ArticleFrontiers in cellular and infection microbiology2021
A New Prognostic Index PDPI for the Risk of Pneumonia Among Patients With Diabetes.
Article in Frontiers in cellular and infection microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed, 4 citations in OpenAlex.
- Clinical characteristics and microbial signatures in the lower airways of diabetic and nondiabetic patients with pneumonia.Journal of thoracic disease · 2024Article
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12 authors at 6 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Objective: Risk factors for the development of pneumonia among patients with diabetes mellitus are unclear. The aim of our study was to elucidate the potential risk factors and attempt to predict the probability of pneumonia based on the history of diabetes. Methods: We performed a population-based, prospective multicenter cohort study of 1,043 adult patients with diabetes in China during 2017-2019. Demographic information, comorbidities, or laboratory examinations were collected. Results: The study included 417 diabetic patients with pneumonia and 626 no-pneumonia-onset diabetic patients. The predictive risk factors were chosen on the basis of a multivariate logistic regression model to predict pneumonia among patients with diabetes including male sex [odds ratio (OR) = 1.72, 95% confidence interval (CI): 1.27-2.33, p < 0.001], age ≥ 75 years (OR = 2.31, 95% CI: 1.61-3.31, p < 0.001), body mass index < 25 (OR = 2.59, 95% CI: 1.92-3.50, p < 0.001), chronic obstructive pulmonary disease (OR = 6.58, 95% CI: 2.09-20.7, p = 0.001), hypertension (OR = 4.27, 95% CI: 3.12-5.85, p < 0.001), coronary heart disease (OR = 2.98, 95% CI: 1.61-5.52, p < 0.001), renal failure (OR = 1.82, 95% CI: 1.002-3.29, p = 0.049), cancer (OR = 3.57, 95% CI: 1.80-7.06, p < 0.001), use of insulin (OR = 2.28, 95% CI: 1.60-3.25, p < 0.001), and hemoglobin A1c ≥ 9% (OR = 2.70, 95% CI: 1.89-3.85, p < 0.001). A predictive nomogram was established. This model showed c-statistics of 0.811, and sensitivity and specificity were 0.717 and 0.780, respectively, under cut-off of 125 score. Conclusion: We designed a clinically predictive tool for assessing the risk of pneumonia among adult patients with diabetes. This tool stratifies patients into relevant risk categories and may provide a basis for individually tailored intervention for the purpose of early prevention.
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