Key result
Cardiovascular computational models targeting clinical use mostly remain prototypes, with only 25% incorporating patient personalization.
Why the study?
Standardized treatment approaches struggle with the multifactorial nature and variability of hemodynamic instability in critical care, making computational physiological models a promising individualised solution whose landscape requires evaluation.
While cardiovascular computational physiological models show promise for critical care applications like fluid management, most remain in pre-clinical stages with limited rigorous credibility reporting.
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Most models targeting clinical use remain non-personalized prototypes; leaves open routine adoption in critical care fluid management.
Hemodynamic instability is a highly prevalent, complex and life-threatening condition in critically ill patients. Its multifactorial nature and patient-specific variability challenge standardised treatment approaches. Computational physiological models (CPMs) offer a promising solution by simulating cardiovascular dynamics to guide individualised hemodynamic management. This systematic review evaluates the current landscape of cardiovascular CPMs, focusing on their design, credibility, and clinical readiness. A systematic search was conducted in MEDLINE ALL, Embase, Scopus, and Web of Science. Original research articles describing zero-dimensional, closed-loop cardiovascular models with (potential) applications in critical care were included. Data were extracted on context of use, model design, and validation. Model credibility was assessed using a risk-based framework and clinical readiness using a nine-level technology maturity scale. Out of 10,704 screened articles, 183 were included. Direct clinical applications were described in 50% of these studies, including diagnosis, decision support, and closed-loop control. Fluid management was the most common application domain (30%). Personalisation of model parameters was reported in 25% of the articles. While 66% of the articles presented model validation, only 21% achieved moderate credibility scores. Reporting of model characteristics was consistently (100%) insufficient. Most models (75%) were at clinical readiness level 3-4 (model prototyping and development), with four studies reaching clinical testing (level 6-8). A substantial body of cardiovascular CPMs exists with promising prospects for relevant applications in critical care, while a large part is currently confined to pre-clinical research settings. Advancing clinical integration requires leveraging existing models, improving transparency in verification and validation, and establishing robust personalisation strategies. PROSPERO - CRD42022300137, registered on February 11, 2022. • 183 cardiovascular lumped-parameter, closed-loop models systematically reviewed • Half of the models target direct clinical use, most commonly for fluid management • Model personalisation is implemented in only 25% of studies • Validation is common (66%), but rigorous credibility reporting is limited • Most models remain prototypes despite promising critical care applications
Mulder et al. (2026) studied this question. Half of cardiovascular computational physiological models target direct clinical use, mostly for fluid management, but only 25% include personalization and most remain prototypes.
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