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Record W2968239675 · doi:10.1002/ejp.1472

Premorbid and concurrent predictors of TMD onset and persistence

2019· article· en· W2968239675 on OpenAlexaff
Richard Ohrbach, Gary D. Slade, Eric Bair, Nuvan Rathnayaka, Luda Diatchenko, Joel D. Greenspan, William Maixner, Roger B. Fillingim

Bibliographic record

VenueEuropean Journal of Pain · 2019
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsMcGill University Health Centre
FundersNational Institute of Dental and Craniofacial ResearchNational Institutes of Health
KeywordsPersistence (discontinuity)PsychologyMedicineClinical psychologyGeology

Abstract

fetched live from OpenAlex

BACKGROUND: Multiple risk factors predict temporomandibular disorders (TMD) onset, but temporal changes in risk factors and their contribution to risk of TMD have not been evaluated. The study aims were to (a) describe changes occurring in premorbid TMD risk factors when re-measured at TMD onset and 6 months later, and (b) determine if measures of change improve accuracy in predicting TMD incidence compared to premorbid measures alone. METHODS: In this observational prospective cohort study at four university research clinics, 3,258 community-based, 18- to 44-year-olds without TMD were enrolled. During the 3-year median follow-up, 260 incident cases of first-onset TMD were identified, and 196 TMD-free subjects were selected as matched controls. Six-months later, 147 of 260 incident cases (56.6%) were re-examined revealing 72 (49%) with 'persistent TMD' and 75 (51%) whose condition had resolved ('transient TMD'). Virtually all (126) of the 127 re-examined controls remained without TMD. Questionnaires and clinical measurements evaluated risk factors from clinical, health, psychological and behavioural and neurosensory domains. RESULTS: Most risk factors across all four domains increased with TMD onset, remained elevated in the persistent group and declined in the transient group (i.e., significant ANOVA interactions, p < .05). Accuracy in predicting first-onset TMD, quantified as area under the receiver operating characteristic curve was 0.71 (95% CL 0.68, 0.73) using only premorbid measures of risk factors, which increased to 0.91 (95% CL 0.89, 0.94) after addition of change measures. CONCLUSIONS: TMD pain onset and persistence appear to be determined by enduring characteristics of the person as well as mutually interactive with temporally evolving variables. SIGNIFICANCE: TMD is known to be a complex disorder, in which onset and persistence are associated with disease-related variables in multiple domains, including environmental exposure, clinical, psychological, health status, and pain processing variables. Using a more dynamic approach in order to capture change across time, many aspects of those domains were found to worsen prior to the reporting of pain, with bidirectional influences between domains and pain emergence likely. TMD onset appears to represent the cumulative effect of multiple system dysregulation.

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)0.004
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 score0.029
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.035
GPT teacher head0.313
Teacher spread0.278 · 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

Citations43
Published2019
Admission routes1
Has abstractyes

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