ASPECT SCORE AND TRANSCRANIAL DOPPLER FLOW PARAMETERS IN MIDDLE CEREBRAL ARTERY IN ACUTE BRAIN ISCHAEMIA.
Bibliographic record
Abstract
Background and AimsTranscranial Doppler (TCD) flow parameters assessed with Thrombolysis in Brain Ischaemia (TIBI) score may reflect early brain hypoperfusion. Alberta Stroke Programme early CT score (ASPECT) may also reveal acute brain ischaemia. However, little is known about the relationship between the above parameters. Thus, our goal was to assess the relationship between TCD flow parameters in middle cerebral artery (MCA) and ASPECT score in patients with stroke in MCA territory.MethodMaterials and methods: 80 patients with acute MCA ischemia (66 with stroke, mean age 68 yrs and 14 with TIA mean age 68 yrs) were examined. MCA flow was assessed with TCD and scored with TIBI classification on admission and on the 7th day. ASPECT score was established for the CT performed on admission and after 24 h of follow up (with CT or DW-MRI)ResultsResults: A significant correlation was found between ASPECT and the TIBI scores assessed on admission for both, all patients and only those with stroke (r=0,23; p=0,04 and r=0,28; p=0,02; respectively). In stroke patients, there were also associations between ASPECT score in the follow-up imaging and TIBI score assessed on admission and on the 7th day stroke (r=0,25; p=0,04 and r=0,45; p<0,01; respectively). ConclusionConclusions: ASPECT score is related to TCD flow parameters in the middle cerebral artery stroke, both in hyper- and subacute phase of stroke.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".