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Prognostic and predictive analysis of effectiveness of pharmacological and non-pharmaceutical treatment approaches for chronic insomnia

2021· article· en· W4206581631 on OpenAlexaboutno aff
Polina Pchelina, М Г Полуэктов

Bibliographic record

VenueConsilium Medicum · 2021
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsInsomniaEpworth Sleepiness ScaleBeck Depression InventoryAnxietyMedicineClinical psychologyInternal medicinePhysical therapyUnivariate analysisPsychologyPsychiatryMultivariate analysisPolysomnography

Abstract

fetched live from OpenAlex

Background. Limited access to cognitive behavioral therapy for insomnia (CBT-I) which is the most effective and safe treatment approach for chronic insomnia leads to the elaboration of shortened and interned delivered CBT-I methods. Investigation of effectiveness predictors of the new methods is important for their better result.
 Aim. Investigation of effectiveness predictors for pharmacotherapy and CBT-I based brief behavioral therapy for insomnia (BBT-I).
 Materials and methods. The data for the analysis were acquired from a randomized study of 42 participants with chronic insomnia who received either zopiclone 7.5 mg or BBT-I for 2 weeks. The difference of the insomnia severity index from pre- to post-treatment was the main outcome measure. Potential predictors included demographic and medical history data, objective sleep characteristics, baseline scores of Beck depression inventory (BDI), Spielberger anxiety scale, Toronto alexithymia scale, sleep hygiene index, dysfunctional beliefs and attitudes about sleep scale, Epworth sleepiness scale. Univariate linear regression analysis was used for prognostic analysis. To identify predictors of treatment outcome after the treatment course and after the 2 weeks follow-up we used multiple linear regression models with interaction.
 Results. In the prognostic analysis higher amount of awakenings during the night and a higher proportion of the 1 stage NREM sleep measured objectively correlated with better outcome E=0.2202 (p=0.05) and E=0.55 (p=0.039) respectively. Older age and higher baseline BDI score significantly worsened the outcome: E=0.233 (p=0.047) and E=0.2 (р=1.55e-06) respectively. Clinical predictors of the BBT-I effectiveness were an absence of the sleep onset problems and absence of GABA hypnotics use in medical history and the higher baseline daytime sleepiness.
 Conclusion. Neurophysiological (frequency of awakenings, percentage of the sleep stage N1) and clinical (severity of depression, age, daytime sleepiness) predictors of the effectiveness of BBT-I were revealed. This findings will help to select the patients who should undergo a shortened course of CBT-I.

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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 score0.105
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.042
GPT teacher head0.348
Teacher spread0.306 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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