Family History of Renal Disease Severity Predicts the Mutated Gene in ADPKD
Bibliographic record
Abstract
Mutations of PKD1 and PKD2 account for 85 and 15% of cases of autosomal dominant polycystic kidney disease (ADPKD), respectively. Clinically, PKD1 is more severe than PKD2, with a median age at ESRD of 53.4 versus 72.7 yr. In this study, we explored whether a family history of renal disease severity predicts the mutated gene in ADPKD. We examined the renal function (estimated GFR and age at ESRD) of 484 affected members from 90 families who had ADPKD and whose underlying genotype was known. We found that the presence of at least one affected family member who developed ESRD at age < or =55 was highly predictive of a PKD1 mutation (positive predictive value 100%; sensitivity 72%). In contrast, the presence of at least one affected family member who continued to have sufficient renal function or developed ESRD at age >70 was highly predictive of a PKD2 mutation (positive predictive value 100%; sensitivity 74%). These data suggest that close attention to the family history of renal disease severity in ADPKD may provide a simple means of predicting the mutated gene, which has prognostic implications.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".