Sonographic Assessment of Renal Growth in Patients with Beckwith-Wiedemann Syndrome: The Beckwith-Wiedemann Syndrome Renal Nomogram
Bibliographic record
Abstract
BACKGROUND: Beckwith-Wiedemann syndrome is a disorder of somatic overgrowth. Evidence of kidney overgrowth is a diagnostic criterion that may be used to help identify those patients who are at the greatest risk of developing Wilms tumors. In such subjects, kidney size is typically larger than that of age-matched normal controls. OBJECTIVE: The purpose of our study was to generate a nomogram that could be used to measure renal dimensions in children with Beckwith-Wiedemann syndrome in a clinical setting. MATERIALS & METHODS: All of the Beckwith-Wiedemann syndrome patients followed at our institution from 1996 to 2004 were eligible for inclusion in our study. Renal length was measured with a curvilinear transducer and with the patient supine. Renal lengths were measured for both kidneys using real-time ultrasound for all patients. Their data were compared with those of age-matched controls reported in the 1984 study by Rosenbaum et al. RESULTS: Ninety-six children with Beckwith-Wiedemann syndrome were followed from 1996 to 2004. Forty-three of these patients met our criteria for inclusion in the study: 28 girls (65%) and 15 boys (35%). We identified a linear relationship between kidney length and patient age. No statistically significant differences in renal length were found between boys and girls (p=0.2153) or between the kidneys on either side of the body (p=0.9613). CONCLUSION: Our study provides a practical, simple renal growth chart that offers a reasonable, sensitive method for evaluating kidney size in children with Beckwith-Wiedemann syndrome.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".