and 0.715, respectively). qSOFA was the most specific score (specificity 95.7%) albeit its sensitivity was only 26.2%. PSI had the highest sensitivity (84.1%) and a specificity of 72.2%.ConclusionsPSI and CURB-65, specific severity scores for pneumonia, were the best scores for COVID-19 pneumonia and were better than qSOFA and MuLBSTA. Additionally, qSOFA, the simplest score to perform, was the most specific albeit the least sensitive.

Predicting clinical outcome with phenotypic clusters in COVID-19 pneumonia: 2 an analysis of 12,066 hospitalized patients from the Spanish registry SEMI-3 COVID-19. (preprint)

(1) Background: This study aims to identify different clinical phenotypes in COVID-19 88 pneumonia using cluster analysis and to assess the prognostic impact among identified clusters in 89 such patients. (2) Methods: Cluster analysis including 11 phenotypic variables was performed in a 90 large cohort of 12,066 COVID-19 patients, collected and followed-up from March 1, to July 31, 2020, 91 from the nationwide Spanish SEMI-COVID-19 Registry. (3) Results: Of the total of 12,066 patients 92 included in the study, most were males (7,052, 58.5%) and Caucasian (10,635, 89.5%), with a mean 93 age at diagnosis of 67 years (SD 16). The main pre-admission comorbidities were arterial 94 hypertension (6,030, 50%), hyperlipidemia (4,741, 39.4%) and diabetes mellitus (2,309, 19.2%). The 95 average number of days from COVID-19 symptom onset to hospital admission was 6.7 days (SD 7). 96 The triad of fever, cough, and dyspnea was present almost uniformly in all 4 clinical phenotypes 97 identified by clustering. Cluster C1 (8,737 patients, 72.4%) was the largest, and comprised patients 98 with the triad alone. Cluster C2 (1,196 patients, 9.9%) also presented with ageusia and anosmia; 99 cluster C3 (880 patients, 7.3%) also had arthromyalgia, headache, and sore throat; and cluster C4 100 (1,253 patients, 10.4%) also manifested with diarrhea, vomiting, and abdominal pain. Compared to 101 each other, cluster C1 presented the highest in-hospital mortality (24.1% vs. 4.3% vs. 14.7% vs. 102 18.6%; p<0.001). The multivariate study identified phenotypic clusters as an independent factor for 103 in-hospital death. (4) Conclusion: The present study identified 4 phenotypic clusters in patients with 104 COVID-19 pneumonia, which predicted the in-hospital prognosis of clinical outcomes.

The Prognostic Value of Eosinophil Recovery in COVID-19: A Multicentre, Retrospective Cohort Study on Patients Hospitalised in Spanish Hospitals. (preprint)

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.