Prevalence of Hypertension in Patient with General Anxiety Disorder
Bibliographic record
Abstract
Background: People with hypertension are more likely to suffer from mental health illnesses such as depression and/or anxiety. Anxiety influences medication adherence in hypertensive patients and limits their treatment options. Worsens the prognosis and raises the death rate. Objective: To determine the prevalence of anxiety and its relationship to hypertension in hypertensive individuals. Materials and Methods: The study was a hospital-based descriptive cross-sectional study that took place at Sheba Susrusha Hospital in Dhaka from February 2022 to February 2023. All study participants provided written informed consent. In total, 165 patients with hypertension were included in the study. The patients with general anxiety disorders were selected by DSM 5 criteria. We included all patients, regardless of medication. The patient's demographic information, clinical presentations, and questionnaire were all completed. Results: The majority of patients (61.2%) were female, 45 (27.3%) were prehypertensive, 69 (41.8%) were stage I, 18 (10.9%) were stage II, and 33 (20.0%) were normal. There were 78 (47.3%) individuals with general anxiety disorders, 49 (56.32%) with hypertension stages I and II. The difference between the four groups was statistically significant (p <0.05). Conclusion: There is a strong relation between generalized anxiety disorder and hypertension. Anxiety in patients with hypertension at younger ages has to be assessed because it may contribute to hypertension.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".