Associations with health-related quality of life after intracerebral haemorrhage: pooled analysis of INTERACT studies
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Limited data exist on health-related quality of life (HRQoL) after intracerebral haemorrhage (ICH). We aimed to determine baseline factors associated with HRQoL among participants of the pilot and main phases of the Intensive Blood Pressure Reduction in Acute Cerebral Haemorrhage Trials (INTERACT 1 and 2). METHODS: The INTERACT studies were randomised controlled trials of early intensive blood pressure (BP) lowering in patients with ICH (<6 hours) and elevated systolic BP (150-220 mm Hg). HRQoL was determined using the European Quality of Life Scale (EQ-5D) at 90 days, completed by patients or proxy responders. Binary logistic regression analyses were performed to identify factors associated with poor overall HRQoL. RESULTS: 2756 patients were included. Demographic, clinical and radiological factors associated with lower EQ-5D utility score were age, randomisation outside of China, antithrombotic use, high baseline National Institutes of Health Stroke Scale (NIHSS) score, larger ICH, presence of intraventricular extension and use of proxy responders. High (≥14) NIHSS score, larger ICH and proxy responders were associated with low scores in all five dimensions of the EQ-5D. The NIHSS score had a strong association with poor HRQoL (p<0.001). Female gender and antithrombotic use were associated with decreased scores in dimensions of pain/discomfort and usual activity, respectively. CONCLUSIONS: Poor HRQoL was associated with age, comorbidities, proxy source of assessment, clinical severity and ICH characteristics. The strongest association was with initial clinical severity defined by high NIHSS score. TRIAL REGISTRATION NUMBERS: NCT00226096 and NCT00716079; Post-results.
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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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.024 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".