Predicting target vessel revascularization in older patients undergoing percutaneous coronary intervention in the drug-eluting stent era

Digital Health Interventions in Patient Management Following Acute Coronary Syndrome: A Meta-Analysis of the Literature

OBJECTIVE

Acute coronary syndrome patients should be closely followed-up to maintain optimal adherence to medical treatments and to reduce adverse events. Digital health interventions might provide improved outcomes for patient care by providing closer follow- up, compared to standard care. Thus, in this meta-analysis, we aimed to evaluate the effect of digital health interventions on follow-up in acute coronary syndrome patients.

METHODS

We searched medical databases to obtain all relevant studies comparing digital health interventions with standard care in acute coronary syndrome patients. After reviewing all eligible studies, a meta-analysis was conducted with the remaining 11 randomized controlled studies and 2 non-randomized controlled studies. A modified Jadad scale and Newcastle-Ottawa scale were used to assess the quality of the publications for randomized controlled studies and non-randomized controlled studies, respectively.

RESULTS

This meta-analysis consisted of 7657 patients. The all-cause mortality rate was 49% lower in the digital health intervention cases, compared to those who received standard care [relative risk (RR) = 0.51 (0.37; 0.70), P <.01]. There was a significant decrease in systolic blood pressure in the digital health interventions group, compared to the standard care group [mean difference = -5.28 (-9.47; -1.08), P =.01]. The rate of nonadherence to anti-aggregant drugs was 69% lower in the digital health interventions than in the standard care group [RR = 0.31 (0.20; 0.46), P <.01]. Also, nonadherence rates for statin and beta-blockers were lower in the digital health interventions group. The risk of rehospitalization was observed to be 55% less in the digital health interventions patients, compared to the standard care group [RR = 0.45 (0.30; 0.67), P <.01].

CONCLUSION

Digital health interventions can be effective in follow-up for secondary prevention in acute coronary syndrome patients.

A Simple Model to Predict Repeat Revascularization After Drug-Eluting Stent Implantation in Patients With Stable Coronary Artery Disease

Repeat revascularization is still common in the era of drug-eluting stents (DES), especially for non-target lesions. However, few validated models exist to predict the need for revascularization. We aimed to develop and validate an easy-to-use predictive model for repeat revascularization after DES implantation in patients with stable coronary artery disease (CAD). A total of 1,653 stable CAD patients with angiographic follow-up after DES implantation were consecutively enrolled. Split-sample testing was adopted to develop and validate the model. In the training set, male, diabetes, number of target lesions, occlusion lesion, number of non-target lesions, recurrent angina, suboptimal low density lipoprotein-cholesterol level, and high lipoprotein (a) level were independent predictors of repeat revascularization using logistic regression analyses. The established model (Model 1) yielded a bias-corrected concordance index of 0.700 (95% confidence interval: 0.667 to 0.735), with good calibration. It also performed well in the validation set. Compared with the traditional empirical model only including recurrent angina (Model 2), Model 1 had better discriminative ability and clinical usefulness. In conclusion, we established and validated a simple model including 8 easily accessible variables to predict repeat revascularization after DES implantation in stable CAD patients, contributing to better risk stratification, decision making, and patient consultation.

Association of stent diameter and target vessel revascularization in patients undergoing percutaneous coronary intervention: a secondary retrospective analysis based on a Chinese cohort study

Background

In the treatment of coronary heart disease, target vessel revascularization (TVR) has attracted increasing attention as an efficient means of percutaneous coronary intervention (PCI). The purpose of this study was to explore the association between stent diameter and TVR in patients undergoing PCI.

Methods

This was a secondary retrospective analysis involving patients with PCI with at least one stent implanted. Information was obtained from the Dryad Digital Repository. Multivariable logistic regression models, interaction analyses, subgroup analyses and piecewise linear regression models were used to evaluate the association between stent diameter and TVR.

Results

A total of 2522 patients were eventually enrolled in this study, of which 122 (4.8%) had undergone TVR. Significant positive associations were observed between stent diameter and TVR (continuous: odds ratio [OR] 0.485, 95% confidence interval [CI] 0.305–0.773, P = 0.002; categorical variable: T2 vs. T1, OR 0.541, 95% CI 0.348–0.843; T3 vs. T1, OR 0.520, 95% CI 0.334–0.809; P for trend = 0.005). The association remained stable in the fully adjusted model (continuous: OR 0.526, 95% CI 0.306–0.902, P = 0.020; categorical variable: T2 vs. T1, OR 0.510, 95% CI 0.310–0.839; T3 vs. T1, OR 0.585, 95% CI 0.352–0.973; P for trend = 0.042). Among the subgroups of differing clinical presentations, stent diameter was a powerful protective factor for TVR, especially in the delayed PCI group (P for interaction = 0.002). The association was highly consistent across all the other subgroups studied (all P for interaction > 0.05). In the piecewise linear regression model, the need for TVR decreased with an increase in stent diameter when this ranged between 2.5 and 2.9 mm (OR 0.01, 95% CI: 0.01–0.13, P < 0.001).

Conclusions

A large stent diameter is a powerful protective factor for TVR in PCI patients, especially in the delayed PCI group. This “bigger-is-better” protective effect is remarkable in stents with diameter 2.5–2.9 mm.