Use of Machine Learning to Assess the Management of Uncomplicated Urinary Tract Infection Article Swipe
Noah Jones
,
Ming‐Chieh Shih
,
Elizabeth Healey
,
Chen Wen Zhai
,
Sonali D. Advani
,
Aaron Smith‐McLallen
,
David Sontag
,
Sanjat Kanjilal
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1001/jamanetworkopen.2024.56950
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1001/jamanetworkopen.2024.56950
Importance Uncomplicated urinary tract infection (UTI) is a common indication for outpatient antimicrobial therapy. National guidelines for the management of uncomplicated UTI were published in 2011, but the extent to which they align with current practices, patient diversity, and pathogen biology, all of which have evolved greatly in the time since their publication, is not fully known. Objective To reevaluate the effectiveness and adverse event profile for first-line antibiotics, fluoroquinolones, and oral β-lactams for treating uncomplicated UTI in contemporary clinical practice. Design, Setting, and Participants This retrospective, population-based cohort study used a claims dataset from Independence Blue Cross, which contains inpatient, outpatient, laboratory, and pharmacy claims that occurred between 2012 and 2021, formatted into the Observational Medical Outcomes Partnership (OMOP) common data model. Participants were nonpregnant female individuals aged 18 years or older with a diagnosis of uncomplicated, nonrecurrent UTI at an outpatient setting. Patients must also have been treated with first-line (nitrofurantoin or trimethoprim-sulfamethoxazole), fluoroquinolone (ciprofloxacin, levofloxacin, or ofloxacin), or oral β-lactam (amoxicillin-clavulanate, cefadroxil, or cefpodoxime) antibiotics. Data analysis was performed from November 2021 to August 2024. Exposures Patients exposed to first-line antibiotics were assigned to the treatment group, and those exposed to fluoroquinolone or β-lactam treatments were assigned to control groups. Main Outcomes and Measures The primary outcome was a composite end point for treatment failure, defined as outpatient or inpatient revisit within 30 days for UTI, pyelonephritis, or sepsis. Secondary outcomes were the risk of 4 common antibiotic-associated adverse events: gastrointestinal symptoms, rash, kidney injury, and Clostridium difficile infection. Results There were 57 585 episodes of UTI among 49 037 female patients (mean [SD] age, 51.7 [20.1]) years), with prescriptions for first-line antibiotics in 35 018 episodes (61%), fluoroquinolones in 21 140 episodes (37%), and β-lactams in 1427 episodes (2%). After adjustment, receipt of first-line therapies was associated with an absolute risk difference of −1.78% (95% CI, −2.37% to −1.06%) for having a revisit for UTI within 30 days of diagnosis vs fluoroquinolones. First-line therapies were associated with an absolute risk difference of −6.40% (95% CI, −10.14% to −3.24%) for 30-day revisit compared with β-lactam antibiotics. Differences in adverse events were similar between all comparators. Results were identical for models built with an automated OMOP feature extraction package. Conclusions and Relevance In this cohort study of patients with uncomplicated UTI derived from a large regional claims dataset, national treatment guidelines published almost 14 years ago continue to recommend optimal treatments. These results also provide proof-of-principle that automated feature extraction methods for OMOP formatted data can emulate manually curated models, thereby promoting reproducibility and generalizability.
Related Topics
Concepts
Medicine
Nitrofurantoin
Amoxicillin
Internal medicine
Antimicrobial stewardship
Levofloxacin
Population
Adverse effect
Cefpodoxime
Pharmacy
Bacteriuria
Intensive care medicine
Antibiotics
Ciprofloxacin
Pediatrics
Antibacterial agent
Urinary system
Antibiotic resistance
Family medicine
Biology
Environmental health
Microbiology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1001/jamanetworkopen.2024.56950
- OA Status
- gold
- Cited By
- 1
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4407009967
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4407009967Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1001/jamanetworkopen.2024.56950Digital Object Identifier
- Title
-
Use of Machine Learning to Assess the Management of Uncomplicated Urinary Tract InfectionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-01-31Full publication date if available
- Authors
-
Noah Jones, Ming‐Chieh Shih, Elizabeth Healey, Chen Wen Zhai, Sonali D. Advani, Aaron Smith‐McLallen, David Sontag, Sanjat KanjilalList of authors in order
- Landing page
-
https://doi.org/10.1001/jamanetworkopen.2024.56950Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1001/jamanetworkopen.2024.56950Direct OA link when available
- Concepts
-
Medicine, Nitrofurantoin, Amoxicillin, Internal medicine, Antimicrobial stewardship, Levofloxacin, Population, Adverse effect, Cefpodoxime, Pharmacy, Bacteriuria, Intensive care medicine, Antibiotics, Ciprofloxacin, Pediatrics, Antibacterial agent, Urinary system, Antibiotic resistance, Family medicine, Biology, Environmental health, MicrobiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
31Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.UTI, | 228 |
| abstract_inverted_index.[SD] | 266 |
| abstract_inverted_index.age, | 267 |
| abstract_inverted_index.aged | 128 |
| abstract_inverted_index.also | 146, 405 |
| abstract_inverted_index.been | 148 |
| abstract_inverted_index.data | 121, 416 |
| abstract_inverted_index.days | 226, 321 |
| abstract_inverted_index.from | 94, 172, 384 |
| abstract_inverted_index.have | 44, 147 |
| abstract_inverted_index.into | 113 |
| abstract_inverted_index.must | 145 |
| abstract_inverted_index.oral | 71, 161 |
| abstract_inverted_index.risk | 236, 304, 333 |
| abstract_inverted_index.that | 106, 408 |
| abstract_inverted_index.they | 31 |
| abstract_inverted_index.this | 375 |
| abstract_inverted_index.time | 49 |
| abstract_inverted_index.used | 90 |
| abstract_inverted_index.were | 22, 124, 184, 198, 234, 254, 328, 353, 359 |
| abstract_inverted_index.with | 33, 133, 150, 271, 301, 330, 346, 364, 380 |
| abstract_inverted_index.(2%). | 292 |
| abstract_inverted_index.(UTI) | 5 |
| abstract_inverted_index.(mean | 265 |
| abstract_inverted_index.2011, | 25 |
| abstract_inverted_index.2021, | 111 |
| abstract_inverted_index.2024. | 177 |
| abstract_inverted_index.After | 293 |
| abstract_inverted_index.There | 253 |
| abstract_inverted_index.These | 403 |
| abstract_inverted_index.align | 32 |
| abstract_inverted_index.among | 260 |
| abstract_inverted_index.built | 363 |
| abstract_inverted_index.event | 64 |
| abstract_inverted_index.fully | 55 |
| abstract_inverted_index.large | 386 |
| abstract_inverted_index.older | 132 |
| abstract_inverted_index.point | 214 |
| abstract_inverted_index.rash, | 245 |
| abstract_inverted_index.since | 50 |
| abstract_inverted_index.study | 89, 377 |
| abstract_inverted_index.their | 51 |
| abstract_inverted_index.those | 191 |
| abstract_inverted_index.tract | 3 |
| abstract_inverted_index.which | 30, 43, 98 |
| abstract_inverted_index.years | 130, 396 |
| abstract_inverted_index.(37%), | 286 |
| abstract_inverted_index.(61%), | 280 |
| abstract_inverted_index.(OMOP) | 119 |
| abstract_inverted_index.30-day | 343 |
| abstract_inverted_index.August | 176 |
| abstract_inverted_index.Cross, | 97 |
| abstract_inverted_index.almost | 394 |
| abstract_inverted_index.claims | 92, 105, 388 |
| abstract_inverted_index.cohort | 88, 376 |
| abstract_inverted_index.common | 8, 120, 239 |
| abstract_inverted_index.events | 352 |
| abstract_inverted_index.extent | 28 |
| abstract_inverted_index.female | 126, 263 |
| abstract_inverted_index.group, | 189 |
| abstract_inverted_index.having | 314 |
| abstract_inverted_index.kidney | 246 |
| abstract_inverted_index.known. | 56 |
| abstract_inverted_index.model. | 122 |
| abstract_inverted_index.models | 362 |
| abstract_inverted_index.within | 224, 319 |
| abstract_inverted_index.Design, | 81 |
| abstract_inverted_index.Medical | 116 |
| abstract_inverted_index.Results | 252, 358 |
| abstract_inverted_index.[20.1]) | 269 |
| abstract_inverted_index.adverse | 63, 241, 351 |
| abstract_inverted_index.between | 108, 355 |
| abstract_inverted_index.control | 201 |
| abstract_inverted_index.curated | 420 |
| abstract_inverted_index.current | 34 |
| abstract_inverted_index.dataset | 93 |
| abstract_inverted_index.defined | 218 |
| abstract_inverted_index.derived | 383 |
| abstract_inverted_index.emulate | 418 |
| abstract_inverted_index.events: | 242 |
| abstract_inverted_index.evolved | 45 |
| abstract_inverted_index.exposed | 180, 192 |
| abstract_inverted_index.feature | 368, 410 |
| abstract_inverted_index.greatly | 46 |
| abstract_inverted_index.groups. | 202 |
| abstract_inverted_index.injury, | 247 |
| abstract_inverted_index.methods | 412 |
| abstract_inverted_index.models, | 421 |
| abstract_inverted_index.optimal | 401 |
| abstract_inverted_index.outcome | 209 |
| abstract_inverted_index.patient | 36 |
| abstract_inverted_index.primary | 208 |
| abstract_inverted_index.profile | 65 |
| abstract_inverted_index.provide | 406 |
| abstract_inverted_index.receipt | 295 |
| abstract_inverted_index.results | 404 |
| abstract_inverted_index.revisit | 223, 316, 344 |
| abstract_inverted_index.sepsis. | 231 |
| abstract_inverted_index.similar | 354 |
| abstract_inverted_index.thereby | 422 |
| abstract_inverted_index.treated | 149 |
| abstract_inverted_index.urinary | 2 |
| abstract_inverted_index.years), | 270 |
| abstract_inverted_index.Measures | 206 |
| abstract_inverted_index.National | 14 |
| abstract_inverted_index.November | 173 |
| abstract_inverted_index.Outcomes | 117, 204 |
| abstract_inverted_index.Patients | 144, 179 |
| abstract_inverted_index.Setting, | 82 |
| abstract_inverted_index.absolute | 303, 332 |
| abstract_inverted_index.analysis | 169 |
| abstract_inverted_index.assigned | 185, 199 |
| abstract_inverted_index.biology, | 40 |
| abstract_inverted_index.clinical | 79 |
| abstract_inverted_index.compared | 345 |
| abstract_inverted_index.contains | 99 |
| abstract_inverted_index.continue | 398 |
| abstract_inverted_index.dataset, | 389 |
| abstract_inverted_index.episodes | 257, 279, 285, 291 |
| abstract_inverted_index.failure, | 217 |
| abstract_inverted_index.manually | 419 |
| abstract_inverted_index.national | 390 |
| abstract_inverted_index.occurred | 107 |
| abstract_inverted_index.outcomes | 233 |
| abstract_inverted_index.package. | 370 |
| abstract_inverted_index.pathogen | 39 |
| abstract_inverted_index.patients | 264, 379 |
| abstract_inverted_index.pharmacy | 104 |
| abstract_inverted_index.regional | 387 |
| abstract_inverted_index.setting. | 143 |
| abstract_inverted_index.therapy. | 13 |
| abstract_inverted_index.treating | 74 |
| abstract_inverted_index.−1.78% | 307 |
| abstract_inverted_index.−2.37% | 310 |
| abstract_inverted_index.−6.40% | 336 |
| abstract_inverted_index.Exposures | 178 |
| abstract_inverted_index.Objective | 57 |
| abstract_inverted_index.Relevance | 373 |
| abstract_inverted_index.Secondary | 232 |
| abstract_inverted_index.automated | 366, 409 |
| abstract_inverted_index.composite | 212 |
| abstract_inverted_index.diagnosis | 135, 323 |
| abstract_inverted_index.difficile | 250 |
| abstract_inverted_index.formatted | 112, 415 |
| abstract_inverted_index.identical | 360 |
| abstract_inverted_index.infection | 4 |
| abstract_inverted_index.inpatient | 222 |
| abstract_inverted_index.performed | 171 |
| abstract_inverted_index.practice. | 80 |
| abstract_inverted_index.promoting | 423 |
| abstract_inverted_index.published | 23, 393 |
| abstract_inverted_index.recommend | 400 |
| abstract_inverted_index.symptoms, | 244 |
| abstract_inverted_index.therapies | 298, 327 |
| abstract_inverted_index.treatment | 188, 216, 391 |
| abstract_inverted_index.β-lactam | 162, 196, 347 |
| abstract_inverted_index.−1.06%) | 312 |
| abstract_inverted_index.−10.14% | 339 |
| abstract_inverted_index.−3.24%) | 341 |
| abstract_inverted_index.First-line | 326 |
| abstract_inverted_index.Importance | 0 |
| abstract_inverted_index.associated | 300, 329 |
| abstract_inverted_index.difference | 305, 334 |
| abstract_inverted_index.diversity, | 37 |
| abstract_inverted_index.extraction | 369, 411 |
| abstract_inverted_index.first-line | 67, 151, 182, 274, 297 |
| abstract_inverted_index.guidelines | 15, 392 |
| abstract_inverted_index.indication | 9 |
| abstract_inverted_index.infection. | 251 |
| abstract_inverted_index.inpatient, | 100 |
| abstract_inverted_index.management | 18 |
| abstract_inverted_index.outpatient | 11, 142, 220 |
| abstract_inverted_index.practices, | 35 |
| abstract_inverted_index.reevaluate | 59 |
| abstract_inverted_index.treatments | 197 |
| abstract_inverted_index.β-lactams | 72, 288 |
| abstract_inverted_index.Clostridium | 249 |
| abstract_inverted_index.Conclusions | 371 |
| abstract_inverted_index.Differences | 349 |
| abstract_inverted_index.Partnership | 118 |
| abstract_inverted_index.adjustment, | 294 |
| abstract_inverted_index.antibiotics | 183, 275 |
| abstract_inverted_index.cefadroxil, | 164 |
| abstract_inverted_index.individuals | 127 |
| abstract_inverted_index.laboratory, | 102 |
| abstract_inverted_index.nonpregnant | 125 |
| abstract_inverted_index.ofloxacin), | 159 |
| abstract_inverted_index.outpatient, | 101 |
| abstract_inverted_index.treatments. | 402 |
| abstract_inverted_index.Independence | 95 |
| abstract_inverted_index.Participants | 84, 123 |
| abstract_inverted_index.antibiotics, | 68 |
| abstract_inverted_index.antibiotics. | 167, 348 |
| abstract_inverted_index.cefpodoxime) | 166 |
| abstract_inverted_index.comparators. | 357 |
| abstract_inverted_index.contemporary | 78 |
| abstract_inverted_index.nonrecurrent | 138 |
| abstract_inverted_index.publication, | 52 |
| abstract_inverted_index.Observational | 115 |
| abstract_inverted_index.Uncomplicated | 1 |
| abstract_inverted_index.antimicrobial | 12 |
| abstract_inverted_index.effectiveness | 61 |
| abstract_inverted_index.levofloxacin, | 157 |
| abstract_inverted_index.prescriptions | 272 |
| abstract_inverted_index.uncomplicated | 20, 75, 381 |
| abstract_inverted_index.retrospective, | 86 |
| abstract_inverted_index.uncomplicated, | 137 |
| abstract_inverted_index.(ciprofloxacin, | 156 |
| abstract_inverted_index.(nitrofurantoin | 152 |
| abstract_inverted_index.fluoroquinolone | 155, 194 |
| abstract_inverted_index.pyelonephritis, | 229 |
| abstract_inverted_index.reproducibility | 424 |
| abstract_inverted_index.fluoroquinolones | 281 |
| abstract_inverted_index.gastrointestinal | 243 |
| abstract_inverted_index.population-based | 87 |
| abstract_inverted_index.fluoroquinolones, | 69 |
| abstract_inverted_index.fluoroquinolones. | 325 |
| abstract_inverted_index.generalizability. | 426 |
| abstract_inverted_index.proof-of-principle | 407 |
| abstract_inverted_index.antibiotic-associated | 240 |
| abstract_inverted_index.(amoxicillin-clavulanate, | 163 |
| abstract_inverted_index.trimethoprim-sulfamethoxazole), | 154 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5003736818 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I136199984, https://openalex.org/I4210111543 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/17 |
| sustainable_development_goals[0].score | 0.5 |
| sustainable_development_goals[0].display_name | Partnerships for the goals |
| citation_normalized_percentile.value | 0.82059369 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |