Cognitive impairment in patients with hypothyroidism and possibilities of its correction
Bibliographic record
Abstract
Aim. To identify and correct cognitive impairment in patients with hypothyroidism. Materials and methods. The study included 76 patients with primary hypothyroidism. All patients were divided into 2 groups: compensated and decompensated hypothyroidism. In addition to general clinical, and hormonal blood tests all participants in the study underwent ultrasound of the thyroid gland and ECG, the neurophysiological study of cognitive evoked potentials, and testing according to the Montreal cognitive function assessment scale. Results. In the majority of patients with a lack of thyroid hormones, cognitive impairments were detected, which increase with worsening compensation for hypothyroidism according to the results of Montreal Cognitive Assessment Scale testing. The study of evoked potentials in patients with hypothyroidism revealed an increase in latency and a decrease in the amplitude of the P300 indicator, indicating the presence of cognitive deficit. The addition of ethylmethylhydroxypyridine succinate to hormone replacement therapy in patients with hypothyroidism significantly improves cognitive performance more than hormone monotherapy. Conclusions. This study showed the need to identify cognitive impairments in patients with primary hypothyroidism, and their correction with the help of complex therapy increases the cognitive potential and the effectiveness of their treatment.
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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 | 0.001 | 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".