Avery Shuei-He Yang, Hsin-Yu Fan Chiang, Daniel Hsiang-Te Tsai, Albert Tzu-Ming Chuang, Edward Chia-Cheng Lai
{"title":"不同虚弱程度患者肺炎风险与抗胆碱能负荷的关系","authors":"Avery Shuei-He Yang, Hsin-Yu Fan Chiang, Daniel Hsiang-Te Tsai, Albert Tzu-Ming Chuang, Edward Chia-Cheng Lai","doi":"10.2147/CLEP.S524645","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>We aimed to evaluate the association between recent increase in anticholinergic burden and risk of hospitalised pneumonia, taking frailty levels into consideration.</p><p><strong>Setting: </strong>We conducted a case-crossover study using data drawn from Taiwan's National Health Insurance Research Database.</p><p><strong>Participants: </strong>We enrolled patients aged over 65 years old who were hospitalised for pneumonia between 2011 and 2020. Exclusion criteria included prior diagnosis of ventilator dependency, pneumonia and immune dysfunction.</p><p><strong>Measurements: </strong>The observational period was divided into a hazard period, a washout period and one of four reference periods, based on the 30-day interval before the admission. We calculated the anticholinergic cognitive burden (ACB) scale for the hazard period and one randomly selected reference period. Using a multimorbidity frailty index we classified patients into four groups (ie, fit, mildly frail, moderately frail and very frail).</p><p><strong>Statistical analysis: </strong>We used conditional logistic regression to evaluate the risk of pneumonia by comparing the anticholinergic burden between the hazard window and the randomly selected reference window and conducted sensitivity analyses based on case-time control and case-case-time control analysis to examine the robustness of the findings.</p><p><strong>Results: </strong>The fit group included 188,740 patients, followed by 133,038, 61,805 and 18,198 patients for the mildly, moderately and very frail groups, respectively. Each single point increase in ACB scale was associated with a pneumonia risk increase by 1.35 (95% CI: 1.34-1.35), 1.24 (95% CI: 1.24-1.24), 1.18 (95% CI: 1.17-1.18) and 1.12 (95% CI: 1.11-1.13) times in the fit and mildly, moderately and very frail groups, respectively. The results of the case-time control and case-case-time control analyses remained consistent with the main analysis.</p><p><strong>Conclusion: </strong>Our study confirmed the association between recently elevated ACB and the risk of hospitalised pneumonia. Even in the less frail, exposure to anticholinergic drugs warrants close monitoring for pneumonia.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"787-796"},"PeriodicalIF":3.2000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12495931/pdf/","citationCount":"0","resultStr":"{\"title\":\"Association Between Pneumonia Risk and Anticholinergic Burden Among Patients with Different Frailty Levels.\",\"authors\":\"Avery Shuei-He Yang, Hsin-Yu Fan Chiang, Daniel Hsiang-Te Tsai, Albert Tzu-Ming Chuang, Edward Chia-Cheng Lai\",\"doi\":\"10.2147/CLEP.S524645\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>We aimed to evaluate the association between recent increase in anticholinergic burden and risk of hospitalised pneumonia, taking frailty levels into consideration.</p><p><strong>Setting: </strong>We conducted a case-crossover study using data drawn from Taiwan's National Health Insurance Research Database.</p><p><strong>Participants: </strong>We enrolled patients aged over 65 years old who were hospitalised for pneumonia between 2011 and 2020. Exclusion criteria included prior diagnosis of ventilator dependency, pneumonia and immune dysfunction.</p><p><strong>Measurements: </strong>The observational period was divided into a hazard period, a washout period and one of four reference periods, based on the 30-day interval before the admission. We calculated the anticholinergic cognitive burden (ACB) scale for the hazard period and one randomly selected reference period. Using a multimorbidity frailty index we classified patients into four groups (ie, fit, mildly frail, moderately frail and very frail).</p><p><strong>Statistical analysis: </strong>We used conditional logistic regression to evaluate the risk of pneumonia by comparing the anticholinergic burden between the hazard window and the randomly selected reference window and conducted sensitivity analyses based on case-time control and case-case-time control analysis to examine the robustness of the findings.</p><p><strong>Results: </strong>The fit group included 188,740 patients, followed by 133,038, 61,805 and 18,198 patients for the mildly, moderately and very frail groups, respectively. Each single point increase in ACB scale was associated with a pneumonia risk increase by 1.35 (95% CI: 1.34-1.35), 1.24 (95% CI: 1.24-1.24), 1.18 (95% CI: 1.17-1.18) and 1.12 (95% CI: 1.11-1.13) times in the fit and mildly, moderately and very frail groups, respectively. The results of the case-time control and case-case-time control analyses remained consistent with the main analysis.</p><p><strong>Conclusion: </strong>Our study confirmed the association between recently elevated ACB and the risk of hospitalised pneumonia. 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Association Between Pneumonia Risk and Anticholinergic Burden Among Patients with Different Frailty Levels.
Objective: We aimed to evaluate the association between recent increase in anticholinergic burden and risk of hospitalised pneumonia, taking frailty levels into consideration.
Setting: We conducted a case-crossover study using data drawn from Taiwan's National Health Insurance Research Database.
Participants: We enrolled patients aged over 65 years old who were hospitalised for pneumonia between 2011 and 2020. Exclusion criteria included prior diagnosis of ventilator dependency, pneumonia and immune dysfunction.
Measurements: The observational period was divided into a hazard period, a washout period and one of four reference periods, based on the 30-day interval before the admission. We calculated the anticholinergic cognitive burden (ACB) scale for the hazard period and one randomly selected reference period. Using a multimorbidity frailty index we classified patients into four groups (ie, fit, mildly frail, moderately frail and very frail).
Statistical analysis: We used conditional logistic regression to evaluate the risk of pneumonia by comparing the anticholinergic burden between the hazard window and the randomly selected reference window and conducted sensitivity analyses based on case-time control and case-case-time control analysis to examine the robustness of the findings.
Results: The fit group included 188,740 patients, followed by 133,038, 61,805 and 18,198 patients for the mildly, moderately and very frail groups, respectively. Each single point increase in ACB scale was associated with a pneumonia risk increase by 1.35 (95% CI: 1.34-1.35), 1.24 (95% CI: 1.24-1.24), 1.18 (95% CI: 1.17-1.18) and 1.12 (95% CI: 1.11-1.13) times in the fit and mildly, moderately and very frail groups, respectively. The results of the case-time control and case-case-time control analyses remained consistent with the main analysis.
Conclusion: Our study confirmed the association between recently elevated ACB and the risk of hospitalised pneumonia. Even in the less frail, exposure to anticholinergic drugs warrants close monitoring for pneumonia.
期刊介绍：
Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment.
Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews.
Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews.
When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes.
The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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