Cognitive impairment and neuropsychiatric manifestations of neurobrucellosis
Bibliographic record
Abstract
AIM: This study aimed to reveal insight into the unclear areas of the diagnosis in neurobrucellosis and to decide the neuropsychiatric manifestations and cognitive impairment among patients with brucellosis. METHODS: 82 patients with serologically confirmed brucellosis were included and divided into two groups according to the neuropsychiatric manifestations, the first group included 18 patients with neurobrucellosis and the second group included 64 patients with non-neurobrucellosis. Both groups were compared regarding the general symptoms and neurological symptoms and signs. Cognitive impairment in both groups was assessed by Montreal-Cognitive Assessment (MoCA), Wechsler Memory Scale-Revised (WMS-R), and forward and backward digital test. Also, depression and anxiety were assessed by Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI). RESULTS: 18 (21.9%) patients were diagnosed as neurobrucellosis and 64 (78.1%) patients were diagnosed as non-neurobrucellosis. The mean age of the total patients was 34.91 ± 14.74, consisted of 45 males and 37. Most of the patients were living in rural areas 60 patients (74.4%). The most significantly higher neurological symptoms in neurobrucellosis patients were confusion and headache (P = 0.008 and P = 0.01, respectively). While the most significant higher neurological signs were loss of orientation (P = 0.009), muscle weakness (P = 0.04), neck rigidity (P < 0.05), pyramidal signs, and lost deep reflexes (P < 0.05). The neurobrucellosis patients had significantly impaired cognition in comparison with nonneurobrucellosis patients and more psychiatric signs like behavioral changes, anxiety, and depression (P < 0.001, P < 0.001, and P = 0.01, respectively). CONCLUSIONS: Patients with neuropsychiatric manifestations and cognitive impairment should be considered for neurobrucellosis and should receive proper therapy.
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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 | 0.001 | 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) | 0.002 | 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".