THE COMPREHENSIVE EVALUATION OF PATIENTS’ CONDITION IN RECOVERY AND RESIDUAL PERIODS OF ANEURYSMAL SUBARACHNOID HEMORRHAGE
Bibliographic record
Abstract
OBJECTIVE: The aim: is to evaluate peculiarities of clinical and neurological characteristics, quality of life, brain morphometry changes and metabolic deviations of patients, who suffered from aneurysmal subarachnoid hemorrhage. PATIENTS AND METHODS: Materials and methods: In the period of 2016-2019 we examined 114 patients, who signed the informed consent, taking into account their age, clinical and anatomical form of hemorrhage, disease duration, Hunt-Hess severity grade, complications of acute period. Such parameters were evaluated, as clinical and neurological characteristics, the degree of the Barthel index and the modified Rankin scale, cognitive functioning (MoCA), psycho-emotional sphere and quality of life (HADS, SF-36), morphometric parameters based on brain computed tomography measurements, explored the indicators of apoptosis, mitochondrial dysfunction, intracellular oxidative stress. RESULTS: Results: Сephalgia (90,35 %), pyramidal syndrome (53,50 %), sensibility deficit (36,84 %) were leading among the all neurological syndromes. Slight dependence and disability grade was found during assessment of the Barthel index and the modified Rankin scale. In 85,96 % of patiens we revealed cognitive impairment of different severity grades. The anxiety was manifested in 65,79 %, depression - in 64,91 % of patients. Due to the morphometry data, the process of cerebral atrophy was detected (central - in 26,31 % of patients, cortical - in 16,67% and mixed - in 28,07 %). AnV+ and PI+ - cells level exceeded normal values in 2,88 and 1,96 times while the level of JC-1+ and ROS+-cells - in 2,17 and 2,82 times (p<0,01). CONCLUSION: Conclusions: Having studied clinical and neurological, neuropsychological, morphometric and metabolic factors, we found their pathogenetic role in the course of late recovery and residual periods of aneurysmal subarachnoid hemorrhage, that would help us to improve the diagnostic tactics and reveal the predictors of unfavorable outcome.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".