Predictive model development for invasive syndrome in type 2 diabetes mellitus patients with Klebsiella pneumoniae liver abscess: A 5-year multi-center retrospective case-control study

This study aimed to develop and validate a robust nomogram for predicting the risk of invasive Klebsiella pneumoniae liver abscess syndrome (IKPLAS) in patients with type 2 diabetes mellitus (T2DM) and K pneumoniae liver abscess. In this multicenter retrospective case-control study, clinical data from 213 patients with T2DM and K pneumoniae liver abscess, treated between January 1, 2019, and January 1, 2024, at Beijing Rehabilitation Hospital, Capital Medical University, The Sanming Integrative Medicine Hospital, and The First Affiliated Hospital of Guangzhou Medical University, were analyzed. Patients were categorized into IKPLAS (n = 25) and non-IKPLAS (n = 188) groups. Candidate variables, including fasting blood glucose, hemoglobin, blood urea nitrogen, abscess size, and Sequential Organ Failure Assessment score, were evaluated. Lasso regression and multivariate logistic regression analyses were used to identify significant predictors, which were then incorporated into a nomogram. The model's performance was assessed using receiver operating characteristic curves, calibration curves, and decision curve analysis. Multivariate logistic regression identified fasting blood glucose (odds ratio [OR] = 1.20, 95% confidence interval [CI]: 0.98-1.48, P = .006), hemoglobin (OR = 0.90, 95% CI: 0.86-0.95, P < .001), blood urea nitrogen (OR = 1.22, 95% CI: 1.03-1.43, P = .017), abscess size (OR = 0.76, 95% CI: 0.61-0.94, P = .010), and Sequential Organ Failure Assessment score (OR = 3.08, 95% CI: 2.18-4.36, P < .001) as significant predictors of IKPLAS. The nomogram demonstrated excellent discriminatory ability, with an area under the receiver operating characteristic curve of 0.966 (95% CI: 0.943-0.989) in the training set and 0.946 (95% CI: 0.902-0.991) in the validation set. Calibration curves indicated strong agreement between predicted and observed outcomes, and decision curve analysis showed that the nomogram provided substantial clinical net benefit, particularly within the risk threshold range of 0.10 to 0.40. These findings suggest that the proposed nomogram is an effective tool for predicting IKPLAS risk in patients with T2DM and K pneumoniae liver abscess, enabling early identification of high-risk patients and supporting timely clinical intervention to improve prognosis.

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Journal
Medicine
Published
2025-12-05
DOI
https://doi.org/10.1097/md.0000000000046456
Primary Topic
Amoebic Infections and Treatments
Type
article
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article

Predictive model development for invasive syndrome in type 2 diabetes mellitus patients with Klebsiella pneumoniae liver abscess: A 5-year multi-center retrospective case-control study

Yue Zhou, Qitao Chen, Long Xia, Hong Pan et al.
Medicine
Amoebic Infections and Treatments
article

Predictive model development for invasive syndrome in type 2 diabetes mellitus patients with Klebsiella pneumoniae liver abscess: A 5-year multi-center retrospective case-control study

Yue Zhou, Qitao Chen, Long Xia, Hong Pan, Zhibin Xu, Jianhua Liu
article en

Abstract

This study aimed to develop and validate a robust nomogram for predicting the risk of invasive Klebsiella pneumoniae liver abscess syndrome (IKPLAS) in patients with type 2 diabetes mellitus (T2DM) and K pneumoniae liver abscess. In this multicenter retrospective case-control study, clinical data from 213 patients with T2DM and K pneumoniae liver abscess, treated between January 1, 2019, and January 1, 2024, at Beijing Rehabilitation Hospital, Capital Medical University, The Sanming Integrative Medicine Hospital, and The First Affiliated Hospital of Guangzhou Medical University, were analyzed. Patients were categorized into IKPLAS (n = 25) and non-IKPLAS (n = 188) groups. Candidate variables, including fasting blood glucose, hemoglobin, blood urea nitrogen, abscess size, and Sequential Organ Failure Assessment score, were evaluated. Lasso regression and multivariate logistic regression analyses were used to identify significant predictors, which were then incorporated into a nomogram. The model's performance was assessed using receiver operating characteristic curves, calibration curves, and decision curve analysis. Multivariate logistic regression identified fasting blood glucose (odds ratio [OR] = 1.20, 95% confidence interval [CI]: 0.98-1.48, P = .006), hemoglobin (OR = 0.90, 95% CI: 0.86-0.95, P < .001), blood urea nitrogen (OR = 1.22, 95% CI: 1.03-1.43, P = .017), abscess size (OR = 0.76, 95% CI: 0.61-0.94, P = .010), and Sequential Organ Failure Assessment score (OR = 3.08, 95% CI: 2.18-4.36, P < .001) as significant predictors of IKPLAS. The nomogram demonstrated excellent discriminatory ability, with an area under the receiver operating characteristic curve of 0.966 (95% CI: 0.943-0.989) in the training set and 0.946 (95% CI: 0.902-0.991) in the validation set. Calibration curves indicated strong agreement between predicted and observed outcomes, and decision curve analysis showed that the nomogram provided substantial clinical net benefit, particularly within the risk threshold range of 0.10 to 0.40. These findings suggest that the proposed nomogram is an effective tool for predicting IKPLAS risk in patients with T2DM and K pneumoniae liver abscess, enabling early identification of high-risk patients and supporting timely clinical intervention to improve prognosis.

MedicineVol. 104(49)
Capital Medical University (CN), China Rehabilitation Research Center (CN), First Affiliated Hospital of Guangzhou Medical University (CN), Sanming University (CN), Guangzhou Medical University (CN)
Openalex Percentile: Top 55%
Amoebic Infections and Treatments
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