Bibliographic record
Abstract
The authors define the frequency, nature, and extent of cerebrovascular sequelae of Takayasu arteritis using functional imaging. Retrospective analysis of the cases derived from the Durban Stroke Data Bank (n = 1100) and Durban Metropolitan Vascular Surgery Database (n = 5300) consisted of evaluation by contemporary neuroimaging modalities including single positron emission computed tomography (SPECT), magnetic resonance imaging (MRI) diffusion scanning, and transcranial Doppler (TCD). Of all the patients identified with Takayasu disease (n = 142), 29 (20%) patients were identified with a primarily cerebrovascular presentation. The recent advent of modern functional imaging techniques allowed only the 10 most recent patients with a cerebrovascular presentation to be evaluated. Of these 10, 8 (80%) had normal neurologic deficit scores (Canadian neurologic score) and 9 (90%) were not disabled as determined by handicap scores (Rankin). The anatomic brain scans (9 MRI, 1 CT) were normal in 5 patients (50%). In 7 patients, transcranial Doppler sonography revealed increased velocities mainly in the anterior circulation with turbulence that was not circumscribed. Single positron emission computed tomography scanning revealed areas of hypoperfusion, mostly multiple, in all of the 7 cases investigated. The cerebral perfusion index was determined in 7 patients, with a good prognosis in 2 patients and a moderate prognosis in 5. Cerebral effects of Takayasu disease are best monitored by a combination of clinical and functional imaging such as TCD and SPECT scanning.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".