Plasma cell neoplasm as a risk factor for early thrombosis of arteriovenous fistula
Bibliographic record
Abstract
INTRODUCTION: We hypothesized that presence of plasma cell neoplasms might be a risk for thrombosis of arteriovenous fistulas (AVFs) as well as other well-known factors including age, sex, race, and presence of diabetes mellitus or certain vascular disorders. METHODS: In this single-center, retrospective study based on medical record data, we investigated the influence of plasma cell neoplasms and the above-mentioned factors on the occurrence of complete occlusive thrombosis of the AVF within 30 days after surgery for creation of the AVF. Thrombosis was defined as the absence of bruit or thrill on auscultation and palpation, throughout systole and diastole. FINDINGS: We retrospectively assessed the medical records of 91 patients with end-stage renal failure, including 8 patients with plasma cell neoplasm (5 with multiple myeloma and 3 with amyloid light-chain amyloidosis), who underwent surgical creation of an AVF at the wrist or anatomical snuff box for the first time between April 2014 and December 2016. Early thrombosis (i.e., within 30 days of surgery) occurred in 50.0% (4/8) and 10.8% (9/83) of patients with and without plasma cell neoplasm, respectively (P = 0.013). Multivariate analysis revealed that, after adjusting for baseline characteristics, plasma cell neoplasm was the only significant risk factor for early AVF thrombosis (odds ratio, 38.8; 95% confidence interval, 4.0-378.9; P = 0.0017). DISCUSSION: Considering the poor prognosis of plasma cell neoplasm and its association with higher risk for AVF thrombosis, another type of vascular access is likely to be more suitable than AVF in such patients.
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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 | 0.003 |
| 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 | 0.000 | 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".