Cardiac implications of upper-arm arteriovenous fistulas: A case series
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease is a major cause of morbidity and mortality in patients with end-stage kidney disease. Arterio-venous fistulas (AVF), the gold standard for hemodialysis vascular access, are known to alter cardiac morphology and circulatory hemodynamics. We present a prospective case series of patients after creation of an AVF, explore the timeline for changes in their cardiac morphology, and detail considerations for clinicians. METHODS: Patients were recruited in 2010 at multiple centers immediately prior to the creation of an upper-arm AVF and the initiation of hemodialysis. Cardiovascular magnetic resonance images were taken at intake before the creation of the AVF, 6-month follow-up, and 12-month follow-up. Image segmentation was used to measure left ventricular volume and mass, left atrial volume, and ejection fraction. RESULTS: Eight patients met eligibility criteria. All eight patients had a net increase in left ventricular mass over enrollment, with a mean increase of 9.16 g (+2.96 to +42.66 g). Five participants had a net decrease in ejection fraction, with a mean change in ejection fraction of -5.4% (-21% to +5%). Upon visual inspection the patients with the largest ejection fraction decrease had noticeably hypertrophic and dilated ventricles. Left atrial volume change was varied, decreasing in five participants, while increasing in three participants. Changes in morphology were present at 6-month follow-up, even in patients who did not maintain AVF patency for the entirety of the 6-month period. CONCLUSION: All patients included in this prospective case series had increases in left ventricular mass, with variability in the effects on the ejection fraction and left atrial volume. As left ventricular mass is an independent predictor of morbidity and mortality, further research to determine appropriate vascular access management in both end-stage kidney disease and kidney transplant populations is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".