ArticleFrontiers in public health2024
A novel multivariate logistic model for predicting risk factors of failed treatment with carbapenem-resistant
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Investigation of immunohistochemical marker expression in breast cancer of varying severity and construction of a predictive model.Translational cancer research · 2026Article
- Precision Approaches to Carbapenem-Resistant Infections in the ICU: Integrating Diagnostics, Stewardship, and Novel Therapies.Diagnostics (Basel, Switzerland) · 2026Review
- Application of machine learning models for predicting risk factors of acute exacerbations in chronic obstructive pulmonary disease.Frontiers in medicine · 2026Article
- Prognostic Indicators of Carbapenem-ResistantHealth science reports · 2025Review
- Efficacy and safety of polymyxin B sulfate versus colistin sulfate in ICU patients with nosocomial pneumonia caused by carbapenem-resistant Acinetobacter baumannii: a multicenter, propensity score-matched, real-world cohort study.BMC infectious diseases · 2025Article
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Authors and funding
7 authors.
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Abstract
Background: This study aimed to explore the risk factors for failed treatment of carbapenem-resistant Methods: A total of 189 CRAB-VAP patients were included in the safety analysis set from two Grade 3 A national-level hospitals between 1 January 2022 and 31 December 2022. The risk factors for failed treatment with CRAB-VAP were identified using univariate analysis, multivariate logistic analysis, and an independent nomogram to show the results. Results: Of the 189 patients, 106 (56.1%) patients were in the successful treatment group, and 83 (43.9%) patients were in the failed treatment group. The multivariate logistic model analysis showed that age (OR = 1.04, 95% CI: 1.02, 1.07, Conclusion: Age, hypoproteinemia, daily dose, medication within 14 days prior to surgical intervention, and microbial clearance are all significant risk factors for failed treatment with CRAB-VAP, with the nomogram model indicating that high age was the most important factor. Because the failure rate of CRAB-VAP treatment with tigecycline was high, this prediction model can help doctors correct or avoid risk factors during clinical treatment.
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