Regression of left ventricular mass following conversion from conventional hemodialysis to thrice weekly in-centre nocturnal hemodialysis
Bibliographic record
Abstract
BACKGROUND: Increased left ventricular mass (LVM) is associated with adverse outcomes in patients receiving chronic hemodialysis. Among patients receiving conventional hemodialysis (CHD, 3×/week, 4 hrs/session), we evaluated whether dialysis intensification with in-centre nocturnal hemodialysis (INHD, 3×/week, 7-8 hrs/session in the dialysis unit) was associated with regression of LVM. METHODS: We conducted a retrospective cohort study of CHD recipients who converted to INHD and received INHD for at least 6 months. LVM on the first echocardiogram performed at least 6 months post-conversion was compared to LVM pre-conversion. In a secondary analysis, we examined echocardiograms performed at least 12 months after starting INHD. The effect of conversion to INHD on LVM over time was also evaluated using a longitudinal analysis that incorporated all LVM data on patients with 2 or more echocardiograms. RESULTS: Thirty-seven patients were eligible for the primary analysis. Mean age at conversion was 49 ± 12 yrs and 30% were women. Mean pre-conversion LVM was 219 ± 66 g and following conversion, LVM declined by 32 ± 58 g (p = 0.002). Among patients whose follow-up echocardiogram occurred at least 12 months following conversion, LVM declined by 40 ± 56 g (p = 0.0004). The rate of change of LVM decreased significantly from 0.4 g/yr before conversion, to -11.7 g/yr following conversion to INHD (p < 0.0001). CONCLUSION: Conversion to INHD is associated with a significant regression in LVM, which may portend a more favourable cardiovascular outcome. Our preliminary findings support the need for randomized controlled trials to definitively evaluate the cardiovascular effects of INHD.
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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 | 0.003 |
| 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 | 0.001 |
| 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".