ปัจจัยทำนายและการประมาณค่าความเสี่ยงของผลการรักษาที่ไม่ดีในผู้ป่วยโรคปอดอักเสบที่เข้ารับการรักษาในโรงพยาบาลชุมชน

Methawee Watcharakul; Akemat Wongpairin

Authors

Methawee Watcharakul Krong Pinang Hospital, Krong Pinang District, Yala Province
Akemat Wongpairin Sirindhorn College of Public Health, Yala Province, Faculty of Public Health and Allied Health Sciences, Praboromarajchanok Institute

Keywords:

Pneumonia, Comorbidities, Risk estimation of treatment outcomes

Abstract

Background and Objectives Pneumonia is a major cause of morbidity and mortality, especially in the elderly and those with comorbidities. This study aimed to analyze the relationship between comorbidities and treatment outcomes in patients with pneumonia and to estimate the risk of poor treatment outcomes in the context of community hospitals.

Methods This was a retrospective analytical study using inpatient data from the Hospital Information System of Krong Pinang Hospital, Yala Province, between 2020 and 2024. A total of 876 cases were analyzed using the chi-square test and multiple logistic regression, along with variable combination techniques and risk estimation using sum contrast.

Results The multivariate analysis revealed that the factors predicting poor treatment outcomes included being male (AOR = 2.01, 95 % CI: 1.12–3.59) and chronic kidney disease
(AOR = 2.51, 95 % CI: 1.20–5.20). In contrast, chronic obstructive pulmonary disease was associated with better treatment outcomes (AOR = 0.31, 95 % CI: 0.11–0.73). The variable combination between diabetes and bacterial lung infection showed a complex risk pattern, and the risk estimation using sum contrast indicated that the highest risk groups were males, those with chronic kidney disease, and patients with diabetes combined with bacterial infection.

Conclusion and Recommendations Male gender, chronic kidney disease, and the coexistence of diabetes with bacterial infection are significant risk factors for poor treatment outcomes in community hospitals. The study results should be used to screen for higher-risk patients and develop a proactive care system based on risk levels.

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