Volume: 43 Issue: 2
Year: 2023, Page: 696-700, Doi: https://doi.org/10.51248/.v43i02.2250
Introduction and Aim: Pneumonia is a common and serious illness among the elderly. Early identification of the risk factors for pneumonia is essential for improving the survival outcomes among elderly. The present study aimed to identify an optimal regression approach to determine the risk factors for pneumonia among elderly patients.
Materials and Methods: The present study utilized data from the Medical Information Mart for Intensive Care (MIMIC III) to evaluate the use of alternative generalized linear models to identify the risk factors for pneumonia. The regression model with the smallest AIC, BIC and SE was considered as the appropriate regression model for the data. Robust Poisson model was considered the best fit for the current data as it had the lowest AIC, BIC and standard error compared to other regression models.
Results: Variables such as BMI, renal failure, hypertension, diabetes and asthma were identified as the significant risk factors for pneumonia. The risk of pneumonia was found to be significantly higher in the underweight category of BMI [RRadj=1.70; 95% CI=1.38, 2.08]; diabetic patients [RRadj =1.29; 95% CI=1.03, 1.61); asthmatic patients [RRadj =1.35; 95% CI=1.15, 1.58] and patients with renal failure [RRadj =1.16; 95% CI= 1.05, 1.29].
Conclusion: Among various binary regression models, Poisson regression with robust variance (sandwich Poisson regression) provided unbiased estimates of the relationship. In the present study, variables such as BMI, renal failure, diabetics, hypertension and asthma were identified as the significant risk factors for pneumonia in the elderly using robust Poisson regression.
Keywords: Regression models; robust Poisson regression; negative binomial; elderly; pneumonia; risk factors; MIMIC III.
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Kalesh M. Karun1, Amitha Puranik2, Lintu M. K.3 Deepthy M. S. Risk factors of pneumonia among elderly with robust Poisson regression - A study on mimic III data. Biomedicine: 2023; 43(2): 696-700