Excessive weight gain during peritoneal dialysis
Bibliographic record
Abstract
The authors carried out a retrospective chart review in 114 patients treated for at least two years at the Toronto Western Hospital Peritoneal Dialysis Unit and identified eight, who gained an "excessive" amount of weight equal to or greater than 10 kg of their initial weight. These patients had gained an average of 13.1 kg over the preceding two years. They are mostly males and their average age is 51 years. They are well-nourished normotenseive nondiabetics with mostly normal cardiac function. They are adequately dialyzed (per KT/V urea), have little residual renal function and typically have peritoneal membranes characterized by high average transport. According to BIA analysis, this weight gain was likely due to an increase in fat mass accompanied by a trend toward decreasing body-cell mass. This weight gain may be due to increased caloric intake secondary to dialysate glucose absorption in the setting of high average (peritoneal membrane) transport. Such excessive weight gain also may occur if these patients have polymorphism of the UCP-2 gene, which can alter metabolic rate.
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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".