Screening for Intracranial Stenosis With Transcranial Doppler: The Accuracy of Mean Flow Velocity Thresholds
Bibliographic record
Abstract
BACKGROUND: Patients with 50% intracranial arterial stenosis may require more intensive therapies for stroke prevention. Transcranial Doppler (TCD) is a convenient noninvasive screen for intracranial stenosis. The accuracy of different mean flow velocity (MFV) thresholds for determining the degree of stenosis remains uncertain. METHODS: The authors prospectively compared the accuracy of TCD criteria and MFV thresholds to magnetic resonance, computed tomography, and digital subtraction angiography in patients with symptoms of recent or remote stroke or transient ischemic attack. Stenosis on angiography was measured as 0%, < 50%, or > or = 50% diameter reduction. RESULTS: Of 136 consecutive patients, 33 (24%) had distal internal carotid artery (ICA), middle cerebral artery (MCA), posterior cerebral artery, or basilar artery stenosis on angiography (14 patients [10%] were excluded due to incomplete TCD examinations, mainly from a lack of temporal windows). TCD showed 31 true-positive, 9 false-positive, 2 false-negative, and 94 true-negative studies. For all vessels, TCD had a sensitivity of 93.9% (confidence interval [CI] = 89%-98%), a specificity of 91.2% (CI = 87%-96%), a positive predictive value (PPV) of 77.5%, and a negative predictive value (NPV) of 97.9%. The trade-off in sensitivity and specificity for MCA MFV thresholds was as follows: MFV > or = 80 cm/s had a sensitivity of 100%, a specificity of 96.9% (CI = 94%-99%), a PPV of 84%, and an NPV of 100%. MFV > or = 100 cm/s had a sensitivity of 100%, a specificity of 97.9% (CI = 96%-99%), a PPV of 88.8%, and an NPV of 94.9%. MFV > or = 120 cm/s had a sensitivity of 68.7% (CI = 61%-78%), a specificity of 100%, a PPV of 100%, and an NPV of 94.9%. Reasons for false-positive findings include collateralization of flow in the presence of proximal ICA stenosis and prestenotic to stenotic MCA velocity ratios of 1: < or = 2. CONCLUSION: TCD is both sensitive and specific in identifying > or = 50% intracranial arterial stenosis. A MFV threshold cutoff of 100 cm/s has an optimal sensitivity and specificity trade-off for > or = 50% MCA stenosis. To help avoid false-positive results, a prestenotic to stenotic MCA velocity ratio of 1: > or = 2 should be used in addition to the MFV threshold.
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 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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".