The initial experience of turkish neurosurgical stroke centers: a national study
Bibliographic record
Abstract
AIM: To evaluate the clinical and radiological outcomes of newly established Turkish neurosurgical stroke centers , and to assess their competency in managing acute ischemic stroke from June 2023 to June 2024. MATERIAL AND METHODS: We retrospectively analyzed data from 69 patients (mean age = 69.06 ± 13.48 years) from three stroke centers in Türkiye by reviewing hospital records and patient interviews, focusing on demographic variables, comorbidities, treatment methodologies, outcomes (using the Modified Rankin Scale (mRS)), stroke severity (using the National Institutes of Health Stroke Scale [NIHSS]), Alberta Stroke Program Early CT (ASPECT) scores, reperfusion status (using the modified Thrombolysis in Cerebral Ischemia (mTICI) score), complications, blood glucose levels, and creatinine levels. RESULTS: Of 392 acute ischemic stroke patients, 280 (71.4%) had no identifiable occlusion, 43 (11%) were out of the MT time window, and 69 (17.6%) underwent MT, with 57 (14.5%) having LVO and 12 (3%) MVO. Final reperfusion (mTICI ?2b) was achieved in 78.3% of MT patients, and 29% achieved favorable outcomes (mRS ?2) at three months. Younger age, lower baseline NIHSS, and higher ASPECT scores correlated with better outcomes, while elevated blood glucose ( > 127.50 mg/dL) and creatinine ( > 0.80 mg/dL) were linked to worse mRS scores. Complications occurred in 21.7%, including symptomatic intracranial hemorrhage in six patients. CONCLUSION: While Turkish neurosurgical stroke centers have made significant strides in managing acute ischemic stroke, challenges remain in optimizing patient outcomes. This initial experience underscores the need for further research, continued training, and educational standardization for neurosurgeons in endovascular techniques to improve patient care.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".