Changes in Body Weight Before and After Kidney Donation
Bibliographic record
Abstract
Background: Living kidney donors remain at low risk of end-stage kidney disease (ESKD), but the risk for obese and overweight donors is increased. The Kidney Disease Improving Global Outcomes (KDIGO) clinical guideline recommends that overweight and obese patients pursue weight loss before donation and maintain a healthy post-donation weight. Objective: To determine the trajectory of weight changes before and after living kidney donation. Design: Retrospective cohort study. Setting: The Living Kidney Donor program in the Champlain Local Health Integration Network at The Ottawa Hospital in Ottawa, Canada. Patients: The study included 151 living kidney donors who donated between January 2009 and December 2017. Measurements: Date of kidney donation, relationship to the transplant recipient, and cause of ESKD in the transplant recipient were documented. Demographic data, markers of glycemic control, and weights at the time of clinic visits were recorded. Methods: The analysis included use of paired Student’s t tests to compare mean differences in weight at kidney donation relative to the time of initial assessment and at last follow-up. Results: The median (interquartile range [IQR]) follow-up was 392 (362, 1096) days post-donation. Among donors with normal body mass index (BMI; 18.5-24.9 kg/m 2 ), weight loss occurred before donation (62.8 ± 3.1 kg to 61.5 kg ± 2.9 kg; mean difference 1.1 ± 2.7 kg, P < .01) and did not change significantly post-donation. Among overweight/obese donors (BMI ≥25 kg/m 2 ), weight did not change significantly pre-donation, but increased significantly post-donation (86.0 ± 2.1 kg to 88.8 ± 2.7 kg; mean difference 2.3 ± 0.9 kg, P < .0001). Limitations: The single-center design of the study limits generalizability. Conclusions: Donors with normal BMI experienced significant weight loss before donation and maintained healthy body weight post-donation. Conversely, donors with BMI ≥25 kg/m 2 at donation experienced significant weight gain over 1-year post-donation. Our findings suggest the need for enhanced weight control efforts among obese and overweight kidney donors to reduce the risk of ESKD.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".