Treatment of hypertension in patients 80 years and older: the lower the better? A meta-analysis of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Results of randomized controlled trials are consistent in showing reduced rates of stroke, heart failure and cardiovascular events in very old patients treated with antihypertensive drugs. However, inconsistencies exist with regard to the effect of these drugs on total mortality. METHODS: We performed a meta-analysis of available data on hypertensive patients 80 years and older by selecting total mortality as the main outcome. Secondary outcomes were coronary events, stroke, cardiovascular events, heart failure and cause-specific mortality. The common relative risk (RR) of active treatment versus placebo or no treatment was assessed using a random-effect model. Linear meta-regression was performed to explore the relationship between intensity of antihypertensive therapy and blood pressure (BP) reduction and the log-transformed value of total mortality odds ratios (ORs). RESULTS: The overall RR for total mortality was 1.06 (95% confidence interval 0.89-1.25), with significant heterogeneity between hypertension in the very elderly trial (HYVET) and the other trials. This heterogeneity was not explained by differences in the follow-up duration between trials. The meta-regression suggested that a reduction in mortality was achieved in trials with the least BP reductions and the lowest intensity of therapy. Antihypertensive therapy significantly reduced (P < 0.001) the risk of stroke (35%), cardiovascular events (27%) and heart failure (50%). Cause-specific mortality was not different between treated and untreated patients. CONCLUSION: Treating hypertension in very old patients reduces stroke and heart failure with no effect on total mortality. The most reasonable strategy is the one associated with significant mortality reduction; thiazides as first-line drugs with a maximum of two drugs.
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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 | 0.024 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.037 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".