Patients With Mild ADPKD by Kidney Imaging but Low Estimated GFR
Bibliographic record
Abstract
Introduction High height-adjusted total kidney volume (HtTKV) and low estimated glomerular filtration rate (eGFR) typically indicate high cystic burden by imaging and low kidney function, respectively, identifying high-risk patients for disease progression in autosomal dominant polycystic kidney disease (ADPKD). Here, we report the prevalence, clinical characteristics, and causes of mild ADPKD in patients using imaging and low eGFR, an ill-defined clinical scenario. Methods We studied 473 patients with kidney function measurements, PKD1 and PKD2 genetic screen, and total kidney volume (TKV) measurements by magnetic resonance imaging (MRI) or computed tomography. Mayo Clinic Imaging Classification (MCIC) based on age and HtTKV was used to assess cystic disease severity. Patients with a discordant phenotype were defined as those with MCIC 1A/B and eGFR < 80 ml/min per 1.73 m 2 . We reviewed medical records to compare patients with and without the discordant phenotype, examining clinical characteristics such as second kidney disease(s), nephrotoxic exposure, diabetes mellitus, and metabolic syndrome-related traits. Results Of 473 patients, 55 (12%) displayed a discordant phenotype. Among these patients, 13 (24%) had normal kidney functions by 24-h creatinine clearance (CrCl 24 ) (> 80 ml/min per 1.73 m 2 ) and high urinary creatinine excretion rates, indicating underestimation of their kidney function by eGFR likely because of high muscle mass. In addition, discordant patients showed a higher prevalence of hypertension (82% vs. 57%, P < 0.001), dyslipidemia (58% vs. 15%, P < 0.001), diabetes mellitus (15% vs. 3%, P < 0.05), and a second kidney disease (16% vs. 1%, P < 0.001). Conclusion Mild ADPKD by imaging with low eGFR represents a significant clinical scenario with conflicting prognostic indicators, underscoring the need for delineating underlying causes and providing more appropriate management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".