<scp>Post‐dialysis</scp> recovery time in <scp>ESRD</scp> patients receiving more frequent hemodialysis in skilled nursing facilities
Bibliographic record
Abstract
INTRODUCTION: Post-dialysis recovery time (DRT) has an important relationship to quality of life and survival, as identified in studies of ESRD patients on conventional dialysis. ESRD patients are often discharged from hospitals to skilled nursing facilities (SNFs) where on-site treatment using home hemodialysis technology is increasingly offered, but nothing is known about DRT in this patient population. METHODS: From November 4, 2019 to June 11, 2021, within a dialysis organization providing service across 12 states and 154 SNFs, patients receiving in-SNF, more frequent dialysis (MFD) (modeled to deliver 14 treatment hours minimum per week and stdKt/V ≥2.0) were asked to describe their post-dialysis recovery time following their previous treatment, within predefined categoric choices: 0-½, ½-1, 1-2, 2-4, 4-8, 8-12 h, by next morning, or not even by next morning. Patients reporting DRT following at least one full-week treatment opportunity were included in a mixed model logistic regression of rapid recovery (DRT ≤2 h). FINDINGS: Two thousand three hundred and nine patients met the statistical modeling inclusion criteria, providing DRT on 108,876 dialysis sessions, while receiving mean (SD) 4.3 (0.96) weekly dialysis treatments. 2118 (92%) reported DRT ≤2 h. Results appeared biologically plausible, as lower odds of rapid DRT were observed for patients who were older, missed their previous treatment, or experienced intradialytic hypotension. Greater odds of rapid DRT were observed in patients receiving five dialyses in the previous week or having 160-179 mmHg pre-hemodialysis systolic blood pressure. Rapid recovery was associated with reduced mortality or hospitalization. DISCUSSION: SNF dialysis patients receiving 5x per week MFD report rapid recovery time ≤2 h in 92% of dialyses despite advanced age, frailty, and comorbidities. Future studies will assess the practical ramifications of rapid DRT perception/experience on nursing home rehabilitation programs, which could impact patient health beyond the nursing home stay.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".