Predictors of receipt of a fluoroquinolone versus trimethoprim‐sulfamethoxazole for treatment of acute pyelonephritis in women in Manitoba, Canada
Bibliographic record
Abstract
PURPOSE: The increasing and comparatively high proportion of uropathogens in Canada resistant to trimethoprim-sulfamethoxazole (TMP-SMX) may be partially responsible for the increasing use of fluoroquinolones. A number of patient-specific variables have been identified as risk factors for infections caused by antibiotic-resistant pathogens. However, variables unrelated to need, have also been associated with receipt of broad-spectrum antibiotics. We identified patient variables associated with receipt of a fluoroquinolone versus TMP-SMX for treatment of acute pyelonephritis. METHODS: Healthcare claims from the province of Manitoba, Canada for the period February 1996 to March 1999 were examined to identify episodes of pyelonephritis in non-pregnant females between 18 and 65 years of age treated with TMP-SMX or a fluoroquinolone. Patient variables were identified based on healthcare claims review and data from Statistics Canada. Logistic regression was used to model the probability of receipt of a fluoroquinolone. RESULTS: A total of 1084 women met inclusion criteria; 653 treated with TMP-SMX and 431 treated with a fluoroquinolone. Age, income, rural residence, recent antibiotic use, recent hospitalization and presentation to an emergency room (ER) were positively associated with receipt of a fluoroquinolone. CONCLUSIONS: Patient variables reportedly associated with an increased probability of resistant organisms (e.g., age, recent antibiotic use and recent hospitalization) were significantly associated with an increased probability of receipt of fluoroquinolones. However, variables unrelated to antibiotic resistance (e.g., income, rural residence and presentation to an ER) were also significantly associated with receipt of a fluoroquinolone.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".