(2024) Association of the medication protocols and longitudinal change of COVID-19 symptoms: a hospital-based mixed-statistical methods study. Journal of Biopharmaceutical Statistics. p. 21. ISSN 1054-3406
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Abstract
The objective of this study was to identify the relationship between hospitalization treatment strategies leading to change in symptoms during 12-week follow-up among hospitalized patients during the COVID-19 outbreak. In this article, data from a prospective cohort study on COVID-19 patients admitted to Khorshid Hospital, Isfahan, Iran, from February 2020 to February 2021, were analyzed and reported. Patient characteristics, including socio-demographics, comorbidities, signs and symptoms, and treatments during hospitalization, were investigated. Also, to investigate the treatment effects adjusted by other confounding factors that lead to symptom change during follow-up, the binary classification trees, generalized linear mixed model, machine learning, and joint generalized estimating equation methods were applied. This research scrutinized the effects of various medications on COVID-19 patients in a prospective hospital-based cohort study, and found that heparin, methylprednisolone, ceftriaxone, and hydroxychloroquine were the most frequently prescribed medications. The results indicate that of patients under 65 years of age, 76 had a cough at the time of admission, while of patients with Cr levels of 1.1 or more, 80 had not lost weight at the time of admission. The results of fitted models showed that, during the follow-up, women are more likely to have shortness of breath (OR = 1.25; P-value: 0.039), fatigue (OR = 1.31; P-value: 0.013) and cough (OR = 1.29; P-value: 0.019) compared to men. Additionally, patients with symptoms of chest pain, fatigue and decreased appetite during admission are at a higher risk of experiencing fatigue during follow-up. Each day increase in the duration of ceftriaxone multiplies the odds of shortness of breath by 1.15 (P-value: 0.012). With each passing week, the odds of losing weight increase by 1.41 (P-value: 0.038), while the odds of shortness of breath and cough decrease by 0.84 (P-value: 0.005) and 0.56 (P-value: 0.000), respectively. In addition, each day increase in the duration of meropenem or methylprednisolone decreased the odds of weight loss at follow-up by 0.88 (P-value: 0.026) and 0.91 (P-value: 0.023), respectively (among those who took these medications). Identified prognostic factors can help clinicians and policymakers adapt management strategies for patients in any pandemic like COVID-19, which ultimately leads to better hospital decision-making and improved patient quality of life outcomes.
Item Type: | Article |
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Keywords: | COVID-19 treatment protocols generalized linear mixed model joint generalized estimating equation methods machine learning longitudinal study COVID-19 symptoms outcomes Pharmacology & Pharmacy Mathematics |
Page Range: | p. 21 |
Journal or Publication Title: | Journal of Biopharmaceutical Statistics |
Journal Index: | ISI |
Identification Number: | https://doi.org/10.1080/10543406.2024.2333527 |
ISSN: | 1054-3406 |
Depositing User: | خانم ناهید ضیائی |
URI: | http://eprints.mui.ac.ir/id/eprint/29144 |
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