High‐output heart failure secondary to arteriovenous fistula
Bibliographic record
Abstract
In the hemodialysis patient population, a surgically created arteriovenous fistula is the preferred vascular access option. Development of high-output heart failure may be an underappreciated complication in patients who have undergone this procedure. When a large proportion of arterial blood is shunted from the left-sided circulation to the right-sided circulation via the fistula, the increase in preload can lead to increased cardiac output. Over time, the demands of an increased workload may lead to cardiac hypertrophy and eventual heart failure. Patients may present with the usual signs of high-output heart failure including tachycardia, elevated pulse pressure, hyperkinetic precordium, and jugular venous distension. Typically, the AV fistula is quite large and is likely located in the upper arm, more proximal to the heart. Routine access flow monitoring should demonstrate blood flows (Qa) >2000 ML/min. Echocardiogram may reveal either a low or high left ventricular ejection fraction, and right-heart catheterization demonstrates an elevated cardiac output with a low to normal systemic vascular resistance. When addressing the problem of high-output heart failure, the nephrologist is faced with the dilemma of preventing progression of heart failure at the expense of loss of vascular access. Nevertheless, treatment should be directed at correcting the underlying problem by surgical banding or ligation of the fistula.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".