Features of the impact of combat-related traumatic brain injury in the long-term period, depending on the severity and course of the injury on the cognitive sphere of patients
Bibliographic record
Abstract
Background. The number of consequences of mine-explosive injuries, multiple gunshot and shrapnel wounds has increased significantly in the world of current events related to the conduct of full-scale military operations on the territory of Ukraine. In particular, cases of combat traumatic brain injury (TBI) have increased, which is becoming one of the most important problems. Purpose The purpose of the research was to study the characteristics of cognitive functions in patients with the consequences of a combat craniocerebral injury (bTBI) depending on the severity and catamnesis of the received injury. Materials and Methods. 350 patients Cognitive functions of 350 patients who suffered a combat traumatic brain injury (cTBI),was carried out using the Montreal scale of cognitive deficits (MoCA test). The assessment of neurological status was carried out by a routine method and NOS-TBI (Neurological Outcome Scale for Traumatic Brain Injury), the level of anxiety and depression was determined using the HADS scale. In addition, the state of cognitive functions was evaluated using a number of modern neuropsychological tests: the method of learning 10 words, which allowed to investigate memory processes (memorization, preservation and reproduction of information). Schulte’s tables were used to assess the pace of sensorimotor reactions, mental capacity, and the volume of active attention. Results. The results of the MoCA scale in patients with consequences of combat TBI of varying degrees of severity corresponded to mild cognitive decline: Mild cTBI 22.21 ± 0.29 points, cTBI (ST) 21.36 ± 0.33 points, Severe cTBI 21.32 ± 0.28 points. There was no statistically significant difference between MoCA values at different severity of combat TBI. A longer injury history had a negative effect on cognitive function in patients with Mild effects combat TBI and Severe combat TBI. Conclusions. As a result of the investigation, officials who contributed to the formation of cognitive deficits were identified: anxiety disorder (with mild effects combat TBI and severe combat TBI), anxiety-depressive state (with mild effects combat TBI with a follow-up period of up to 3 years and combat TBI (moderate) with follow-up). period more than 5 years), age (combat TBI (moderate) up to 7 years), neurological deficit (severe combat TBI, follow-up period in case of injury more than 5 years).
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".