Diagnostic and Therapeutic Management of Urinary Tract Infections in Catalonia, Spain: Protocol for an Observational Cohort Study
Bibliographic record
Abstract
BACKGROUND: Antibiotic resistance is an individual and public health problem; multidrug-resistant infections could cause an estimated 10 million deaths worldwide by 2050. Unnecessary use of antimicrobials is the most important cause of resistance generation in the community, and an estimated 80% of antimicrobials are prescribed in primary health care, frequently for urinary tract infections (UTIs). OBJECTIVE: This paper presents the protocol for the first phase of the Urinary Tract Infections in Catalonia (Infeccions del tracte urinari a Catalunya) project. We aim to examine the epidemiology of the different types of UTIs in Catalonia (an autonomous community in Spain) and their diagnostic and therapeutic management by health professionals. Furthermore, we aim to evaluate the correlation between types and total consumption of antibiotics for recurrent UTIs in 2 cohorts of women with the presence and severity of infectious complications of urological origin, especially pyelonephritis and sepsis, and 2 potentially serious infections: pneumonia and COVID-19. METHODS: The study is a population-based observational cohort study including adults with a diagnosis of UTI registered in the Information System for the Development of Research in Primary Care (in Catalan: Sistema d'informació per al desenvolupament de la investigació en atenció primària), the Minimum Basic Data Sets of Hospital Discharges and Emergency Departments (in Catalan: Conjunt mínim bàsic de dades a l'hospitalització d'aguts i d'atenció urgent), and data from the Hospital Dispensing Medicines Register (in Catalan: Medicació hospitalària de dispensació ambulatòria) of Catalonia from the period between 2012 and 2021. We will evaluate the variables obtained from the databases to analyze the proportion of different types of UTIs, the percentage of adequate antibiotic treatments prescribed or received for recurrent UTIs according to the national guidelines, and the proportion of UTIs with complications. RESULTS: We expect to describe the epidemiology of UTIs in Catalonia from 2012 to 2021, as well as describe the diagnostic and therapeutic management of UTIs by health professionals. CONCLUSIONS: We expect to find a high percentage of UTI cases with inadequate management according to the national guidelines, considering that on many occasions UTIs are treated with second- or third-line antibiotic therapies with a preference for the longest regimens. Furthermore, the use of antibiotic suppressive therapies, or prophylaxis, in recurrent UTIs will likely be highly variable. Moreover, we aim to determine whether women with recurrent UTIs treated with antibiotic suppressive therapies have a higher incidence and severity of potentially serious future infections, with special attention to acute pyelonephritis, urosepsis, COVID-19, and pneumonia, compared to women who receive antibiotic treatment after they present with a UTI. This is an observational study of data from administrative databases that will not allow causality analysis. The limitations of the study will be handled according to the appropriate statistical methods. TRIAL REGISTRATION: European Union Electronic Register of Post-Authorisation Studies EUPAS49724; https://www.encepp.eu/encepp/viewResource.htm?id=49725. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44244.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".