Effect of an In-Hospital Chronic Kidney Disease Education Program among Patients with Unplanned Urgent-Start Dialysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The effect of in-hospital education on the adoption of home dialysis (peritoneal dialysis [PD] and home hemodialysis [HHD]) after an unplanned dialysis start is unknown. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Clinical demographics of consecutive patients acutely initiating hemodialysis (HD) from January 2005 to December 2009 were abstracted using institutional electronic records. All patients received multimedia chronic kidney disease education by the same advanced care nurse practitioner before discharge from the hospital. Clinical characteristics of patients choosing home dialysis or staying on in-center HD were compared. RESULTS: Between 2005 and 2009, 228 patients acutely started renal replacement therapy (RRT) at the center. Seventy-one patients chose home dialysis (49 patients adopted PD and 22 adopted HHD), 132 chose to remain on in-center HD, and 25 died before discharge from the hospital. Patients adopting home dialysis tended to be younger than in-center HD patients (55 ± 18 [home dialysis] versus 59 ± 16 [in center] years; P=0.09) and were similar in gender distribution (49% [home dialysis] versus 56% [in center] male; P=0.2). Patients adopting home dialysis were more likely to have a failed kidney transplant (24% [home dialysis] versus 12% [in center]; P=0.045) and less likely to have ischemic nephropathy (9% [home dialysis] versus 21% [in center]; P=0.03). The distribution of comorbid conditions was different between patients adopting home dialysis and in-center HD. CONCLUSIONS: Home dialysis is feasible after urgent dialysis start. Education should be promoted among patient experiencing acute-start dialysis.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".