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Prediction of the quality of mental life in patients with aseptic necrosis of the femoral head with non-psychotic mental disorders

2023· article· en· W4320719139 on OpenAlexaboutno aff
Andrii Shornikov, Вікторія Огоренко

Bibliographic record

VenueUkrains kyi Visnyk Psykhonevrolohii · 2023
Typearticle
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsBeck Anxiety InventoryBeck Depression InventoryAnxietyToronto Alexithymia ScaleMental healthPsychopathologyPsychologyQuality of life (healthcare)Depression (economics)AlexithymiaPsychiatryClinical psychologyMedicinePsychotherapist

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.283
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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