The need for outpatient back‐up for home hemodialysis patients: Implications for resource utilization
Bibliographic record
Abstract
INTRODUCTION: The provision of sufficient support contributes to home hemodialysis (HHD) technique survival. The need for back-up treatment in incident and prevalent patients on HHD has not been well described previously, and is important from both technique survival and resource allocation. We aimed to quantify the amount of back-up treatment given to patients in our HHD unit, and hypothesized that the provision of back-up HD facilitated technique survival. METHODS: This was a retrospective, single-center cohort study quantifying the provision of back-up HD between January and December 2018. Electronic and paper medical records were accessed for data collection. FINDINGS: One hundred and nineteen patients dialyzed independently at home during the study period (96 patient years of HHD). Seventy-eight (66%) patients required a total of 292 back-up HD sessions in the HHD unit, representing an average of three back-up HD runs per patient year of HHD. Fifty-three percent of back-up HD runs were required for vascular access related issues. The most common clinical issue requiring assessment and back-up HD was extracellular fluid volume management. An equal proportion (95%) of those that utilized back-up HD and those that did not utilize back-up HD maintained a positive disposition (transplant or ongoing HHD) in relation to technique survival in the short term. CONCLUSIONS: From a resource viewpoint, this program of approximately 100 HHD patients required the availability of one to two staffed HD stations each weekday for back-up HD. The provision of back-up HD was not a harbinger of HHD discontinuation.
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 | 0.005 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".