Closed-loop IV drug delivery system
Closed-loop drug delivery systems are autonomous computers able to administer medication in response to changes in physiological parameters (controlled variables). While limited evidence suggested that closed-loop systems can perform better than manual drug administration in certain settings, this technology remains a research tool with an uncertain risk/benefit profile. Our aim was comparing the performance of closed-loop systems with manual intravenous drug administration in adults. We searched MEDLINE, CENTRAL, and Embase from inception until November 2022, without restriction to language. We assessed for inclusion randomised controlled trials comparing closed-loop and manual administration of intravenous drugs in adults, intraoperatively or in the Intensive Care Unit. We identified 32 studies on closed-loop administration of propofol, noradrenaline, phenylephrine, insulin, neuromuscular blockers, and vasodilators. Most studies were at moderate or high risk of bias. The results showed that closed-loop systems reduced the duration of blood pressure outside prespecified targets during noradrenaline (MD 14.9%, 95% CI 9.6-20.2%, I2 = 66.6%) and vasodilators administration (MD 7.4%, 95% CI 5.2-9.7%, I2 = 62.3%). Closed-loop systems also decreased the duration of recovery after propofol (MD 1.3 min, 95% CI 0.4-2.1 min, I2 = 58.6%) and neuromuscular blockers (MD 9.0 min, 95% CI 7.9-10.0 min, I2 = 0%). The certainty of the evidence was low or very low for most outcomes. Automatic technology may be used to improve the hemodynamic profile during noradrenaline and vasodilators administration and reduce the duration of postanaesthetic recovery.
Registration: This systematic review was registered with PROSPERO (CRD42022336950) on the 7th of June 2022.
Spataru A, Eiben P, Pluddemann A. Performance of closed-loop systems for intravenous drug administration: a systematic review and meta-analysis of randomised controlled trials. J Clin Monit Comput. 2023 Sep 11. doi: 10.1007/s10877-023-01069-3. Epub ahead of print. PMID: 37695449.