The role of gaze-face-arm-speech-time score in evaluating prognosis of intravenous thrombolysis in acute ischemic stroke
Bibliographic record
Abstract
Objective To evaluate the predictive value of gaze-face-arm-speech-time (G-FAST) score, a simple and rapid scoring tool, for the prognosis of intravenous thrombolysis in patients with acute ischemic stroke. Methods The clinical data of 386 patients with acute ischemic stroke who received intravenous thrombolytic therapy in 4.5 hours in the Department of Neurology of Beijing Shijitan Hospital from May 2010 to April 2018 were analyzed retrospectively. Among them, 126 cases completed CT angiography or magnetic resonance angiography before intravenous thrombolysis. According to the modified Rankin scale (mRS) score of 90 days after treatment, those with the mRS score ≤ 2 were regarded as good prognosis group (74 cases), and those with the mRS score ≥ 3 as poor prognosis group (52 cases). The baseline clinical data of the two groups were analyzed, including age, sex, previous history, the National Institutes of Health Stroke Scale (NIHSS) score, G-FAST score, Alberta Stroke Early CT Score (ASPECTS), anterior circulating large artery occlusion (LAVO), etc. And further multifactor Logistic regression analysis was used to analyze the influencing factors of poor prognosis. Results The rate of good prognosis of these patients was 58.7% (74/126). The age ((61.72±11.98) years vs (69.53±11.58) years, t=-3.317, P=0.001), history of atrial fibrillation (18.9%(14/74) vs 36.5%(19/52), χ2=4.905, P=0.027), thrombolytic time window ((145.19±43.44) min vs (164.26±40.07) min, t=-2.19, P=0.031), baseline NIHSS score (9.65±5.33 vs 12.83±6.25, t=-2.760, P=0.007), pre thrombolytic G-FAST score (2.46±1.00 vs 3.02±0.79, t=-3.068, P=0.003), ASPECTS (8.06±1.29 vs 6.89±1.91, t=3.613, P=0.000) and LAVO (39.2%(29/74) vs 67.3%(35/52), χ2=9.661, P=0.002) showed statistically significant differences between the good and the poor prognosis groups. Multiple factor Logistic regression analysis showed that the age (OR=1.609, 95%CI 1.067-2.001, P=0.026), history of atrial fibrillation (OR=1.302, 95%CI 1.157-1.658, P=0.002), LAVO (OR=6.416, 95%CI 3.302-12.84, P=0.000), longer thrombolytic time window (OR=6.756, 95%CI 2.035-9.754, P=0.001), lower ASPECTS (OR=1.452, 95%CI 1.035-2.279, P=0.002), higher baseline NIHSS score (OR=1.309, 95%CI 1.083-1.542, P=0.033) and G-FAST score (OR=1.583, 95%CI 1.432-1.855, P=0.000) were independent risk factors for the poor prognosis of acute ischemic stroke. The age ((67.89±17.28) years vs (62.24±12.54) years, t=2.317, P=0.024), history of atrial fibrillation (34.3%(24/70) vs 16.1%(9/56), χ2=5.339, P=0.021), baseline NIHSS score (11.68±5.68 vs 9.02±4.36, t=2.150, P=0.034), ASPECTS (7.06±2.08 vs 8.77±1.85, t=-1.613, P=0.042) and LAVO (68.6%(48/70) vs 28.6%(16/56), χ2=19.916, P=0.000) showed statistically significant difference between the G-FAST score ≥ 3 group and the G-FAST score ≤ 2 group by further analysis. And the good prognosis of 90 days was lower in the G-FAST score ≥ 3 group (51.4% (36/70)) than in the G-FAST score ≤ 2 group (67.9% (38/56), χ2=4.953, P=0.026). Conclusions High G-FAST score is an independent risk factor for thrombolytic therapy for acute ischemic stroke. The high score of G-FAST may suggest the incidence of LAVO, the obvious changes in early cerebral ischemia, and the poor prognosis of 90 days. Patients in this group may consider bridging endovascular treatment as early as possible. Key words: Stroke; Thrombolytic therapy; Prognosis; G-FAST score; Arterial occlusive diseases
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".