MétaCan
Menu
Back to cohort
Record W2895571837 · doi:10.3390/jcm7100327

Evaluation of Intensity of Sleep Bruxism in Arterial Hypertension

2018· article· en· W2895571837 on OpenAlexaff
Helena Martynowicz, P. Dymczyk, Marzena Dominiak, Klaudia Kazubowska, Robert Skomro, Rafał Poręba, Paweł Gać, Anna Wojakowska, Grzegorz Mazur, Mieszko Więckiewicz

Bibliographic record

VenueJournal of Clinical Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineCardiorespiratory fitnessBody mass indexMasticatory forceInternal medicineOxygen saturationEtiologyCardiologyRapid eye movement sleepBlood pressureAnesthesiaElectroencephalographyDentistry

Abstract

fetched live from OpenAlex

Sleep bruxism (SB) is a masticatory muscle activity during sleep that is characterized as rhythmic (phasic) or non-rhythmic (tonic). The recent hypothesis on the etiology of SB supports the role of the central and autonomic nervous systems. Therefore, in this study, we aimed to assess the intensity of SB in patients with arterial hypertension. A total of 70 adults participated in this study: 35 patients with hypertension (study group) and 35 normotensive subjects (control group). Data were recorded using home portable cardiorespiratory polygraphy. The bruxism episode index (BEI) in the study group was found to be significantly higher compared to the control group (3.4 ± 3.25 vs. 2.35 ± 2.29, p = 0.04). Hypertension, higher body mass index (BMI), lower values of mean oxygen saturation (SpO2), and a higher percentage of SpO2 < 90% constituted independent risk factors for increased BEI. These results suggest the need for special oral care in hypertensive patients, patients with higher BMI, lower values of SpO2 and a higher percentage of SpO2 < 90%.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.224
GPT teacher head0.495
Teacher spread0.270 · 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".

Quick stats

Citations41
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical MedicineSame topicObstructive Sleep Apnea ResearchFrench-language works237,207