Factors Determining Fluoroscopy Time During Ureteroscopy
Bibliographic record
Abstract
PURPOSE: The aim of this study was to prospectively identify predictors of radiation exposure during ureteroscopy. PATIENTS AND METHODS: Eighty-five consecutive patients who presented for ureteroscopies and laser lithotripsy were considered. Fluoroscopy time (FT) was obtained from radiology reports for each patient, and clinical data were obtained from chart review. Nine patients were excluded (three unconfirmed FTs, four staghorn calculi, one ectopic kidney, and one multiple ureteral strictures). Seventy-six patients were included in the study. Univariate and multivariate linear regression were used to identify factors that determined FT. RESULTS: The patient cohort was 65.8% male with a mean age of 52.7 years. Mean FT was 183 s, and mean surgical time was 68.4±29 minutes. Mean stone size was 10±5 mm in the greatest dimension. A large proportion of patients (50%) had renal stones, multiple stones were present in 31.6% of cases, and 22.3% of stones were radiolucent. Cases were equally distributed between surgeons A and B, and 46% of patients had preoperative stents. On multivariate analysis, increased FT was independently associated with surgeon A (104 additional seconds per case, P<0.001), longer duration of surgery (14 s per 10 minutes, P<0.001), and male patients (54 s per procedure, P=0.02). Age, stone characteristics, presence of ureteral stent, and stone-free status did not correlate with FT. CONCLUSIONS: Surgeon behavior, longer duration of surgery, and male gender were significant predictors of FT and, hence, radiation exposure during ureteroscopy. In the present study, stone characteristics were not found to be predictors of FT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".