Analisis Meta Menggunakan Effect Size Odds Ratio Pada Pasien COVID-19 - Hartina Husain; Azmidar Azmidar (Politeknik Statistika STIS, 2022)
Meta analysis is an analytical method using effect size to summarize various studies to obtain comprehensive conclusions. The effect size odds ratio method was used to determine the difference between the experimental group and the control group on COVID-19 data. Research data sourced from journal references that meet the inclusion-exclusion criteria. This study aims to analyze the risk factors that can affect the death of COVID-19 patients in terms of the Intensive Care Unit (ICU) handling in the hospital, gender, and age of the patient. There are 12 research references that meet the inclusion and exclusion criteria that serve as literature for this meta-analysis. The results showed that the risk factors for COVID-19 patients dying were influenced by the category of treatment of patients with ICU, patient gender and age, each of which had an odds ratio of 9.51 , 2.34, and 0.23. Patients who received ICU treatment had a greater risk of dying than control patients (without ICU treatment). Male patients have an increased risk of death compared to female patients. Meanwhile, patients aged less than 60 years have a 77% lower risk of dying compared to patients aged 60 years and over.