Topographic correlation of infarct area on CT perfusion with functional outcome in acute ischemic stroke
Bibliographic record
Abstract
OBJECTIVE: The role of CT perfusion (CTP) in the management of patients with acute ischemic stroke (AIS) remains a matter of debate. The primary aim of this study was to evaluate the correlation between the areas of infarction and penumbra on CTP scans and functional outcome in patients with AIS. METHODS: This was a retrospective review of 100 consecutively treated patients with acute anterior circulation ischemic stroke who underwent CT angiography (CTA) and CTP at admission between February 2011 and October 2014. On CTP, the volume of ischemic core and penumbra was measured using the Alberta Stroke Program Early CT Score (ASPECTS). CTA findings were also noted, including the site of occlusion and regional leptomeningeal collateral (rLMC) score. Functional outcome was defined by modified Rankin Scale (mRS) score obtained at discharge. Associations of CTP and CTA parameters with mRS scores at discharge were assessed using multivariable proportional odds logistic regression models. RESULTS: The median age was 67 years (range 19-95 years), and the median NIH Stroke Scale score was 16 (range 2-35). In a multivariable analysis adjusting for potential confounding variables, having an infarct on CTP scans in the following regions was associated with a worse mRS score at discharge: insula ribbon (p = 0.043), perisylvian fissure (p < 0.001), motor strip (p = 0.007), M2 (p < 0.001), and M5 (p = 0.023). A worse mRS score at discharge was more common in patients with a greater volume of infarct core (p = 0.024) and less common in patients with a greater rLMC score (p = 0.004). CONCLUSIONS: The results of this study provide evidence that several CTP parameters are independent predictors of functional outcome in patients with AIS and have potential to identify those patients most likely to benefit from reperfusion therapy in the treatment of AIS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".