Outcome of endovascular thrombectomy in patients with end-stage renal disease undergoing dialysis
Bibliographic record
Abstract
BACKGROUND: Patients with end-stage renal disease (ESRD) are often excluded from clinical trials of endovascular thrombectomy (EVT). This study investigated the outcome in these patients. METHODS: but no dialysis), and ESRD undergoing dialysis (ESRD-dialysis). The clinical features and outcomes were compared. RESULTS: Of 482 patients included, there were 20 ESRD-dialysis, 110 RD, and 352 non-RD patients. The Alberta Stroke Program Early CT Score (ASPECTS), National Institutes of Health Stroke Scale (NIHSS), use of intravenous thrombolysis, EVT-related time metrics, and successful recanalization rates were comparable among the three groups. However, the ESRD-dialysis patients had more symptomatic intracerebral hemorrhage (ICH, 15% vs 3.6% vs 3.7%), more contrast-induced encephalopathy (15% vs 1.8% vs 0.9%), and a higher mortality at 90 days (35% vs 18% vs 11%) than the other groups. Multivariable analysis revealed that ESRD-dialysis was associated with a less favorable outcome (OR 0.21, 95% CI 0.04 to 0.77) and more severe disability or mortality (modified Rankin Scale 5 or 6; OR 13.1, 95% CI 3.93 to 48.1) at 90 days. In the ESRD-dialysis group, the patients with premorbid functional dependence had a significantly higher mortality than those without (75% vs 8.3%; P=0.004). CONCLUSION: ESRD-dialysis patients were associated with symptomatic ICH and less favorable outcome at 90 days. Patients with premorbid functional dependency had an excessively high mortality.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".