Impact of a Home Dialysis Virtual Longitudinal Education Series
Bibliographic record
Abstract
Background: Home dialysis has clinical benefits over in-center hemodialysis (HD), yet as of 2020, home dialysis use is low at 13.3% in the United States. One barrier to expanding home dialysis is a lack of experience amongst fellows due to inadequate training opportunities. In 2023, the American Society of Nephrology (ASN) launched the Home Dialysis Virtual Longitudinal Education Program with Home Dialysis University (HDU) to increase exposure for fellows through virtual case-based discussions. We aimed to understand the impact of this program. Methods: We evaluated the ASN-HDU program using mixed-methods. We sampled participants from (1) fellows who attended HDU and the ASN virtual program (ASN-HDU), and (2) fellows who only attended HDU from Aug-Sep 2023. We sent a survey in Sep 2023 to assess baseline comfort in home dialysis. Results of the survey were used to design the interview guide for qualitative thematic analysis. We used a constant comparative method to identify themes that described the participant’s experiences with home dialysis and the impact of the ASN-HDU program. Results: Survey response rates were 65.5% (19/29) and 50% (33/66) in the ASN-HDU arm and HDU arm, respectively. Participants felt comfortable with management of peritoneal dialysis but not home HD (Fig 1). We completed 10 semi-structured interviews between Dec 2023 – Mar 2024, with 5 participants from the ASN-HDU arm and 5 from the HDU arm. Three themes emerged: (1) HDU complements fellowship training by filling in gaps in home dialysis knowledge, (2) the ASN virtual program provides an opportunity for longitudinal exposure to topics learned during HDU, which helps retain knowledge and incorporate learning into practice, and (3) all participants voiced desire for more exposure to home dialysis including in-person training, and expansion of the ASN-HDU program. Conclusion: Baseline survey results suggest a lack of comfort in home HD. ASN-HDU trainees felt the program addresses training gaps in home dialysis and provides an opportunity to retain knowledge. Results from a follow-up survey, sent May 2024, will be available at Kidney Week to evaluate changes in comfort levels among ASN-HDU fellows. Funding: Other U.S. Government Support
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".