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Article: Risk stratification for cardiac surgery: Comparison in a Hong Kong population

TitleRisk stratification for cardiac surgery: Comparison in a Hong Kong population
Authors
Keywordscardiac surgery
Hong Kong population
risk stratification
Issue Date2019
PublisherWiley-Blackwell Publishing Asia. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1744-1633
Citation
Surgical Practice, 2019, v. 23 n. 4, p. 146-155 How to Cite?
AbstractAim: Risk stratification is an important tool in preoperative decision‐making, counseling, informed consent and quality improvement. The European System for Cardiac Operative Risk Evaluation (logistic EuroSCORE) and EuroSCORE II were designed for the assessment of surgical risk. However, there are significant geographical and demographic differences between European and Hong Kong patients. The Queen Mary Hospital (QMH) risk score is a risk model designed to predict in‐hospital mortality for patients undergoing coronary artery bypass grafting (CABG) and valve surgery based on local data. In the present study, we compared the precision and clinical performance of the three scoring systems. Patients and Methods: Data were collected prospectively from patients undergoing CABG and valve surgery between 2010 and 2015 in a single institution (n = 1693) in Hong Kong. Patients <18 years old and who had undergone congenital/aortic surgery were excluded. The receiver–operator curve (ROC) analysis was used to determine the discriminative ability of each score. Calibration was tested with the Hosmer–Lemeshow (HL) goodness‐of‐fit test. Results: Observed mortality was 49/1639 (2.89 per cent). The predicted mortality rates were logistic EuroSCORE 9.23 per cent [95 per cent confidence interval (CI): 8.65–9.78 per cent], EuroSCORE II 3.87 per cent (95 per cent CI: 3.58–4.14) and QMH risk score 4.20 per cent (95 per cent CI: 4.04–4.33). The area under the ROC analysis revealed 0.849 (95 per cent CI: 0.804–0.895) for the logistic EuroSCORE, 0.87 (95 per cent CI: 0.826–0.913) for the EuroSCORE II and 0.841 (95 per cent CI: 0.788–0.895) for QMH risk score. The HL goodness‐of‐fit test showed that the QMH risk score was a good fit (P = 0.207); however, the logistic EuroSCORE (P = 0.003) and EuroSCORE II (P = 0.003) showed a poor fit. Conclusions: All three scoring systems can be applied to a Chinese population with excellent risk prediction. The QMH risk score has a role in accurately predicting mortality rates in a Hong Kong population.
Persistent Identifierhttp://hdl.handle.net/10722/283397
ISSN
2013 Impact Factor: 0.172
2020 SCImago Journal Rankings: 0.109
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWong, MKH-
dc.contributor.authorBhatia, I-
dc.contributor.authorChan, DTL-
dc.contributor.authorHo, CKL-
dc.contributor.authorAu, TWK-
dc.date.accessioned2020-06-22T02:55:54Z-
dc.date.available2020-06-22T02:55:54Z-
dc.date.issued2019-
dc.identifier.citationSurgical Practice, 2019, v. 23 n. 4, p. 146-155-
dc.identifier.issn1744-1625-
dc.identifier.urihttp://hdl.handle.net/10722/283397-
dc.description.abstractAim: Risk stratification is an important tool in preoperative decision‐making, counseling, informed consent and quality improvement. The European System for Cardiac Operative Risk Evaluation (logistic EuroSCORE) and EuroSCORE II were designed for the assessment of surgical risk. However, there are significant geographical and demographic differences between European and Hong Kong patients. The Queen Mary Hospital (QMH) risk score is a risk model designed to predict in‐hospital mortality for patients undergoing coronary artery bypass grafting (CABG) and valve surgery based on local data. In the present study, we compared the precision and clinical performance of the three scoring systems. Patients and Methods: Data were collected prospectively from patients undergoing CABG and valve surgery between 2010 and 2015 in a single institution (n = 1693) in Hong Kong. Patients <18 years old and who had undergone congenital/aortic surgery were excluded. The receiver–operator curve (ROC) analysis was used to determine the discriminative ability of each score. Calibration was tested with the Hosmer–Lemeshow (HL) goodness‐of‐fit test. Results: Observed mortality was 49/1639 (2.89 per cent). The predicted mortality rates were logistic EuroSCORE 9.23 per cent [95 per cent confidence interval (CI): 8.65–9.78 per cent], EuroSCORE II 3.87 per cent (95 per cent CI: 3.58–4.14) and QMH risk score 4.20 per cent (95 per cent CI: 4.04–4.33). The area under the ROC analysis revealed 0.849 (95 per cent CI: 0.804–0.895) for the logistic EuroSCORE, 0.87 (95 per cent CI: 0.826–0.913) for the EuroSCORE II and 0.841 (95 per cent CI: 0.788–0.895) for QMH risk score. The HL goodness‐of‐fit test showed that the QMH risk score was a good fit (P = 0.207); however, the logistic EuroSCORE (P = 0.003) and EuroSCORE II (P = 0.003) showed a poor fit. Conclusions: All three scoring systems can be applied to a Chinese population with excellent risk prediction. The QMH risk score has a role in accurately predicting mortality rates in a Hong Kong population.-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing Asia. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1744-1633-
dc.relation.ispartofSurgical Practice-
dc.rightsPreprint This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Postprint This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.-
dc.subjectcardiac surgery-
dc.subjectHong Kong population-
dc.subjectrisk stratification-
dc.titleRisk stratification for cardiac surgery: Comparison in a Hong Kong population-
dc.typeArticle-
dc.identifier.emailAu, TWK: auwkt@hkucc.hku.hk-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/1744-1633.12391-
dc.identifier.scopuseid_2-s2.0-85075076914-
dc.identifier.hkuros310474-
dc.identifier.volume23-
dc.identifier.issue4-
dc.identifier.spage146-
dc.identifier.epage155-
dc.identifier.isiWOS:000496619900004-
dc.publisher.placeAustralia-
dc.identifier.issnl1744-1625-

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