Survival analysis of Intensive Care Units (ICUs) of field hospitals in the Federal District - Brazil during the COVID 19 pandemic using Kaplan Meier curves.
Análise de sobrevida das Unidades de Terapia Intensivas (UTIs) de hospitais de campanha do Distrito Federal - Brasil durante a pandemia de COVID 19 por curvas de Kaplan Meier.
Palavras-chave:
Curves, Kaplan-Meier Survival, COVID-19, Field Hospitals, ICU Intensive Care Units, Severe Acute RespiratoryResumo
The COVID-19 pandemic is one of the most impactful public health emergencies the world has ever seen. A classic epidemiological analysis tool that can be used is the Kaplan-Meier (KM) survival model, which calculates the probability of survival for a group of patients. This study aims to describe the Estimated Survival of patients admitted to the ICUs of Field Hospitals in the Federal District during the COVID 19 Pandemic. Methodology: It is a non-concurrent cohort study of patients with COVID-19 consecutively admitted to the ICUs of field hospitals. The variables collected upon admission to the ICU were evaluated using KM curves and the non-parametric log-rank test. Results: For all patients admitted to the ICUs of field hospitals, the median length of stay was 10 days. Patients have a 94.95%, 58.45% and 19.92% probability of surviving 1 day, 10 days and 30 days of hospitalization respectively. Conclusion: The Kaplan-Meier curve is a strategic tool, it provides a clear view of how long the healthcare system needs to treat a person.
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Referências
ABANI, O. et al. Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial RECOVERY Collaborative Group*The Lancet. [s.l: s.n.]. Disponível em: .
BOTELHO, F.; SILVA, C.; CRUZ, F. Artigos de Revisão Epidemiologia explicada-Análise de Sobrevivência. [s.l: s.n.]. Disponível em: .
BRANQUINHO, A. L. A. et al. Descriptive study of patients with COVID-19 referred to the ICU and outcome in field hospitals in the Federal District during the Pandemic. Concilium, v. 24, n. 5, p. 507–519, 1 abr. 2024.
CALABUIG, J. M. et al. Kaplan-Meier Type Survival Curves for COVID-19: A Health Data Based Decision-Making Tool. Frontiers in Public Health, v. 9, 25 out. 2021.
CHURPEK, M. M. et al. Hospital-level variation in death for critically Ill patients with COVID-19. American Journal of Respiratory and Critical Care Medicine, v. 204, n. 4, p. 403–411, 15 ago. 2021.
CORRÊA, T. D. et al. Clinical characteristics and outcomes of COVID-19 patients admitted to the intensive care unit during the first year of the pandemic in Brazil: a single center retrospective cohort study. Einstein (Sao Paulo, Brazil), v. 19, p. eAO6739, 2021.
DESIGNED RESEARCH; S, A. P. G. M. M. Projecting hospital utilization during the COVID-19 outbreaks in the United States. v. 117, n. 16, p. 9122–9126, 2020.
FAUST, J. S.; DEL RIO, C. Assessment of deaths from COVID-19 and from seasonal influenza. JAMA Internal MedicineAmerican Medical Association, , 1 ago. 2020.
GÓMEZ-ROMERO, F. J. et al. Clinical features and mortality of COVID-19 patients admitted to ICU according to SOFA score. Medicine (United States), v. 101, n. 28, p. E29206, 15 jul. 2022.
HUANG, Y. et al. Obesity in patients with COVID-19: a systematic review and meta-analysis. Metabolism: Clinical and Experimental, v. 113, 1 dez. 2020.
KASS, D. A.; DUGGAL, P.; CINGOLANI, O. Obesity could shift severe COVID-19 disease to younger ages. The LancetLancet Publishing Group, , 16 maio 2020.
MA, X.; VERVOORT, D. Critical care capacity during the COVID-19 pandemic: Global availability of intensive care beds. Journal of Critical Care, v. 58, p. 96–97, 1 ago. 2020.
MIOT, H. A. Análise de sobrevivência em estudos clínicos e experimentais. Jornal Vascular BrasileiroSociedade Brasileira de Angiologia e Cirurgia Vascular, , 1 out. 2017.
MORENO, R. P. et al. SAPS 3 - From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Medicine, v. 31, n. 10, p. 1345–1355, 2005.
PERES, I. T. et al. Sociodemographic factors associated with COVID-19 in-hospital mortality in Brazil. Public Health, v. 192, p. 15–20, 1 mar. 2021.
POTERE, N. et al. Acute complications and mortality in hospitalized patients with coronavirus disease 2019: A systematic review and meta-analysis. Critical CareBioMed Central, , 2 jul. 2020.
RIBEIRO, K. B. et al. Social inequalities and COVID-19 mortality in the city of Saõ Paulo, Brazil. International Journal of Epidemiology, v. 50, n. 3, p. 732–742, 1 jun. 2021.
SOARES, M. et al. Organizational characteristics, outcomes, and resource use in 78 Brazilian intensive care units: the ORCHESTRA study. Intensive Care Medicine, v. 41, n. 12, p. 2149–2160, 1 dez. 2015.
VELANOVICH, V. et al. Accumulating deficits model of frailty and postoperative mortality and morbidity: its application to a national database. Journal of Surgical Research, v. 183, n. 1, p. 104–110, 2013.
VINCENT, J.-L. et al. The SOFA (Sepsis.related Organ Failure Assessment) score to describe organ dysfunction/failureIntensive Care Med. [s.l.] Springer-Verlag, 1996.
XU, Z. et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. The Lancet Respiratory Medicine, v. 8, n. 4, p. 420–422, 1 abr. 2020.
YAN, Y. et al. Clinical characteristics and outcomes of patients with severe covid-19 with diabetes. BMJ Open Diabetes Research and Care, v. 8, n. 1, 27 abr. 2020.
