Derivation of Power M‐Mode Transcranial Doppler Criteria for Angiographic Proven MCA Occlusion
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Bibliographic record
Abstract
BACKGROUND: Stringent transcranial Doppler (TCD) criteria for diagnosing occlusion are needed for more reliable TCD performance at bedside in the acute stroke setting. SUBJECTS AND METHODS: At three academic stroke centers, we performed TCD examination for patients with symptoms of cerebral ischemia who underwent digital subtraction angiography (DSA). We used a standard insonation protocol with power M-mode Doppler (PMD) TCD (TCD 100 M, Spencer Technologies Inc., Seattle, WA). We collected mean flow velocity (MFV), pulsatility indices (PI), and power M-mode resistance signature (absent, high, or low) in symptomatic middle (MCA), anterior (ACA), posterior (PCA), and in affected (a), ipsilateral (i), and contralateral (c-lat) cerebral arteries. Ratios of aMCA/c-lat MCA, aMCA/iACA, and aMCA/iPCA MFV were subsequently calculated. PMD-TCD flow findings were evaluated with a receiver-operating characteristic (ROC) analysis for angiographically proven MCA occlusion. RESULTS: We studied 120 patients with acute cerebral ischemia with PMD-TCD examinations prior to or immediately after DSA. Lower aMCA velocities pointed to higher probability of occlusion (P= .055). The aMCA/iPCA MFV ratio was superior to the aMCA/iACA ratio and strongly predictive of occlusion at a threshold ratio of 0.5 (RR 2.31 CI(95) 2.13-2.51). High resistance or absent M-mode flow signatures in the proximal MCA were present in 87% of M1 and M2 MCA occlusions (probability 87%). In the presence of a low-resistance PMD signature, obtaining the aMCA/iPCA MFV ratio <0.5 increases probability of occlusion to 87%. Normal MFV ratios and low-resistance M-mode signatures are highly predictive of a negative angiogram for MCA occlusion. CONCLUSION: In acute cerebral ischemia, reliable criteria for proximal MCA occlusion have been developed based on combination of MFV ratios and M-mode flow resistance signatures. Validation of these criteria will require multicenter studies.
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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 | 0.000 | 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) | 0.000 | 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 it