A prognostic nomogram for event-free survival in patients with atrial fibrillation before cardiac resynchronization therapy

Risk scores in cardiac resynchronization therapy-A review of the literature

Cardiac resynchronization therapy (CRT) for selected heart failure (HF) patients improves symptoms and reduces morbidity and mortality; however, the prognosis of HF is still poor. There is an emerging need for tools that might help in optimal patient selection and provide prognostic information for patients and their families. Several risk scores have been created in recent years; although, no literature review is available that would list the possible scores for the clinicians. We identified forty-eight risk scores in CRT and provided the calculation methods and formulas in a ready-to-use format. The reviewed score systems can predict the prognosis of CRT patients; some of them have even provided an online calculation tool. Significant heterogeneity is present between the various risk scores in terms of the variables incorporated and some variables are not yet used in daily clinical practice. The lack of cross-validation of the risk scores limits their routine use and objective selection. As the number of prognostic markers of CRT is overwhelming, further studies might be required to analyze and cross-validate the data.

Development and Validation of a Nomogram for Predicting Mortality in Patients with Atrial Fibrillation and Acute Coronary Syndrome Who Underwent Percutaneous Coronary Intervention in a Chinese Multicenter Cohort

Background

This study is aimed at to establish an effective prognostic nomogram for patients with atrial fibrillation (AF) and acute coronary syndrome (ACS) underwent percutaneous coronary intervention (PCI).

Methods

The nomogram was based on a retrospective study of 977 patients with AF and ACS who underwent PCI who were admitted to any of the 11 tertiary hospitals in the Beijing area between 2009 and 2015. The predictive accuracy and discriminative ability of the nomogram were determined by a concordance index (C-index) and calibration curve and were compared using current risk scores such as GRACE, CRUSADE, CHA2DS2-VASc, and HAS-BLED. The results were validated using bootstrap resampling and a retrospective cohort study of 409 patients enrolled in Fuwai Hospital at the same institution.

Results

Independent factors derived from multivariable analysis of the primary cohort to predict all-cause mortality were age, pattern of ACS, red blood cell distribution width, N-terminal proBNP, and serum creatinine, all of which were assembled into the nomogram. The calibration curve for the probability of recurrence showed that the nomogram-based predictions were in good agreement with actual observations. The C-index of the nomogram for predicting mortality was 0.764 (95% CI, 0.718-0.810), which was statistically higher than the C-index values for the current risk scores (from 0.573 to 0.681). In the validation cohort, the C-index of the nomogram for predicting all-cause death was 0.706 (95% CI 0.601-0.811), with no significant differences compared with GRACE and CRUSADE, but better than that of CHA2DS2-VASc and HAS-BLED.

Conclusions

The nomogram has good prognostic prediction for patients with AF and ACS who underwent PCI.

A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation

BACKGROUND

The use of anticoagulants and antiplatelet therapies is associated with a higher risk of bleeding in atrial fibrillation (AF) patients after percutaneous coronary intervention, especially after stent implantation. However, no accurate bleeding risk prediction tool has been developed for these patients. The aim of this study was thus to establish a bleeding risk prediction model (predictive nomogram) for patients with AF after stent implantation.

METHODS

Construction of the predictive nomogram was based on a retrospective study, which enrolled 943 AF patients who underwent drug-eluting stent implantation between May 2012 and September 2016. A range of factors, including demographics, comorbidities, medication strategies, arterial access, and laboratory tests, were collected as baseline data. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis were used to identify the key clinical features for construction of the predictive nomogram. The concordance index (C-index) and internal validation were used to evaluate the efficacy of the nomogram.

RESULTS

Of the 943 AF patients that underwent stent implantation, the occurrence of bleeding events was 8.2% (77 out of 943). Key predictors included the number of antiplatelet drugs, peptic ulcer, cerebral infarction, type 2 diabetes, thrombocytopenia, anemia, prior myocardial infarction, sex (male), use of anticoagulant drugs, liver dysfunction, hypertension, and acute myocardial infarction. These predictors were used to construct the nomogram. The C-index for the prediction of bleeding risk by the nomogram was 0.841 (95% CI: 0.79-0.89), which indicated good discrimination and calibration. The C-index of internal validation was 0.795, which demonstrated good efficacy of the model.

CONCLUSIONS

This study suggests that our novel nomogram can accurately predict bleeding risk in AF patients after stent implantation during hospitalization, thereby helping to avoid complications. The nomogram may also be helpful for the creation of individualized post-discharge medication strategies.