O-021 Evaluation of Baseline CT ASPECTS in Perfusion-guided Selected Patients for Intra-arterial Reperfusion Therapy
Bibliographic record
Abstract
Background and Purpose Appropriate patient selection in acute ischaemic stroke (AIS) is central for improving patient outcomes following intra-arterial (IA) reperfusion therapy (thrombolysis/mechanical thrombectomy). Perfusion imaging with CTP/MR DWI-PWI has been utilised increasingly to identify subpopulations with acceptable risk-benefit profiles for reperfusion, avoiding futile or harmful recanalisation. Earlier studies reported to have prognostic value of baseline Alberta Stroke Program Early CT Score (ASPECTS) of >7 in determining good functional outcomes following IA reperfusion. We investigated baseline CT ASPECTS in AIS patients selected for IA reperfusion therapy based on perfusion mismatch profiles. Furthermore, we studied the predictive value of CT ASPECTS for clinical outcomes following recanalisation. Materials and Methods In a multicentre review, all AIS patients that underwent IA thrombolysis/thrombectomy between January 2010 and September 2012 were studied retrospectively for the following inclusion criteria: baseline NIHSS >8, presentation <8 hours from symptom onset, CTA/MRA verified M1-M2 MCA occlusion, and favourable perfusion (CTP/MR DWI-PWI) mismatch profile. Patient demographics, medical comorbidities, time from symptom onset to recanalisation, final recanalisation (TICI scale), and clinical outcomes (90 day mRS score) were obtained. One neuroradiologist conducted blinded scoring of ASPECTS for all baseline noncontrast CT scans. For evaluation of inter-rater reliability, scores by another neuroradiologist were used and analysed using Intraclass Correlation Coefficient (ICC) and Bland and Altman method. ASPECTS scores were dichotomised into >7 and ≤7 for primary analysis. Chi-square, Mann-Whitney U and student t tests were used for univariate analyses as appropriate. To obtain the optimal cut-off ASPECTS for discriminating patients with favourable outcomes, receiver operating characteristic (ROC) curve analysis was performed. Results Seventy-one consecutive patients (39 female/32 male patients with mean age of 71.2 ± 15.5 years) met inclusion criteria for analysis. Successful recanalisation (TICI > 2b/3) was achieved in 38 patients (53.5%), highly correlating with good functional outcomes (mRS 0–2) in 43 patients (60.6%) (P < 0.001). No significant difference was observed between ASPECTS reading (P=0.9) with good inter-rater reliability (ICC=0.80, 95% confidence interval: 0.66 to 0.87). Patients with ASPECTS >7 (n=43) and ≤7 (n=28) were comparable in baseline characteristics,medical history, and treatment related variables (age, P=0.8; sex, P=0.8; baseline NIHSS score, P=0.2; diabetes, P=0.8; atrial fibrillation, P=1.0; hyperlipidemia, P=1.0; hypertension, P=0.8; recanalisation, P=0.6; time from symptom onset to recanalisation, P=0.7). Relatively high ASPECTS correlated with perfusion-based patient selection with mean and median baseline ASPECTS of eight. However, no significant correlation was observed between baseline ASPECTS and final clinical outcomes (P=0.5). Additionally, baseline ASPECTS score >7 did not correlate with final outcome in patients with successful recanalisation (P=0.4). The ROC curve analysis demonstrated a cut-off point of eight for discrimination of final outcome, but with poor predictive value (sensitivity=65.1%; specificity=28.6%; P=0.8, AUC=0.51). Conclusion Our results indicate favourable baseline CT ASPECTS correlate with favourable perfusion mismatch profiles and may represent an equivalent surrogate for primary patient selection in IA reperfusion therapy. However, CT ASPECTS did not clearly predict good functional outcomes independent of recanalisation, suggesting other confounding variables such as core infarct volume versus eloquence may impact clinical outcomes and have to be elucidated. Disclosures A. Honarmand: None. M. Soltanolkotabi: None. S. Prabhakaran: None. M. Hurley: None. O. Rahman: None. A. Shaibani: None. S. Ansari: None.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".