Prediction of the quality of mental life in patients with aseptic necrosis of the femoral head with non-psychotic mental disorders
Bibliographic record
Abstract
The article presents the results of a study of the quality of mental life in patients with avascular necrosis of the femoral head and non-psychotic mental disorders. The aim of the work was to study the mental component of the quality of life in patients with avascular necrosis of the femoral head and non-psychotic mental disorders and to determine the predictors that influence its formation. A study of 137 people was conducted, of which 96 reached the end of the study. The Short Form Health Survey (SF-12) quality of life questionnaire was used to assess the mental component of quality of life. The SCL-90-R scale, Beck Depression Inventory (BDI-II), Beck Anxiety Inventory (BAI) and Taylor Manifest Anxiety Scale (TMAS), Beck Hopelessness Scale (BHS), and Toronto Alexithymia Scale (TAS-20) were also used. The determined psychopathological and psychometric factors that influenced the quality of life of patients with avascular necrosis of the femoral head and non-psychotic mental disorders made it possible to develop a logistic model for predicting the achievement of an average level of the mental component of the quality of life in the postoperative period. The mental component of qua lity of life at the preoperative stage, the general index of severity of psychopathological symptoms according to the SCL-90-R method, the presence of anxiety-depressive or apathy-abulic syndromes and alexithymia according to the TAS-20 method acted as predictors. The resulting lo- gistic model has an outstanding predictive ability: AUC = 0.849 (95 % CI 0.761—0.914), p < 0.0001, sensitivity — 77.78 % (CI 60.8—89.9) and specificity — 78.33 % (CI 65.8—87.9).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".