- Design
- Bayesian random-effects meta-analysis of 15 randomised trials
- Population
- Adults having major non-cardiac surgery
- Primary outcome
- All-cause mortality
- Effect
- OR 1.00 (95% CI 0.83 to 1.21); AKI OR 0.87 (0.73 to 1.03); MINS OR 1.04 (0.93 to 1.15)
A Bayesian meta-analysis in Anesthesiology pooled 15 randomised trials comparing protocolised intraoperative arterial pressure targets — often higher or individualised — with usual care or lower targets during major non-cardiac surgery.
Mortality was unchanged, centred exactly on an odds ratio of 1.00. Myocardial injury after non-cardiac surgery showed no effect. Acute kidney injury had the most favourable estimate, about 12–13% lower odds, but the interval included no benefit, heterogeneity was moderate, and removing single trials changed the picture.
This does not mean blood pressure does not matter; avoiding profound or prolonged hypotension remains good practice and the comparator was contemporary usual care, which already avoids it. What it suggests is that adding a formal protocol to target a specific higher pressure has not shown further benefit. Any renal benefit may depend on the wider haemodynamic approach, including fluids and cardiac output, rather than pressure alone.
- Keep avoiding profound or prolonged intraoperative hypotension; that is the comparator these protocols were measured against.
- Do not expect a protocolised higher blood pressure target alone to lower mortality or myocardial injury.
- Consider tighter pressure management in patients at high risk of kidney injury, recognising the evidence is uncertain.
- Look at the whole haemodynamic picture — volume, cardiac output, depth of anaesthesia — rather than a single number.
Why it matters
It tempers enthusiasm for rigid pressure protocols while leaving the case against prolonged hypotension intact.
Don't overread it
The acute kidney injury signal is fragile and sensitive to single trials; it is not evidence to adopt a protocol for renal protection.
The statistics, in plain English
A Bayesian credible interval for mortality of 0.73 to 1.38 means, given the data, the true effect could plausibly be anywhere from a 27% reduction to a 38% increase. The prediction interval (0.56 to 1.78) shows what a new trial might find, and it is wider still.
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