Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-24 @ 10:10 PM
Ignite Modification Date:
2025-12-24 @ 10:10 PM
NCT ID:
NCT05592535
Brief Summary:
The use of fractional flow reserve (FFR) to assess the functional relevance of coronary stenoses has been demonstrated to reduce the risk urgent revascularization in chronic coronary syndrome patients.\[1\] The goal of this study is to assess whether the utility of using FFR during percutaneous coronary intervention (PCI) in chronic coronary syndrome patients is confirmed in a real-life scenario. This study will implement a regression discontinuity design (RDD). RDD is a quasi-experimental study design able to provide robust findings on causality using observational data.
Detailed Description:
All patients in this study were included in the Swedish Coronary Angiography and Angioplasty Registry (SCAAR), a sub-registry of SWEDEHEART. \[2\] Data regarding FFR assessments are documented in SCAAR in terms of FFR values and coronary segments investigated with FFR. The use of FFR during PCI is left at the discretion of the operator. Since a nondeterministic assignment to revascularization is expected at the cut-off, a fuzzy RDD design will be used in the analyses. Moreover, FFR values equal to 0.80 (at the cut-off) will be excluded from the analysis since treatment assignment exactly at the cut-off may substantially vary across operators and this may create distortions in the treatment discontinuity. Local linear regression estimates with Kernel triangulation and asymmetric bandwidth selection will be used in the analysis. Bandwidth selection will be based on a fully data-driven approach that minimizes the bias-variance trade-off.\[3\] Estimates from RDD will be presented as risk differences \[RD\] complemented by 95% robust confidence intervals.\[4\]
Study:
NCT05592535
Study Brief:
Protocol Section:
NCT05592535