GANAB-Associated Severe Autosomal Dominant Polycystic Kidney Disease in an 18-Year-Old Female: A Case Report
Bibliographic record
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is a hereditary disorder, characterized by the formation of multiple cysts in the kidneys, leading to progressive kidney enlargement and, eventually, renal failure. It is most frequently associated with PKD1 or PKD2 mutations, although rare variants, such as the GANAB gene, are also associated, but they present as a milder renal phenotype. ADPKD patients often present with renal manifestations, such as hypertension, abdominal pain, hematuria, or urinary tract infections, along with extrarenal manifestations, such as liver cysts, heart valve disease, and cerebral aneurysms. ADPKD is usually diagnosed in the fourth or fifth decade of life. This case report discusses the clinical presentation, diagnostic approach, and management of an 18-year-old female patient with no known first-degree family history of ADPKD, who presented with hypertension and bilateral renal cysts on ultrasound. The diagnosis was confirmed by imaging studies and genetic testing. The GANAB gene mutation found in this patient is typically associated with mild kidney disease; however, according to the Mayo Clinic Imaging Classification (MIC) for ADPKD, our patient falls under Classification 1E, which is predictive of rapid progression to end-stage renal disease (ESRD). It highlights the challenges in treating young patients with ADPKD, given the limited studies available for managing this progressive disease in the young population. This case questions the assumption that GANAB-associated ADPKD progresses in a mild manner. Clinicians should prioritize vigilant monitoring and a multidisciplinary approach for young patients with high-risk imaging characteristics, regardless of their genetic findings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".