Influence of postnatal hydroureter in determining the need for voiding cystourethrogram in children with high-grade hydronephrosis
Bibliographic record
Abstract
ObjectiveTo evaluate the utility of hydroureter (HU) to identify high-grade vesico-ureteric reflux (VUR) in patients with high-grade postnatal hydronephrosis (PH).Patients and methodsWe retrospectively reviewed patients’ charts that had antenatal hydronephrosis from 2008 to 2014. Patients were excluded if they presented with febrile urinary tract infection (fUTI), neurogenic bladder, posterior urethral valve, multi-cystic dysplastic kidney, and multiple congenital malformations. We reviewed postnatal ultrasonography images and patients with Society of Fetal Urology (SFU) Grades 3 and 4 hydronephrosis with a renal pelvic antero-posterior diameter of ≥10 mm were included. The ureter was assessed and considered dilated if the ureteric diameter was ≥4 mm. The voiding cystourethrogram (VCUG) studies, fUTI incidence, and surgical reports were reviewed.ResultsOf the 654 patients reviewed, we included 148 patients (164 renal units) of whom 113 (76.4%) were male and 35 (23.6%) female. SFU Grade 3 PH was identified in 49% of the renal units, with the remaining 51% being SFU Grade 4. HU was found in 50/164 renal units and was not detected in the remaining 114 units. VUR was diagnosed in four units (3.5%) without HU (low-grade VUR); whilst it was detected in 19 units (38%) with HU (72.7% were high-grade VUR) (P < 0.001). VUR was diagnosed on the contralateral side in four/105 patients with PH without HU and diagnosed in 10/43 patients with PH with HU (P < 0.001). During a median follow-up of 25.9 months, none of the renal units that had VUR without HU developed UTI or had surgeries.ConclusionLow-grade uncomplicated VUR was diagnosed in 3.5% of renal units without HU. Our results support limiting the use of VCUG to renal units with PH if associated with HU.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".