{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T03:59:11Z","timestamp":1788580751146,"version":"build-2803163510"},"reference-count":61,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2024,6,14]],"date-time":"2024-06-14T00:00:00Z","timestamp":1718323200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Annually, urinary tract infections (UTIs) affect over a hundred million people worldwide. Early detection of high-risk individuals can help prevent hospitalization for UTIs, which imposes significant economic and social burden on patients and caregivers. We present two methods to generate risk score models for UTI hospitalization. We utilize a sample of patients from the insurance claims data provided by the Centers for Medicare and Medicaid Services to develop and validate the proposed methods. Our dataset encompasses a wide range of features, such as demographics, medical history, and healthcare utilization of the patients along with provider quality metrics and community-based metrics. The proposed methods scale and round the coefficients of an underlying logistic regression model to create scoring tables. We present computational experiments to evaluate the prediction performance of both models. We also discuss different features of these models with respect to their impact on interpretability. Our findings emphasize the effectiveness of risk score models as practical tools for identifying high-risk patients and provide a quantitative assessment of the significance of various risk factors in UTI hospitalizations such as admission to ICU in the last 3 months, cognitive disorders and low inpatient, outpatient and carrier costs in the last 6 months.<\/jats:p>","DOI":"10.1371\/journal.pone.0290215","type":"journal-article","created":{"date-parts":[[2024,6,14]],"date-time":"2024-06-14T17:21:48Z","timestamp":1718385708000},"page":"e0290215","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["Risk score models for urinary tract infection hospitalization"],"prefix":"10.1371","volume":"19","author":[{"given":"Nasrin","family":"Alizadeh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kimia","family":"Vahdat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8515-5877","authenticated-orcid":true,"given":"Sara","family":"Shashaani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julie L.","family":"Swann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0093-5645","authenticated-orcid":true,"given":"Osman Y.","family":"\u00d6zalt\u03b9n","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,6,14]]},"reference":[{"key":"pone.0290215.ref001","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1016\/j.molmed.2016.09.003","article-title":"Urinary Tract Infection: Pathogenesis and Outlook","volume":"22","author":"LK McLellan","year":"2016","journal-title":"Trends Mol Med"},{"key":"pone.0290215.ref002","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1310\/sci2503-228","article-title":"Pathophysiology, Treatment, and Prevention of Catheter-Associated Urinary Tract Infection","volume":"25","author":"A Flores-Mireles","year":"2019","journal-title":"Top Spinal Cord Inj Rehabil"},{"key":"pone.0290215.ref003","first-page":"269","article-title":"Urinary tract infections: epidemiology, mechanisms of infection and treatment options","volume":"13","author":"AL Flores-Mireles","year":"2015","journal-title":"Nature Reviews Microbiology 2015 13:5"},{"key":"pone.0290215.ref004","doi-asserted-by":"crossref","first-page":"2669","DOI":"10.1007\/s00345-019-03071-4","article-title":"Epidemiology of urological infections: a global burden","volume":"38","author":"R \u00d6zt\u00fcrk","year":"2020","journal-title":"World J Urol"},{"key":"pone.0290215.ref005","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1080\/02813432.2019.1569425","article-title":"Prescription of antibiotics for urinary tract infection in general practice in Denmark","volume":"37","author":"A Holm","year":"2019","journal-title":"Scand J Prim Health Care"},{"key":"pone.0290215.ref006","doi-asserted-by":"crossref","DOI":"10.3390\/ijerph19159193","article-title":"Using Ambulatory Care Sensitive Conditions to Assess Primary Health Care Performance during Disasters: A Systematic Review","volume":"19","author":"A Lamberti-Castronuovo","year":"2022","journal-title":"Int J Environ Res Public Health"},{"key":"pone.0290215.ref007","unstructured":"Moy E, Chang E, Barrett M. 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