Evaluating convolutional neural network-enhanced electrocardiography for hypertrophic cardiomyopathy detection in a specialized cardiovascular setting.

The efficacy of convolutional neural network (CNN)-enhanced electrocardiography (ECG) in detecting hypertrophic cardiomyopathy (HCM) and dilated HCM (dHCM) remains uncertain in real-world applications. This retrospective study analyzed data from 19,170 patients (including 140 HCM or dHCM) in the Shinken Database (2010-2017). We evaluated the sensitivity, positive predictive rate (PPR), and F1 score of CNN-enhanced ECG in a ''basic diagnosis'' model (total disease label) and a ''comprehensive diagnosis'' model (including disease subtypes). Using all-lead ECG in the "basic diagnosis" model, we observed a sensitivity of 76%, PPR of 2.9%, and F1 score of 0.056. These metrics improved in cases with a diagnostic probability of ≥ 0.9 and left ventricular hypertrophy (LVH) on ECG: 100% sensitivity, 8.6% PPR, and 0.158 F1 score. The ''comprehensive diagnosis'' model further enhanced these figures to 100%, 13.0%, and 0.230, respectively. Performance was broadly consistent across CNN models using different lead configurations, particularly when including leads viewing the lateral walls. While the precision of CNN models in detecting HCM or dHCM in real-world settings is initially low, it improves by targeting specific patient groups and integrating disease subtype models. The use of ECGs with fewer leads, especially those involving the lateral walls, appears comparably effective.

Descriptions of Etiology, Clinical Course, and Prognosis of Patients Presenting with Pericardial Effusion.

Pericardial effusion (PE) presentation varies from an incidental finding to a life-threatening situation; thus, its etiology and clinical course remain unknown. The aim of the present study was to retrospectively investigate these factors.We analyzed 171 patients (0.4%) who presented with PE among 34,873 patients who underwent echocardiography between 2011 and 2021 at our hospital. Clinical and prognostic information was retrieved from electronic medical records. The primary endpoints were all-cause death, hospitalization due to heart failure (HF), and other cardiovascular events such as cardiovascular death, acute coronary syndrome, elective percutaneous coronary intervention, and stroke.The etiologies of PE were as follows: idiopathic (32%), HF-related (18%), iatrogenic (11%), cardiac surgery-related (10%), radiation therapy-related (9%), malignancy (8%), pericarditis/myocarditis (8%), myocardial infarction-related (2%), and acute aortic dissection (2%). Patients with idiopathic/HF etiology were more likely to be older than the others.During a mean follow-up period of 2.5 years, all-cause death occurred in 21 patients (12.3%), cardiovascular events in 10 patients (5.8%), and hospitalization for HF in 24 patients (14.0%). All-cause death was frequently observed in patients with malignancy (44% per person-year). Cardiovascular events were mostly observed in patients with radiation therapy-related and malignancy (8.6% and 7.3% per person-year, respectively).The annual incidence of hospitalization for HF was the highest in patients with HF-related (25.1% per person-year), followed by radiation therapy-related (10.4% per person-year).This retrospective study is the first, to the best of our knowledge, to reveal the contemporary prevalence of PE, its cause, and outcome in patients who visited a cardiovascular hospital in an urban area of Japan.

Association between serum alkaline phosphatase and cardiovascular events in patients with atrial fibrillation.

High alkaline phosphatase (ALP) levels are reported to be associated with an increased risk of cardiovascular events in patients with chronic kidney disease (CKD). Given the pathological link with CKD, a similar relationship may exist in patients with atrial fibrillation (AF). We retrospectively evaluated 1,719 patients with AF and normal hepatic function who were registered in the Shinken Database between November 2011 and March 2017. Study patients were divided into three groups according to ALP value tertiles with cut-offs of 175 and 227 IU/L (normal range: 95-350 IU/L). Each group's incidence rate was recorded, and the risks of cardiovascular events and each component for patients in the middle and high ALP tertiles were compared with those in the low tertile and evaluated using Cox regression models. The additional predictive value of the high ALP tertile over the existing risk scores for the components of cardiovascular events was evaluated via receiver operating characteristic (ROC) curve analysis. During the median follow-up of 731 days (IQR: 444-1095 days), 137 cardiovascular events occurred, with incidence rates of 2.94%, 3.44%, and 6.19%/person-year for the low, middle, and high ALP tertiles, respectively. Of these cardiovascular events, heart failure had the highest incidence rates (1.34%, 1.89%, and 4.29%/person-year for the low, middle, and high ALP tertiles, respectively) and the incidence rates of the other components of cardiovascular event were similar in each ALP groups. Multivariate Cox regression analysis yielded hazard ratios of 1.22 (95% confidence interval [CI] 0.70-1.96) and 1.62 (95% CI 1.06-2.48) for cardiovascular events and 1.66 (95% CI 0.87-3.15) and 2.50 (95% CI 1.39-4.48) for heart failure admission in the middle and high ALP tertiles, respectively. By ROC curve analysis for heart failure admission showed that the high ALP tertile lacked significant additive predictive value over the existing risk scores. High serum ALP levels, even those in the normal range, were significantly associated with an increased risk of cardiovascular events, especially heart failure admission in patients with AF.

Glasgow prognostic score can be a prognostic indicator after percutaneous coronary intervention: a two-center study in Japan.

Glasgow prognostic score (GPS) has been used to evaluate inflammatory response and nutritional status. This study aimed to investigate the impact of nutritional status on cardiac prognosis by using GPS in patients after undergoing percutaneous coronary intervention (PCI). We included 862 patients who underwent PCI for stable angina pectoris between 2015 and 2018. We used the original cutoff values, which were an albumin (Alb) level of 3.5 g/dl and a C-reactive protein (CRP) level of 0.3 mg/dl. We categorized them into the three groups: originally defined GPS (od-GPS) 0 (high Alb and low CRP), 1 (low Alb or high CRP), and 2 (low Alb and high CRP). Major adverse clinical events (MACEs) included all-cause death, nonfatal myocardial infarction, revascularization, and hospitalization for heart failure. The median follow-up period was 398.5 days. During the follow-up, MACEs occurred in 136 patients. Od-GPS 2 had higher prevalence rates in terms of chronic kidney disease (CKD; 31.7% [229/722] vs. 44.9% [53/118] vs. 63.6% [14/22], p < 0.001), hemodialysis (6.4% [46/722] vs. 14.4% [17/118] vs. 31.8% [7/22], p < 0.001), and heart failure cases (HF; 9.1% [66/722] vs. 14.4% [17/118] vs. 27.3% [6/22], p = 0.007), with higher creatinine (1.17 ± 1.37 mg/dl vs. 1.89 ± 2.60 mg/dl vs. 3.49 ± 4.01 mg/dl, p < 0.001) and brain natriuretic peptide levels (104.1 ± 304.6 pg/ml vs. 242.4 ± 565.9 pg/ml vs. 668.1 ± 872.2 pg/ml, p < 0.001) and lower low-density lipoprotein cholesterol (101.5 ± 32.9 mg/dl vs. 98.2 ± 28.8 mg/dl vs. 77.1 ± 24.3 mg/dl, p = 0.002) than od-GPS 0 and 1.Od-GPS 2 (HR 2.42; 95% CI 1.16-5.02; p = 0.018), od-GPS 1 (HR 2.09; 95% CI 1.40-3.13; p < 0.001), diabetes (HR 1.41; 95% CI 1.00-1.99; p = 0.048), CKD (HR 2.10; 95% CI 1.49-2.96; p < 0.001), and HF (HR 1.64; 95% CI 1.05-2.56; p = 0.029) were independent predictors of MACEs. A scoring system using CRP and Alb levels with a milder definition than GPS suitably predicted the risk of MACEs in the patients who underwent PCI.

Relationship between resting 12-lead electrocardiogram and all-cause death in patients without structural heart disease: Shinken Database analysis.

BACKGROUND: Resting 12-lead electrocardiography is widely used for the detection of cardiac diseases. Electrocardiogram readings have been reported to be affected by aging and, therefore, can predict patient mortality. METHODS: A total of 12,837 patients without structural heart disease who underwent electrocardiography at baseline were identified in the Shinken Database among those registered between 2010 and 2017 (n = 19,170). Using 438 electrocardiography parameters, predictive models for all-cause death and cardiovascular (CV) death were developed by a support vector machine (SVM) algorithm. RESULTS: During the observation period of 320.4 days, 55 all-cause deaths and 23 CV deaths were observed. In the SVM prediction model, the mean c-statistics of 10 cross-validation models with training and testing datasets were 0.881 ± 0.027 and 0.927 ± 0.101, respectively, for all-cause death and 0.862 ± 0.029 and 0.897 ± 0.069, respectively for CV death. For both all-cause and CV death, high values of permutation importance in the ECG parameters were concentrated in the QRS complex and ST-T segment. CONCLUSIONS: Parameters acquired from 12-lead resting electrocardiography could be applied to predict the all-cause and CV deaths of patients without structural heart disease. The ECG parameters that greatly contributed to the prediction were concentrated in the QRS complex and ST-T segment.

Left atrial dimension and ischemic stroke in patients with and without atrial fibrillation.

The incidence of ischemic stroke (IS) increases in patients with enlarged left atrium (LA) irrespective of whether or not the existence of atrial fibrillation (AF). In such situation, it is unclear whether the impact of LA on incidence of IS still significant in young, non-AF patients with enlarged LA who are primarily unconcerned on anticoagulation therapy. The study population consisted of 18,511 consecutive patients not receiving oral anticoagulants and undergoing echocardiography with measurement of LAD at baseline. The incidence rate of ischemic stroke was calculated in 3 groups according to left atrial dimension (LAD; < 30, 30-45 and ≥ 45 mm) in AF and non-AF patients. Further subgroup analysis was performed in stratification by elderly and young (aged ≥ 65 and < 65 years, respectively). The incidences of IS (per 100 patient-years) were 0.11 and 0.71 in non-AF and AF patients with LAD < 30 mm, respectively, which increased to 0.58 and 1.35 in LAD ≥ 45 mm (adjusted hazard ratios [HRs]; 1.95 [95% confidence intervals, CIs: 0.76-5.01] and 1.22 [95% CIs: 0.27-5.58], interaction P was 0.246). In non-AF patients, the incidences of IS were 0.30 and 0.04 in elderly and young patients with LAD < 30 mm, which increased to 0.67 and 0.48 in LAD ≥ 45 mm (adjusted HRs; 1.34 [95% CIs: 0.43-4.15] and 4.21 [95% CIs: 0.77-23.12], interaction P was 0.158). The incidence of IS significantly increased with increase of LAD in non-AF, especially in non-AF and young patients, although the difference was not independent of other clinical factors. The impact of LAD on IS was numerically larger in non-AF than in AF, and larger in young and non-AF than in elderly counterpart, although a significant interaction was not observed in this small population. Further studies with large population are necessary to judge whether these population with enlarged LA need antithrombotic therapy.

Seasonal Variations in the Incidence of Ischemic Stroke, Extracranial and Intracranial Hemorrhage in Atrial Fibrillation Patients.

BACKGROUND: Ischemic stroke (IS) and major bleeding, which are serious adverse events in patients with atrial fibrillation (AF), could have seasonal variations, but there are few reports.Methods and Results:In the Shinken Database 2004-2016 (n=22,018), 3,581 AF patients (average age, 63.5 years; 2,656 men, 74.2%; 1,388 persistent AF, 38.8%) were identified. Median CHADS2and HAS-BLED scores were both 1 point. Oral anticoagulants were prescribed for 2,082 (58.1%) patients (warfarin, 1,214; direct oral anticoagulants [DOACs], 868). Incidence and observation period (maximum 3 years) of IS, extracranial hemorrhage (ECH), and intracranial hemorrhage (ICH) were counted separately for the northern hemisphere seasons. During the mean follow-up period of 2.4 years, there were totals of 90 IS, 73 ECH, and 33 ICH cases. The respective incidence rates per 1,000 patient-years in spring, summer, autumn, and winter were 8.5, 8.8, 7.5, and 16.8 for IS, 7.2, 9.7, 3.8, and 13.1 for ECH, and 2.7, 1.9, 3.8, and 7.0 for ICH. The number of patients with DOACs relatively increased among those with ECH in summer. CONCLUSIONS: Significant seasonal variations were observed for IS, ECH, and ICH events in AF patients, and were consistently the highest in winter. A small peak of ECH was observed in summer, which seemed, in part, to be related to increased DOAC use.

Clinical Differences of Recent Myocardial Infarction Compared With Acute Myocardial Infarction　- Insights From the Tokyo CCU Network Multicenter Registry.

BACKGROUND: Characteristics and treatment outcomes of acute myocardial infarction (AMI) patients have been studied; however, those of recent myocardial infarction (RMI) patients remain unclear. This study aimed to clarify characteristics, treatment strategy, and in-hospital outcomes of RMI patients in the Tokyo CCU network database.Methods and Results:In total, 1,853 RMI and 12,494 AMI patients from the Tokyo CCU network database during 2013-2016 were compared. Both RMI and AMI were redefined by onset times of 2-28 days and ≤24 h, respectively. The RMI group had a higher average age (70.4±12.9 vs. 68.0±13.4 years, P<0.001), more women (27.6% vs. 23.6%, P<0.001), lower proportion of patients with chest pain as the chief complaint (75.2% vs. 83.6%, P<0.001), higher prevalence of diabetes mellitus (35.9% vs. 31.0%, P<0.001), and higher mechanical complication incidence (3.0% vs. 1.5%, P<0.001) than did the AMI group. Thirty-day mortality was comparable (5.3% vs. 5.8%, P=0.360); major causes of death were cardiogenic shock and mechanical complications in the AMI and RMI groups, respectively. Death from mechanical complications (not onset time) in the AMI group plateaued almost 1 week after hospitalization, whereas it continued to increase in the RMI group. CONCLUSIONS: Both RMI and AMI patients have distinctive clinical features, sequelae, and causes of death. Although treatment of RMI patients adhered to guidelines, it was insufficient, and death from mechanical complications continues to increase.

Empagliflozin attenuates neointimal hyperplasia after drug-eluting-stent implantation in patients with type 2 diabetes.

The effects of empagliflozin, a sodium-glucose co-transporter 2 inhibitor, on neointimal response after drug-eluting-stent (DES) implantation remains unknown. Insufficiently controlled diabetes patients with coronary artery disease planned for DES stenting were consecutively enrolled. The patients were assigned to receive empagliflozin in addition to standard therapy or intensive therapy using other glucose-lowering drugs (oGLD). The primary endpoint was thickness of neointimal hyperplasia (NIH) 12 months after stenting assessed by optical coherence tomography (OCT). A total of 28 patients were analyzed (n = 15 in the empagliflozin group, n = 13 in the oGLD group). The levels of glucose profile were not significantly different between both groups at follow-up [HbA1c; 7.2 ± 0.8 vs 7.3 ± 0.9%, p = 0.46]. In OCT analysis, neointima was significantly less in the empagliflozin group than the oGLD group [mean NIH thickness: 137 ± 32 vs 168 ± 39 µm, p = 0.02]. Changes of systolic and diastolic blood pressure (BP), changes of body mass index, and changes of hematocrit after additional treatment were significantly associated with NIH attenuation, whereas no correlation was observed in changes in blood glucose parameters. Multivariate logistic regression analysis revealed that changes in systolic BP was the strongest predictor for NIH attenuation, followed by changes in diastolic BP. In patients with type 2 diabetes, standard plus empagliflozin attenuated neointimal progression as compared with intensive standard therapy after DES implantation. Our data possibly support a beneficial effect of empagliflozin in type 2 diabetes required for coronary revascularization therapy.

Differences in treatment and prognosis by the experience of falls or bone fracture in elderly patients with atrial fibrillation.

Treatment and prognosis of elderly patients with atrial fibrillation (AF) may differ by the experience of fall or bone fracture. However, their current status is still unclear. From our institute database between 2010 and 2015, 674 AF patients with age ≥ 70 years were selected and were divided into those who experienced fall or fracture during the observation period (F/F group; n = 49) and those who did not (non-F/F group; n = 625). We compared the treatment and prognosis between the 2 groups. Patients in the F/F group were older (79 vs 76 years, P < 0.001) and had more comorbidities compared with those in the non-F/F group. The prescription rate of oral anticoagulant was similar between the two groups (77.6% vs 68.2%, P = 0.201), where warfarin was predominant. The F/F group was not associated with higher incidence of ischemic stroke. The F/F group was associated with a higher incidence of heart failure events (adjusted odds ratio (OR) 3.88; 95% confidence intervals (Cl) 1.70-8.85; P = 0.001), and cardiovascular events (OR 3.43; 95% Cl 1.71-6.85; P < 0.001). In elderly AF patients in a cardiovascular hospital, the experience of fall or fracture did not affect the prescription of oral anticoagulants and the incidence of ischemic stroke, but it was significantly associated with increase of heart failure.

Rural-Urban Disparity in Emergency Care for Acute Myocardial Infarction in Japan.

BACKGROUND: There are few reports examining regional differences between rural prefectures and metropolitan areas in the management of acute myocardial infarction (AMI) in Japan.Methods and Results:In the Rural AMI registry, a prospective, multi-prefectural registry of AMI in 4 rural prefectures (Ishikawa, Aomori, Ehime and Mie), a total of 1,695 consecutive AMI patients were registered in 2013. Among them, 1,313 patients who underwent primary percutaneous coronary intervention (PPCI) within 24 h of onset were enrolled in this study (Rural group), and compared with the cohort data from the Tokyo CCU Network registry for AMI in the same period (Metropolitan group, 2,075 patients). The prevalence of direct ambulance transport to PCI-capable facilities in the Rural group was significantly lower than that in the Metropolitan group (43.8% vs. 60.3%, P<0.01), which resulted in a longer onset-to-balloon time (OTB: 225 vs. 210 min, P=0.02) and lower prevalence of PPCI in a timely fashion (OTB ≤2 h: 11.5% vs. 20.7%, P<0.01) in the Rural group. Multivariate analysis revealed that direct ambulance transport was the strongest predictor for PPCI in a timely fashion (odds ratio=4.13, P<0.001). CONCLUSIONS: AMI patients in rural areas were less likely to be transported directly to PCI-capable facilities, resulting in time delay to PPCI compared with those in metropolitan areas.

Identifying patients with acute aortic dissection using an electrocardiogram with convolutional neural network.

Background: The potential of utilizing artificial intelligence with electrocardiography (ECG) for initial screening of aortic dissection (AD) is promising. However, achieving a high positive predictive rate (PPR) remains challenging. Methods and results: This retrospective analysis of a single-center, prospective cohort study (Shinken Database 2010-2017, N = 19,170) used digital 12-lead ECGs from initial patient visits. We assessed a convolutional neural network (CNN) model's performance for AD detection with eight-lead (I, II, and V1-6), single-lead, and double-lead (I, II) ECGs via five-fold cross-validation. The mean age was 63.5 ± 12.5 years for the AD group (n = 147) and 58.1 ± 15.7 years for the non-AD group (n = 19,023). The CNN model achieved an area under the curve (AUC) of 0.936 (standard deviation [SD]: 0.023) for AD detection with eight-lead ECGs. In the entire cohort, the PPR was 7 %, with 126 out of 147 AD cases correctly diagnosed (sensitivity 86 %). When applied to patients with D-dimer levels ≥1 µg/dL and a history of hypertension, the PPR increased to 35 %, with 113 AD cases correctly identified (sensitivity 86 %). The single V1 lead displayed the highest diagnostic performance (AUC: 0.933, SD: 0.03), with PPR improvement from 8 % to 38 % within the same population. Conclusions: Our CNN model using ECG data for AD detection achieved an over 30% PPR when applied to patients with elevated D-dimer levels and hypertension history while maintaining sensitivity. A similar level of performance was observed with a single-lead V1 ECG in the CNN model.

Lead-Specific Performance for Atrial Fibrillation Detection in Convolutional Neural Network Models Using Sinus Rhythm Electrocardiography.

Background: We developed a convolutional neural network (CNN) model to detect atrial fibrillation (AF) using the sinus rhythm ECG (SR-ECG). However, the diagnostic performance of the CNN model based on different ECG leads remains unclear. Methods and Results: In this retrospective analysis of a single-center, prospective cohort study, we identified 616 AF cases and 3,412 SR cases for the modeling dataset among new patients (n=19,170). The modeling dataset included SR-ECGs obtained within 31 days from AF-ECGs in AF cases and SR cases with follow-up ≥1,095 days. We evaluated the CNN model's performance for AF detection using 8-lead (I, II, and V1-6), single-lead, and double-lead ECGs through 5-fold cross-validation. The CNN model achieved an area under the curve (AUC) of 0.872 (95% confidence interval (CI): 0.856-0.888) and an odds ratio of 15.24 (95% CI: 12.42-18.72) for AF detection using the eight-lead ECG. Among the single-lead and double-lead ECGs, the double-lead ECG using leads I and V1 yielded an AUC of 0.871 (95% CI: 0.856-0.886) with an odds ratio of 14.34 (95% CI: 11.64-17.67). Conclusions: We assessed the performance of a CNN model for detecting AF using eight-lead, single-lead, and double-lead SR-ECGs. The model's performance with a double-lead (I, V1) ECG was comparable to that of the 8-lead ECG, suggesting its potential as an alternative for AF screening using SR-ECG.

Clinical features and predictors of non-cardiac death in patients hospitalised for acute myocardial infarction: Insights from the Tokyo CCU network multicentre registry.

BACKGROUND: Patients with acute myocardial infarction (AMI) commonly have multiple comorbidities, and some die in hospitals due to causes other than cardiac complications. However, limited information is available on noncardiac death in patients hospitalised for AMI. Therefore, the present study was performed to determine the incidence, annual trend, clinical characteristics, and predictors of in-hospital non-cardiac death in patients with AMI using the Tokyo Cardiovascular Care Unit (CCU) network registry. METHODS: The registry included 38,589 consecutive patients with AMI who were admitted to the CCU between 2010 and 2019. The primary endpoint was in-hospital noncardiac death. Further, predictors of cardiac and non-cardiac death were identified. RESULTS: The incidence of all-cause in-hospital mortality was 7.0% (n = 2700), and the proportion of mortality was 15.6% (n = 420) and 84.4% (n = 2280) for noncardiac and cardiac causes, respectively. The proportion of noncardiac deaths did not change annually over the last decade (p = 0.66). After adjusting for all variables, age, Killip classification grade, peak creatine kinase, hemoglobin, serum creatinine, and C-reactive protein were common predictors of cardiac and non-cardiac deaths. Indicators of malnutrition, such as lower body mass index (kg/m2) [odds 0.94, 95%CI (0.90-0.97), p < 0.001] and serum low-density lipoprotein cholesterol level (per 10 mg/dl) [odds 0.92, 95%CI (0.89-0.96), p < 0.001] were the specific predictors for non-cardiac deaths. CONCLUSIONS: The incidence of in-hospital noncardiac death was significant in patients with AMI, accounting for 15.6% of all in-hospital mortalities. Thus, prevention and management of non-cardiac complications are vital to improve acute-phase outcomes, especially those with predictors of non-cardiac death.

Identification of patients with dilated phase of hypertrophic cardiomyopathy using a convolutional neural network applied to multiple, dual, and single lead electrocardiograms.

Background: This study sought to develop an artificial intelligence-derived model to detect the dilated phase of hypertrophic cardiomyopathy (dHCM) on digital electrocardiography (ECG) and to evaluate the performance of the model applied to multiple-lead or single-lead ECG. Methods: This is a retrospective analysis using a single-center prospective cohort study (Shinken Database 2010-2017, n = 19,170). After excluding those without a normal P wave on index ECG (n = 1,831) and adding dHCM patients registered before 2009 (n = 39), 17,378 digital ECGs were used. Totally 54 dHCM patients were identified of which 11 diagnosed at baseline, 4 developed during the time course, and 39 registered before 2009. The performance of the convolutional neural network (CNN) model for detecting dHCM was evaluated using eight-lead (I, II, and V1-6), single-lead, and double-lead (I, II) ECGs with the five-fold cross validation method. Results: The area under the curve (AUC) of the CNN model to detect dHCM (n = 54) with eight-lead ECG was 0.929 (standard deviation [SD]: 0.025) and the odds ratio was 38.64 (SD 9.10). Among the single-lead and double-lead ECGs, the AUC was highest with the single lead of V5 (0.953 [SD: 0.038]), with an odds ratio of 58.89 (SD:68.56). Conclusion: Compared with the performance of eight-lead ECG, the most similar performance was achieved with the model with a single V5 lead, suggesting that this single-lead ECG can be an alternative to eight-lead ECG for the screening of dHCM.

10-Year Temporal Trends of In-Hospital Mortality and Emergency Percutaneous Coronary Intervention for Acute Myocardial Infarction.

Background: The mortality rate of acute myocardial infarction (AMI) has improved dramatically because of reperfusion therapy during the last 40 years; however, recent temporal trends for AMI have not been fully clarified in Japan. Objectives: The purpose of this study was to elucidate the temporary trend in in-hospital mortality and treatment of AMI for the last decade in the Tokyo Metropolitan area. Methods: We enrolled 30,553 patients from the Tokyo Cardiovascular Care Unit Network Registry, diagnosed with AMI from 2007 to 2016, as part of an ongoing, multicenter, cohort study. We analyzed the temporal trends in basic characteristics, treatment, and in-hospital mortality of AMI. Results: The overall emergency percutaneous coronary intervention (PCI) rate significantly increased (P < 0.001). In particular, it remarkably increased in patients older than 80 years of age (58.3% to 70.3%, P < 0.001) and patients with Killip III or IV (Killip III, 46.9% to 65.7%; Killip IV, 65.2% to 76.6%, P < 0.001 for both). The crude and age-adjusted in-hospital mortality remained low (5.2% to 8.2% and 3.4% to 5.5%, respectively) and significantly decreased during the decade (P < 0.001). The in-hospital mortality remarkably decreased in patients older than 80 years of age (17.3% to 12.7%, P < 0.001) and in those with cardiogenic shock (38.5% to 27.3%, P < 0.001). Conclusions: This large cohort study from Tokyo revealed that in-hospital mortality of AMI significantly decreased with the increase in emergency percutaneous coronary intervention rate over the decade, particularly for high-risk patients such as older patients and those with cardiogenic shock.

Relationship between number of medications and incidence of falls or bone fracture in elderly patients with non-valvular atrial fibrillation: Shinken database analysis.

AIM: Polypharmacy is known to be a risk factor for falls or bone fracture (F/F) in elderly patients. However, this relationship is not fully described in patients with non-valvular atrial fibrillation (NVAF), for which F/F may lead to serious clinical outcomes, including major bleeding. METHODS: We analyzed 509 elderly (aged ≥75 years) patients with NVAF who had recently visited a hospital specializing in cardiology, of which 272 patients had paroxysmal atrial fibrillation (PAF) and 237 had persistent/permanent atrial fibrillation (PeAF). Patients were divided into four groups according to the number of medications: ≤3, 4-6, 7-9, and ≥10. The relationship between the number of medications and incidence rate of F/F in AF patients was analyzed. In addition, this relationship was analyzed in patients with each AF type. RESULTS: Cumulative incidence of F/F at 3 years in the respective categories was 3.7%, 5.4%, 4.3% and 5.7% for PAF, and 5.2%, 7.5%, 7.8% and 25.0% for PeAF (log-rank test, P = 0.930 and 0.003, respectively). In a multivariable model, patients with ≥10 medications showed a significantly higher risk for F/F compared with those with ≤3 medications as reference only in PeAF (adjusted hazard ratio 4.82, 95%CI 1.42-16.33), without significant interaction (P = 0.081). CONCLUSIONS: Elderly NVAF patients using ≥10 medications showed a higher risk for F/F. In subgroup analysis, this association was observed only in patients with PeAF, although there was no significant interaction between number of medications and AF type. Geriatr Gerontol Int 2021; 21: 802-809.

Association between number of medications and mortality among older adult patients in a specialized cardiology hospital.

AIM: Although polypharmacy has been associated with poor clinical outcomes, whether taking an increased number of medications is harmful or beneficial for older adult patients treated for cardiovascular diseases might require further discussion. METHODS: We analyzed data of 2089 patients aged ≥75 years in a single hospital-based cohort. The study population was divided into three groups according to the tertiles of the number of medications at baseline: <3 (n = 647), 3-7 (n = 707) and ≥8 (n = 735). RESULTS: The cumulative incidences of all-cause death at 3 years among patients taking less than three, three to seven and eight or more medications were 3.7%, 4.1% and 7.8%, respectively (log-rank test P = 0.015). In a Cox regression analysis, taking eight or more total medications (vs 0-2) was independently associated with all-cause death (hazard ratio 1.67, 95% CI 1.01-2.78). For predicting mortality using the number of medications, the maximum Youden Index was 7. In subgroups with certain heart diseases, no regular tendency of an increase in the risk of all-cause death was observed with an increase in the number of medications. CONCLUSIONS: The number of medications taken was independently associated with mortality among older adult patients, with a relatively high cut-off point. This association was not observed in patients with certain heart diseases, possibly indicating the merit - rather than the harm - of medical treatment in the cardiovascular field. Geriatr Gerontol Int 2021; 21: 985-995.

Identifying risk patterns in older adults with atrial fibrillation by hierarchical cluster analysis: A retrospective approach based on the risk probability for clinical events.

BACKGROUND: Older adults with atrial fibrillation (AF) have highly diverse risk levels for mortality, heart failure (HF), thromboembolism (TE), and major bleeding (MB), thus an integrated risk-pattern algorithm is warranted. METHODS: We analyzed 573 AF patients aged ≥ 75 years from our single-center cohort (Shinken Database 2010-2018). The 3-year risk scores (risk probability) for mortality (M-score), HF (HF-score), TE (TE-score), and MB (MB-score) were estimated for each patient by logistic regression analysis. Using the four risk scores, cluster analysis was performed with Ward's linkage hierarchical algorithm. RESULTS: Three clusters were identified: Clusters 1 (n = 429, 74%), 2 (n = 24, 5%), and 3 (n = 120, 21%). The clusters were characterized as standard risk (Cluster 1), high TE- and MB-risk (Cluster 2), and high M- and HF-risk (Cluster 3). Oral anticoagulants were prescribed for over 80% of the patients in each cluster. Catheter ablation for AF was performed only in Cluster 1 (8.9%). Compared with Cluster 1, Cluster 2 was more closely associated with males, asymptomatic AF, history of cerebral infarction or transient ischemic attack, history of intracranial hemorrhage, high HAS-BLED score (≥3), and low body mass index (<18.0 kg/m2). Cluster 3 was more closely associated with old age, heart failure, and low estimated creatinine clearance (<30 mL/min). CONCLUSION: The cluster analysis identified those at a high risk for all-cause death and HF or a high risk for TE and MB and could support decision making in older adults with AF.

Prediction of current and new development of atrial fibrillation on electrocardiogram with sinus rhythm in patients without structural heart disease.

BACKGROUND: Diagnosis of atrial fibrillation (AF) based on electrocardiogram (ECG) with sinus rhythm remains a major challenge. Obtaining a panoramic view with hundreds of automatically measured ECG parameters at sinus rhythm on the predictive capability for AF would be informative. METHODS: We used a single-center database of a specialist cardiovascular hospital (Shinken Database 2010-2017; n = 19,170). We analyzed 12,863 index ECGs with sinus rhythm after excluding those showing AF rhythm, other atrial tachyarrhythmia, pacing beat, or indeterminate axis, and those of patients with structural heart diseases. We used 438 automatically measured ECG parameters in the MUSE data management system. The predictive models were developed using random forest algorithm with the 10-fold cross-validation method. RESULTS: In 12,863 index ECGs with sinus rhythm, a predictive capability for current paroxysmal AF (n = 1131) by c-statistics was 0.99981 ± 0.00037 for training dataset and 0.91337 ± 0.00087 for testing dataset, respectively. Excluding AF at baseline (n = 11,732), a predictive capability for newly developed AF (n = 98) by c-statistics was 0.99973 ± 0.00086 for training dataset and 0.99160 ± 0.00038 for testing dataset, respectively. The distribution of parameter importance was mostly similar among P, QRS, and ST-T segment for both current and newly developed AF. CONCLUSIONS: This study intended to provide panoramic information in relation between ECG parameters and AF. The parameter importance of ECG parameters for predicting AF was mostly similar in P, QRS, and ST-T segment in models for both current and future AF.