SinoSCORE: a logistically derived additive prediction model for post-coronary artery bypass grafting in-hospital mortality in a Chinese population

Zheng, Zhe; Zhang, Lu; Li, Xi; Hu, Shengshou

doi:10.1007/s11684-013-0284-0

Cited by 29 publications

(38 citation statements)

References 16 publications

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“…This may limit the applicability of the scoring system beyond health systems that routinely collect this information, particularly centres in China 29 and Australia. 30 Furthermore, risk prediction models are subject to constant revision, 31 potentially further limiting the applicability of derived models that make use of them.…”

Section: Discussionmentioning

confidence: 99%

The ACTA PORT-score for predicting perioperative risk of blood transfusion for adult cardiac surgery

Klein

Collier

Yeates

et al. 2017

British Journal of Anaesthesia

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Objective: To derive a simple and accurate scoring system to predict risk of transfusion for patients undergoing cardiac surgery Design: Retrospective analysis of data collected from the ACTA National Audit; for the derivation dataset, we included data from 20,036 patients, which we then externally validated using a further group of 1,047 patients. Methods:We identified independent risk factors associated with transfusion by performing univariate analysis, followed by logistic regression. We then simplified the score to aninteger-based system and tested it using AUC characteristic statistic. A Hosmer-Lemeshow goodness-of-fit test was applied. Finally, the scoring system was applied to the external validation dataset and the same statistical methods applied to test the accuracy of the ACTA-PORT score.Results: Several factors were shown to be independently associated with risk of transfusion.These included age, gender, body surface area, logistic EuroSCORE, preoperative haemoglobin and creatinine, and type of surgery. In our primary dataset, the score accurately predicted risk of perioperative transfusion in cardiac patients with an AUC of 0.76. The external validation confirmed the accuracy of the scoring method with an AUC of 0.84 and good agreement across all scores with a minor tendency to under-estimate transfusion risk in very high-risk patients. Conclusion:The ACTA-PORT score is a reliable, validated tool for predicting the risk of transfusion for patients undergoing cardiac surgery. This score will allow clinicians to easily identify patients at increased risk for transfusion and apply patient blood management strategies appropriately, with the potential to reduce perioperative morbidity and mortality.

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Section: Discussionmentioning

confidence: 99%

The ACTA PORT-score for predicting perioperative risk of blood transfusion for adult cardiac surgery

Klein

Collier

Yeates

et al. 2017

British Journal of Anaesthesia

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“…2). We discuss the details of a random subset of 50 studies (Table 1) [24–73]. Forty of them analyzed observational multicenter data.…”

Section: Resultsmentioning

confidence: 99%

Untapped potential of multicenter studies: a review of cardiovascular risk prediction models revealed inappropriate analyses and wide variation in reporting

et al. 2019

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Background Clinical prediction models are often constructed using multicenter databases. Such a data structure poses additional challenges for statistical analysis (clustered data) but offers opportunities for model generalizability to a broad range of centers. The purpose of this study was to describe properties, analysis, and reporting of multicenter studies in the Tufts PACE Clinical Prediction Model Registry and to illustrate consequences of common design and analyses choices. Methods Fifty randomly selected studies that are included in the Tufts registry as multicenter and published after 2000 underwent full-text screening. Simulated examples illustrate some key concepts relevant to multicenter prediction research. Results Multicenter studies differed widely in the number of participating centers (range 2 to 5473). Thirty-nine of 50 studies ignored the multicenter nature of data in the statistical analysis. In the others, clustering was resolved by developing the model on only one center, using mixed effects or stratified regression, or by using center-level characteristics as predictors. Twenty-three of 50 studies did not describe the clinical settings or type of centers from which data was obtained. Four of 50 studies discussed neither generalizability nor external validity of the developed model. Conclusions Regression methods and validation strategies tailored to multicenter studies are underutilized. Reporting on generalizability and potential external validity of the model lacks transparency. Hence, multicenter prediction research has untapped potential. Registration This review was not registered. Electronic supplementary material The online version of this article (10.1186/s41512-019-0046-9) contains supplementary material, which is available to authorized users.

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“…Based on original SinoSCORE methodology, a SinoSCORE was then calculated for each patient. STS mortality risk scores were retrieved from the HeartSource database 9. SinoSCORE was calculated for all patients undergoing CABG, including those with associated valve surgery, whereas separate STS risk models were employed for each isolated CABG and combined CABG/valve procedure 12 13.…”

Section: Methodsmentioning

confidence: 99%

East meets West: the influence of racial, ethnic and cultural risk factors on cardiac surgical risk model performance

et al. 2018

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Objective To explore the impact of racial and ethnic diversity on the performance of cardiac surgical risk models, the Chinese SinoSCORE was compared with the Society of Thoracic Surgeons (STS) risk model in a diverse American population. Methods The SinoSCORE risk model was applied to 13 969 consecutive coronary artery bypass surgery patients from twelve American institutions. SinoSCORE risk factors were entered into a logistic regression to create a 'derived' SinoSCORE whose performance was compared with that of the STS risk model. results Observed mortality was 1.51% (66% of that predicted by STS model). The SinoSCORE 'low-risk' group had a mortality of 0.15%±0.04%, while the medium-risk and high-risk groups had mortalities of 0.35%±0.06% and 2.13%±0.14%, respectively. The derived SinoSCORE model had a relatively good discrimination (area under of the curve (AUC)=0.785) compared with that of the STS risk score (AUC=0.811; P=0.18 comparing the two). However, specific factors that were significant in the original SinoSCORE but that lacked significance in our derived model included body mass index, preoperative atrial fibrillation and chronic obstructive pulmonary disease. Conclusion SinoSCORE demonstrated limited discrimination when applied to an American population. The derived SinoSCORE had a discrimination comparable with that of the STS, suggesting underlying similarities of physiological substrate undergoing surgery. However, differential influence of various risk factors suggests that there may be varying degrees of importance and interactions between risk factors. Clinicians should exercise caution when applying risk models across varying populations due to potential differences that racial, ethnic and geographic factors may play in cardiac disease and surgical outcomes.

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SinoSCORE: a logistically derived additive prediction model for post-coronary artery bypass grafting in-hospital mortality in a Chinese population

Cited by 29 publications

References 16 publications

The ACTA PORT-score for predicting perioperative risk of blood transfusion for adult cardiac surgery

The ACTA PORT-score for predicting perioperative risk of blood transfusion for adult cardiac surgery

Untapped potential of multicenter studies: a review of cardiovascular risk prediction models revealed inappropriate analyses and wide variation in reporting

East meets West: the influence of racial, ethnic and cultural risk factors on cardiac surgical risk model performance

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