ABC-GOALScl Score Predicts Admission to the Intensive Care Unit and Mortality of COVID-19 Patients over 60 years of Age
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Background: One of the risk factors for getting seriously ill from COVID-19 and reaching high mortality rates is older age. Older age is also associated with comorbidities, which are risk factors for severe COVID-19 infection. Among the tools that have been evaluated to predict intensive care unit (ICU) admission and mortality is ABC-GOALScl.
Aim: In the present study we validated the utility of ABC-GOALScl to predict in-hospital mortality in subjects over 60 years of age who were positive for SARS-CoV-2 virus at the moment of admission with the purpose of optimizing sanitary resources and offering personalized treatment for these patients.
Methods: This was an observational, descriptive, transversal, non-interventional and retrospective study of subjects (≥ 60 years of age), hospitalized due to COVID-19 infection at a general hospital in northeastern Mexico. A logistical regression model was used for data analysis.
Results: Two hundred forty-three subjects were included in the study, whom 145 (59.7%) passed away, while 98 (40.3%) were discharged. Average age was 71, and 57.6% were male. The prediction model ABC-GOALScl included sex, body mass index, Charlson comorbidity index, dyspnea, arterial pressure, respiratory frequency, SpFi coefficient (Saturation of oxygen/Fraction of inspired oxygen ratio), serum levels of glucose, albumin, and lactate dehydrogenase; all were measured at the moment of admission. The area under the curve for the scale with respect to the variable of discharge due to death was 0.73 (IC 95% = 0.662-0.792).
Conclusion: The ABC-GOALScl scale to predict ICU admission in COVID-19 patients is also useful to predict in-hospital death in COVID-19 patients ≥ 60 years old.
Casas-Rojo J, Ventura P, Anton Santos J, de Latierro A, Arevalo-Lorido J, Mauri M Intern Emerg Med. 2023; 18(6):1711-1722.
PMID: 37349618 DOI: 10.1007/s11739-023-03338-0.
Zhu Y, Yu B, Tang K, Liu T, Niu D, Zhang L Front Public Health. 2023; 11:1194349.
PMID: 37304114 PMC: 10254410. DOI: 10.3389/fpubh.2023.1194349.