Long-term urological follow-up of multicystic dysplastic kidneys: Is it still indicated in 2007?
Bibliographic record
Abstract
OBJECTIVE: To determine whether the current indications for the long-term urological follow-up of children with multicystic dysplastic kidneys (MCDKs) are supported by the literature. METHODS: The membership of the Pediatric Urologists of Canada was surveyed to determine if long-term urological follow-up was being performed, and if so, for what indications. A literature search using PubMed, EMBASE and a Conference Papers Index was performed to determine whether the indications listed were supported by the literature. RESULTS: A response rate of 72% was achieved for the survey, with most respondents following children with MCDK long-term. The main indications for long-term follow-up were the increased risk of Wilms' tumour (54%) and hypertension (32%), observation of the contralateral kidney (43%) and involution of the MCDK (36%). The literature search did not support long-term urological follow-up for any of these indications, provided unilateral MCDK was an isolated genitourinary abnormality. Although it is rare, a primary care physician could monitor for hypertension. CONCLUSION: Long-term urological follow-up of children with "simple MCDK" is not supported by the literature, provided the diagnosis has been confirmed with a follow-up renal ultrasound at 12-24 months. Blood pressure monitoring by a primary care physician is recommended.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".