Nonpharmacologic and Nonsurgical Weight Management Interventions for Patients With Advanced CKD: A Scoping Review of the Medical Literature
Bibliographic record
Abstract
Rationale & Objective: Obesity is associated with morbidity and mortality in people with chronic kidney disease (CKD). Identifying safe and effective nonpharmacologic and nonsurgical interventions to achieve a healthier body weight is essential. Study Design: Scoping review of observational studies and randomized control trials. Setting & Study Populations: and advanced CKD (category G3-G5D). Selection Criteria for Studies: Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews (PRISMA-ScR), we systematically searched 2 electronic databases (MEDLINE and Embase) for studies that examined the effect of nonpharmacologic and nonsurgical interventions for weight loss between January 2010-July 2024. Outcomes included weight loss and BMI. We also examined adherence, whether participants were involved in the design of the study, and adverse events. Data Extraction: Two reviewers screened relevant citations and extracted study characteristics and outcomes. Discrepancies were resolved by a third reviewer. Analytical Approach: Study data were summarized descriptively following guidance from the PRISMA-ScR. Results: Of the 2,453 citations, 17 met inclusion criteria (9 randomized controlled trials, 2 nonrandomized trials, 5 prospective cohort studies, and 1 retrospective cohort study) and included a total of 960 participants. Interventions included exercise programs, dietary therapy, and/or cognitive behavioral therapy with follow-up ranging from 3-12 months. It appeared that dietary intervention that promoted significant caloric restriction over the short term led to the most weight loss (average, 7 kg). Interventions with monitored coaching appeared helpful. No adverse events were reported. None of the studies involved participants as partners. Limitations: . Conclusions: Programs encouraging very low-energy diets along with monitored coaching, may result in modest short-term weight loss. Patient views on these programs and their longer term success remain unclear.
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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 | 0.028 | 0.099 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.038 | 0.029 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".