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Mediterranean Journal of Infection, Microbes and Antimicrobials ; 10, 2021.
Article in English | EMBASE | ID: covidwho-1614129

ABSTRACT

Introduction: Four scoring models, including the Rapid Emergency Medicine Score (REMS), Charlson Comorbidity Index (CCI), Acute Physiology and Chronic Health Assessment-II (APACHE-II), and Sequential Organ Failure Assessment (SOFA), were examined. The effectiveness of these scores in mortality prediction of intensive care unit (ICU)-admitted Coronavirus disease-2019 (COVID-19) patients was investigated. Materials and Methods: The present retrospective analysis was conducted in a single center among patients with confirmed or suspected COVID-19 diagnosis who were admitted to emergency department and then ICU between March and December 2020. The REMS, APACHE-II, CCI, and SOFA were used to evaluate the mortality associated factors. Results: The sample included 411 patients above 18 years of age, with a median age of 71 (interquartile range: 60-80), and made up of 61.6% males. High creatinine, potassium, fraction of inspired oxygen and white blood cell levels as well as low hematocrit levels, pH, mean arterial pressure, and systolic and diastolic blood pressure accounted for a poor prognosis. Statistically significant differences were determined between laboratory values and physiological findings (p<0.05). Comorbidity was found in 368 (89.5%) patients while malignancy and dementia were significantly associated to mortality (p<0.001 and 0.019, respectively). The scoring systems are clearly among the important indicators of in-hospital mortality (p<0.001). Additionally, the receiver operating curve analysis did not reveal significant differences in the scoring systems when considered in terms of discriminative power (p>0.05). Conclusion: The results revealed the effectiveness of REMS, CCI, APACHE-II, and SOFA in the prediction of critical COVID-19 patients' in-hospital mortality;but none of the scoring systems prevailed over others. Therefore, the REMS, APACHE-II, CCI, and SOFA scoring models can guide not only emergency physicians but also all clinicians who contribute to the management of critical COVID-19 cases.

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