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Quality of life prognosis in patients with somatoform disorders with sleep disorders

2024· article· en· W4405861483 on OpenAlexaboutno aff
Вікторія Огоренко, И.И. Макарова, Andrii Shornikov

Bibliographic record

VenueMedicni perspektivi · 2024
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineQuality of life (healthcare)Sleep (system call)PsychiatrySleep qualityPsychologyInsomnia

Abstract

fetched live from OpenAlex

In recent years, the impact of psychotraumatic factors has been increasing, leading to an increased prevalence of psychogenic disorders. Patients with somatoform disorders place a significant burden on the healthcare system. Depending on the diagnostic approach, the prevalence of somatoform disorders ranges from 0.8% to 34%, with nearly half of the patients experiencing sleep disorders. The study aimed to determine the quality of life in patients with somatoform disorders combined with sleep disorders and to identify factors influencing its formation. A total of 120 individuals with somatoform disorders combined with sleep disorders were examined. A comprehensive assessment of the patient’s condition was conducted, including clinical-anamnestic, clinical-psychopathological, and psychodiagnostic examinations, supplemented by the use of psychometric scales (Pittsburgh Sleep Quality Index, Beck Depression Inventory, Insomnia Severity Index, Toronto Alexithymia Scale-20, Integrative Quality of Life Questionnaire, and Spielberger Anxiety Scale). It was found that only 51 out of 120 patients who completed the study had a sufficient level of quality of life. Patients with sufficient quality of life demonstrated lower levels of depression, insomnia severity, and quality of life and its components, but higher levels of personal anxiety. Analyzing categorical indicators, significant differences were also identified in the presence of depression, anxiety, alexithymia, and severe insomnia. As a result of the study, it was established that predictors of quality of life are the severity of sleep disorders and the presence of alexithymia and severe insomnia before the start of treatment. The multiple logistic regression model demonstrated the highest discriminatory ability (AUC 0.872 (95% CI 0.799–0.926)), with predictors of insufficient quality of life including sleep latency, personal anxiety, and depression before the intervention, as well as the presence of severe insomnia after intervention. The combination of these predictors increases the chances of having a low quality of life level by 17.6 times. The study’s results served as the basis for developing individualized therapeutic and corrective strategies in sleep disorders treatment in patients with somatoform disorders and sleep disturbances.

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 score0.017
Threshold uncertainty score0.784

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 head0.009
GPT teacher head0.263
Teacher spread0.253 · 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
Published2024
Admission routes1
Has abstractyes

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