VIABAHN® Stent Graft Implantation for Iatrogenic Arteriovenous Fistula and Pseudoaneurysm of the Deep Femoral Artery.

Femoral arteriovenous access is most commonly used in endovascular diagnosis and treatment. Complications arising during femoral arteriovenous access include hematoma, retroperitoneal hemorrhage, pseudoaneurysm, and arteriovenous fistula. A 66-year-old woman diagnosed with paroxysmal atrial fibrillation was treated with catheter ablation. This patient had a high femoral artery bifurcation, and we punctured the femoral vein by the conventional Merkmal method, which led to a femoral vein puncture through the deep femoral artery. The next day, echography revealed a pseudoaneurysm communicating with the deep femoral artery. We performed a thrombin injection without complication, and the pseudoaneurysm was occluded. However, echography three days after thrombin embolization showed a recurrence of the pseudoaneurysm and an arteriovenous fistula connecting to the common femoral vein. The first choice for the treatment of pseudoaneurysms and arteriovenous fistula is surgical treatment, but in addition to the lack of vascular surgery in our hospital, the patient did not want an invasive treatment and strongly preferred to be treated with a catheter. We performed endovascular treatment by VIABAHN® stent graft insertion. VIABAHN® stent graft was implanted at the deep femoral artery, and the patient was discharged without complications. VIABAHN® stent graft placement in the deep femoral artery sealed the entrance of the pseudoaneurysm and the arteriovenous fistula at once, which simultaneously treated both the pseudoaneurysm and AV fistula, and helped avoid the use of an invasive surgical procedure.

Underuse of heart failure medications and poor long-term prognosis in chronic heart failure patients with polypharmacy - A report from the CHART-2 study.

Background: In patients with chronic heart failure (CHF), comorbidities are often managed with multiple medications, characterized by polypharmacy, leading to increased risk of potentially inappropriate medication and adverse effects. Methods: We studied 4,876 consecutive patients with CHF (Stage C/D, age 69.0 ± 12.3 years) in the CHART-2 study to evaluate the association among polypharmacy, underuse of HF medications, and all-cause death. Polypharmacy was defined as the daily use of ≥ 8 medications for the survival classification and regression tree analysis. Results: The average number of medications was 10 in the polypharmacy group and 5 in the non-polypharmacy group, respectively. Over a median of 8.3 (4.1-11.7) years, the incidence rate of all-cause death was significantly higher in the polypharmacy group (n = 2,108) than in the non-polypharmacy group (57.3 % vs. 40.6 %; adjusted hazard ratio [aHR] 1.34 (95 %CI, 1.22-1.48), P < 0.001), even in age < 55 years (26.6 % vs. 14.3 %; adjusted hazard ratio [aHR] 1.61 (95 %CI, 1.04-2.50), P = 0.033). In patients with polypharmacy, those without renin-angiotensin system inhibitors (RAS-I) and/or beta-blockers (N = 1,023) were associated with increased incidence of all-cause death as compared with those with both medications (aHR 1.18; 95 %CI 1.04-1.35, P = 0.012). Conclusions: Polypharmacy was associated with poor long-term prognosis, even in younger patients with CHF. Among 4,876 patients with CHF, 1023 (20.9%) with polypharmacy and underuse of RAS-I and/or beta-blocker were associated with increased risk of all-cause death.

Prognostic impacts of serum uric acid levels in patients with chronic heart failure: insights from the CHART-2 study.

AIMS: Prognostic impacts of serum uric acid (UA) levels in patients with chronic heart failure (CHF) remain inconclusive, especially for the whole range of serum UA levels. METHODS AND RESULTS: In the Chronic Heart Failure Registry and Analysis in the Tohoku District-2 (CHART-2) study, we enrolled 4652 consecutive patients with CHF and classified them into four groups based on baseline serum UA levels by the Classification and Regression Tree: G1 (<3.8 mg/dL, N = 313), G2 (3.8-7.1 mg/dL, N = 3070), G3 (7.2-9.2 mg/dL, N = 1018), and G4 (>9.2 mg/dL, N = 251). Mean age was 71 ± 12, 69 ± 12, 68 ± 13, and 69 ± 15 years in G1, G2, G3, and G4, respectively (P < 0.001). During the median follow-up of 6.3 years, in G1, G2, G3, and G4, 111 (35%), 905 (29%), 370 (36%), and 139 (55%) patients died and 79 (25%), 729 (24%), 300 (29%), and 115 (46%) experienced heart failure hospitalization, respectively (both P < 0.001). G1 was characterized by a significantly high prevalence of women as compared with G2, G3, and G4 (59%, 32%, 24%, and 23%, respectively). Serum creatinine levels (0.8 ± 0.4, 0.9 ± 0.4, 1.2 ± 0.6, and 1.4 ± 0.8 mg/dL, respectively), prevalence of atrial fibrillation (34%, 39%, 45%, and 50%, respectively), and diuretics use (36%, 45%, 67%, and 89%, respectively) increased from G1, G2, G3 to G4 (all P < 0.001), while left ventricular ejection fraction decreased from G1, G2, G3 to G4 (59 ± 15, 58 ± 15, 54 ± 15, and 52 ± 17%, respectively, P < 0.001). Multivariable Cox proportional hazards models showed that, as compared with G2, both G1 and G4 had increased incidence of all-cause death [adjusted hazard ratio (aHR) 1.34, 95% confidence interval (CI) 1.08-1.67, P = 0.009; aHR 1.28, 95% CI 1.02-1.61, P = 0.037, respectively] and heart failure admission (aHR 1.39, 95% CI 1.09-1.78, P = 0.008 and aHR 1.35, 95% CI, 1.06-1.71, P = 0.014, respectively). This U-shaped relationship was evident in the elderly patients. Furthermore, abnormal transitions to either higher or lower levels of serum UA from G2 were associated with increased mortality (aHR 1.29, 95% CI 1.06-1.57, P = 0.012; aHR 1.57, 95% CI 1.12-2.20, P = 0.009). CONCLUSIONS: These results demonstrate that serum UA levels have the U-shaped prognostic effects and abnormal transitions to either higher or lower levels are associated with poor prognosis in the elderly patients with CHF.

Risk prediction for new-onset atrial fibrillation using the Minnesota code electrocardiography classification system.

BACKGROUND: Few risk models are available to predict future onset of atrial fibrillation (AF) in workers. We aimed to develop risk prediction models for new-onset AF, using annual health checkup (HC) data with electrocardiogram findings. METHODS AND RESULTS: We retrospectively included 56,288 factory or office workers (mean age = 51.5 years, 33.0% women) who underwent a HC at a medical center and fulfilled the following criteria; age ≥ 40 years, no history of AF, and greater than 1 annual follow-up HC in 2013-2016. Using Cox models with the Akaike information criterion, we developed and compared prediction models for new-onset AF with and without the Minnesota code information. We externally validated the discrimination accuracy of the models in a general Japanese population cohort, the Hisayama cohort. During the median 3.0-year follow-up, 209 (0.37%) workers developed AF. Age, sex, waist circumference, blood pressure, LDL cholesterol, and γ-GTP were associated with new-onset of AF. Using the Minnesota code information, the AUC significantly improved from 0.82 to 0.84 in the derivation cohort and numerically improved from 0.78 to 0.79 in the validation cohort, and from 0.77 to 0.79 in the Hisayama cohort. The NRI and IDI significantly improved in all and male subjects in both the derivation and validation cohorts, and in female subjects in both the validation and the Hisayama cohorts. CONCLUSIONS: We developed useful risk model with Minnesota code information for predicting new-onset AF from large worker population validated in the original and external cohorts, although study interpretation is limited by small improvement of AUC.

Temporal changes in left ventricular ejection fraction and their prognostic impacts in patients with Stage B heart failure.

BACKGROUND: We have recently demonstrated that left ventricular ejection fraction (LVEF) dynamically changes over time with prognostic impacts in Stage C/D patients, namely, those who have a current or past history of heart failure (HF). However, it is unknown whether this is also the case in asymptomatic Stage B patients, namely, those who have a risk of HF, but do not have a history of HF. METHODS: In our CHART-2 Study (N = 10,219), we enrolled 4005 Stage B patients and divided them into 3 groups by LVEF; preserved EF (pEF, LVEF ≥50%, N = 3526), mid-range EF (mrEF, LVEF 41-49%, N = 302), and reduced EF (rEF, LVEF ≤40%, N = 177). We examined the prognostic impacts of LVEF transitions among the 3 groups in comparison with 4477 patients with Stage C/D HF. RESULTS: Stage B were characterized by less severe clinical status and better prognosis compared with Stage C/D. Stage B in mrEF and rEF at baseline dynamically transitioned to other groups at 1-year, whereas those in pEF unchanged; at 1-year, mrEF transitioned to pEF/rEF by 50/16%, and rEF transitioned to pEF/mrEF by 25/31%, respectively, whereas pEF transitioned to mrEF/rEF by only 3.6/0.7%, respectively, which were consistent with findings in findings with Stage C/D. Although LVEF decrease was directly associated with all-cause mortality in both the Stage B and Stage C/D with pEF, factors related to LVEF changes were different between the 2 groups. CONCLUSIONS: In Stage B, LVEF dynamically changes with prognostic impacts as in Stage C/D, whereas different determination factors may be involved in the 2 stages. CLINICAL TRIAL REGISTRATION: Chronic Heart Failure Analysis and Registry in the Tohoku District (CHART)-2 (NCT00418041).

Prognostic impacts of dynamic cardiac structural changes in heart failure patients with preserved left ventricular ejection fraction.

AIMS: We aimed to examine temporal changes in left ventricular (LV) structures and their prognostic impacts in patients with heart failure (HF) and preserved ejection fraction (HFpEF). METHODS AND RESULTS: In the Chronic Heart Failure Analysis and Registry in the Tohoku District-2 (CHART-2) study (n = 10 219), we divided 2698 consecutive HFpEF patients (68.9 ± 12.2 years, 32.1% female) into three groups by LV hypertrophy (LVH) and enlargement (LVE) at baseline: (-)LVH/(-)LVE (n = 989), (+)LVH/(-)LVE (n = 1448), and (+)LVH/(+)LVE (n = 261). We examined temporal changes in LV structures and their prognostic impacts during a median 8.7-year follow-up. From (-)LVH/(-)LVE, (+)LVH/(-)LVE to (+)LVH/(+)LVE at baseline, the incidence of the primary outcome, a composite of cardiovascular death or HF admission, significantly increased. Among 1808 patients who underwent echocardiography at both baseline and 1 year, we noted substantial group transitions from baseline to 1 year; the transition rates from (-)LVH/(-)LVE to (+)LVH/(-)LVE, from (+)LVH/(-)LVE to (-)LVH/(-)LVE, from (+)LVH/(-)LVE to (+)LVH/(+)LVE, and from (+)LVH/(+)LVE to (+)LVH/(-)LVE were 27% (182/671), 22% (213/967), 6% (59/967), and 26% (44/170), respectively. In the univariable Cox proportional hazard model, patients who transitioned from (+)LVH/(-)LVE to (+)LVH/(+)LVE or remained in (+)LVH/(+)LVE had the worst subsequent prognosis [hazard ratio (HR) 4.65, 95% confidence interval (CI) 3.09-6.99, P < 0.001; HR 4.01, 95% CI 2.85-5.65, P < 0.001, respectively], as compared with those who remained in (-)LVH/(-)LVE. These results were unchanged after adjustment for the covariates including baseline LV ejection fraction (LVEF) and 1-year LVEF change. CONCLUSION: In HFpEF patients, LV structures dynamically change over time with significant prognostic impacts, where patients who develop LVE with LVH have the worst prognosis.

Clinical benefits and risks of antithrombotic therapy in patients with atrial fibrillation with comorbidities - A report from the CHART-2 Study.

BACKGROUND: The benefits of antithrombotic therapy (ATT) for atrial fibrillation (AF) are occasionally offset by major bleeding complications. However, the clinical benefits and risks of ATT in AF patients, with special references to comorbidities, such as heart failure (HF), coronary artery disease (CAD), and the patterns of AF, remain to be fully elucidated. METHODS: A total of 3221 consecutive AF patients from our Chronic Heart Failure Analysis and Registry in the Tohoku District-2 (CHART-2) Study (N = 10,219) were divided into 4 groups based on ATT at enrollment; no-ATT, anticoagulant alone, antiplatelet alone, and both of them (AC&AP). Then, efficacy and safety outcomes including thromboembolic events, major bleeding, and mortality were evaluated among the 4 groups. RESULTS: Anticoagulant monotherapy was associated with reduced risk of ischemic stroke in patients with but not in those without HF, CAD, or non-paroxysmal AF. Although there was no significant difference in major bleeding among the 4 groups, a composite of thromboembolism and major bleeding occurred more frequently in the AC&AP group, even in combination with anticoagulants and single antiplatelet therapy, indicating that the combination therapy is more harmful than anticoagulant monotherapy for AF patients, especially for those with HF or CAD. Lastly, no-ATT group was associated with worse prognosis compared with other 3 groups. CONCLUSIONS: These results indicate that ATT is beneficial for AF patients particularly for those with HF, CAD, or non-paroxysmal AF and that among ATT, anticoagulant monotherapy may be most profitable for both clinical benefits and risks for AF patients.

Risk of de-novo heart failure and competing risk in asymptomatic patients with structural heart diseases.

AIMS: Asymptomatic patients with structural heart diseases are classified as a population at high risk for heart failure (HF) in Stage B. However, limited data are available regarding incidence and related factors of de-novo HF (DNHF) considering competing risk in this population. METHODS AND RESULTS: In 3362 Stage B patients (mean age 68 yrs, male 76%) from the CHART-2 Study (N = 10,219), we examined incidence of death and DNHF, defined as the first episode of either HF hospitalization or HF death, and factors related to DNHF. RESULTS: During the median 6.0-year follow-up, 627 deaths (31/1000 person-years) and 293 DNHF (15/1000 person-years) occurred. Among the 627 deaths, 212 (34%) and 325 (52%) were specified as cardiovascular and non-cardiovascular deaths, respectively. During the follow-up of 271 DNHF hospitalizations, we observed 124 deaths, including 65 (52%) cardiovascular and 47 (40%) non-cardiovascular deaths. The competing risk model showed that age, diabetes mellitus, stroke, atrial fibrillation, diastolic blood pressure, hemoglobin levels, estimated glomerular filtration ratio and left ventricular ejection fraction was significantly associated with DNHF. Bayesian structural equation modeling showed that many of these cardiac and non-cardiac variables contribute to DNHF by affecting each other, while diabetes mellitus was independently associated with DNHF. CONCLUSIONS: Stage B patients had a high incidence of DNHF as well as that of death due to both cardiovascular and non-cardiovascular causes. Thus, management of Stage B patients should include multidisciplinary approaches considering both cardiac and non-cardiac factors, in order to prevent DNHF as well as non-HF death as a competing risk. TRIAL REGISTRATION: clinicaltrials.gov identifier: NCT00418041.

Clinical characteristics and prognostic factors in elderly patients with chronic heart failure -A report from the CHART-2 study.

BACKGROUND: Since most of the randomized clinical trials for heart failure (HF) were designed to exclude elderly patients, limited data are available on their clinical characteristics, prognosis, and prognostic factors. METHODS: We compared clinical characteristics, prognosis, and prognostic factors among Stage C/D HF patients in our CHART-2 Study (N = 4876, mean 69 years, women 32%, 6.3-year follow-up) by age (G1, ≤64 years, N = 1521; G2, 65-74 years, N = 1510; and G3, ≥75 years, N = 1845). RESULTS: From G1 to G3, the prevalence of women, left ventricular ejection fraction (LVEF) and plasma levels of B-type natriuretic peptide (BNP) increased (all P < 0.001). Similarly, 5-year mortality increased (9.9, 17.3 to 39.9%, P < 0.001) along with a decrease in proportion of cardiovascular death and an increase in non-cardiovascular death in both sexes. While all-cause and cardiovascular mortality was comparable between the sexes, women had significantly lower incidence of non-cardiovascular death than men in G2 and G3, which was attributable to the higher incidence of cancer death and pneumonia death in men than in women. Although NYHA functional class III-IV, chronic kidney disease, cancer, LVEF, and BNP had significant impacts on all-cause death in all groups, their impacts were less evident in G3 as compared with G1. CONCLUSIONS: The elderly HF patients, as compared with younger HF patients, were characterized by more severe clinical background, increased proportion of non-cardiovascular death and worse prognosis with different impacts of prognostic factors across the age groups.

Conversion formula from B-type natriuretic peptide to N-terminal proBNP values in patients with cardiovascular diseases.

BACKGROUND: Although B-type natriuretic peptide (BNP) and N-terminal prohormone B-type natriuretic peptide (NT-proBNP) are released in equimolar proportions, their values differ depending on clinical conditions. A useful conversion formula between BNP and NT-proBNP remains to be developed for the clinical use. AIM: To develop a conversion formula from BNP to NT-proBNP. METHODS: In the derivation cohort, 923 patients with chronic heart failure, in whom both BNP and NT-proBNP values were available, were enrolled from our SUPPORT (Supplemental Benefit of ARB in Hypertensive Patients with Stable Heart Failure using Olmesartan) trial. The validation cohort included 1154 consecutive patients with or at risk of cardiovascular diseases, in whom both BNP and NT-proBNP values were measured simultaneously at Tohoku University Hospital. We regressed log10 NT-proBNP onto log10 BNP and factors influencing BNP and NT-proBNP values. RESULTS: We adopted the model with the smallest Akaike information criterion consisting of log10 BNP, age, sex, BMI, creatinine clearance (CCr), hemoglobin, and atrial fibrillation (AF). As compared with the previously reported conversion formulas, the present conversion formula utilized non-linear transformation by spline function, and exhibited the strongest correlation between actual and calculated values of NT-proBNP (r = 0.928). The root mean squared error (RMSE) of the present conversion formula was smallest compared with the previously reported conversion formulas, indicating that this formula most effectively converts BNP values to NT-proBNP values. CONCLUSIONS: We have developed a useful conversion formula from BNP to NT-proBNP values, using age, sex, BMI, CCr, hemoglobin, and AF, which could be widely used in daily clinical practice.