A new post-PCI scoring system for in-hospital mortality in STEMI patients

Critical appraisal and assessment of bias among studies evaluating risk prediction models for in-hospital and 30-day mortality after percutaneous coronary intervention: a systematic review

OBJECTIVE

We systematically assessed prediction models for the risk of in-hospital and 30-day mortality in post-percutaneous coronary intervention (PCI) patients.

DESIGN

Systematic review and narrative synthesis.

DATA SOURCES

Searched PubMed, Web of Science, Embase, Cochrane Library, CINAHL, CNKI, Wanfang Database, VIP Database and SinoMed for literature up to 31 August 2023.

ELIGIBILITY CRITERIA

The included literature consists of studies in Chinese or English involving PCI patients aged ≥18 years. These studies aim to develop risk prediction models and include designs such as cohort studies, case-control studies, cross-sectional studies or randomised controlled trials. Each prediction model must contain at least two predictors. Exclusion criteria encompass models that include outcomes other than death post-PCI, literature lacking essential details on study design, model construction and statistical analysis, models based on virtual datasets, and publications such as conference abstracts, grey literature, informal publications, duplicate publications, dissertations, reviews or case reports. We also exclude studies focusing on the localisation applicability of the model or comparative effectiveness.

DATA EXTRACTION AND SYNTHESIS

Two independent teams of researchers developed standardised data extraction forms based on CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies to extract and cross-verify data. They used Prediction model Risk Of Bias Assessment Tool (PROBAST) to assess the risk of bias and applicability of the model development or validation studies included in this review.

RESULTS

This review included 28 studies with 38 prediction models, showing area under the curve values ranging from 0.81 to 0.987. One study had an unclear risk of bias, while 27 studies had a high risk of bias, primarily in the area of statistical analysis. The models constructed in 25 studies lacked clinical applicability, with 21 of these studies including intraoperative or postoperative predictors.

CONCLUSION

The development of in-hospital and 30-day mortality prediction models for post-PCI patients is in its early stages. Emphasising clinical applicability and predictive stability is vital. Future research should follow PROBAST's low risk-of-bias guidelines, prioritising external validation for existing models to ensure reliable and widely applicable clinical predictions.

PROSPERO REGISTRATION NUMBER

CRD42023477272.

Using the RISK-PCI Score in the Long-Term Prediction of Major Adverse Cardiovascular Events and Mortality after Primary Percutaneous Coronary Intervention

Background/Aim

The RISK-PCI is a simple score for the prediction of 30-day major adverse cardiovascular events (MACE) and mortality in patients treated with primary PCI (pPCI). The aim of the present study is to evaluate the prognostic performance of the RISK-PCI score in predicting MACE and mortality in the long-term follow-up of STEMI patients treated with pPCI.

Method

The present study enrolled 2,096 STEMI patients treated with pPCI included in the RISK-PCI trial. Patients presenting with cardiogenic shock were excluded. The composite end-point MACE comprising cardiovascular mortality, nonfatal reinfarction and stroke. Patients were followed up at 6 years after enrollment.

Results

One-year and 6-year MACE occurred in 229 (10.9%) and 285 (13.6%) patients, respectively; and 1-year and 6-year mortality occurred in 128 (6.2%) and 151 (7.2%) patients, respectively. The RISK-PCI score was an independent predictor for 1-year MACE (HR 1.24, 95% CI 1, 18–1.31, p < 0.001), 6-year MACE (HR 1.22, 95% CI 1.16–1.28, p < 0.001), 1-year mortality (HR 1.21, 95% CI 1.13–1.29, p < 0.001), and 6-year mortality (HR 1.23, 95% CI 1.15–1.31, p < 0.001). The discrimination of the RISK-PCI score to predict 1-year and 6-year MACE and mortality was good: for 1-year MACE c-statistic 0.78, for 6-year MACE c-statistic 0.75, for 1-year mortality c-statistic 0.87, and for 6-year mortality c-statistic 0.83. The nonsignificant Hosmer–Lemeshow goodness-of-fit estimates for 1-year MACE (p=0.619), 6-year MACE (p=0.319), 1-year mortality (p=0.258), and 6-year mortality (p=0.540) indicated a good calibration of the model.

Conclusion

The RISK-PCI score demonstrates good characteristics in the assessment of the risk for the occurrence of MACE and mortality during long-term follow-up after pPCI.