Background Urinary tract infections are among the most common infectious diseases in women, with incidence increasing after menopause. The genitourinary syndrome of menopause increases susceptibility to recurrent urinary tract infections through urogenital atrophy and microbiome disruption, compounding the risk of antimicrobial resistance. Objective To synthesise evidence on digital health technologies for the prevention and management of urinary tract infections in menopausal women. Methods Four databases (PubMed/MEDLINE, Scopus, Web of Science, Cochrane) were systematically searched from January 2000 to March 2026 following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study quality was assessed using risk-of-bias and critical appraisal tools. Menopausal status was classified as explicitly, proxy or not reported. Results Of 9935 records identified, 14 studies met the inclusion criteria. Certainty of evidence ranged from very low to moderate. Four technology clusters emerged: patient-facing digital interventions (n = 4), predictive machine-learning models (n = 7), clinician-facing electronic health record-integrated decision support systems (n = 2), and point-of-care biosensors (n = 1). Digital tools reduced inappropriate antibiotic prescribing by up to 60% and ciprofloxacin use by 80.5%. Predictive models achieved discrimination values of 0.57–0.96 but lacked prospective validation. No study applied formal staging criteria for reproductive aging or integrated hormonal variables. Time to diagnosis and treatment were not assessed. Conclusions Digital health technologies show potential for antimicrobial stewardship in menopausal women with urinary tract infections but remain largely insensitive to menopause-specific biological factors. One randomised controlled trial demonstrated increased uptake of vaginal oestrogen therapy with the use of these technologies, providing evidence of digitally supported non-antibiotic prevention. Future research should integrate menopausal staging, hormonal variables, and user-centred design. PROSPERO registration CRD420251052764.

Digital health technologies for the prevention and management of urinary tract infections in menopausal women: A systematic review

Addis, E.;Nazeri, A.;
2026-01-01

Abstract

Background Urinary tract infections are among the most common infectious diseases in women, with incidence increasing after menopause. The genitourinary syndrome of menopause increases susceptibility to recurrent urinary tract infections through urogenital atrophy and microbiome disruption, compounding the risk of antimicrobial resistance. Objective To synthesise evidence on digital health technologies for the prevention and management of urinary tract infections in menopausal women. Methods Four databases (PubMed/MEDLINE, Scopus, Web of Science, Cochrane) were systematically searched from January 2000 to March 2026 following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study quality was assessed using risk-of-bias and critical appraisal tools. Menopausal status was classified as explicitly, proxy or not reported. Results Of 9935 records identified, 14 studies met the inclusion criteria. Certainty of evidence ranged from very low to moderate. Four technology clusters emerged: patient-facing digital interventions (n = 4), predictive machine-learning models (n = 7), clinician-facing electronic health record-integrated decision support systems (n = 2), and point-of-care biosensors (n = 1). Digital tools reduced inappropriate antibiotic prescribing by up to 60% and ciprofloxacin use by 80.5%. Predictive models achieved discrimination values of 0.57–0.96 but lacked prospective validation. No study applied formal staging criteria for reproductive aging or integrated hormonal variables. Time to diagnosis and treatment were not assessed. Conclusions Digital health technologies show potential for antimicrobial stewardship in menopausal women with urinary tract infections but remain largely insensitive to menopause-specific biological factors. One randomised controlled trial demonstrated increased uptake of vaginal oestrogen therapy with the use of these technologies, providing evidence of digitally supported non-antibiotic prevention. Future research should integrate menopausal staging, hormonal variables, and user-centred design. PROSPERO registration CRD420251052764.
2026
Antimicrobial stewardship Artificial Intelligence Clinical decision support systems Digital health Genitourinary syndrome of menopause Menopause Urinary tract infections
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1205807
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