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International Journal of Biomedical Science and Travel Medicine
Published by Universitas Warmadewa
ISSN : 30477441     EISSN : 30477433     DOI : https://doi.org/10.22225/ijbstm
Core Subject : Health,
Medicine & Pharmacology Public Health
International Journal of Biomedical Science and Travel Medicine is published twice (March and September) a year. The objective is to promote articles on biology and medicine. International Journal of Biomedical Science and Travel Medicine publishes original research work related to biological and medicine. The journal publishes Original articles, Short Reports, Case Reports, and Review articles. All articles published in International Journal of Biomedical Science and Travel Medicine (IJBSTM) are peer-reviewed and published online for immediate access and citation. International Journal of Biomedical Science and Travel Medicine (IJBSTM) publishes the Original clinical and experimental research studies, Review articles, Case reports on topics but not limited to: Biocemistry, Genetics and molecular biology, Medicine, Environmental health, Tropical diseases, Diseases in tropics, Global health, Pharmacological sciences, Biomedical sciences, Public health, Infection, Epidemiology and clinical epidemiology, Molecular biology, Microbiology, Travel Medicine
Arjuna Subject : Kedokteran - Kedokteran (Lain-Lain)
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Search results for , issue "7-11" : 1 Documents clear
Probability-based Equation for Predicting Mortality in COVID-19 Patients Pande Putu Dimas Yoga Pratama; I Made Wisnu Wardhana; Made Dharmesti Wijaya
International Journal of Biomedical Science and Travel Medicine 7-11
Publisher : Publication Department, Universitas Warmadewa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22225/ijbstm.1.1.2024.7-11

Abstract

Background The global mortality rate for coronavirus disease-2019 (COVID-19) continues to climb. The study goal is to provide a proper equation to predict mortality in COVID-19 patients based on medical history, and laboratory examination Methods This was a case-control study. Patients with COVID-19 confirmed case was taken for medical history, physical, and laboratory examination. CBC and D-Dimer were checked when patients were admitted to the hospital. Statistical analysis that was use include Chi-Square or Fisher’s test as comparative study, risk estimate for odds ratio, and logistic regression to formulated the equation. Results Ninety-six patients were gathered at the end of study. The study grouped patients based on survival at end of care which is life and death as dependent variable. We also grouped patients based on several parameter like geriatric age, comorbidities, symptoms (fever, cough, anosmia, cold, dysphagia, and shortness of breath), anemia, leukocytosis/leukopenia, thrombocytopenia, elevated D-Dimer, and pneumonia, as independent variables. Geriatric, comorbidities, fever, cough, shortness of breath, anemia, leukocytosis/leucopenia, lymphopenia, and elevated D-Dimer had significant differences with p < 0.05. Odds ratio and 95%CI for these parameters were 3.02 (1.11-8.20), 4.07 (1.35-12.27), 3.57 (0.96-13.23), 5.04 (1.08-23.34), 4.75 (1.02-22.02), 3.26 (1.15-9.25), 6.40 (2.19-18.63), 3.16 (0.97-10.30), and 0.70 (0.61-0.81), respectively. Multivariate analysis using logistic regression based on this result was calculated and we were able to make this probability equation, p = 1/(1+e-y), with e =2.7, and y = - 24.99 + 1.621(comorbidities) + 1.944(cough) + 1.643(leukocytosis/leukopenia) + 1.397(anemia) + 20.625(elevated D-Dimer). ROC was use to confirm this predicted probability with AUC 0.88 Conclusion This equation was simple enough to be used as tool for clinician to predict mortality in COVID-19 patients. If we were to assume that for example patient with COVID-19 with comorbidities had cough as symptoms, and also had leukocytosis/leukopenia, anemia, and elevated D-Dimer level based on laboratory result, then that patient had 90.25% probability of death as outcome. The study was able to predict death in COVID-19 patients with up to 90.25% probability using our equation with excellent discrimination between these patients

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