Long‐Term Outcome and Quality of Life in Patients With Stroke Presenting With Extensive Early Infarction
Bibliographic record
Abstract
Background The benefit of mechanical thrombectomy in patients with low Alberta Stroke Program Early Computed Tomography Score (ASPECTS) for short‐term outcomes is debatable and long‐term outcomes remain unknown. This retrospective, monocentric cohort study aimed to assess the association between reperfusion grade and the long‐term functional outcome measured with modified Rankin scale as well as the long‐term health‐related quality of life recorded at the last follow‐up in patients according to baseline ASPECTS (0–5 versus 6–10). Methods Deceased patients were identified from the Swiss population register and follow‐up telephone interviews were conducted with all surviving patients with stroke treated with mechanical thrombectomy between January 1, 2010, and December 31, 2018. Favorable outcome was defined as modified Rankin scale 0 to 3; health‐related quality of life was assessed using the 3‐level version of the EuroQol 5‐dimensional questionnaire. The EuroQol 5‐dimension utility index was calculated for statistical analyses. The reperfusion grade was core laboratory adjudicated using the expanded treatment in cerebral ischemia score. Adjusted odds ratios for the association between the reperfusion grade assessed by expanded treatment in cerebral ischemia and outcomes were calculated from multivariable logistic regression. Results Of the 1114 patients with available long‐term follow‐up records (median follow‐up, 3.67 years), 997 were included in the final analysis. Respectively, patients with low ASPECTS more often had complaints regarding mobility (67.1% versus 42.1%, P <0.001), self‐care (53.4% versus 31.2%, P <0.001), and usual activities (65.8% versus 41.4%, P <0.001) than patients with high ASPECTS, whereas reported pain/discomfort (65.7% versus 69.9%, P =0.49) and anxiety/depression (71.2% versus 78.9%, P =0.17) did not differ. In patients with low ASPECTS, increasing reperfusion grade was associated with a higher likelihood of long‐term favorable functional outcome (adjusted odds ratio, 1.43; 95% CI, 1.09–1.88 [ P= 0.01]) and health‐related quality of life (adjusted linear correlation coefficient, 0.05; 95% CI, 0.02–0.08) despite early extensive infarction. Conclusion Despite low baseline ASPECTS, a higher reperfusion grade results in better functional outcomes and may improve health‐related quality of life in the long term.
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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 | 0.002 |
| 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 | 0.000 |
| 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".