P6448Major cardiovascular events free survival in the long term follow up of “real world” diabetic patients with stable coronary artery disease at the beginning of the 21st century. The CICCOR Registry

Background

Safety trials of antidiabetic drugs have included a main endpoint of cardiovascular morbidity and mortality. However, “real world” data on long term prognosis of diabetic patients with stable coronary artery disease (sCAD) are limited. This study aimed to assess long-term incidence of major cardiovascular events in this population and to identify clinical predictors of this end-point.

Methods

The CICCOR registry is a prospective, monocentric, cohort study. From February 1, 2000 to January 31, 2004, all consecutive patients with sCAD attended at two outpatient cardiology clinics in a city of the south of Spain were included in the study and prospectively followed. Patients with type 2 diabetes mellitus were selected for this analysis. None of these patients received sodium-glucose cotransporter-2 inhibitors at first visit, as they were not commercially available at that time. Survival free of major cardiovascular events (combined end-point: acute myocardial infarction, stroke, or cardiovascular death) and variables associated with this end-point were investigated.

Results

The study sample included 394 patients (mean age 68±9 years, 61% male). After up to 17 years of follow-up (median 9 years, IQR 4–14 years, only 2 patients lost in follow-up, with a total of 3517 patients-years of observation), 66 had an acute myocardial infarction, 55 had an stroke and 165 died for cardiovascular causes. Survival free of major cardiovascular events was 88%, 70%, 57%, 47% and 32% at 3, 6, 9, 12 and 15 years. Multivariate predictors of the combined end-point are shown in the table.

Predictors of major cardiovascular event Variable Hazard Ratio (95% CI) p value Age (year) 1.06 (1.04–1.08) <0.0005 Tobacco use 0.02 Never smoker 1 (reference) Ex-smoker 1.43 (1.02–1.99) 0.04 Active smoker 2.23 (1.16–4.30) 0.02 Functional Class ≥II (angina) 1.57 (1.14–2.16) 0.006 Resting heart rate (10 bpm increase) 1.12 (1.01–1.24) 0.04 Diuretic treatment at first visit 1.71 (1.26–2.30) 0.001

Conclusions

Probability of major event-free survival was only 47% at 12 years in this “real world” cohort of diabetic patients with sCAD followed in the first 17 years of this century in a single center in the south of Spain. Simple clinical variables can identify patients at higher risk of events.

Acknowledgement/Funding

This work has been partially financed by an investigational grant by Boehringher Ingelheim

P2525Relationship of Charlson Comorbidity Index with adverse events in elderly patients with Acute Coronary Syndromes: an analysis from LONGEVO-SCA Registry

Background

Elderly patients with Acute Coronary Syndromes (ACS) are under-represented in clinical trials and they have higher risk of new due their comorbidities. Charlson Comorbidity Index (CCI) is an established tool for evaluating the burden of comorbidity status and a high score of CCI is related with an increased risk of death.

Purpose

The aim of this study was to analyze the relationship of CCI in adverse outcomes at short-term follow-up in elderly patients admitted by an ACS.

Methods

The prospective multicenter LONGEVO-SCA included unselected elderly patients (≥80 years old) hospitalized after non-STACS. In this substudy, we analyze the influence of comorbidities, comparing the relationship between quartiles of CCI and adverse events at 6 months follow-up of CCI.

Results

We analyzed 520 patients (mean age 84.4±3.6 years; 320 (61.5%) male). 196 (37.6%) were classified into Q1, 105 (20.2%) into Q2, 93 (17.9%) into Q3 and 126 (24.2%) into Q4. No differences were observed in treatment at discharge across different quartiles for aspirin (p=0.648), beta-blockers (p=0.908) or statins (p=0.756). We observed a significant increase for all-cause mortality [9 (4.8%) vs 10 (10.2%) vs 11 (12.0%) vs 32 (26.0%); p<0.001] and readmissions [36 (18.4%) vs 21 (20%) vs 33 (35.5%) vs 48 (38.1%); p<0.001] respectively from Q1 to Q4. After Cox multivariate regression analysis, CCI was independently associated with mortality or readmissions [HR 1.15, 95% CI (1.06–1.26); p=0.001] and patients into high quartile had 6-fold risk of mortality [HR 6.19, 95% CI (2.95–12.99); p<0.001]. Kaplan Meier analysis showed that patients in the highest quartiles had significantly worse prognosis during the follow-up with high risk of all-cause mortality and readmissions (both p<0.001).

Event Free Survival according Charlson

Conclusions

In LONGEVO-SCA registry, we validated for the first time CCI as an independent factor related with adverse events. Patients into high quartiles of CCI had significantly worse prognosis during the follow-up and elderly patients into Q4 had 6-fold risk of mortality compared to Q1 patients.

P3612Validation of Charlson Comorbidity Index to predict adverse events in elderly patients with Atrial Fibrillation and Acute Coronary Syndrome: an analysis from LONGEVO-SCA Registry

Background

Aging is frequently characterized by the coexistence of several comorbid conditions that increase the adverse prognosis during hospitalization. There are few scores to analyze the impact of comorbidities in prognosis. Charlson Comorbidity Index (CCI). This score evaluates the burden of comorbidity in general population but the influence within cardiac diseases is unknown.

Purpose

The aim of this study was to analyze the relationship of CCI in adverse outcomes at short-term follow-up in elderly patients with atrial fibrillation (AF) admitted after an acute coronary syndrome (ACS).

Methods

The prospective multicenter LONGEVO-SCA included unselected elderly patients hospitalized after non-STACS. In this substudy, we analyze the influence of comorbidities in elderly AF patients, comparing high quartiles of CCI (Q3-Q4: high burden of comorbidities) to low quartiles (Q1-Q2) and the predictive performance of adverse events at 6 months follow-up of CCI.

Results

We analyzed 531 patients (mean age 84.4±3.6 years; 322 (60.6%) male). 128 (24.1%) had AF diagnosis. 91 (71.1%) patients were classified into Q1-Q2 and 37 (28.9%) patients into Q3-Q4. We analyzed the association of clinical factors and adverse events and, after Cox multivariate regression analysis, CCI was independently associated with readmissions [HR 1.19, 95% CI (1.02–1.39); p=0.020) and all-cause mortality [HR 1.32, 95% CI (1.09–1.59); p=0.003]. Patients into Q3-Q4 had higher risk of mortality than patients into Q1-Q2 [HR 5.52, 95% CI (1.01–30.3); p=0.049]. Kaplan Meier analysis showed that AF patients into Q3-Q4 had significantly worse prognosis during the follow-up with high risk of all-cause mortality (p=0.034) and readmissions due to ACS (p=0.027). We observed good predictive performance of CCI for mortality (c-statistic 0.705; p<0.001) and modest predictive performance for readmissions (c-statistic 0.627; p<0.001).

Event Free Survival according Charlson

Conclusions

Patients into high quartiles of CCI had higher risk of adverse events during the follow-up. CCI was an independent predictor of all-cause mortality and readmissions in elderly patients. Indeed, this is the first time to validate CCI to predict adverse events in AF patients with ACS.

P2530Frailty assessment in atrial fibrillation patients with acute coronary syndromes: a subanalysis from LONGEVO-SCA registry

Background

Different studies have observed a significant correlation between frailty, morbidity and mortality in elderly patients with cardiovascular diseases.Several scores have been developed to assess frailty in elderly patients. The FRAIL scale is a bed-side and easy tool that evaluates 5 items: fatigue, resistance, ambulation, concomitant diseases and weight loss. However, the evaluation of frailty status in AF patients with ACS is scarce.

Purpose

The aim of this study was to analyze the management of elderly patients with AF and ACS and the predictive value of frailty for adverse events.

Methods

The prospective multicentre LONGEVO-SCA enrolled unselected elderly patients hospitalized after non-STACS. In this substudy, we divided patients according to rhythm status (AF or sinus rhythm [SR]) and to frail status. We validated the predictive performance of FRAIL scores for adverse events at 6 months follow-up.

Results

We analyzed 531 patients (mean age 84.4±3.6 years; 322 (60.6%) male). 128 (24.1%) had AF diagnosis and 145 (27.3%) patients were frail. Frail AF patients had higher risk of global mortality [HR 2.61, (95% CI 1.28–5.31; p=0.008)], readmissions [HR 2.28, (95% CI 1.37–3.80); p=0.002)] and the composite endpoint [HR 2.28, (95% CI 1.44–3.60); p<0.001)] compared with non-frail SR patients. After multivariate adjustment, Frail score [HR 1.41; 95% CI (1.02–1.97); p=0.040] was independently associated with mortality. Kaplan Meier analysis showed that frail AF patients had significantly worse prognosis during the follow-up with high risk of global mortality (log rank p=0.024) and readmission (log rank p<0.001) followed closely by those frail SR patients.

Event Free Survival according Frailty

Conclusions

In the LONGEVO-SCA registry, frail AF patients have 2-fold risk of adverse events compared to non-frail SR patients. Frailty status was an independent condition associated with high risk of adverse events at 6 months of follow-up.

P1752Impact of frailty addition in ischemic and bleeding risk scores in elderly patients with Atrial Fibrillation and Acute Coronary Syndrome: a subanalysis from LONGEVO-SCA registry

Background

The prevalence of Atrial Fibrillation (AF) and Acute Coronary Syndrome (ACS) increases with age. Frail older adults are at high risk of multiple adverse events during admission and short term mortality. FRAIL score is an easy tool that evaluates: fatigue, resistance, ambulation, concomitant diseases and weight loss.

Purpose

The aim of this study was to validate FRAIL score in AF elderly patients with ACS related to adverse events and the impact of its addition in clinical scores.

Methods

The prospective multicenter LONGEVO-SCA enrolled unselected elderly patients hospitalized after non-STACS. We analyzed the predictive performance of FRAIL score in AF subgroup for adverse events (primary endpoint mortality or readmission) and the impact of frailty addition in ischaemic and bleeding scores.

Results

We analyzed 531 patients. 128 (24.1%) of them have AF (main age 84.6±3.7 years; 78 (61%) male) and 27.3% were frail (defined by FRAIL score ≥3). Frail AF patients had more prevalent comorbidities and received less evidence-based ACS therapies at discharge as oral anticoagulation (66% vs 60%; p<0.001) or statins 96.3% vs 82.6%; p<0.001). We analyzed the predictive performance of FRAIL score to adverse events and observed a modest predictive performance for mortality (c-statistic 0.648; 95% CI [0.605–0.690]; p<0.001), readmissions (c-statistic 0.600; 95% CI [0.557–0.642]; p<0.001) and for composite endpoint (c-statistic 0.620; 95% CI [0.577–0.663]; p<0.001). We compared the addition of FRAIL score to the original risk scores and observed a significant improvement for the primary endpoint with the addition to CHA2DS2-Vasc score (p=0.009), GRACE (p<0.001) and CRUSADE scores (p<0.001). (Table)

C-indexes for mortality or readmissions C-index 95% CI p p* Z* CHA2DS2-VASc score 0.619 0.576 to 0.662 <0.001 0.009 2.586 CHA2DS2-VASc score + FRAIL 0.641 0.598 to 0.683 <0.001 HAS-BLED score 0.649 0.606 to 0.691 <0.001 0.445 0.764 HAS-BLED score + FRAIL 0.634 0.590 to 0.675 <0.001 GRACE score 0.599 0.554 to 0.644 0.006 0.001 3.930 GRACE score + FRAIL 0.602 0.556 to 0.646 <0.001 CRUSADE score 0.660 0.613 to 0.705 0.051 0.001 3.287 CRUSADE score + FRAIL 0.664 0.617 to 0.709 <0.001 CI: Confidence interval. *For c-index comparison. p: P value.

Conclusions

This is the first validation of the FRAIL score in AF patients under ACS with a modest predictive performance to adverse events. The addition of frailty to clinical scores improved the predictive performance to adverse events in AF patients.