Preoperative risk assessment tools for morbidity after cardiac surgery: a systematic review.

BACKGROUND: Postoperative morbidity places considerable burden on health and resources. Thus, strategies to identify, predict, and reduce postoperative morbidity are needed. AIMS: To identify and explore existing preoperative risk assessment tools for morbidity after cardiac surgery. METHODS: Electronic databases (including MEDLINE, CINAHL, and Embase) were searched to December 2020 for preoperative risk assessment models for morbidity after adult cardiac surgery. Models exploring one isolated postoperative morbidity and those in patients having heart transplantation or congenital surgery were excluded. Data extraction and quality assessments were undertaken by two authors. RESULTS: From 2251 identified papers, 22 models were found. The majority (54.5%) were developed in the USA or Canada, defined morbidity outcome within the in-hospital period (90.9%), and focused on major morbidity. Considerable variation in morbidity definition was identified, with morbidity incidence between 4.3% and 52%. The majority (45.5%) defined morbidity and mortality separately but combined them to develop one model, while seven studies (33.3%) constructed a morbidity-specific model. Models contained between 5 and 50 variables. Commonly included variables were age, emergency surgery, left ventricular dysfunction, and reoperation/previous cardiac surgery, although definition differences across studies were observed. All models demonstrated at least reasonable discriminatory power [area under the receiver operating curve (0.61-0.82)]. CONCLUSION: Despite the methodological heterogeneity across models, all demonstrated at least reasonable discriminatory power and could be implemented depending on local preferences. Future strategies to identify, predict, and reduce morbidity after cardiac surgery should consider the ageing population and those with minor and/or multiple complex morbidities.

Computerized technologies informing cardiac catheterization and guiding coronary intervention.

Advances in image processing and computer hardware have enabled the development of user-friendly software which operate in real-time and can be used in the catheterization laboratory to facilitate percutaneous coronary intervention (PCI). The two dimensional-(2D) quantitative coronary angiography (QCA) systems that have traditionally been used to assess lesion severity have been replaced by 3D-QCA systems, enabling more reliable evaluation of vessel geometry and lesion dimensions. This also allows 3D reconstruction of coronary bifurcation anatomy and generation of models that can be processed by computational fluid dynamic techniques to reliably detect flow-limiting lesions. More recently, software has been introduced that has the capability of generating a digital silhouette of the coronary arteries superimposed onto X-ray angiography to facilitate wire crossing and stent placement, and potentially reduce contrast use. In parallel, methodologies have been developed that operate with an accessible interface and can process intravascular imaging data, reliably quantify lesion severity and co-register intravascular and X-ray angiographic data to comprehensively assess plaque distribution and guide PCI. The above advances are used in daily practice to improve procedural results and outcomes. This review aims to provide an overview of the developments in the field - it presents the computer-based technologies that have been designed to accurately assess lesion severity, summarizes the advantages and limitations of the systems introduced to co-register imaging data and discusses the potential value of the existing and emerging software in the catheterization laboratory.