Patient Reported Outcomes Predicting Spontaneous Stone Passage May Not Have Acceptable Accuracy
Bibliographic record
Abstract
PURPOSE: We assessed the accuracy of patient reported outcomes for predicting spontaneous ureteral stone passage. MATERIALS AND METHODS: Patients with new unilateral ureteral calculi were prospectively assessed regarding current symptoms and whether they believed their stone had passed. The primary outcome was successful spontaneous stone passage as confirmed by ultrasound, and kidney, ureter and bladder x-ray. Spontaneous stone passage was compared to patient reported outcome responses to assess accuracy. RESULTS: Of the 212 patients 105 (49.5%) had successful spontaneous stone passage at a mean followup of 17.6 days. Compared to the unsuccessful spontaneous stone passage group, those with successful spontaneous stone passage had significantly smaller (mean 5.4 vs 7.6 mm), more distal (71.4% vs 34.6%) stones with slightly longer average time to followup at first visit (19.2 vs 16.0 days). Additionally, there was more patient reported cessation of pain (77.1% vs 44.9%) and perceived stone passage (55.2% vs 13.1%) in this group. Cessation of pain was 79.7% (95% CI 67.1-89.0) sensitive and 55.8% (95% CI 44.0-67.1) specific for successful spontaneous stone passage. Likewise, patient reported stone passage was 59.3% (95% CI 45.7-71.9) sensitive and 87.0% (95% CI 77.4-93.5%) specific. In the multivariable logistic regression analysis cessation of pain (OR 4.02, 95% CI 1.91-8.47, p <0.01) and reported stone passage (OR 3.79, 95% CI 1.73-8.28, p <0.01) were independent predictors of successful spontaneous stone passage. CONCLUSIONS: Cessation of pain and patient reported stone passage are independent predictors of successful spontaneous stone passage. However, both assessments may incorrectly gauge spontaneous stone passage, which raises concern for their validity as a sole clinical end point.
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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 | 0.017 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".