Rates, Predictors, and Impact of Smoking Cessation after Stroke or Transient Ischemic Attack: A Systematic Review and Meta-Analysis

Development and validation of a clinical prediction model for ischemic stroke recurrence after successful stent implantation in symptomatic intracranial atherosclerotic stenosis

OBJECTIVE

This study aimed to analyze the risk factors for recurrent ischemic stroke in patients with symptomatic intracranial atherosclerotic stenosis (ICAS) who underwent successful stent placement and to establish a nomogram prediction model.

METHODS

We utilized data from a prospective collection of 430 consecutive patients at Jining NO.1 People's Hospital from November 2021 to November 2022, conducting further analysis on the subset of 400 patients who met the inclusion criteria. They were further divided into training (n=321) and validation (n=79) groups. In the training group, we used univariate and multivariate COX regression to find independent risk factors for recurrent stroke and then created a nomogram. The assessment of the nomogram's discrimination and calibration was performed through the examination of various measures including the Consistency index (C-index), the area under the receiver operating characteristic (ROC) curves (AUC), and the calibration plots. Decision curve analysis (DCA) was used to evaluate the clinical utility of the nomogram by quantifying the net benefit to the patient under different threshold probabilities.

RESULTS

The nomogram for predicting recurrent ischemic stroke in symptomatic ICAS patients after stent placement utilizes six variables: coronary heart disease (CHD), smoking, multiple ICAS, systolic blood pressure (SBP), in-stent restenosis (ISR), and fasting plasma glucose. The C-index (0.884 for the training cohort and 0.87 for the validation cohort) and the time-dependent AUC (>0.7) indicated satisfactory discriminative ability of the nomogram. Furthermore, DCA indicated a clinical net benefit from the nomogram.

CONCLUSIONS

The predictive model constructed includes six predictive factors: CHD, smoking, multiple ICAS, SBP, ISR and fasting blood glucose. The model demonstrates good predictive ability and can be utilized to predict ischemic stroke recurrence in patients with symptomatic ICAS after successful stent placement.

Impact of a Medical Fitness Model on Incident Major Adverse Cardiovascular Events: A Prospective Cohort Study of 11 000 Members

BACKGROUND

Cardiovascular disease remains the leading cause of disease burden and death in the world. The medical fitness model may be an alternative public health strategy to address cardiovascular risk factors with medical integrated programming.

METHODS AND RESULTS

We performed a retrospective cohort study between January 1, 2005, and December 31, 2015. Adults (aged ≥18 years) who did not have a prior major adverse cardiovascular event were included. Controls were assigned a pseudo-index date at random on the basis of the frequency distribution of start dates in the medical fitness facility group. Multivariate Cox proportional hazards regression models were adjusted for age, sex, socioeconomic status, comorbidities, and year of index date. We stratified the medical fitness facility group into low-frequency attenders (≤1 weekly visit) and regular-frequency attenders (>1 weekly visit). Our primary outcome was a hospitalization for nonfatal myocardial infarction and stroke, heart failure, or cardiovascular death. We included 11 319 medical fitness facility members and 507 400 controls in our study. Compared with controls, members had a lower hazard risk of a major adverse cardiovascular event-plus (hazard ratio [HR], 0.88 [95% CI, 0.81-0.96]). Higher weekly attendance was associated with a lower hazard risk of a major adverse cardiovascular event-plus compared with controls, but the effect was not significant for lower weekly attendance (low-frequency attenders: HR, 0.94 [95% CI, 0.85-1.04]; regular-frequency attenders: HR, 0.77 [95% CI, 0.67-0.89]).

CONCLUSIONS

Medical fitness facility membership and attendance at least once per week may lower the risk of a major adverse cardiovascular event-plus. The medical fitness model should be considered as a public health intervention, especially for individuals at risk for cardiovascular disease.

Smoking cessation behavior in patients with a diagnosis of a non-communicable disease: The impact of perceived disease severity of and susceptibility to the disease

INTRODUCTION

The Health Belief Model comprises two constructs influencing changed behaviors impacting on health, namely perceived severity and susceptibility. The aim of this study was to identify the impact of the combination of, or interactions between, these two constructs on quitting smoking in smokers with a diagnosis of a non-communicable disease (NCD).

METHODS

From the large insurance claims database maintained by JMDC database (JMDC, Tokyo), we extracted data on 13284 participants who smoked. All participants were stratified according to their NCD diagnosis based on perceived severity and susceptibility as follows: Category I (high severity and high susceptibility) - acute myocardial infarction, and lung cancer; Category II (high severity and low susceptibility) - colorectal cancer, and stomach cancer; Category III (low severity and high susceptibility) - asthma, and transient ischemic attack; Category IV (low severity and low susceptibility) - appendicitis, and glaucoma. We performed multi-variable logistic regression analysis and calculated the proportion of those who were smoking at the first health check-up after the diagnosis and every three years thereafter.

RESULTS

Using glaucoma as the reference, the adjusted odds ratios for smoking cessation were 14.2 (95% CI: 11.4-17.8) to 14.8 (95% CI: 12.5-17.4) in Category I; 4.5 (95% CI: 3.8-5.4) to 6.6 (95% CI: 5.4-8.0) in Category II; and 1.9 (95% CI: 1.7-2.1) to 2.8 (95% CI: 2.2-3.7) in Category III. In Categories I and II, the proportion of smokers rapidly decreased after diagnosis and mostly remained low thereafter. Smoking cessation rates for Categories I and II were not associated with readiness to improve lifestyles prior to NCD diagnosis.

CONCLUSIONS

Our study confirms the significant impact of perceived severity of and susceptibility to the diagnosed disease on smoking cessation. The multiplicative effect of these two constructs at NCD diagnosis represents a 'teachable moment', a window of opportunity, for encouraging successful long-term smoking cessation.

Development and validation of a nomogram model for predicting unfavorable functional outcomes in ischemic stroke patients after acute phase

Introduction

Prediction of post-stroke functional outcome is important for personalized rehabilitation treatment, we aimed to develop an effective nomogram for predicting long-term unfavorable functional outcomes in ischemic stroke patients after acute phase.

Methods

We retrospectively analyzed clinical data, rehabilitation data, and longitudinal follow-up data from ischemic stroke patients who underwent early rehabilitation at multiple centers in China. An unfavorable functional outcome was defined as a modified Rankin Scale (mRS) score of 3-6 at 90 days after onset. Patients were randomly allocated to either a training or test cohort in a ratio of 4:1. Univariate and multivariate logistic regression analyses were used to identify the predictors for the development of a predictive nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive ability in both the training and test cohorts.

Results

A total of 856 patients (training cohort: n = 684; test cohort: n = 172) were included in this study. Among them, 518 patients experienced unfavorable outcomes 90 days after ischemic stroke. Trial of ORG 10172 in Acute Stroke Treatment classification (p = 0.024), antihypertensive agents use [odds ratio (OR) = 1.86; p = 0.041], 15-day Barthel Index score (OR = 0.930; p < 0.001) and 15-day mRS score (OR = 13.494; p < 0.001) were selected as predictors for the unfavorable outcome nomogram. The nomogram model showed good predictive performance in both the training (AUC = 0.950) and test cohorts (AUC = 0.942).

Conclusion

The constructed nomogram model could be a practical tool for predicting unfavorable functional outcomes in ischemic stroke patients underwent early rehabilitation after acute phase.

A methodological framework allows the identification of personomic markers to consider when designing personalized interventions

OBJECTIVES

To develop a methodological framework to identify and prioritize personomic markers (e.g., psychosocial situation, beliefs…) to consider for personalizing interventions and to test in smoking cessation interventions.

STUDY DESIGN AND SETTING

(1) We identified potential personomic markers considered in protocols of personalized interventions, in reviews of predictors of smoking cessation, and in interviews with general practitioners. (2) Physicians, and patient smokers or former smokers selected the markers they considered most relevant during online paired comparison experiments. Data were analyzed with Bradley Terry Luce models.

RESULTS

Thirty-six personomic markers were identified from research evidence. They were evaluated by 795 physicians (median age: 34, IQR [30-38]; 95% general practitioners) and 793 patients (median age: 54, IQR [42-64], 71.4% former smokers) during 11,963 paired comparisons. Physicians identified patients' motivation for quitting (e.g., Prochaska stages), patients' preferences, and patients' fears and beliefs (e.g., concerns about weight gain) as the most relevant elements to personalize smoking cessation. Patients considered their motivation for quitting, smoking behavior (e.g., smoking at home/at work), and tobacco dependence (e.g., Fagerström Test) as the most relevant elements to consider.

CONCLUSION

We provide a methodological framework to prioritize which personomic markers should be considered when developing smoking cessation interventions.

Predictors of smoking cessation outcomes identified by machine learning: A systematic review

This systematic review aims to characterize the utility of machine learning to identify the predictors of smoking cessation outcomes and identify the machine learning methods applied in this area. In the current study, multiple searches occurred through December 9, 2022 in MEDLINE, Science Citation Index, Social Science Citation Index, EMBASE, CINAHL Plus, APA PsycINFO, PubMed, Cochrane Central Register of Controlled Trials, and the IEEE Xplore were performed. Inclusion criteria included various machine learning techniques, studies reporting cigarette smoking cessation outcomes (smoking status and the number of cigarettes), and various experimental designs (e.g., cross-sectional and longitudinal). Predictors of smoking cessation outcomes were assessed, including behavioral markers, biomarkers, and other predictors. Our systematic review identified 12 papers fitting our inclusion criteria. In this review, we identified gaps in knowledge and innovation opportunities for machine learning research in the field of smoking cessation.

Post-stroke cardiovascular management: Current concepts, integrated care and future developments

After an ischaemic stroke patients often have cardiovascular complications known as stroke-heart syndrome. The cardiovascular management after stroke has a significant impact on life expectancy as well as the quality of life. The development and implementation of management pathways to improve outcomes for patients with stroke-heart syndrome requires a multidisciplinary involvement from health care professionals from primary, secondary and tertiary prevention levels. A holistic, integrated care approach could follow the ABC pathway: A) Appropriate antithrombotic therapy in all stroke/TIA patients in the acute phase as well as recommendations for the longer term treatment regimen are required to avoid recurrent stroke. B) For better functional and psychological status the assessment of post-stroke cognitive and physical impairment, depression, and anxiety as part of routine post-stroke work-up in every patient is necessary. C) Cardiovascular risk factors and comorbidities management further includes cardiovascular work-up, adapted drug therapy, but often also lifestyle changes that are central to the success of integrated care for stroke-heart syndrome. Greater patient and family/caregiver involvement in planning actions and the input and feedback on optimizing stroke care pathways is needed. Achieving integrated care is challenging and highly context dependent on different healthcare levels. A tailored approach will utilize a variety of enabling factors. In this narrative review, we summarize the current evidence and outline potential factors that will contribute to the successful implementation of integrated cardiovascular care for stroke-heart syndrome management.

Cost-Effectiveness of Smoking Cessation Interventions in Patients With Ischemic Stroke and Transient Ischemic Attack

BACKGROUND

Smoking cessation rates after stroke and transient ischemic attack are suboptimal, and smoking cessation interventions are underutilized. We performed a cost-effectiveness analysis of smoking cessation interventions in this population.

METHODS

We constructed a decision tree and used Markov models that aimed to assess the cost-effectiveness of varenicline, any pharmacotherapy with intensive counseling, and monetary incentives, compared with brief counseling alone in the secondary stroke prevention setting. Payer and societal costs of interventions and outcomes were modeled. The outcomes were recurrent stroke, myocardial infarction, and death using a lifetime horizon. Estimates and variance for the base case (35% cessation), costs and effectiveness of interventions, and outcome rates were imputed from the stroke literature. We calculated incremental cost-effectiveness ratios and incremental net monetary benefits. An intervention was considered cost-effective if the incremental cost-effectiveness ratio was less than the willingness-to-pay threshold of $100 000 per quality-adjusted life-year (QALY) or when the incremental net monetary benefit was positive. Probabilistic Monte Carlo simulations modeled the impact of parameter uncertainty.

RESULTS

From the payer perspective, varenicline and pharmacotherapy with intensive counseling were associated with more QALYs (0.67 and 1.00, respectively) at less total lifetime costs compared with brief counseling alone. Monetary incentives were associated with 0.71 more QALYs at an additional cost of $120 compared with brief counseling alone, yielding an incremental cost-effectiveness ratio of $168/QALY. From the societal perspective, all 3 interventions provided more QALYs at less total costs compared with brief counseling alone. In 10 000 Monte Carlo simulations, all 3 smoking cessation interventions were cost-effective in >89% of runs.

CONCLUSIONS

For secondary stroke prevention, it is cost-effective and potentially cost-saving to deliver smoking cessation therapy beyond brief counseling alone.

Change in Smoking Behavior and Outcome After Ischemic Stroke: Post-Hoc Analysis of the SPS3 Trial

BACKGROUND

Cigarette smoking is a known risk factor for cardiovascular disease, including ischemic stroke. The literature regarding the rate of persistent smoking after acute ischemic stroke and its effect on subsequent cardiovascular events is scarce. With this study, we aimed to report the rate of persistent smoking after ischemic stroke and the association between smoking status and major cardiovascular outcomes.

METHODS

This is a post-hoc analysis of the SPS3 trial (Secondary Prevention of Small Subcortical Strokes). Patients were divided into 4 groups based on smoking status at trial enrollment: (1) never smokers, (2) former smokers, (3) smokers who quit at 3 months, and (4) persistent smokers. The primary outcome is a major adverse cardiovascular events composite of stroke (ischemic and hemorrhagic), myocardial infarction, and mortality. Outcomes were adjudicated after month 3 of enrollment until an outcome event or the end of study follow-up.

RESULTS

A total of 2874 patients were included in the study. Of the total cohort, 570 patients (20%) were smokers at enrollment, of whom 408 (71.5%) patients continued to smoke and 162 (28.4%) quit smoking by 3 months. The major adverse cardiovascular events outcome occurred in 18.4%, 12.4%, 16.2%, and 14.4%, respectively, in persistent smokers, smokers who quit, prior smokers, and never smokers. In a model adjusted for age, sex, race, ethnicity, education, employment status, history of hypertension, diabetes, hyperlipidemia, myocardial infarction, and intensive blood pressure randomization arm, the risk of major adverse cardiovascular events, and death were higher in the persistent smokers compared with never smokers (HR for major adverse cardiovascular events: 1.56 [95% CI, 1.16-2.09]; HR for death: 2.0 [95% CI, 2.18-3.12]). The risk of stroke, and MI did not differ according to smoking status Conclusions: Compared with never smoking, persistent smoking after acute ischemic stroke was associated with an increased risk of cardiovascular events and death.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT00059306.

Factors associated with successful smoking cessation in men with or without cardiovascular disease or cancer: Nationwide Korean population analysis

INTRODUCTION

This study was conducted to explore factors associated with smoking cessation in male smokers with cardiovascular disease (CVD) or cancer, the two leading causes of death worldwide, and to compare them with quitting factors in smokers without the two diseases.

METHODS

This is a secondary dataset analysis of the Korea National Health and Nutrition Examination Survey (KNHANES), nationally representative data from 2008-2019 (excluding 2013-2014), and included 12998 men without CVD or cancer (group without CVD or cancer), 1027 men with CVD (CVD group), and 616 men with cancer (cancer group). A Wald test with multiple logistic regression analysis was conducted.

RESULTS

The quitting success rates in the CVD and cancer groups were consistently higher than those in the group without CVD or cancer. Old age and willpower in the CVD group, and old age and being married in the cancer group were associated with quitting success. Secondhand smoking and methods of quitting other than willpower were related to quitting failure in both groups. When interaction effects between the groups were examined, household income was the only factor associated with successful cessation in the group without CVD or cancer (AOR=1.17, 1.18, and 1.40, among the second, third, and fourth highest income quartiles, respectively; p for interaction=0.023). Higher smoking amounts (AOR=0.85; p<0.001) and poor health perception (AOR=0.64; p=0.035) were associated with quitting failure in the group without CVD or cancer. However, no significant factor was detected related to smoking cessation in both the CVD and cancer groups when the interaction effect was investigated.

CONCLUSIONS

The quitting success rates in the CVD and cancer groups were higher, but no disease-specific quitting factors were identified. Therefore, being diagnosed with CVD or cancer itself could be inferred as a motive for quitting smoking.

Practice Current: Variability in Smoking Cessation Intervention Practice Patterns After Ischemic Stroke and Transient Ischemic Attack

People who continue to smoke after ischemic stroke and transient ischemic attack (TIA) are at increased risk for subsequent stroke and cardiovascular events. Although effective smoking cessation strategies exist, smoking rates after stroke remain high. Through case-based discussions with 3 international vascular neurology panelists, this article seeks to explore practice patterns and barriers to smoking cessation for patients with stroke/TIA. We sought to answer these questions: What are the barriers to using smoking cessation interventions for patients with stroke/TIA? Which interventions are most used for hospitalized patients with stroke/TIA? Which interventions are most used for patients who continue smoking during follow-up? Our synthesis of panelists' commentaries is complemented by the preliminary results of an online survey posed to global readership. Together, the interviews and survey results identify practice variability and barriers to smoking cessation after stroke/TIA, suggesting that there is substantial need for research and standardization.

Uptake of prescription smoking cessation pharmacotherapies after hospitalization for major cardiovascular disease

AIMS

We determined the prevalence of prescription smoking cessation pharmacotherapy (SCP) use after hospitalization for major cardiovascular disease (MCD) among people who smoke and whether this varies by sex.

METHODS AND RESULTS

We conducted a population-based cohort study including all people hospitalized in New South Wales, Australia, between July 2013 and December 2018 (2017 for private hospitals) with an MCD diagnosis. For patients who also had a diagnosis of current tobacco use, we used linked pharmaceutical dispensing records to identify prescription SCP dispensings within 90 days post-discharge. We determined the proportion who were dispensed an SCP within 90 days, overall and by type of SCP. We used logistic regression to estimate the odds of females being dispensed an SCP relative to males. Of the 150 758 patients hospitalized for an MCD, 20 162 (13.4%) had a current tobacco use diagnosis, 31% of whom were female. Of these, 11.3% (12.4% of females, 10.9% of males) received prescription SCP within 90 days post-discharge; 3.0% were dispensed varenicline, and 8.3% were dispensed nicotine replacement therapy patches. Females were more likely than males to be dispensed a prescription SCP [odds ratio (OR) 1.16, 95% confidence interval (CI) 1.06-1.27)]; however, this was not maintained after adjusting for potential confounders (adjusted OR 1.04, 95% CI 0.94-1.15).

CONCLUSION

Very few females and males who smoke use prescription SCPs after hospitalization for an MCD. The use of varenicline, the SCP with the highest efficacy, was particularly low. This represents a missed opportunity to increase smoking cessation in this high-risk population, thereby reducing their risk of recurrent cardiovascular events.

Harmful Impact of Tobacco Smoking and Alcohol Consumption on the Atrial Myocardium

Tobacco smoking and alcohol consumption are widespread exposures that are legal and socially accepted in many societies. Both have been widely recognized as important risk factors for diseases in all vital organ systems including cardiovascular diseases, and with clinical manifestations that are associated with atrial dysfunction, so-called atrial cardiomyopathy, especially atrial fibrillation and stroke. The pathogenesis of atrial cardiomyopathy, atrial fibrillation, and stroke in context with smoking and alcohol consumption is complex and multifactorial, involving pathophysiological mechanisms, environmental, and societal aspects. This narrative review summarizes the current literature regarding alterations in the atrial myocardium that is associated with smoking and alcohol.

Juvenile patients with the homozygous MTHFR C677T genotype develop ischemic stroke 5 years earlier than wild type

To compare age at 1st ischaemic stroke (IS) in a cohort of juvenile (< 46 years of age) IS patients evaluated for the rs1801133 polymorphism (C → T677) of the methylene tetrahydrofolate reductase (MTHFR) gene; to identify predictors of age at IS and of type of cerebral vessel involvement, small vessel disease (SVD) vs large vessel disease (LVD) responsible for the IS; to evaluate possible associations between other clinical and laboratory variables. Retrospective cohort study on 82 MTHFR TT, 54 MTHFR TC and 34 MTHFR CC participants; data regarding age, sex, age at IS, history of dyslipidaemia, hypertension, smoking, migraine and homocysteine (HC) as well as neuroimaging were collected. Age at IS was lower in MTHFR TT than MTHFR TC and CC (35 ± 4 vs 38 ± 0 vs 40 ± 3 years, respectively, p = 0.002); plasma HC (median, interquartile range) was higher in MTHFR TT than in the other groups [16.7 (11.8, 28.6) vs 11.4 (8.2, 16.1) vs 9.8 (7.9, 1.3) respectively, p < 0.0001)] and was higher in SVD than LVD [17.4 (12.4, 32.5) vs  11.4 (8.8, 16.4) p < 0.0001]. MTHFR TT independently predicted age at IS (p = 0.0008) alongside smoking both as a categorical (p = 0.003) or continuous variable (p = 0.02), whereas HC independently predicted SVD as categorical (p = 0.01) and continuous variable (p < 0.0001). Smoking positively predicted plasma HC (p = 0.005) and negatively the activated partial thromboplastin ratio (aPTTr) (p = 0.02). Juvenile IS carriers of the MTHFR TT genotype develop their 1st occlusion on average 5 years earlier compared to the CC genotype; smoking contributes to this prematurity adversely affecting plasma HC and coagulation whereas plasma HC predicts IS secondary to SVD. Public health campaigns against smoking should highlight the prematurity of IS in the juvenile population.

Prescription smoking-cessation medication pharmacy claims after stroke and transient ischemic attack

Smoking cessation is critical in secondary prevention after stroke and transient ischemic attack. Data regarding use of smoking-cessation interventions after stroke and transient ischemic attack are sparse. We examined the use of prescription smoking-cessation medications in these patients. This is a retrospective cohort study using 2013-2016 data from the INSIGHT Clinical Research Network, comprised of Medicare prescription claims data merged with electronic health record data for patients receiving care across five New York City health care institutions. Active smoking was ascertained based on a validated ICD-9-CM diagnosis code or the presence of an electronic health record active smoking indicator, reflecting clinician-entered data in the health record. The primary outcome was a claim for any prescription smoking-cessation medication (varenicline or bupropion) within 12 months of hospital discharge. We evaluated claims for any statin medication as a comparator because statins are a standard component of stroke secondary prevention. We identified 3,153 patients with stroke or transient ischemic attack who were active smokers at the time of their event. Among these patients, 3.1% (95% CI, 2.5-3.9) had a pharmacy claim for a prescription smoking-cessation medication at 6 months, and 4.7% (95% CI, 3.9-5.6) did at 12 months hospital discharge. In contrast, cumulative statin medication claims rates were 67.5% (95% CI, 65.5-69.5%) at 6 months and 74.6% (95% CI, 72.7-76.6%) at 12 months. Prescription smoking-cessation medications were infrequently used after stroke and transient ischemic attack.