External validity of the PRECISE-DAPT score in patients undergoing PCI: a systematic review and meta-analysis
Andrea Munafò, Claudio Montalto, Marco Franzino, Lorenzo Pistelli, Gianluca Di Bella, Marco Ferlini, Sergio Leonardi, Fabrizio D'Ascenzo, Felice Gragnano, Jacopo Oreglia, Fabrizio Oliva, Luis Ortega‐Paz, Paolo Calabrò, Dominick J. Angiolillo, Marco Valgimigli, Antonio Micari, Francesco Costa
Abstract
AIMS: To summarize the totality of evidence validating the Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy (PRECISE-DAPT) score, ascertaining its aggregate discrimination and validation power in multiple population subsets. METHODS AND RESULTS: We searched electronic databases from 2017 (PRECISE-DAPT proposal) up to March 2023 for studies that reported the occurrence of out-of-hospital bleedings according to the PRECISE-DAPT score in patients receiving DAPT following percutaneous coronary intervention (PCI). Pooled odds ratios (OR) with 95% confidence interval (CI) were used as summary statistics and were calculated using a random-effects model. Primary and secondary endpoints were the occurrence of any and major bleeding, respectively. A total of 21 studies and 67 283 patients were included; 24.7% of patients (N = 16 603) were at high bleeding risk (PRECISE-DAPT score ≥25), and when compared to those at low bleeding risk, they experienced a significantly higher rate of any out-of-hospital bleeding (OR: 2.71; 95% CI: 2.24-3.29; P-value <0.001) and major bleedings (OR: 3.51; 95% CI: 2.71-4.55; P-value <0.001). Pooling data on c-stat whenever available, the PRECISE-DAPT score showed a moderate discriminative power in predicting major bleeding events at 1 year (pooled c-stat: 0.71; 95% CI: 0.64-0.77). CONCLUSION: This systematic review and meta-analysis confirms the external validity of the PRECISE-DAPT score in predicting out-of-hospital bleeding outcomes in patients on DAPT following PCI. The moderate discriminative ability highlights the need for future improved risk prediction tools in the field.