Implementation of a clinical practice guideline for assessment and management of renal colic in the emergency department
Bibliographic record
Abstract
INTRODUCTION: Renal colic is a common emergency department (ED) presentation. Variations in assessment and management of suspected renal colic may have significant implications on patient and hospital outcomes. We developed a clinical practice guideline to standardize the assessment and management of renal colic in the ED. We subsequently compared outcomes before and after guideline implementation. METHODS: The guideline standardizes the analgesia regimen, urology consult criteria, imaging modality, patient education, and followup instructions. This is a single-center, observational cohort study of patients presenting to the ED with renal colic prospectively collected after guideline implementation (December 2018 to May 2019) compared to a control group retrospectively collected before guideline implementation (December 2017 to May 2018). A total of 528 patients (pre-guideline n=283, post-guideline n=245) were included. Statistical analysis was performed with SPSS using multivariate linear regression. RESULTS: ED length of stay (LOS) was significantly shorter after guideline implementation (pre-guideline 295.82±178.8 minutes vs. post-guideline 253.2±118.2 minutes, p=0.017). The number of computed tomography (CT) scans patients received was significantly less after guideline implementation (pre guideline 1.35±1.34 vs. post-guideline 1.00±0.68, p=0.034). Patients discharged for conservative management had a lower re-presentation rate in the post-guideline group (12.6%) than the pre-guideline group (17.2%); however, this did not reach statistical significance (p=0.18). CONCLUSIONS: Implementation of a clinical practice guideline for ureteric stones reduces the ED LOS and the total number of CT scan in patients who present with renal colic. Standardizing assessment and management of ureteric stones can potentially improve patient and hospital outcomes without compromising the quality of care.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".