Higher arteriovenous fistulae blood flows are associated with a lower level of dialysis‐induced cardiac injury
Bibliographic record
Abstract
Native arteriovenous fistulae (AVF) remain the vascular access of choice for hemodialysis (HD). Despite being associated with superior long-term outcomes (cf. catheter use), little is known about the systemic hemodynamic consequences of AVFs. Repetitive myocardial injury (myocardial stunning) is an under-recognized common consequence of HD. The aim of this study was to examine the impact of AVF flow (Qa) on dialysis-induced cardiac injury. We studied 50 chronic HD patients. All patients underwent echocardiography (and subsequent quantitative offline analysis) at baseline, during and post dialysis, to assess left ventricular function and the development of regional wall motion abnormalities. Qa was measured using ionic dialysance. Patients were divided into Qa tertiles (<500, mean 291+/-101 mL/min, 500-1000, mean 739+/-130 mL/min and >1000, mean 1265+/-221 mL/min). There were no significant differences between the groups in terms of age, sex, diabetes, or resting ejection fraction. Patients with Qa>1000 mL/min had a lower prevalence of left ventricular hypertrophy (55% vs. 76%, P=0.01). Dialysis-induced myocardial stunning (seen in 65% of the patients studied) was significantly and sequentially reduced in those patients with higher Qas. This was seen in a lower number of segments and ventricular regions developing regional wall motion abnormalities, as well as a significantly reduced mean and cumulative percentage reduction in fractional shortening of those ventricular segments affected (-187+/-37%, -161+/-26%, and -101+/-25%, respectively, P=0.04). Relatively higher AVF flows appear to be associated with a lower level of observed HD-induced cardiac injury.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".