Prevalence of hypertension and correlation with mental health in women with burning mouth syndrome: A case-control study
Bibliographic record
Abstract
Background The relationship between hypertension (HTN) and chronic pain is still a matter of debate, and its prevalence in patients with burning mouth syndrome (BMS) has never been evaluated. This study aimed to assess the prevalence of HTN in women with BMS and to evaluate its relationship with potential predictors such as risk factors for cardiovascular diseases, pain, and mental health status analyzing differences with healthy women. Methods In total, 250 women with BMS (WBMS) were prospectively recruited and compared with an equal number of healthy women (HW) matched for age. Education, body mass index, smoke and alcohol consumption, intensity and quality of pain, and psychological profile were further investigated to identify the potential predictors of HTN. Specifically, pain assessment [the Numeric Rating Scale (NRS) and Short-Form McGill Pain Questionnaire (SF-MPQ)] and psychological assessment [Hamilton Rating Scale for Depression and Anxiety (HAM-D and HAM-A), Pittsburgh Sleep Quality Index (PSQI), and Epworth Sleepiness Scale (ESS)] was carried out for the participants. Results HTN was found in 128 (51.2%) WBMS and 76 (30.4%) HW ( p < 0.001 ** ). The scores of the NRS, SF-MPQ, HAM-D, HAM-A, and PSQI were statistically significantly higher in the WBMS than in the HW ( p < 0.001 ** ). A strongly linear correlation between HTN and employment status, systemic diseases, and education level ( p < 0.001 ** ) was found in WBMS, while a strong correlation between HTN and employment status, hypercholesterolemia, systemic diseases, and drug consumption was found in HW ( p < 0.001 ** ). No statistically significant correlation was found between HTN and pain, anxiety, depression, and sleep disturbances. Conclusion These results suggest that WBMS showed a higher prevalence of HTN compared with controls. Unemployed WBMS with lower education and other systemic comorbidities are at an increased risk of developing HTN. HTN is associated with alteration in the vascular structure and function of the brain, and these processes accelerate brain aging, which contributes to a reduction in intracortical connectivity, thus affecting the modulatory system of control of pain in patients with BMS, independently of their mental health assessment. Predictors that may underlie this association remain unclear, taking into account the differences found in HW, and should be further elucidated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".