ArticleSaudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association2020
Developing a risk prediction model for multidrug-resistant bacterial infection in patients with biliary tract infection.
Article in Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 5 citations in OpenAlex.
- Development of predictive nomogram for clinical use of special-grade antimicrobial agents in patients with diabetes foot infections.Frontiers in endocrinology · 2025Article
- Construction and validation of a predictive risk model for nosocomial infections with MDRO in NICUs: a multicenter observational study.Frontiers in medicine · 2023Article
- Korean Guidelines for Use of Antibiotics for Intra-abdominal Infections in Adults.Infection & chemotherapy · 2022Review
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9 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimsThe aim of this study was to develop a tool to predict multidrug-resistant bacteria infections among patients with biliary tract infection for targeted therapy. PATIENTS AND
methodsWe conducted a single-center retrospective descriptive study from January 2016 to December 2018. Univariate and multivariable logistic regression analysis were used to identify independent risk factors of multidrug-resistant bacterial infections. A nomogram was constructed according to multivariable regression model. Moreover, the clinical usefulness of the nomogram was estimated by decision curve analysis.
results121 inpatients were randomly divided into a training cohort (n = 79) and validation cohort (n = 42). In multivariate analysis, 5 factors were associated with biliary tract infections caused by multidrug-resistant bacterial infections: aspartate aminotransferase (Odds ratio (OR), 13.771; 95% confidence interval (CI), 3.747-64.958; P < 0.001), previous antibiotic use within 90 days (OR, 4.130; 95% CI, 1.192-16.471; P = 0.032), absolute neutrophil count (OR, 3.491; 95% CI, 1.066-12.851; P = 0.046), previous biliary surgery (OR, 3.303; 95% CI, 0.910-13.614; P = 0.079), and hemoglobin (OR, 0.146; 95% CI, 0.030-0.576; P = 0.009). The nomogram model was constructed based on these variables, and showed good calibration and discrimination in the training set [area under the curve (AUC), 0.86] and in the validation set (AUC, 0.799). The decision curve analysis demonstrated the clinical usefulness of our nomogram. Using the nomogram score, high risk and low risk patients with multidrug-resistant bacterial infection could be differentiated.
conclusionsThis simple bedside prediction tool to predict multidrug-resistant bacterial infection can help clinicians identify low versus high risk patients as well as choose appropriate, timely initial empirical antibiotics therapy. This model should be validated before it is widely applied in clinical settings.
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