Oral nutritional supplements and 30‐day readmission rate in hypoalbuminemic maintenance hemodialysis patients
Bibliographic record
Abstract
INTRODUCTION: Hemodialysis (HD) patients are hospitalized nearly twice yearly, and 35% of these patients are rehospitalized within 30-days postdischarge. We hypothesized that monitored oral nutritional supplementation (ONS) during HD treatment may decrease readmissions. METHODS: A cohort of maintenance HD patients, treated at a large dialysis organization, who were hospitalized with a postdischarge albumin of ≤3.5 g/dL, without documented ONS use 90 days prior to the index hospitalization were identified. Individuals who received monitored intradialytic ONS postdischarge were compared to those without receipt of ONS. The outcome of interest was 30-day hospital readmissions. Logistic regression was used to assess the association between ONS receipt and 30-day readmission events, with adjustment for case-mix and laboratory variables. FINDINGS: Of 5479 eligible patients, ONS was prescribed to 1420 individuals. Mean age was 64.6 ± 14.1 (SD) years; median dialysis vintage was 3.9 years. There were 274 (19%) readmissions among ONS recipients vs. 1571 (38.7%) among controls during the 30-day follow-up period. Individuals who did not receive ONS had increased odds of readmission [OR 2.26 (95% CI 1.02, 2.53)] in 30 days, as compared to those who did receive ONS postdischarge. In sensitivity analyses using a propensity score matched cohort, the odds ratio of readmissions within 30 days postdischarge was 1.71 (95% CI: 1.42, 2.07) for individuals who did not receive ONS as compared to those who received ONS. DISCUSSION: Consumption of ONS during HD sessions is associated with reduced hospital readmission rates among in-center maintenance HD with severe hypoalbuminemia at 30 days post-hospital discharge.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".