Development and validation of a user-friendly risk nomogram for the prediction of catheter-associated urinary tract infection in neuro-intensive care patients.

OBJECTIVE

This study aimed to develop a user-friendly nomogram model to evaluate the risk of catheter-associated urinary tract infections in neuro-critically ill patients.

METHODS

A retrospective cohort analysis was conducted on 537 patients with indwelling catheters admitted to the neuro-intensive care unit. Patients' general information, laboratory examination findings, and clinical characteristics were collected. Multivariate regression analysis was applied to develop the nomogram for the prediction of catheter-associated urinary tract infections in this group of patients. The discriminative capacity, calibration ability, and clinical effectiveness of the nomogram were evaluated.

RESULTS

The occurrence of catheter-associated urinary tract infections was 3.91 % and Escherichia coli was the major causative pathogen. Multivariate regression analysis showed that age ≥ 60 years (odds ratio: 35.2, 95 % confidence interval: 2.3-550.8), epilepsy (39.3, 5.1-301.4), a length of neuro-intensive care stay > 30 days (272.2, 8.3-8963.5), and low albumin levels (<35 g/L) (12.1, 2.1-69.9) were independent risk factors associated with catheter-associated urinary tract infection in neuro-intensive care patients. The nomogram demonstrated good calibration and discrimination in both the training and the validation sets. The model exhibited good clinical use since the decision curve analysis covered a large threshold probability.

CONCLUSIONS

We developed a user-friendly nomogram to predict catheter-associated urinary tract ibfection in neuro-intensive care patients. The nomogram incorporated clinical variables collected on admission (age, admission diagnosis, and albumin levels) and the length of stay and enabled the effective prediction of the likelihood of catheter-associated urinary tract infections.