Abstract T P354: The Role of Lindegaard Ratio on TCD for Predicting Angiographic Vasospasm Following Aneurysmal Subarachnoid Haemorrhage
Bibliographic record
Abstract
Background and objective: Middle cerebral artery (MCA) Lindegaard ratio (LR) has been used as indicator of moderate to severe vasospasm (VSP) following subarachnoid hemorrhage (SAH). However there have been many criticisms about the ability to detect impending vasospasm using Transcranial Doppler (TCD). The purpose of this study was to determine the correlation between TCD Mean Flow Velocities (MFV) and angiographic VSP after aneurysmal SAH using LR of several anterior circulation vessels. Methods: The study population included prospective collected data of 134 patients with aneurysmal SAH admitted to University of Alberta hospital from January 2006 to December 2008. Complete TCD was performed daily from day 2 to 14 from symptoms onset. All patients underwent cerebral angiography on admission and within 7 days following onset of symptoms. The M1, M2 MCA, ACA and intracranial ICA/ipsilateral extra cranial ICA velocity ratios (LR) were calculated and correlation was made with the presence of angiographic vasospasm (defined as more than one-third luminal narrowing). Then, anterior circulation LR was defined as the highest LR in the ipsilateral anterior circulation arteries. Moderate to severe VSP was defined as LR > 3. Results: Results are shown in table. The probability of VSP in the presence of one anterior circulation vessel LR > 3 is 14 % (2/14), 2 vessels LR >3 (4/16. 16 %), 3 vessels LR > 3 (3/6, 50 %) and 4 vessels LR >3 (5/5 = 100 %). (P< 0.001) Conclusion: LR of M2 MCA has higher sensitivity compared to other vessels and ACA LR has less sensitivity but more specificity whereas the rest of anterior circulation LR had modest predictive value. The likelihood of VSP increases as more number of vessels in anterior circulation shows LR>3. LR should not be interpreted in a blind fashion to the rest of TCD MFV numbers.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".