Assessment of the prevalence and clinical features of cognitive disorders among patients with Lyme disease depending on the stage and clinical manifestation of the disease
Bibliographic record
Abstract
Annotation. Lyme disease is the most frequent disease among naturally occurring zoonoses. The first cases of tick-borne borreliosis in Ukraine were confirmed in 1994. The disease has been officially registered since 2000. Despite the high prevalence of cognitive and neuropsychological disorders in Lyme borreliosis, data on their frequency and degree of severity are contradictory. The examination of cognitive status is still not included in the standard clinical examination of this category of patients. The purpose of the study is to assess the prevalence and severity of cognitive disorders among patients with Lyme disease depending on the clinical features of the disease. We conducted a case-control study. Thirty-eight (29 women, 9 men) patients aged from 23 to 77 years (average - 48.58±16.81 years) were examined. For each patient, 38 controls matched by gender, age (±5 years), nationality, and place of birth were selected. Mini-Mental Scale Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were used to assess cognitive function. All obtained data were processed by methods of variational statistics using the statistical package "SPSS 20" (SPSS Inc.) version 21.0.0 for Windows using the Shapiro-Wilk test. Data are presented as M±σ or Me [Q25-Q75]. Depending on the needs, Student's t-test, Mann-Whitney test were used, χ2 (Pearson) and odds ratio (OR), 95% confidence interval (CI), linear correlation coefficient (r) were determined. Lyme disease was associated with a more than threefold increase in the risk of developing cognitive impairment (OR 3.59; 95% CI [1.27-10.14]). Seven patients (18.4%) suffered from mild, 15 (39.5%) had moderate cognitive impairment, and 9 (23.7%) patients were diagnosed with mild dementia. Cognitive disorders were significantly more common in patients with neuroborreliosis (OR 12.44; 95% CI [1.84-84.26]) and the late stage of the disease (OR 6.11; 95% CI [1.1-37.49]). The severity of cognitive impairment according to the MMSE was negatively correlated with the age of onset (r = -0.631, p<0.001) and the duration of the disease (r = -0.406, p=0.011). Prospects for further research are to study and analyze the correlations of cognitive and psychoemotional disorders in patients with various manifestations of Lyme disease.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".