Smoking and Provision of Smoking Cessation Interventions among Inpatients with Acute Coronary Syndrome in China: Findings from the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome Project

Utilizing EMR Data for Smoking Behavior Surveillance in Hospitalized Patients With Chronic Respiratory Diseases and Its Impact on Clinical Outcomes - Beijing Municipality, China, 2014-2023

What is already known on this topic?

Smoking is the primary risk factor for a poor prognosis in chronic respiratory disease (CRD). Current tobacco surveillance efforts in China focus on the general population and do not adequately cover CRD patients.

What is added by this report?

We employed electronic medical records (EMR) to track smoking habits in 28,334 hospitalized CRD patients at Beijing Chao-Yang Hospital. The rates of former and current smokers were 30.7% and 18.0%, respectively. Both former and current smokers exhibited an increased risk of respiratory symptoms and extended hospital stays.

What are the implications for public health practice?

These results underscore the importance of implementing smoking monitoring and targeted cessation interventions for hospitalized patients with CRDs.

In-hospital mortality of patients with acute coronary syndrome (ACS) after implementation of national health insurance (NHI) in Indonesia

BACKGROUND

The National Health Insurance (NHI) was implemented in Indonesia in 2014, and cardiovascular diseases are one of the diseases that have overburdened the healthcare system. However, data concerning the relationship between NHI and cardiovascular healthcare in Indonesia are scarce. We aimed to describe changes in cardiovascular healthcare after the implementation of the NHI while determining whether the implementation of the NHI is related to the in-hospital mortality of patients with acute coronary syndrome (ACS).

METHODS

This is a retrospective comparative study of two cohorts in which we compared the data of 364 patients with ACS from 2013 to 2014 (Cohort 1), before and early after NHI implementation, with those of 1142 patients with ACS from 2018 to 2020 (Cohort 2), four years after NHI initiation, at a tertiary cardiac center in Makassar, Indonesia. We analyzed the differences between both cohorts using chi-square test and Mann-Whitney U test. To determine the association between NHI and in-hospital mortality, we conducted multivariable logistic regression analysis.

RESULTS

We observed an increase in NHI users (20.1% to 95.6%, p < 0.001) accompanied by a more than threefold increase in patients with ACS admitted to the hospital in Cohort 2 (from 364 to 1142, p < 0.001). More patients with ACS received invasive treatment in Cohort 2, with both thrombolysis and percutaneous coronary intervention (PCI) rates increasing more than twofold (9.2% to 19.2%; p < 0.001). There was a 50.8% decrease in overall in-hospital mortality between Cohort 1 and Cohort 2 (p < 0.001).

CONCLUSIONS

This study indicated the potential beneficial effect of universal health coverage (UHC) in improving cardiovascular healthcare by providing more accessible treatment. It can provide evidence to urge the Indonesian government and other low- and middle-income nations dealing with cardiovascular health challenges to adopt and prioritize UHC.

Characteristics, Treatment, and In-Hospital Outcomes of Older Patients With STEMI Without Standard Modifiable Risk Factors

Background

Strategies targeting standard modifiable cardiovascular risk factors (SMuRFs), including hypertension, diabetes, hypercholesterolemia, and smoking, have been well established to prevent coronary heart disease. However, few studies have evaluated the management and outcomes of older patients without SMuRFs after myocardial infarction.

Objectives

The authors sought to evaluate the profile of patients with ST-segment elevation myocardial infarction (STEMI) aged ≥75 years without SMuRFs.

Methods

This study is based on the CCC-ACS (Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome) project. Patients aged ≥75 years with a first presentation of STEMI were enrolled in this study between November 2014 and December 2019. Modified Poisson regression was used to evaluate the association between SMuRF-less and in-hospital outcomes.

Results

Among 10,775 patients with STEMI aged ≥75 years, 1,633 (15.16%) had no SMuRFs. Compared with those with SMuRF, SMuRF-less patients received less evidence-based treatment. In-hospital mortality was similar among patients with and without SMuRFs (5.44% vs 5.14%; P = 0.630). However, after adjustment for patient characteristics and treatment, being SMuRF-less was significantly associated with a reduced risk of mortality (RR: 0.80; 95% CI: 0.65-0.99; P = 0.043). SMuRF-less patients also had a significantly reduced risk of in-hospital death when only adjusting for in-hospital treatment (RR: 0.78; 95% CI: 0.63-0.98; P = 0.030), regardless of patient characteristics.

Conclusions

Approximately 1 in 7 STEMI patients in China ≥75 years old had no SMuRFs. The similar mortality in patients with and without SMuRF can be partially explained by the inadequate in-hospital treatment of SMuRF-less patients. The quality of care for older patients without SMuRF should be improved. (CCC Project-Acture Coronary Syndrome; NCT02306616).

Supra-Normal Left Ventricular Ejection Fraction as a Prognostic Marker for Long-Term Outcomes in Patients with Acute Coronary Syndrome

Recently, the supra-normal left ventricular ejection fraction (snLVEF) has been proposed, based on extensive datasets indicating increased all-cause mortality in individuals with an LVEF exceeding 65%. However, the implications of an LVEF > 65% in the context of acute coronary syndrome (ACS) remain underexplored.The aim of the present study was to investigate the correlation between supra-normal left ventricular ejection fraction (snLVEF) and major adverse cardiovascular events (MACE) in patients with ACS.Methods: A total of 874 ACS patients (560 men, mean age 59.5 ± 10.0; 314 women, mean age 61.5 ± 8.9) who underwent their first coronary angiography during the period from March 2013 to October 2015 were divided into 2 groups: normal LVEF (nLVEF) (55% ≤ EF ≤ 65%) and snLVEF (EF > 65%), according to their echocardiography results. The patients were evaluated for MACE after surgery by collecting clinical data and long-term follow-up data. This correlation was further analyzed by Kaplan-Meier analysis and Cox regression analysis.The follow-up data revealed a significantly higher incidence of MACE among snLVEF patients compared to the nLVEF group (15.6% versus 7.4%; P = 0.020). This heightened risk persisted even after adjustment for multiple variables, indicating a strong association between snLVEF and increased MACE risk (HR: 2.346; 95% CI: 1.196-4.602; P = 0.013).SnLVEF was independently associated with poor prognosis after ACS. Enhanced management strategies for snLVEF patients could potentially reduce the incidence of MACE in ACS patients.

Development of a nomogram based on pericoronary adipose tissue histogram parameters to differentially diagnose acute coronary syndrome

PURPOSE

To develop a nomogram based on pericoronary adipose tissue (PCAT) histogram parameters to identify patients with acute coronary syndrome (ACS).

MATERIALS AND METHODS

This study retrospectively enrolled 114 and 383 eligible patients with ACS and stable coronary artery disease (CAD), respectively, and divided them into training and testing cohorts in a 7:3 ratio. A blinded radiologist obtained PCAT histogram parameters from the right coronary artery's proximal segment using fully automated software and compared clinical characteristics and PCAT histogram parameters between the two patient groups. The binary logistic regression included significant parameters (P < 0.05), and a nomogram was constructed.

RESULTS

In both the training and testing cohorts, the mean, 10th percentile, 90th percentile, median, and minimum values of PCAT were higher, and the interquartile range, skewness, and variance values of PCAT were lower in patients with ACS than in those with stable CAD (P ≤ 0.001). The mean (OR = 4.007), median (OR = 0.576), minimum (OR = 0.893), skewness (OR = 85,158.806) and variance (OR = 1.013) values of PCAT were independent risk factors for ACS and stable CAD in the training cohort. The nomogram was constructed using the five variables mentioned above with area under the curve values of 0.903 and 0.897, respectively, while the calibration and decision curves showed the nomogram's good clinical efficacy for the training and testing cohorts.

CONCLUSIONS

The constructed nomogram had good discrimination and accuracy and can be a noninvasive tool to intuitively and individually distinguish between ACS and stable CAD.

Revisiting the Smoking Paradox in Acute Ischemic Stroke Patients: Findings From the Chinese Stroke Center Alliance Study

Background Smoking is a well-established risk factor for the development of acute ischemic stroke (AIS). However, the "smoker's paradox" suggests that it is associated with favorable clinical outcomes following stroke. We aimed to reevaluate the association between smoking and in-hospital outcomes in patients with AIS in contemporary practice. Methods and Results A total of 649 610 inpatients with AIS from 1476 participating hospitals in the Chinese Stroke Center Alliance were included. In-hospital outcomes measurement included all-cause mortality, discharge against medical advice, and complications. Multivariable logistic regression models adjusting for baseline characteristics, clinical profiles at presentation, and in-hospital management were used to evaluate the association between smoking and in-hospital outcomes. A propensity score-matched analysis was also conducted. Of these patients with AIS, 36.8% (n=238 912) were smokers. Smokers were younger, had fewer comorbidities, and had slightly lower rates of adverse in-hospital outcomes than nonsmokers (all-cause death or discharge against medical advice: 6.0% versus 6.1%; in-hospital complications: 14.5% versus 15.1%). Multivariable analysis revealed that smoking was associated with higher risk of adverse in-hospital outcomes (all-cause death or discharge against medical advice: odds ratio [OR], 1.05 [95% CI, 1.02-1.08]; P<0.001; complications: OR, 1.06 [95% CI, 1.04-1.08]; P<0.001). The excess risk of adverse in-hospital outcomes remained in smoking patients with AIS after propensity score-matching analysis (all-cause death or discharge against medical advice: OR, 1.04 [95% CI, 1.00-1.08]; P=0.034; complications: OR, 1.05 [95% CI, 1.03-1.08]; P<0.001). Conclusions Smoking was associated with increased risk of adverse in-hospital outcomes among patients with AIS in contemporary practice, reinforcing the importance of smoking cessation in patients with AIS.

Stroke Learning Health Systems: A Topical Narrative Review With Case Examples

To our knowledge, the adoption of Learning Health System (LHS) concepts or approaches for improving stroke care, patient outcomes, and value have not previously been summarized. This topical review provides a summary of the published evidence about LHSs applied to stroke, and case examples applied to different aspects of stroke care from high and low-to-middle income countries. Our attempt to systematically identify the relevant literature and obtain real-world examples demonstrated the dissemination gaps, the lack of learning and action for many of the related LHS concepts across the continuum of care but also elucidated the opportunity for continued dialogue on how to study and scale LHS advances. In the field of stroke, we found only a few published examples of LHSs and health systems globally implementing some selected LHS concepts, but the term is not common. A major barrier to identifying relevant LHS examples in stroke may be the lack of an agreed taxonomy or terminology for classification. We acknowledge that health service delivery settings that leverage many of the LHS concepts do so operationally and the lessons learned are not shared in peer-reviewed literature. It is likely that this topical review will further stimulate the stroke community to disseminate related activities and use keywords such as learning health system so that the evidence base can be more readily identified.

In-hospital risk stratification algorithm of Asian elderly patients

Limited research has been conducted in Asian elderly patients (aged 65 years and above) for in-hospital mortality prediction after an ST-segment elevation myocardial infarction (STEMI) using Deep Learning (DL) and Machine Learning (ML). We used DL and ML to predict in-hospital mortality in Asian elderly STEMI patients and compared it to a conventional risk score for myocardial infraction outcomes. Malaysia's National Cardiovascular Disease Registry comprises an ethnically diverse Asian elderly population (3991 patients). 50 variables helped in establishing the in-hospital death prediction model. The TIMI score was used to predict mortality using DL and feature selection methods from ML algorithms. The main performance metric was the area under the receiver operating characteristic curve (AUC). The DL and ML model constructed using ML feature selection outperforms the conventional risk scoring score, TIMI (AUC 0.75). DL built from ML features (AUC ranging from 0.93 to 0.95) outscored DL built from all features (AUC 0.93). The TIMI score underestimates mortality in the elderly. TIMI predicts 18.4% higher mortality than the DL algorithm (44.7%). All ML feature selection algorithms identify age, fasting blood glucose, heart rate, Killip class, oral hypoglycemic agent, systolic blood pressure, and total cholesterol as common predictors of mortality in the elderly. In a multi-ethnic population, DL outperformed the TIMI risk score in classifying elderly STEMI patients. ML improves death prediction by identifying separate characteristics in older Asian populations. Continuous testing and validation will improve future risk classification, management, and results.

An Intelligent Individualized Cardiovascular App for Risk Elimination (iCARE) for Individuals With Coronary Heart Disease: Development and Usability Testing Analysis

Background

Death and disability from coronary heart disease (CHD) can be largely reduced by improving risk factor management. However, adhering to evidence-based recommendations is challenging and requires interventions at the level of the patient, provider, and health system.

Objective

The aim of this study was to develop an Intelligent Individualized Cardiovascular App for Risk Elimination (iCARE) to facilitate adherence to health behaviors and preventive medications, and to test the usability of iCARE.

Methods

We developed iCARE based on a user-centered design approach, which included 4 phases: (1) function design, (2) iterative design, (3) expert inspections and walkthroughs of the prototypes, and (4) usability testing with end users. The usability testing of iCARE included 2 stages: stage I, which included a task analysis and a usability evaluation (January to March 2019) of the iCARE patient app using the modified Health Information Technology Usability Survey (Health-ITUES); and stage II (June 2020), which used the Health-ITUES among end users who used the app for 6 months. The end users were individuals with a confirmed diagnosis of CHD from 2 university-affiliated hospitals in Beijing, China.

Results

iCARE consists of a patient app, a care provider app, and a cloud platform. It has a set of algorithms that trigger tailored feedback and can send individualized interventions based on data from initial assessment and health monitoring via manual entry or wearable devices. For stage I usability testing, 88 hospitalized patients (72% [63/88] male; mean age 60 [SD 9.9] years) with CHD were included in the study. The mean score of the usability testing was 90.1 (interquartile range 83.3-99.0). Among enrolled participants, 90% (79/88) were satisfied with iCARE; 94% (83/88) and 82% (72/88) reported that iCARE was useful and easy to use, respectively. For stage II usability testing, 61 individuals with CHD (85% [52/61] male; mean age 53 [SD 8.2] years) who were from an intervention arm and used iCARE for at least six months were included. The mean total score on usability testing based on the questionnaire was 89.0 (interquartile distance: 77.0-99.5). Among enrolled participants, 89% (54/61) were satisfied with the use of iCARE, 93% (57/61) perceived it as useful, and 70% (43/61) as easy to use.

Conclusions

This study developed an intelligent, individualized, evidence-based, and theory-driven app (iCARE) to improve patients’ adherence to health behaviors and medication management. iCARE was identified to be highly acceptable, useful, and easy to use among individuals with a diagnosis of CHD.

Trial Registration

Chinese Clinical Trial Registry ChiCTR-INR-16010242; https://tinyurl.com/2p8bkrew