The effects of preoperative blood pressure on early failure rate of distal arteriovenous fistulas for hemodialysis access
Bibliographic record
Abstract
INTRODUCTION: The first choice of vascular access for hemodialysis in patients with end-stage renal disease is a distal radiocephalic arteriovenous fistula (AVF). Early failure rates for these AVFs vary from 10% to 53%. The effects of predialysis hypotension on failure of AVFs have been described in the literature. Weather lower blood pressures affect early AVF failure has not been extensively studied. We conducted this study to evaluate the effects of preoperative blood pressures on early AVF failure. METHODS: Ours was a prospective observational study over a period of 2 years that included 224 patients who underwent distal radiocephalic AVF creation. Only those patients were included whose fistulas were made by surgeons with an experience of greater than five cases. The systolic, diastolic, and mean arterial pressures (MAPs) were recorded preoperatively. Early failure was defined as failure to achieve vascular access from the fistula within first 4 months of its creation. FINDINGS: The overall early failure rate was 27.7%. Early failure was more common in females and diabetic patients. The systolic, diastolic, and MAPs were significantly lower in patients with early failure (P < 0.05). In a multivariable adjusted analysis, lower preoperative diastolic and MAPs were predictors for early failure of distal radiocephalic AVF. DISCUSSION: Our study shows that patients with early failure of AVFs have lower preoperative blood pressure. A larger study is required to substantiate our findings and define target preoperative blood pressure for AVF creation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".