Association Between Chronic or Acute Use of Antihypertensive Class of Medications and Falls in Older Adults. A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Evaluating effect of acute or chronic use of antihypertensives on risk of falls in older adults. METHODS: Data sources: Systematic search of primary research articles in CINAHL, Cochrane, EBM, EMBASE, and MEDLINE databases from January 1 2007 to June 1 2017. Study selection: Research studies of cohort, case-control, case-crossover, cross-sectional, or randomized controlled trial (RCT) design examining association between antihypertensives and falls in people older than 60 years were evaluated. Data synthesis: Twenty-nine studies (N = 1,234,667 participants) were included. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). PRISMA and MOOSE guidelines were used for abstracting data and random-effects inverse-variance meta-analysis was conducted on 26 articles examining chronic antihypertensive use, with odds ratios (ORs) and hazards ratios (HRs) analyzed separately. Time-risk analysis was performed on 5 articles examining acute use of antihypertensives. Outcomes: Pooled ORs and HRs were calculated to determine the association between chronic antihypertensive use and falls. For time-risk analysis, OR was plotted with respect to number of days since antihypertensive commencement, change, or dose increase. RESULTS: There was no significant association between risk of falling and chronic antihypertensive medication use (OR = 0.97, 95% confidence interval [CI] 0.93-1.01, I2 = 64.1%, P = 0.000; and HR = 0.96, 95% CI 0.92-1.00, I2 = 0.0%, P = 0.706). The time-risk analysis demonstrated a significantly elevated risk of falling 0-24 hours after antihypertensive initiation, change, or dose increase. When diuretics were used, the risk remained significantly elevated till day 21. CONCLUSIONS: There is no significant association between chronic use of antihypertensives and falls in older adults. Risk of falls is highest on day zero for all antihypertensive medications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.001 |
| 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 | 0.001 |
| 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".