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Multicenter validation of Early Warning Scores for detection of clinical deterioration in COVID-19 hospitalized patients Validación multicéntrica de Sistemas de Alerta Temprana para la detección precoz de deterioro clínico en pacientes hospitalizados por COVID-19
Medicina intensiva ; 2022.
Article in English | EuropePMC | ID: covidwho-2073182
ABSTRACT
Objective Investigate the predictive value of NEWS2, NEWS-C, and COVID-19 Severity Index for predicting intensive care unit (ICU) transfer in the next 24 h. Design Retrospective multicenter study. Setting Two third-level hospitals in Argentina. Patients All adult patients with confirmed COVID-19, admitted on general wards, excluding patients with non-intubated orders. Interventions Patients were divided between those who were admitted to ICU and non-admitted. We calculated the three scores for each day of hospitalization. Variables We evaluate the calibration and discrimination of the three scores for the outcome ICU admission within 24, 48 h, and at hospital admission. Results We evaluate 13,768 days of hospitalizations on general medical wards of 1318 patients. Among these, 126 (9.5%) were transferred to ICU. The AUROC of NEWS2 was 0.73 (95%CI 0.68–0.78) 24 h before ICU admission, and 0.52 (95%CI 0.47–0.57) at hospital admission. The AUROC of NEWS-C was 0.73 (95%CI 0.68–0.78) and 0.52 (95%CI 0.47–0.57) respectively, and the AUROC of COVID-19 Severity Index was 0.80 (95%CI 0.77–0.84) and 0.61 (95%CI 0.58–0.66) respectively. COVID-19 Severity Index presented better calibration than NEWS2 and NEWS-C. Conclusion COVID-19 Severity index has better calibration and discrimination than NEWS2 and NEWS-C to predict ICU transfer during hospitalization.
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Collection: Databases of international organizations Database: EuropePMC Type of study: Prognostic study Language: English Journal: Medicina intensiva Year: 2022 Document Type: Article

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Collection: Databases of international organizations Database: EuropePMC Type of study: Prognostic study Language: English Journal: Medicina intensiva Year: 2022 Document Type: Article