The Effect of Dietary Intervention on Autosomal-Dominant Polycystic Kidney Disease (ADPKD) Patients on Tolvaptan and Their Quality of Life
Bibliographic record
Abstract
Background and objective Autosomal-dominant polycystic kidney disease (ADPKD) is the most common inherited renal disorder; it affects people of all ethnic groups and is found in up to 10% of patients with end-stage renal disease (ESRD). Dietary intervention is important in people with renal disease, and it has been linked to greater estimated glomerular filtration rate (eGFR) preservation. Tolvaptan, an orally-active nonpeptide, selective arginine vasopressin (AVP) V2R antagonist, was recently licensed in numerous countries for the treatment of ADPKD. The aim of this study was to assess the role of dietary intervention in decreasing the osmotic load on the urine volume and its impact on the quality of life (QOL) of patients with ADPKD on tolvaptan. Methods This prospective cohort study was carried out at a Hamilton nephrology genetics clinic. ADPKD patients on well-tolerated doses of tolvaptan for three months were included in the study. Gitelman and Bartter Symptom Health-related QOL questionnaire was used among the study participants. Results Our study consisted of nine adult patients with ADPKD who were on a stable dose of tolvaptan therapy. Patients had laboratory values for urine volume, sodium (Na), and urea. No significant difference was found between pre- and post-diet intervention values in 24-hour urine volume (5.9 vs. 5.49 L/d; p=0.423), urine Na (p=0.174), and 24-hour urine urea (p=0.404). Conclusion Dietary intervention in ADPKD patients on tolvaptan therapy can play a vital role in improving their QOL. Further research including interventional studies and clinical trials with larger sample sizes is needed to gain deeper insight into the subject.
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 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 | 0.001 |
| 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) | 0.001 | 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".