Left ventricular strain analysis using cardiac magnetic resonance imaging in patients undergoing in‐centre nocturnal haemodialysis
Bibliographic record
Abstract
AIM: Intensified haemodialysis is associated with regression of left ventricular (LV) mass. Compared to LV ejection fraction, LV strain allows more direct assessment of LV function. We sought to assess the impact of in-centre nocturnal haemodialysis (INHD) on global LV strain (radial, circumferential, and longitudinal) and torsion by cardiac MRI (CMR). METHODS: In this prospective, two-centre cohort study, 37 participants on conventional haemodialysis (CHD, 3-4 h/session for three sessions/week) converted to INHD (7-8 h/session for three sessions/week) and 30 participants continued CHD. Participants underwent CMR using a standardized protocol and had biomarker measurements at baseline and 52 weeks. RESULTS: Among the 55 participants (mean age 55; 40% women) with complete CMR data, those who converted to INHD had a significant improvement in their global circumferential strain (GCS, P = 0.025), while those continuing CHD did not have any significant changes in LV strain. When the two groups were compared, there was significant improvement in torsion. LV strains were significantly correlated with each other, but not with troponin I, C-reactive protein, or brain natriuretic protein (NT-proBNP), except for global longitudinal strain (GLS) with troponin I (P = 0.001) and NT-proBNP (P = 0.038). CONCLUSION: Conversion to INHD was associated with significant improvement in GCS over one year of study, although comparisons with the CHD group were not significant. There was also a significant decrease in torsion in the INHD group compared with CHD. Improvement in LV regional function would support the notion that INHD has favourable effects on both LV structure and function.
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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 | 0.001 |
| 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) | 0.000 | 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".