Health-related quality of life after thrombectomy in young-onset versus older stroke patients: a multicenter analysis
Bibliographic record
Abstract
BACKGROUND: Information is lacking on self-reported health-related quality of life (HRQoL) as a complementary outcome measure in addition to the modified Rankin scale (mRS) in young patients with ischemic stroke after endovascular thrombectomy (EVT) compared with older patients. METHODS: Data on consecutive patients with stroke who underwent thrombectomy (June 2015-2019) from a multicenter prospective registry (German Stroke Registry) were analyzed. HRQoL was measured by the European QoL-5 dimension questionnaire utility index (EQ-5D-I; higher values indicate better HRQoL) 3 months after stroke in patients aged ≤55 and >55 years. Multivariate regression analyses identified predictors of better HRQoL. RESULTS: Of 4561 included patients, 526 (11.5%) were ≤55 years old. Young-onset patients had a better outcome assessed by mRS (mRS 0-2: 64.3% vs 31.8%, p<0.001) and EQ-5D-I (mean 0.639 vs 0.342, p<0.001). Young survivors after EVT had fewer complaints in the EQ-5D domains mobility (p<0.001), self-care (p<0.001), usual activities (p<0.001) and pain/discomfort (p=0.008), whereas no difference was observed in anxiety/depression (p=0.819). Adjusted regression analysis for 90-day mRS showed no difference in HRQoL between the two subgroups of patients. Lower age, National Institutes of Health Stroke Scale score and pre-stroke mRS, a higher Alberta Stroke Program Early CT Score, concomitant intravenous thrombolysis therapy and successful recanalization were associated with better HRQoL in both patient subgroups. CONCLUSIONS: Young-onset stroke patients have a better HRQoL after EVT than older patients. Their higher HRQoL is mainly explained by less physical disability assessed by mRS. Depressive symptoms should be actively assessed and targeted in rehabilitation therapies of young-onset stroke patients to improve quality of life after stroke.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.001 | 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 teacher head, 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".