Antihypertensive agents acting on the renin–angiotensin system and the risk of sepsis
Bibliographic record
Abstract
AIMS: In response to safety concerns from two large randomized controlled trials, we investigated whether the use of telmisartan, an angiotensin receptor blocker (ARB), ARBs as a class and angiotensin-converting enzyme inhibitors (ACEIs) increase the risk of sepsis, sepsis-associated mortality and renal failure in hypertensive patients. METHODS: We performed a nested case-control study from a retrospective cohort of adults with hypertension from the UK General Practice Research Database diagnosed between 1 January 2000 and 30 June 2009. All subjects hospitalized with sepsis during follow-up were matched for age, sex, practice and duration of follow-up with 10 control subjects. Exposure was defined as current use of antihypertensive drugs. RESULTS: From the cohort of 550 436 hypertensive patients, 1965 were hospitalized with sepsis during follow-up (rate 6.9 per 10 000 per year), of whom 824 died and 346 developed acute renal failure within 30 days. Compared with use of β-blockers, calcium-channel blockers or diuretics, use of ARBs, including telmisartan, was not associated with an elevated risk of sepsis (relative risk 1.09; 95% confidence interval 0.83-1.43); but use ACEIs was (relative risk 1.65; 95% confidence interval 1.42-1.93). Users of ARBs, β-blockers, calcium-channel blockers or diuretics, but not users of ACEIs, had lower rates of hospitalization for sepsis compared with untreated hypertensive patients. Findings were similar for sepsis-related 30 day mortality and renal failure. CONCLUSIONS: Hypertensive patients treated with ARBs, including telmisartan, do not appear to be at increased risk of sepsis or sepsis-related 30 day mortality or renal failure. On the contrary, users of ACEIs may have an increased risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".