Renal ultrasound findings and vesicoureteral reflux in children hospitalised with urinary tract infection
Bibliographic record
Abstract
AIMS: To determine the sensitivity, specificity, and predictive values of renal ultrasound findings for vesicoureteral reflux (VUR). METHODS: Retrospective review of the ultrasound and voiding cystourethrogram (VCUG) results of 162 children under 5 years of age admitted with their first episode of urinary tract infection (UTI) over a two year period. Ultrasound findings were considered suggestive of VUR if "dilatation of the pelvi-calyces", "dilatation of the ureters", or "dilatation of the collecting system" of one or both kidneys was reported. RESULTS: A total of 162 patients were eligible for inclusion (median age 85 days; 71 (44%) were female). The prevalence of VUR was 22%. Ultrasound findings were positive for VUR in 14 of 35 patients with confirmed VUR on VCUG, and positive in 30 of 127 patients without VUR on VCUG. Of 21 patients who had a normal ultrasound but showed VUR on VCUG, 14 had grade II reflux, five grade III reflux, and two grade IV reflux. The sensitivity and specificity of ultrasound in suggesting VUR were 40% and 76%, respectively. The positive predictive value of ultrasound in suggesting VUR was 32%; the negative predictive value was 82%. CONCLUSION: Renal ultrasound findings are neither sensitive nor specific for VUR in children with a first UTI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".