ARTIFICIAL INTELLIGENCE – ASSISTED HEMODYNAMIC MONITORING AND PERIOPERATIVE Outcomes in ADULT Adult CARDIAC SURGERY : A SYSTEMATIC REVIEW and META-ANALYSIS
Year: 2026
Type: dataset
Abstract: This systematic review and meta-analysis provides a rigorous and contemporary evaluation of artificial intelligence (AI)–assisted hemodynamic monitoring in adult cardiac surgery, a high-risk setting characterized by marked physiological instability and susceptibility to adverse outcomes. Conducted in accordance with PRISMA 2020 guidelines, the study synthesized evidence from nine studies including 1,842 patients, of which three methodologically comparable studies were eligible for quantitative meta-analysis. By integrating data from randomized controlled trials and observational studies, the analysis balances methodological rigor with real-world clinical applicability. The findings demonstrate that AI-assisted monitoring—particularly systems such as the Hypotension Prediction Index and other machine learning–based models—significantly reduces intraoperative hypotension duration (mean difference −18.6 minutes; p < 0.001) and is associated with a reduction in ICU length of stay (−0.8 days; p = 0.002), while showing a consistent trend toward lower lactate levels, suggestive of improved tissue perfusion. However, no statistically significant effect on mortality was observed (RR 0.92; 95% CI 0.71–1.18). Mechanistically, these results support the concept that predictive monitoring enables a shift from reactive to proactive hemodynamic management, improving both macrocirculatory stability and potentially microcirculatory perfusion. Despite these promising findings, interpretation is limited by the small number of studies included in the quantitative synthesis, heterogeneity in AI technologies and study methodologies, and the predominance of short-term outcomes. Overall, this study provides a comprehensive and clinically relevant synthesis of the current evidence, supporting AI-assisted monitoring as a key component of precision perioperative care while emphasizing the need for large-scale, high-quality randomized trials to confirm long-term clinical benefits and define its optimal role in cardiac anesthesia.
Source: Figshare
Authors: KHALLIKANE, Said, Nabil, Mehdi, EL BARAKA, Hakim, Didi, Mehdi, Hicham, KBIRI, Elabdi, Monsef, Roukhsi, Redouane, Bentaher, Amine, BOUHABBA, Najib, NAJOUT, Hamza, Chlouchi, Abdelatif, Benakrout, Aziz, Elghoul, Naoufal, SALLAHI, Hicham, Benbouha, Adbelatif, JANAH, Hicham, Arrob, Adil, Zbitou, Anas, Belfquih, Hatim, Nassim sabah, Taoufik, Darouassi, Youssef, Lahkim, Mohammed, Tourabi, Khalid, MARGAD, Omar, ABOUCHADI, Abdeljalil, BOUZERDA, Abdelmajid, Elbarni, Rachid, SEDDIKI, Rachid, KHATOURI, Ali, Balkhi, Hicham, Bousliman, Yassir, Zouhair, Said, A EL GHADBANE, Hatim, QAMOUSS, Youssef, DRISSI, Mohammed, ZYANI, Mohammad
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7159052000