Can we predict the ancillary treatments after extracorporeal shockwave lithotripsy for renal and upper ureteral stones?
Bibliographic record
Abstract
OBJECTIVE: To quantify the predictors for the ancillary treatments after extracorporeal shock wave lithotripsy (SWL) for renal and upper ureteral stones. MATERIALS AND METHODS: From January 2014 to January 2017, patients undergoing SWL using an electromagnetic lithotripter machine (Compact Delta; Dornier MedTech GmbH, Wessling, Germany) for renal and upper ureteral stones ≤ 20 mm were retrospectively reviewed. All patients underwent CT urography prior to SWL. The cohort was subdivided into three groups according to stone attenuation values in Hounsfield Units (HU). Group I; HU < 500 (n = 20), group II; HU 500-1000 (n = 51) and group III; HU ≥ 1000 (n = 180). The parameters included for multivariate analysis were stone size, location, multiplicity, stone attenuation value, number of shocks and stone clearance rate by 3 months. The ancillary treatments were ureteroscopy (URS), ureteral stenting and hospital readmission for pain or fever. RESULTS: A total of 251 patients were included in the study. The overall SWL success rate was 92.4%. Mean stone size was 10.9 ± 2.1, 11.6 ± 3 and 11.4 ± 3.6 mm and mean stone attenuation values were 364 ± 125, 811 ± 154 and 1285 ± 171 HU for groups I, II and III respectively. The stone clearance rates by 3 months were 96%, 92% and 88.4% for groups I, II and III respectively. On subgroup analysis, group III required ancillary treatments in 70% of patients whereas group I, II, did not require any ancillary treatments. On multivariate analysis, stone multiplicity, stone location (lower calyceal stones) and HU were independent significant predictors for the need for ancillary treatments after SWL (p values < 0.05). CONCLUSIONS: Patients with stone attenuation value (HU) > 1000, multiple stones and/or lower calyceal stones have higher risk to necessitate ancillary treatments after SWL. These patients would likely benefit from upfront endoscopic lithotripsy for treating symptomatic renal or upper ureteral stones.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".