Variations in how medical researchers report variables in risk scores or models to predict prognosis of patients after percutaneous coronary intervention: a retrospective analysis of published articles

Background: The use of risk variables in prognostic risk scores/models to evaluate patients after percutaneous coronary intervention (PCI) has been a controversial topic in medical literature. We therefore analyzed variations in risk scores/model variables to assess the prognosis of patients after percutaneous coronary intervention (PCI) in detail. Methods: Articles were included from inception to December 2023 in PubMed/MEDLINE database using a combination of key words "Risk score" or "Risk model" AND "Percutaneous coronary intervention" ( n =822). All English-language articles involving risk scores or models for assessment of patient prognosis after PCI were retained ( n =183). We collected information on the extracted risk scores/models for patients after PCI ( n =138) from the included articles and analyzed the variation variables in the relevant risk scores/models in detail. Results: Among the risk scores/models, age, kidney function index, ACS presentation, diabetes, LVEF, culprit coronary artery, heart failure, SBP, heart rate, and sex were the top ten variables used. There were statistically significant differences in the use of variables such as kidney function index ( χ ² =6.995, P =0.008), ACS presentation ( χ ² =9.611, P =0.002), culprit coronary artery ( χ ² =3.937, P =0.047), SBP ( χ ² =10.556, P =0.001), heart rate ( χ ² =10.704, P =0.001), and ST-segment deviation ( χ ² =11.489, P =0.001) between Caucasian participants ( n =74) and non-Caucasian participants ( n =58). Conclusions: in the risk scores/models for prognostic assessment after PCI. When constructing scores/models, the variable selection should fully consider the ethnic background of the study population.