FP627EVOLUTION OF HIGH-SENSITIVITY TROPONIN-T IN PATIENTS UNDERGOING HIGH EFFICIENCY ON-LINE HEMODIAFILTRATION VERSUS CONVENTIONAL LOW-FLUX HEMODIALYSIS
Bibliographic record
Abstract
Introduction and Aims: On-line hemodiafiltration (HDF) has been associated with better atherosclerosis-related inflammatory markers profile than conventional low-flux hemodialysis (HD). Recent large randomized clinical trials suggested that HDF had a beneficial effect on survival when higher convection volumes are provided. High-sensitivity troponin T (hs-TnT) has been related to all-cause and cardiovascular mortality in end-stage renal disease patients. The aim of this study was to determine the effect HDF vs HD on hs-TnT evolution at one year follow-up. Methods: Patients were randomized from 2007 to 2013 to HD or HDF in accordance with the CONvective TRAnsport STudy (CONTRAST) protocol initially as part of the Montreal CONTRAST cohort (until 2010) and subsequently as part of the local cohort (2010-2013). Hs-TnT were obtained before dialysis session and analyzed at baseline and at 1-year follow-up with STAT assay (Roche Diagnostics) on Cobas e411 instrument. Comparison of the evolution of hs-TnT values between groups were performed with appropriate non-parametric tests. Agreement between hs-TnT values at baseline and at follow-up was analyzed using a Bland-Altman plot.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".