Nocturnal Hemodialysis Improves Productivity of End-Stage Renal Failure Patients
Bibliographic record
Abstract
Background: End-stage renal disease (ESRD) patients undergoing conventional in-center hemodialysis (CHD)[3 sessions per week, 4 hours/session] have poor productivity which often results in unemployment. Nocturnal hemodialysis (NHD)[5–6 sessions per week, 8hours/session] is a novel home-based renal replacement therapy, which has been shown to have significant clinical improvements; including: blood pressure control, regression of left ventricular (LV) hypertrophy and restoration of impaired LV systolic function. The objective of our current study is to examine the impact of NHD on the productivity of ESRD patients before and after conversion from CHD to NHD. Methods: We conducted a retrospective survey of all NHD patients (n = 26) at the Toronto General Hospital, University Heath Network from May 1999 to Dec 2001. The parameters examined included (1. duration of NHD, 2. employment status, and 3. hours of productivity) before and after conversion from CHD to NHD. Paired Student t-Test was used to detect statistical significance. Results: Twenty-six patients (age:40 ± 10; mean ± SD) were included in our study. The mean duration of NHD in our cohort was 1.7 ± 0.9 years. Although, employment status were similar before and after conversion to NHD (CHD: 20/26 versus NHD: 21/26), there was a significant increase in the hours of productivity, CHD: 27.4 ± 18 hours per week versus NHD: 36.9 ± 21.7; p = 0.006. Conclusion: NHD is associated with a significant improvement in productivity in ESRD patients. NHD may be the modality of choice to restore ESRD patients the ability to pursue a normal lifestyle.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".