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Record W7162071457 · doi:10.82308/41202

The impact of insomnia in the persistence of pain-related temporomandibular disorders: a six-month cohort study

2024· dissertation· en· W7162071457 on OpenAlexaboutno aff
Avinash Sarcar

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsInsomniaCohort studyCohortLogistic regressionPersistence (discontinuity)Depression (economics)

Abstract

fetched live from OpenAlex

Background: Though most pain-related temporomandibular disorders (PTMDs) are mild and self-limiting, a significant frequency of patients experience persistent pain, presenting a great challenge in terms of management and often resulting in substantial disability. Individuals with PTMD commonly exhibit sleep-related comorbidities, with insomnia being a prevalent concern.Objective: The aim of this multicenter cohort study was to assess whether insomnia contributed to the persistence of clinically significant PTMD defined by moderate to severe pain intensity within six months of follow-up.Methods: Participants were enrolled from three clinics in Montreal and one in Ottawa. The diagnosis of PTMD was achieved through the utilization of either the Research Diagnostic Criteria (RDC/TMD) or the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD). Insomnia at baseline visit was assessed using the Insomnia Severity Index (ISI). Persistence of clinically significant PTMD defined by moderate to severe pain intensity was measured using Characteristic Pain Intensity (CPI) scores within six months of follow-up period. Crude and multivariable logistic regression analyses were used to estimate the results.Results: Out of the 456 PTMD participants, 447 answered the baseline questionnaires, 377 (84.3%) and 370 (82.8%) completed the three-month and six-month follow-up periods, respectively. Insomnia increased the likelihood of persistent clinically significant PTMD (CPI ≥ 50) in both the crude (ORc= 1.63, 95%CI: 1.24—2.15, P= 0.0005) and multivariable (ORadj= 1.60, 95%CI: 1.10 - 2.31, P= 0.01) analyses, within the six-month follow-up among the participants. Additional analysis showed that mild insomnia (ORadj= 1.42, 95%CI: 0.94—2.12, P= 0.09), moderate insomnia (ORadj= 1.95, 95%CI: 1.23—3.08, P= 0.004) and severe insomnia (ORadj= 2.43, 95%CI: 1.37—4.31, P= 0.002) contributed to the persistence of clinically significant PTMD in a dose-response manner.Conclusion: These results indicate that insomnia increases the likelihood of persistent clinically significant PTMD within six months of follow-up period, and therefore should be considered as an important factor when evaluating and developing treatment plans for patients with PTMD

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.380
Teacher spread0.359 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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