Effect of short-term blood pressure variability on functional outcome after intra-arterial treatment in acute stroke patients with large-vessel occlusion
Bibliographic record
Abstract
BACKGROUND: Endovascular treatment (EVT) is advocated for acute ischaemic stroke with large-vessel occlusion (LVO), but perioperative periods are challenging. This study investigated the relationship between post-EVT short-term blood pressure variability (BPV) and early outcomes in LVO patients. METHODS: We retrospectively reviewed 72 LVO patients undergoing EVT between June 2015 and June 2018. Hourly systolic and diastolic blood pressures (SBP and DBP, respectively) were recorded in the first 24 h post-EVT. BPV were evaluated as standard deviation (SD), coefficient of variation (CV), and successive variation (SV) separately for SBP and DBP. Functional independence at 3 months was defined as a modified Rankin Scale (mRS) score of 0-2. RESULTS: For 58.3% patients with favorable outcomes, the median National Institutes of Health Stroke Scale and Alberta Stroke Program Early CT scores on admission were 14 and 8, respectively. The maximum SBP ([154.3 ± 16.8] vs. [163.5 ± 15.6], P = 0.02), systolic CV ([8. 8% ± 2.0%] vs. [11.0% ± 1.8], P < 0.001), SV ([11.4 ± 2.3] vs. [14.6 ± 2.0], P < 0.001), and SD ([10.5 ± 2.4] vs. [13.8 ± 3.9], P < 0.001) were lower in patients with favorable outcomes. On multivariable logistic regression analysis, systolic SV (OR: 4.273, 95% CI: 1.030 to 17.727, P = 0.045) independently predicted unfavorable prognosis. The area under the curve was 0.868 (95% CI: 0.781 to 0.955, P < 0.001), and sensitivity and specificity were 93.3% and 73.8%, respectively, showing excellent predictive value for 3-month poor-outcomes. CONCLUSIONS: Decreased systolic SV following intra-arterial therapies result in favorable outcomes at 3 months. Systolic SV may be a novel predictor of functional prognosis in LVO patients.
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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 | 0.004 |
| 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 | 0.001 |
| 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".