Clinical Correlates of Mass Effect in Autosomal Dominant Polycystic Kidney Disease
Bibliographic record
Abstract
Mass effect from polycystic kidney and liver enlargement can result in significant clinical complications and symptoms in autosomal dominant polycystic kidney disease (ADPKD). In this single-center study, we examined the correlation of height-adjusted total liver volume (htTLV) and total kidney volume (htTKV) by CT imaging with hepatic complications (n = 461) and abdominal symptoms (n = 253) in patients with ADPKD. "Mass-effect" complications were assessed by review of medical records and abdominal symptoms, by a standardized research questionnaire. Overall, 91.8% of patients had 4 or more liver cysts on CT scans. Polycystic liver disease (PLD) was classified as none or mild (htTLV < 1,600 mL/m); moderate (1,600 ≤ htTLV <3,200 mL/m); and severe (htTLV ≥ 3,200 mL/m). The prevalence of moderate and severe PLD in our patient cohort was 11.7% (n = 54/461) and 4.8% (n = 22/461), respectively, with a female predominance in both the moderate (61.1%) and severe (95.5%) PLD groups. Pressure-related complications such as leg edema (20.4%), ascites (16.6%), and hernia (3.6%) were common, and patients with moderate to severe PLD exhibited a 6-fold increased risk (compared to no or mild PLD) for these complications in multivariate analysis. Similarly, abdominal symptoms including back pain (58.8%), flank pain (53.1%), abdominal fullness (46.5%), and dyspnea/chest-discomfort (44.3%) were very common, and patients with moderate to severe PLD exhibited a 5-fold increased risk for these symptoms. Moderate to severe PLD is a common and clinically important problem in ~16% of patients with ADPKD who may benefit from referral to specialized centers for further management.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".