The value of the ultrasound score to indicate pyloplasty in unilateral hydronephrosis: a retrospective study with 120 Brazilian children
Bibliographic record
Abstract
Abstract: Introduction: Scintigraphy has long been the gold standard for indicating pyeloplasty for UPJO. The Pyeloplasty Prediction Score (PPS) was introduced as an alternative tool to indicate pyeloplasty. Ultrasound is widely available, painless, noninvasive, does not require radiation, and is a low-cost examination. This study evaluates the correspondence between PPS and patients who underwent pyeloplasty. Method: This was a retrospective study involving 120 patients who underwent pyeloplasty. After data collection, the researchers applied the PPS. Results & Discussion: The left kidney was the most commonly affected (68.3%), mainly in boys (67.5%), and 49.2% received an antenatal diagnosis. Intrinsic obstruction was found in 89.7% of the patients. Approximately 69.17% (n=83) had a preoperative PPS grater/equal 8. The affected kidney had a larger longitudinal measure than the contralateral. There was no difference related to sex, laterality, or etiology. The use of the ultrasound score would be sufficient for almost 70% of patients to indicate pyeloplasty without any other complementary exams. Conclusions: Based on this study, it is not possible to state that the PPS, without kidney scintigraphy, is effective in indicating pyeloplasty for every patient. However, it could be an excellent screening method. Keywords: Hydronephrosis. Ultrasonography. Ureteral obstruction. Urogenital abnormalities. Pediatrics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".