The issue of neuropsychiatric disorders in patients with hypothyroidism
Bibliographic record
Abstract
The aim of the study was assessment of thyroid function in patients with psychiatric and psychological assistance; to study the structure of AR in patients with hypothyroidism, to reveal alexithymical identifying of personality characteristics of patients with hypothyroidism and AP Materials and Methods. 406 patients with AR at the age of 51.3±4.7 years. To verify the useofTSH hypothyroidism rate and to assess depressive disorder — Hamilton Scale and the Montgomery— Asberg; with clinical and psychopathological study: 1) the scale of self-BH alarm Spielberger (Y. L. Hanin), 2) questionnaire G. Shmisheka 3) Toronto alexithymia scale. Results. Hypothyroidism is set at 116 (28.6%) of 406 patients suffering from RA. Among the 374 patients with depressive disorders hypothyroidism was observed in 116: subclinical — in 76 patients (65.5%), symptomatic — in 40 (34.5%). The first group consisted of 258 patients with the presence of depressive disorders and without hypothyroidism; second — 116 patients with the presence of depression and hypothyroidism. TSH in patients suffering AR, without thyroid dysfunction was 5.2 times lower than in patients with the presence of hypothyroidism. Among AP comorbid with hypothyroidism, are predominant depressive with a predominance of mild and moderate forms. Dominating are anxious-depressive, dysphoric, adynamic, sad, depressive disorders. Conclusion. In patients with AR and hypothyroidism predominant types of personality accentuation are dysthymic, anxious, demonstrative and meticulous.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".