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Predicting and comparing postoperative infections in different stratification following PCNL based on nomograms
Enyan Jiang1, Haixiang Guo1, Bowei Yang1
1Yunnan Key Laboratory of Urology, Yunnan Urology Speciality Hospital, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, People's Republic of China.
Scientific Reports
|July 11, 2020
Summary
This study developed a nomogram to predict infection severity after percutaneous nephrolithotomy (PCNL). The tool helps identify patients at higher risk for post-PCNL infections, improving clinical management.
Area of Science:
- Urology
- Infectious Diseases
- Medical Informatics
Background:
- Percutaneous nephrolithotomy (PCNL) is a common procedure for kidney stones.
- Post-PCNL infections represent a significant source of morbidity.
- Predictive models for infection severity are needed to guide clinical decisions.
Purpose of the Study:
- To develop and validate nomograms for predicting infection complications after PCNL.
- To compare the predictive accuracy of models for different infection severities.
- To create a dynamic online tool for real-time sepsis risk assessment post-PCNL.
Main Methods:
- Retrospective cohort study of 969 PCNL patients.
- Analysis of clinical, laboratory, and operative data using logistic regression.
- Evaluation of model performance using ROC curves, calibration, and predictive values.
- Development of nomograms for visualizing infection risk and a dynamic online prediction tool.
Main Results:
- Model accuracy increases with infection severity.
- Severe post-PCNL infections are primarily linked to patient homeostasis.
- Developed nomograms effectively visualize infection risk stratification.
- An online dynamic nomogram was created for real-time sepsis prediction.
Conclusions:
- Nomograms can accurately predict varying degrees of post-PCNL infection.
- Patient homeostasis is a key factor in severe post-PCNL infections.
- The online dynamic nomogram offers a valuable tool for real-time sepsis risk management in PCNL patients.
