Prenatal detection of isolated bilateral hyperechogenic kidneys: Etiologies and outcomes
Bibliographic record
Abstract
OBJECTIVES: To delineate the etiology and outcome of prenatally diagnosed isolated bilateral hyperechogenic kidneys (IBHK). STUDY DESIGN: Pregnancies with IBHK on prenatal ultrasound identified and followed by us between January 1, 2000 and January 1, 2015 were evaluated regarding the etiology and outcome by evaluation of family history, targeted AR-PKD and AD-PKD DNA analysis, and microarray analysis, according to renal size and amniotic fluid volume. RESULTS: Of the 52 identified cases, there were 34 cases with enlarged kidneys, 16 with normal size kidneys, and two with small kidneys. There were seven cases with AD-PKD, six inherited, and one with de novo causative variants in the PKD1 gene. Fifteen had AR-PKD, and microarray analysis showed two inherited findings: one with 17q12 deletion including the HNF1B/TCF2 gene inherited from asymptomatic mother and a duplication at 3p26.1 inherited from a healthy father. Of the remaining four cases, three cases had bilateral multicystic dysplastic kidneys, and one had unilateral renal agenesis. CONCLUSION: Microarray analysis and mutation analysis for PKD1 and PKHD1 have an important contribution to the diagnostic investigation of IBHK and to the management of affected and future pregnancies. Poor outcome was associated with large hyperechoic kidneys with oligohydramnios.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".