Development of a new scale for self-reported procedural patient comfort during endovascular therapy for acute stroke
Bibliographic record
Abstract
INTRODUCTION: In stroke patients with acute large vessel occlusion, endovascular therapy (EVT) may be performed with or without sedation. Our aim is to describe self-reported intraprocedural comfort in patients undergoing EVT depending on sedation type. METHODS: We performed a prospective observational single-center study of patients undergoing EVT. Patients were systematically interviewed on the day following intervention using a structured questionnaire addressing five domains (nausea/vomiting, pain of any kind, physical discomfort, emotional discomfort, and medical team interaction). Each domain scored 0 to 2 points for a maximum total of 10 points (a higher score indicating greater discomfort). In addition, satisfaction with procedural comfort was rated on a visual analog scale (VAS), and patients reported whether they would have preferred more, less, or the same amount of sedation. Patients who underwent EVT without sedation (local anesthesia, LA) were compared to those who received procedural sedation (conscious sedation, CS). RESULTS: Seventy-seven questionnaires were completed: 37 (48%) patients underwent EVT with CS while 40 (52%) were treated under LA. Median scores on the self-reported discomfort scale (1[0-2] vs 1[0-2], p = 0.70) and mean scores on VAS (76 ± 25 vs 81 ± 24, p = 0.37) were similar between the CS and the LA group. The proportion of patients who were satisfied with the adopted sedation strategy was similar between groups. CONCLUSION: EVT without prior sedation seems to be well tolerated. Systematic self-evaluation of patient comfort appears feasible and may become integrated into routine clinical care. Patient-oriented outcomes should be included in future trials of sedation during thrombectomy.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".