[Assessing efficacy of carotid endarterectomy by means of intraoperative flowmetry].
Bibliographic record
Abstract
AIM: The study was aimed at determining volumetric blood flow velocity (VBFV) through the internal carotid artery (ICA) and assessing functional outcomes of treatment of patients, taking into consideration the dynamics of VBFV before and after the operation. PATIENTS AND METHODS: The study comprised a total of 53 patients subjected to examination of VBFV through the ICA before and after carotid endarterectomy (CEA) assessed by means of flowmetry. Neurological deficit was evaluated by means of the NIHS Scale (the M NIHSS prior to operation equalling 2.49), the degree of disability and functional independence of the patient after endured stroke was assessed by the modified Rankin Scale (the M mRS before operation amounting to 1.23) and the Rivermead Mobility Index, the severity of cognitive dysfunctions was determined by the Mini-Mental State Examination (the M MMSE before surgery equalling 24.85) and the Montreal Cognitive Assessment scale (the M MoCA before surgery scoring 23.3). RESULTS: At the first stage of examination we determined that the VBFV after the operation increased in all patients, but the highest values of the increment were observed in groups of patients with ICA stenoses of 80-89% and 90-99%. During the second stage, it was determined that with a higher value of the VBFV after carotid endarterectomy regression of neurological deficit occurred faster (the postoperative M NIHSS scoring 2.09, with the M mRS of 1.00), the patients demonstrated higher results while undergoing the tests for intellectual ability (the postoperative MMSE and MoCA equalling 25.4 and 23.91, respectively) compared with the patients showing low values of the increment of the VBFV after the operation. CONCLUSION: Intraoperative flowmetry is a simple and efficient method of evaluating the VBFV through the ICA, an increase in volumetric blood flow (VBF) contributes to restoration of normal perfusion of the brain and creates prerequisites for more complete and faster restoration of the lost functions after ischaemic stroke (IS) and chronic cerebral ischaemia.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".