Antihypertensive Medication and Fracture Risk in Older Veterans Health Administration Nursing Home Residents

Abstract: Importance: Limited evidence exists on the association between initiation of antihypertensive medication and risk of fractures in older long-term nursing home residents. Objective: To assess the association between antihypertensive medication initiation and risk of fracture. Design, Setting, and Participants: This was a retrospective cohort study using target trial emulation for data derived from 29 648 older long-term care nursing home residents in the Veterans Health Administration (VA) from January 1, 2006, to October 31, 2019. Data were analysed from December 1, 2021, to November 11, 2023. Exposure: Episodes of antihypertensive medication initiation were identified, and eligible initiation episodes were matched with comparable controls who did not initiate therapy. Main Outcome and Measures: The primary outcome was nontraumatic fracture of the humerus, hip, pelvis, radius, or ulna within 30 days of antihypertensive medication initiation. Results were computed among subgroups of residents with dementia, across systolic and diastolic blood pressure thresholds of 140 and 80 mm Hg, respectively, and with use of prior antihypertensive therapies. Analyses were adjusted for more than 50 baseline covariates using 1:4 propensity score matching. Results: Data from 29 648 individuals were included in this study (mean [SD] age, 78.0 [8.4] years; 28 952 [97.7%] male). In the propensity score-matched cohort of 64 710 residents (mean [SD] age, 77.9 [8.5] years), the incidence rate of fractures per 100 person-years in residents initiating antihypertensive medication was 5.4 compared with 2.2 in the control arm. This finding corresponded to an adjusted hazard ratio (HR) of 2.42 (95% CI, 1.43-4.08) and an adjusted excess risk per 100 person-years of 3.12 (95% CI, 0.95-6.78). Antihypertensive medication initiation was also associated with higher risk of severe falls requiring hospitalizations or emergency department visits (HR, 1.80 [95% CI, 1.53-2.13]) and syncope (HR, 1.69 [95% CI, 1.30-2.19]). The magnitude of fracture risk was numerically higher among subgroups of residents with dementia (HR, 3.28 [95% CI, 1.76-6.10]), systolic blood pressure of 140 mm Hg or higher (HR, 3.12 [95% CI, 1.71-5.69]), diastolic blood pressure of 80 mm Hg or higher (HR, 4.41 [95% CI, 1.67-11.68]), and no recent antihypertensive medication use (HR, 4.77 [95% CI, 1.49-15.32]). Conclusion and Relevance: Findings indicated that initiation of antihypertensive medication was associated with elevated risks of fractures and falls. These risks were numerically higher among residents with dementia, higher baseline blood pressures values, and no recent antihypertensive medication use. Caution and additional monitoring are advised when initiating antihypertensive medication in this vulnerable population.

Read the full article
Report a problem with this article

Related articles

  • More for Researchers

    Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data

    Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.