[OP.7A.04] ANTIHYPERTENSIVE DRUGS AND THE RISK OF FEMUR FRACTURE IN HYPERTENSIVE PATIENTS IN SWEDISH PRIMARY HEALTH CARE. RESULTS FROM THE SWEDISH PRIMARY CARE CARDIOVASCULAR DATABASE (SPCCD)
Bibliographic record
Abstract
Objective: Hypertension and osteoporosis are major public health problems that often coexist in the aging population. This study aimed to examine the associations between exposure to different antihypertensive drug classes and the risk of femur fracture in hypertensive men and women in Swedish primary health care. Design and method: This retrospective cohort study includes 63591 individuals, 50 years and older, diagnosed with hypertension during 2001–2008 in the Swedish Primary Care Cardiovascular Database (SPCCD). All patients were followed 1 Jan 2006 (or the date of their first diagnosis of hypertension if that date came later) until they had their first femur fracture, died, or reached the end of the database on 31 December 2012, whichever came first. Cox proportional hazards models were used to calculate the relative risk of femur fracture across types of antihypertensive medications. Analyses were adjusted for age, sex, comorbidity, medications and socioeconomic factors. Results: A total of 2737 femur fractures were observed during follow-up. Current use of thiazides was associated with a reduced risk of femur fracture (HR 0.83; 95% CI 0.74–0.93), as well as use of fixed drug combinations containing a thiazide (ACE-inhibitors + thiazide or angiotensin-receptor blocker + thiazide) (HR 0.67; 95% CI 0.56–0.80). Current use of loop-diuretics was associated with an increased risk of femur fracture (HR 1.23; 95% CI 1.09–1.38). No significant associations were found between femur fracture and current exposure to beta-blockers, alfa-blockers, aldosterone-receptor blockers, ACE-inhibitors, angiotensin-receptor blockers or calcium-channel blockers. Conclusions: In this large observational study of hypertensive patients, we could identify a protective effect on femur fracture risk in users of thiazide diuretics or combination pills containing a thiazide, whereas use of loop-diuretics was associated with an increased risk. Exposure to any other antihypertensive agent was associated with neither a decrease nor increase in fracture risk. In conclusion, the risk of femur fracture appear to differ across users of different antihypertensive agents, a knowledge that could have practical applications in primary health care to prevent adverse outcomes from both hypertension and osteoporosis in the aging population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".