Hospital-Acquired Non-catheter Associated UTI Risk Factor Analysis

Dr Dylan Cornish1, Dr Mani Suleiman1, Dr Dorothy Ling1

1Northern Health, Epping, Australia

Biography:

Medical registrar and current basic physician trainee at Northern Health.

Abstract:

Introduction

Hospital-acquired non-catheter associated urinary tract infection (HA-NCAUTI) is a common hospital-acquired complication associated with prolonged admissions and increased morbidity and mortality. Currently, no validated tools exist to identify patients at high-risk of developing HA-NCAUTI. This study aimed to develop a risk-based screening tool to target this patient population.

Methods

(1) Risk factor identification: Candidate risk factors used in the data analysis were identified through a systematic literature review of existing evidence on NCAUTI.

(2) Retrospective data analysis: Adult inpatient episodes of HA-NCAUTI between April 2023 and May 2025 at Northern Health were reviewed and screened against the identified risk factors. The National Healthcare Safety Network (NHSN) diagnostic criteria were applied to confirm accurate case classification.

Results

(1) Risk factor identification: Six articles were reviewed, yielding eight risk factors for inclusion in the analysis.

(2) Retrospective data analysis: Of 292 screened episodes, 80 met NHSN criteria for HA-NCAUTI. The most frequently observed risk factors were post-menopausal status (n=165, 57%), frailty (n=147, 50%) and faecal incontinence (n=140, 48%). The median number of risk factors per patient was 3 (IQR 2-3). Univariate logistic regression was performed; however, no statistically significant risk factors were identified, likely reflecting a small sample size.

Conclusion

Despite a lack of statistical significance, this study provides valuable preliminary insights into the characteristics of the HA-NCAUTI patient cohort. Future work should focus on developing and validating a clinical screening tool to direct target interventions toward high-risk patients. An expanded sample size will be necessary to achieve adequate statistical power.

 

Categories