Determine the Frequency of Blood Pressure Control among Hypertensive Patients and its Relationship with Diabetes Mellitus
Bibliographic record
Abstract
Background: Hypertension plays an important role in the development of secondary comorbidity in the patients. It is also noted that it also plays a role in the onset of diabetes among the patients. Objective: To evaluate the blood pressure control among hypertensive patients and its relationship with diabetes mellitus. Study Design: Cross-sectional study Place and Duration of Study: Department of Medicine, Social Security Teaching Hospital, Ferozpur Road Lahore from 1stMarch 2021 to 31stAugust 2021. Methodology: Two hundred and twenty seven patients with hypertension between 16-60 years of age of either gender were enrolled. Two readings of blood pressure of the patient was measured in supine position from brachial artery 20 minutes apart by the researcher himself and control of blood pressure was noted. Patients were assessed for having diabetes mellitus. Results: The mean age was 38.19±8.93 years and 117 (51%) were males and 110 (49%) were females. Forty four (19.4%) cases were having good blood pressure control. Eighty (35%) cases were having the diabetes mellitus. There were 20 (25%) cases who have diabetes and blood pressure control while 24 (16.3%) cases did not have diabetes but have blood pressure control with non-significant difference. Conclusion: Majority of patients had poor blood pressure control and there was a statistically non-significant relationship between diabetes mellitus and blood pressure control among hypertensive. Keywords: Blood pressure, Diabetes mellitus, Hypertension, Smoking
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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 | 0.002 |
| 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) | 0.003 | 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".