Nutritional Status and Oral Nutritional Supplement (ONS) Use Among Patients with Non-Dialysis CKD in British Columbia (BC)
Bibliographic record
Abstract
Background: Malnutrition and protein-energy wasting are complications of advanced CKD that are associated with increased risk of mortality and morbidity. In BC, a government-funded Nutritional Supplement Policy stewarded by renal dietitians guides ONS prescription for CKD patients who meet weight or nutrient intake criteria. Methods: We conducted a retrospective study of CKD-ND patients who entered multidisciplinary CKD clinics in BC during 2013-2018 (N=15859). We used Wilcoxon signed-rank test to compare baseline nutrition/inflammation parameters among patients with any ONS prescription within 1 year of clinic entry and those not prescribed ONS. Longitudinal ONS prescription patterns over 3 years were described in the 2013-2015 entry cohort (N=7611). Results: 1389 patients (9%) were eligible for and prescribed ONS, with variation between health regions. Patients taking ONS had lower eGFR, BMI, bicarbonate, hemoglobin, and greater age, ferritin, phosphate, PTH, neutrophil-to-lymphocyte ratio compared to those who did not receive ONS (p<0.0001 for all comparisons). Overall ONS use during the first 3 years of follow-up remained stable, with 40% new ONS users and 60% previous ONS users during year 2 and 3 of follow-up. For patients prescribed ONS within the 1st year of clinic entry, 65% had 1-2 ONS prescriptions/year, and among those continuing follow-up in year 2, 38% discontinued ONS, 35% had 1-2 ONS prescriptions/year, and 27% had 3+ ONS prescriptions/year (Figure). Conclusions: This is the first Canadian study to describe ONS use among CKDND, which provides an estmate of incidence of undernutrition, as defined by dietitian assessment and corroborated by nutritional lab parameters. Among patients prescribed ONS, the majority have infrequent ONS use, while another subset has regular ONS use longitudinally. Funding: Government Support - Non-U.S.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".