Bleeding risk prediction after acute myocardial infarction-integrating cancer data: the updated PRECISE-DAPT cancer score.

BACKGROUND AND AIMS: This study assessed the impact of incorporating cancer as a predictor on performance of the PRECISE-DAPT score. METHODS: A nationally linked cohort of ST-elevation myocardial infarction patients between 1 January 2005 and 31 March 2019 was derived from the UK Myocardial Ischaemia National Audit Project and the UK Hospital Episode Statistics Admitted Patient Care registries. The primary outcome was major bleeding at 1 year. A new modified score was generated by adding cancer as a binary variable to the PRECISE-DAPT score using a Cox regression model and compared its performance to the original PRECISE-DAPT score. RESULTS: A total of 216 709 ST-elevation myocardial infarction patients were included, of which 4569 had cancer. The original score showed moderate accuracy (C-statistic .60), and the modified score showed modestly higher discrimination (C-statistics .64; hazard ratio 1.03, 95% confidence interval 1.03-1.04) even in patients without cancer (C-statistics .63; hazard ratio 1.03, 95% confidence interval 1.03-1.04). The net reclassification index was .07. The bleeding rates of the modified score risk categories (high, moderate, low, and very low bleeding risk) were 6.3%, 3.8%, 2.9%, and 2.2%, respectively. According to the original score, 65.5% of cancer patients were classified as high bleeding risk (HBR) and 21.6% were low or very low bleeding risk. According to the modified score, 94.0% of cancer patients were HBR, 6.0% were moderate bleeding risk, and no cancer patient was classified as low or very low bleeding risk. CONCLUSIONS: Adding cancer to the PRECISE-DAPT score identifies the majority of patients with cancer as HBR and can improve its discrimination ability without undermining its performance in patients without cancer.

Oral anticoagulant prescribing among patients with cancer and atrial fibrillation in England, 2009-2019.

BACKGROUND: Anticoagulation of patients with atrial fibrillation (AF) and cancer is challenging because of their high risk for stroke and bleeding. Little is known of the variations of oral anticoagulant (OAC) prescribing in patients with AF with and without cancer. METHODS: Patients with first-time AF during 2009-2019 from the Clinical Practice Research Datalink were included. Cancer diagnosis was defined as a history of breast, prostate, colorectal, lung, or hematological cancer. Competing-risk analysis was used to assess the risk of OAC prescribing in patients with AF and cancer adjusted for clinical and sociodemographic factors. RESULTS: Of 177,065 patients with AF, 11.7% had cancer. Compared to patients without cancer, patients with cancer were less likely to receive OAC: prostate cancer (subhazard ratio [SHR], 0.95; 95% CI, 0.91-0.99), breast cancer (SHR, 0.93; 95% CI, 0.89-0.98), colorectal cancer (SHR, 0.93; 95% CI, 0.88-0.99), hematological cancer (SHR, 0.70; 95% CI, 0.65-0.75), and lung cancer (SHR, 0.44; 95% CI, 0.38-0.50). The cumulative incidence function (CIF) of OAC prescribing was lowest for patients with lung cancer and hematological cancer compared with patients without cancer. The difference between the CIF of OAC prescribing in patients with and without cancer becomes narrower in the most deprived areas. Elderly patients (aged ≥85 years) overall had the lowest CIF of OAC prescribing regardless of cancer status. CONCLUSIONS: In patients with AF, underprescribing of OAC is independently associated with certain cancer types. Patients with hematological and lung cancer are the least likely to receive anticoagulation therapy compared with patients without cancer. Underprescribing of OAC in cancer is linked to old age. Further studies of patients with AF and cancer are warranted to assess the net clinical benefit of anticoagulation in certain cancer types.

The prognostic value of mean platelet volume in patients with coronary artery disease: An updated systematic review with meta-analyses.

BACKGROUND: Mean platelet volume (MPV) is a widely available laboratory index, however its prognostic significance in patients with coronary artery disease (CAD) is still unclear. We intended to investigate and pool the evidence on the prognostic utility of admission MPV in predicting clinical outcomes in patients with CAD. METHODS: PubMed, Web of Science, and Scopus were the major databases used for literature search. The risk of bias was assessed using the quality in prognostic factor studies. We used random-effects pairwise analysis with the Knapp and Hartung approach supported further with permutation tests and prediction intervals (PIs). RESULTS: We identified 52 studies with 47,066 patients. A meta-analysis of nine studies with 14,864 patients demonstrated that one femtoliter increase in MPV values was associated with a rise of 29% in the risk of long-term mortality (hazard ratio [HR] 1.29, 95% confidence interval [CI] 1.22-1.37) in CAD as a whole. The results were further supported with PIs, permutation tests and leave-one-out sensitivity analyses. MPV also demonstrated its stable and significant prognostic utility in predicting long-term mortality as a linear variable in patients treated with percutaneous coronary intervention (PCI) and presented with acute coronary syndrome (ACS) (HR 1.29, 95% CI 1.20-1.39, and 1.29, 95% CI 1.19-1.39, respectively). CONCLUSION: The meta-analysis found robust evidence on the link between admission MPV and the increased risk of long-term mortality in patients with CAD patients, as well as in patients who underwent PCI and patients presented with ACS.

The prognostic value of metabolic dysfunction-associated steatotic liver disease in acute myocardial infarction: A propensity score-matched analysis.

AIM: Patients with metabolic dysfunction-associated steatotic liver disease (MASLD) are at increased risk of incident cardiovascular disease. However, the clinical characteristics and prognostic importance of MASLD in patients presenting with acute myocardial infarction (AMI) have yet to be examined. METHODS: This study compared the characteristics and outcomes of patients with and without MASLD presenting with AMI at a tertiary centre in Singapore. MASLD was defined as hepatic steatosis, with at least one of five metabolic criteria. Hepatic steatosis was determined using the Hepatic Steatosis Index. Propensity score matching was performed to adjust for age and sex. The Kaplan-Meier curve was constructed for long-term all-cause mortality. Cox regression analysis was used to investigate independent predictors of long-term all-cause mortality. RESULTS: In this study of 4446 patients with AMI, 2223 patients with MASLD were matched with patients without MASLD using propensity scores. The mean follow-up duration was 3.4 ± 2.4 years. The MASLD group had higher rates of obesity, diabetes and chronic kidney disease than their counterparts. Patients with MASLD had early excess all-cause mortality (6.8% vs. 3.6%, p < .001) at 30 days, with unfavourable mortality rates sustained in the long-term (18.3% vs. 14.5%, p = .001) compared with those without MASLD. After adjustment, MASLD remained independently associated with higher long-term all-cause mortality (hazard ratio 1.330, 95% confidence interval 1.106-1.598, p = .002). CONCLUSION: MASLD embodies a higher burden of metabolic dysfunction and is an independent predictor of long-term mortality in the AMI population. Its early identification may be beneficial for risk stratification and provide therapeutic targets for secondary preventive strategies in AMI.

Calibration plots for multistate risk predictions models.

INTRODUCTION: There is currently no guidance on how to assess the calibration of multistate models used for risk prediction. We introduce several techniques that can be used to produce calibration plots for the transition probabilities of a multistate model, before assessing their performance in the presence of random and independent censoring through a simulation. METHODS: We studied pseudo-values based on the Aalen-Johansen estimator, binary logistic regression with inverse probability of censoring weights (BLR-IPCW), and multinomial logistic regression with inverse probability of censoring weights (MLR-IPCW). The MLR-IPCW approach results in a calibration scatter plot, providing extra insight about the calibration. We simulated data with varying levels of censoring and evaluated the ability of each method to estimate the calibration curve for a set of predicted transition probabilities. We also developed evaluated the calibration of a model predicting the incidence of cardiovascular disease, type 2 diabetes and chronic kidney disease among a cohort of patients derived from linked primary and secondary healthcare records. RESULTS: The pseudo-value, BLR-IPCW, and MLR-IPCW approaches give unbiased estimates of the calibration curves under random censoring. These methods remained predominately unbiased in the presence of independent censoring, even if the censoring mechanism was strongly associated with the outcome, with bias concentrated in low-density regions of predicted transition probability. CONCLUSIONS: We recommend implementing either the pseudo-value or BLR-IPCW approaches to produce a calibration curve, combined with the MLR-IPCW approach to produce a calibration scatter plot. The methods have been incorporated into the "calibmsm" R package available on CRAN.

Rural-urban stroke mortality gaps in the United States.

INTRODUCTION: Disparities in stroke outcomes, influenced by the use of systemic thrombolysis, endovascular therapies, and rehabilitation services, have been identified. Our study assesses these disparities in mortality after stroke between rural and urban areas across the United States (US). METHODS: We analyzed the CDC data on deaths attributed to cerebrovascular disease from 1999 to 2020. Data was categorized into rural and urban regions for comparative purposes. Age-adjusted mortality rates (AAMR) were computed using the direct method, allowing us to examine the ratios of rural to urban deaths for the cumulative population and among demographic subpopulations. Linear regression models were used to assess temporal changes in mortality ratios over the study period, yielding beta-coefficients (ß). RESULTS: There was a total of 628,309 stroke deaths in rural regions and 2,556,293 stroke deaths within urban regions. There were 1.13 rural deaths for each one urban death per 100,000 population in 1999 and 1.07 in 2020 (ß = -0.001, ptrend = 0.41). The rural-urban mortality ratio in Hispanic populations decreased from 1.32 rural deaths for each urban death per 100,000 population in 1999 to 0.85 in 2020 (ß = -0.011, ptrend < 0.001). For non-Hispanic populations, mortality remained stagnant with 1.12 rural deaths for each urban death per 100,000 population in 1999 and 1.07 in 2020 (ß = -0.001, ptrend = 0.543). Regionally, the Southern US exhibited the highest disparity with a urban-rural mortality ratio of 1.19, followed by the Northeast (1.13), Midwest (1.04), and West (1.01). CONCLUSIONS: Our findings depict marked disparities in stroke mortality between rural and urban regions, emphasizing the importance of targeted interventions to mitigate stroke-related disparities.

The invasive investigation of INOCA in the coronary catheterization lab.

Over half of all patients with angina have no angiographically demonstratable obstructive coronary disease, with a significant proportion of these patients having undiagnosed microvascular dysfunction and/or vasospastic angina. In chronic coronary syndrome, ischemia with non-obstructive coronary artery disease (INOCA) often remains undiagnosed, or uninvestigated. INOCAmay occur due to vasospastic angina and microvascular dysfunction and require invasive assessment in the coronary catheterization lab. To evaluate INOCA coronary flow reserve (CFR) and the index of microcirculatory resistance (IMR) are used to assess microvascular dysfunction before acetylcholine provocation testing for coronary spasm. This review provides an overview of the invasive investigation of INOCA in the coronary catheterization lab for patients with angina to be optimally managed.

Association of myocardial injury with adverse long-term survival among cancer patients.

AIMS: Over time, cardiovascular disease (CVD) deaths increasingly exceed those from malignancy among cancer survivors. However, the association of myocardial injury with long-term survival (beyond three years) in cancer patients has not been previously described. METHODS: The National Health and Nutrition Examination Survey high-sensitivity cardiac troponin (hs-cTn) and morbidities databases (1999-2004) were linked with the latest mortality dataset isolating records were respondents reported cancer diagnosis by a healthcare professional. Myocardial injury was then determined by elevated hs-cTn. RESULTS: 16,225,560 weighted records (1,058 unweighted) were included in this observational study, with myocardial injury identified in 14·2%. Those with myocardial injury had progressively worse survival at 5 (51·6% vs. 89·5%), 10 (28·3% vs. 76·0%), and 15 years (12·6% vs. 61·4%) compared to those without myocardial injury. After adjusting for baseline characteristics, those with myocardial injury had an adjusted hazard ratio (aHR) of 2·10 (95% CI 2·09-2·10, p<0·001) for all-cause mortality, 2·23 (2·22-2·24, p<0·001) for cardiovascular mortality, and 1·59 (95% CI 1·59-1·60, p<0·001) for cancer mortality compared to those without myocardial injury. Among patients with no pre-existing CVD, the hs-cTn I Ortho assay was a strong independent predictor of all cause (aHR 6·29, 95% CI 6·25-6·33, p<0·001), CVD (aHR 11·38, 95% CI 11·23-11·54, p<0·001), and cancer (aHR 5·02, 95% CI 4·96-5·07, p<0·001) mortality. CONCLUSIONS: As a marker for myocardial injury, hs-cTn/s were independently associated with worse long-term survival among cancer patients with a stronger relationship with all-cause, cardiovascular, and cancer mortality using hs-cTn I ortho assay.

We conducted an observational analysis using the Unites States' National Health and Nutrition Examination Survey (NHANES) database to examine the association of myocardial injury, as defined by elevated cardiac biomarkers in the form of four different high sensitivity cardiac troponins, with long-term outcome among cancer survivors. Cancer survivors with myocardial injury had progressively worse survival at 5 (51·6% vs. 89·5%), 10 (28·3% vs. 76·0%), and 15 years (12·6% vs. 61·4%) compared to those without myocardial injury.After adjusting for population characteristics including cancer type, the risk of death from any cause among cancer survivors with myocardial injury were more than double that of those without myocardial injury (adjusted hazard ratio of 2·10 (95% CI 2·09­2·10, p<0·001).

Association of Cardiovascular Health Metrics and Mortality Among Individuals With and Without Cancer.

BACKGROUND: Although metrics of cardiovascular health have been associated with improved mortality, whether the association remains among individuals with a history of cancer has not been well characterized. METHODS AND RESULTS: The National Health and Nutrition Examination Survey data from 2009 to 2018 were used to identify individuals with and without a history of cancer. For each participant, American Heart Association Life's Essential 8 cardiovascular health metrics of health behaviors (diet, physical activity, nicotine exposure, and sleep) and health factors (body mass index, non-high-density lipoprotein cholesterol, blood glucose, and blood pressure) were obtained. All-cause, cardiovascular, and cancer-related mortality were noted. Out of 21 967 individuals, 8% had a history of cancer. In analyses adjusted for age, race and ethnicity, sex, and income among the whole cohort, better Life's Essential 8 cardiovascular health metrics were associated with lower all-cause (adjusted hazard ratio [aHR ], 0.38 [95% CI, 0.29-0.49]; P<0.001), cardiovascular (aHR, 0.38 [95% CI, 0.22-0.49]; P<0.001), and cancer mortality (aHR, 0.50 [95% CI, 0.31-0.79]; P=0.001). This association was driven by better health behaviors that were associated with lower all-cause (aHR, 0.30 [95% CI, 0.26-0.35]; P<0.001), cardiovascular (aHR, 0.39 [95% CI, 0.26-0.52]; P<0.001), and cancer mortality (aHR, 0.35 [95% CI, 0.26-0.47]; P<0.001), whereas better health factors were not associated with lower mortality. There were no significant interactions in these associations between individuals with and without cancer. CONCLUSIONS: Better metrics of cardiovascular health, particularly health behaviors, are associated with improved all-cause, cardiovascular, and cancer mortality to a similar extent in individuals with and without cancer. Attempts to improve cardiovascular health should be prioritized similarly among individuals with and without cancer.

Machine-learning clustering analysis identifies novel phenogroups in patients with ST-elevation acute myocardial infarction.

BACKGROUND: Machine learning clustering of patients with ST-elevation acute myocardial infarction (STEMI) may provide important insights into their risk profile, management and prognosis. METHODS: All adult discharges for STEMI in the National Inpatient Sample (October 2015 to December 2019) were included, excluding patients with prior myocardial infarction. Machine-learning clustering analysis was used to define clusters based on 21 clinical attributes of interest. Main outcomes of the study were cluster-based comparison of risk profile, in-hospital clinical outcomes and utilization of invasive management. Binomial hierarchical multivariable logistic regression with adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) was used to detect the between-cluster differences. RESULTS: Out of overall 470,960 STEMI cases, the machine-learning analysis revealed 4 different clusters with 205,640 (cluster 0: 'behavioural risk cluster'), 146,400 (cluster 1: 'least comorbidity cluster'), 45,100 (cluster 2: 'diabetes with end-organ damage cluster') and 73,820 (cluster 3: 'cardiometabolic cluster') cases. Attributes with the highest importance for clustering were hypertension and diabetes. After multivariable adjustment, patients from 'diabetes with end-organ damage cluster' exhibited the worst mortality, MACCE and ischemic stroke (p < 0.001 for all), as well as the lowest utilization of invasive management (p < 0.001 for all), in comparison to other clusters. Patients from 'behavioural risk cluster' exhibited the best in-hospital prognosis and the highest utilization of invasive management, compared to other clusters (p < 0.001 for all). CONCLUSIONS: Machine learning driven clustering of inpatients with STEMI reveals important population subgroups with distinct prevalence, risk profile, prognosis and management. Data driven approaches may identify high risk phenogroups and warrants further study.

The clinical characteristics, managements, and outcomes of acute myocardial infarction in osteoarthritis patients; a cross-sectional analysis of 6.5 million patients.

OBJECTIVES: The prevalence of osteoarthritis (OA) and cardiovascular disease are increasing and both conditions share similar risk factors. We investigated the association between OA and receipt of invasive managements and clinical outcomes in patients with acute myocardial infarction (AMI). METHODS: Using the National Inpatient Sample, adjusted binary logistic regression determined the association between OA and each outcome variable. RESULTS: Of 6,561,940 AMI hospitalizations, 6.3% had OA. OA patients were older and more likely to be female. OA was associated with a decreased odds of coronary angiography (adjusted odds ratio 0.91; 95% confidence interval 0.90, 0.92), PCI (0.87; 0.87, 0.88), and coronary artery bypass grafting (0.98; 0.97, 1.00). OA was associated with a decreased odds of adverse outcomes (in-hospital mortality: 0.68; 0.67, 0.69; major acute cardiovascular and cerebrovascular events: 0.71; 0.70, 0.72; all-cause bleeding: 0.76; 0.74, 0.77; and stroke/TIA: 0.84; 0.82, 0.87). CONCLUSIONS: This study of a representative sample of the US population highlights that OA patients are less likely to be offered invasive interventions following AMI. OA was also associated with better outcomes post-AMI, possibly attributed to a misclassification bias where unwell patients with OA were less likely to receive an OA code because codes for serious illness took precedence.

Cardiovascular Disease and the Mediterranean Diet: Insights into Sex-Specific Responses.

Cardiovascular disease (CVD) is a leading cause of mortality and disease burden in women globally. A healthy diet is important for the prevention of CVD. Research has consistently favoured the Mediterranean diet as a cardio-protective diet. Several studies have evaluated associations between the Mediterranean diet and cardiovascular outcomes, including traditional risk factors like hypertension, type 2 diabetes mellitus, and obesity. In addition, consistent evidence suggests that the components of the Mediterranean diet have a synergistic effect on cardiovascular risk due to its anti-inflammatory profile and microbiome effects. While the benefits of the Mediterranean diet are well-established, health advice and dietary guidelines have been built on largely male-dominant studies. Few studies have investigated the beneficial associations of the Mediterranean diet in sex-specific populations, including those with non-traditional risk factors that are specific to women, for instance polycystic ovarian syndrome and high-risk pregnancies, or more prevalent in women, such as chronic inflammatory diseases. Therefore, this review aims to provide a comprehensive overview of the current evidence regarding the Mediterranean diet in women in relation to cardiovascular health outcomes.

Has the first year of the COVID pandemic impacted the trends in obesity-related CVD mortality between 1999 and 2019 in the United States?

Background: During the covid-19 pandemic there was a marked rise in the number of cardiovascular deaths. Obesity is a well-known modifiable risk factor for cardiovascular disease and has been identified as a factor which leads to poorer covid-19 related outcomes. In this study we aimed to analyse the impact of covid-19 on obesity-related cardiovascular deaths compared to trends seen 20 years prior. We also analysed the influence different demographics had on mortality. Methods: Multiple Cause of Mortality database was accessed through CDC WONDER to obtain the obesity-related and general cardiovascular crude mortality and age adjusted mortality rates (AMMR) between 1999 and 2020 in the US. The obesity-related sample was stratified by demographics and cardiovascular mortality was subdivided into ischemic heart disease, heart failure, hypertension and cerebrovascular disease. Joinpoint Regression Program (Version 4.9.1.0) was used to calculate the average annual percent change (AAPC) in AAMR, and hence projected AAMR. Excess mortality was calculated by comparing actual AAMR in 2020 to projected values. Results and discussion: There were an estimated 3058 excess deaths during the early stages of the pandemic impacting all cohorts. The greatest excess mortalities were seen in men, rural populations and in Asian/Pacific Islander and Native Americans. Interestingly the greatest overall mortality was seen in the Black American population. Our study highlights important, both pre and during the pandemic, in obesity related cardiovascular disease mortality which has important implications for ongoing public health measures.

Sex differences in Life's Essential Eight and its Association with mortality among US adults without known cardiovascular disease.

Background: The American Heart Association's (AHA) Life's Essential 8 (LE8) score is a helpful tool to quantify cardiovascular health (CVH) metrics. We sought to assess sex differences in relation to LE8 and its components along with association with mortality. Methods: The National Health and Nutrition Examination Survey (NHANES) between 2009 and 2018 was utilized to evaluate the prevalence of health metrics included in LE8 among adult participants > age 18, stratified by sex. We categorized overall CVH, health factors, and health behaviors into 3 levels (low: <50, moderate: 50 -79, high: ≥80) following the AHA's algorithm. Health metrics were further subdivided into health behaviors (diet, physical activity, nicotine exposure, and sleep) and health factors (body mass index, non-high density lipoprotein cholesterol, blood glucose, and blood pressure). LE8 scores were also evaluated based on age, race/ethnicity, and socioeconomic status. Cox proportional hazard models were used to evaluate the association between the levels of CVH and risk of all-cause and cardiovascular mortality, with adjustment for age group and race. Results: Among 22,761 participants, 52 % were female. Overall CVH score was similar in both females and males (65.8 vs. 65.9). Females had higher health factors score (64.3 vs. 63.1, p < 0.001) and lower health behaviors score (67.2 vs 68.6, p < 0.001). Amongst individual metrics, blood pressure score was higher in females (73.2 vs. 67.7, p < 0.001) while males had higher physical activity score (70.6 vs. 54.9, p < 0.001). For individuals under 65 years of age, overall CVH and health factors scores were higher in females while in those age 65 or older, males had higher scores. The most prominent sex differences were noted in non-Hispanic Black females who had significantly lower CVH scores than Black males (62.6 vs. 74.7, respectively, p < 0.001. High LE8 scores vs. low LE8 scores demonstrated lower all-cause (HR 0.37 vs 0.35) and CV mortality (HR 0.35 vs. 0.36) in both males and females, respectively (p-interaction 0.21 and 0.28). High health behaviors scores also demonstrated a significant association with lower all-cause (0.34 vs. 0.24) and CV mortality (HR 0.47 vs. 0.26) in both males and females, respectively (p-interaction 0.20 and 0.11). Conclusions: We demonstrate important sex differences in CVH metrics along with notable variations based on age and race/ethnicity. Furthermore, we highlight that CVH metrics including health factors and health behaviors are associated with mortality in both females and males. These findings underscore the importance of designing and implementing effective strategies for both sexes, aimed at targeting these specific factors.

Impact of Neighborhood Social Deprivation on Delays to Access for Transcatheter Aortic Valve Replacement: Wait-Times and Clinical Consequences.

BACKGROUND: Transcatheter aortic valve replacement (TAVR) has become the standard of care for severe aortic stenosis treatment. Exponential growth in demand has led to prolonged wait times and adverse patient outcomes. Social marginalization may contribute to adverse outcomes. Our objective was to examine the association between different measures of neighborhood-level marginalization and patient outcomes while on the TAVR waiting list. A secondary objective was to understand if sex modifies this relationship. METHODS AND RESULTS: We conducted a population-based retrospective cohort study of 11 077 patients in Ontario, Canada, referred to TAVR from April 1, 2018, to March 31, 2022. Primary outcomes were death or hospitalization while on the TAVR wait-list. Using cause-specific Cox proportional hazards models, we evaluated the relationship between neighborhood-level measures of dependency, residential instability, material deprivation, and ethnic and racial concentration with primary outcomes as well as the interaction with sex. After multivariable adjustment, we found a significant relationship between individuals living in the most ethnically and racially concentrated areas (quintile 4 and 5) and mortality (hazard ratio [HR], 0.64 [95% CI, 0.47-0.88] and HR, 0.73 [95% CI, 0.53-1.00], respectively). There was no significant association between material deprivation, dependency, or residential instability with mortality. Women in the highest ethnic or racial concentration quintiles (4 and 5) had significantly lower risks for mortality (HR values of 0.52 and 0.56, respectively) compared with quintile 1. CONCLUSIONS: Higher neighborhood ethnic or racial concentration was associated with decreased risk for mortality, particular for women on the TAVR waiting list. Further research is needed to understand the drivers of this relationship.

Recommended and observed statin use among US adults with and without cancer.

AIMS: Patients with cancer are at increased cardiovascular (CV) risk. We aimed to compare the recommended and observed statin use among individuals with and without cancer. METHODS AND RESULTS: Using three 2-year cycles from the National Health and Nutrition Examination Survey (2013-18), we analysed data from 17 050 US adults. We compared the prevalence of Class 1 statin recommendations and use between individuals with and without cancer, overall, and among different demographic groups. Individuals with a history of cancer were older and had a higher burden of comorbidities. Stratified by age groups, they were more likely to have a secondary prevention indication compared with individuals without cancer but not a primary prevention indication for statin. Among individuals with an indication for statin therapy, the prevalence of statin use was higher in the cancer group compared with those without cancer (60.8% vs. 47.8%, P < 0.001), regardless of sex, type of indication (primary vs. secondary prevention), and education level. However, the higher prevalence of statin use in the cancer group was noted among younger individuals, ethnic minorities, and those with lower family income. CONCLUSION: Our finding highlights the importance of optimization of CV health in patients with cancer, as individuals with cancer were more likely to have a Class 1 indication for statin treatment when compared with individuals without cancer. Important differences in statin use among cohorts based on sex, age, ethnicity, and socioeconomic status were identified, which may provide a framework through which CV risk factor control can be targeted in this population. KEY FINDINGS: Higher statin use in cancer patients: Among those with Class 1 recommendation to take statins, 60.8% of cancer patients were using them, compared with 47.8% of non-cancer individuals, indicating a greater adherence to heart health recommendations in the cancer group. Demographic variations in statin use: The study found notable differences in statin use among younger individuals, ethnic minorities, and those with lower income within the cancer patient group, suggesting disparities in how these subgroups manage their cardiovascular health.

This study reveals that individuals with cancer more likely to have a secondary prevention indication compared with individuals without cancer but not a primary prevention indication for statin and that they had higher rates of compliance with statin treatment, compared with those without cancer.

Temporal trends of in-hospital mortality and its determinants following percutaneous coronary intervention in patients with acute coronary syndrome in England and Wales: A population-based study between 2006 and 2021.

BACKGROUND: There is limited data around drivers of changes in mortality over time. We aimed to examine the temporal changes in mortality and understand its determinants over time. METHODS: 743,149 PCI procedures for patients from the British Cardiovascular Intervention Society (BCIS) database who were aged between 18 and 100 years and underwent Percutaneous Coronary Intervention (PCI) for Acute Coronary Syndrome (ACS) in England and Wales between 2006 and 2021 were included. We decomposed the contributing factors to the difference in the observed mortality proportions between 2006 and 2021 using Fairlie decomposition method. Multiple imputation was used to address missing data. RESULTS: Overall, there was an increase in the mortality proportion over time, from 1.7% (95% CI: 1.5% to 1.9%) in 2006 to 3.1% (95% CI: 3.0% to 3.2%) in 2021. 61.2% of this difference was explained by the variables included in the model. ACS subtypes (percentage contribution: 14.67%; 95% CI: 5.76% to 23.59%) and medical history (percentage contribution: 13.50%; 95% CI: 4.33% to 22.67%) were the strongest contributors to the difference in the observed mortality proportions between 2006 and 2021. Also, there were different drivers to mortality changes between different time periods. Specifically, ACS subtypes and severity of presentation were amongst the strongest contributors between 2006 and 2012 while access site and demographics were the strongest contributors between 2012 and 2021. CONCLUSIONS: Patient factors and the move towards ST-elevated myocardial infarction (STEMI) PCI have driven the short-term mortality changes following PCI for ACS the most.

Heart Failure Readmission in Patients With ST-Segment Elevation Myocardial Infarction and Active Cancer.

Background: Although numerous studies have examined readmission with heart failure (HF) after acute myocardial infarction (AMI), limited data are available on HF readmission in cancer patients post-AMI. Objectives: This study aimed to assess the rates and factors associated with HF readmission in cancer patients presenting with ST-segment elevation myocardial infarction (STEMI). Methods: A nationally linked cohort of STEMI patients between January 2005 and March 2019 were obtained from the UK Myocardial Infarction National Audit Project registry and the UK national Hospital Episode Statistics Admitted Patient Care registry. Multivariable Fine-Gray competing risk models were used to evaluate HF readmission at 30 days and 1 year. Results: A total of 326,551 STEMI indexed admissions were included, with 7,090 (2.2%) patients having active cancer. The cancer group was less likely to be admitted under the care of a cardiologist (74.5% vs 81.9%) and had lower rates of invasive coronary angiography (62.2% vs 72.7%; P < 0.001) and percutaneous coronary intervention (58.4% vs. 69.5%). There was a significant prescription gap in the administration of post-AMI medications upon discharge such as an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (49.5% vs 71.1%) and beta-blockers (58.4% vs 68.0%) in cancer patients. The cancer group had a higher rate of HF readmission at 30 days (3.2% vs 2.3%) and 1 year (9.4% vs 7.3%). However, after adjustment, cancer was not independently associated with HF readmission at 30 days (subdistribution HR: 1.05; 95% CI: 0.86-1.28) or 1 year (subdistribution HR: 1.03; 95% CI: 0.92-1.16). The opportunity-based quality indicator was associated with higher rates of HF readmission independent of cancer diagnosis. Conclusions: Cancer patients receive care that differs in important ways from patients without cancer. Greater implementation of evidence-based care may reduce HF readmissions, including in cancer patients.

Complex High-Risk Percutaneous Coronary Intervention Types, Trends, and Outcomes in Nonsurgical Centres.

BACKGROUND: Limited data are available on complex high-risk percutaneous coronary intervention (CHiP) trends and outcomes in nonsurgical centres (NSCs), particularly in health care systems where most centres are NSCs. METHODS: Using data from a national registry, we studied the characteristics and outcomes of CHiP procedures performed for stable angina from 2006 to 2017 according to the presence or absence of on-site surgical cover. Multivariate regression analyses and propensity score matching were used to determine risks for in-hospital death, major bleeding, and major cardiovascular or cerebral events (MACCE). RESULTS: Out of 134,730 CHiP procedures, 42,433 (31.5%) were performed in NSCs, increasing from 12.5% in 2006 to 42% in 2017. Compared with surgical centres (SCs), patients who had a CHiP procedure undertaken in NSCs were, on average, 2.4 years older and had a greater prevalence of cardiovascular risks. Common CHiP procedures performed in NSCs included poor left ventricular function (41.6%), chronic renal failure (38.8%), and chronic total occlusion percutaneous coronary intervention (31.1%). NSC-based CHiP is associated with lower odds of mortality (adjusted odds ratio [aOR] 0.7, 95% confidence interval [CI] 0.5-0.8) and major bleeding (aOR 0.7, 95% CI 0.6-0.8). In both groups, MACCE odds were similar (aOR 1.0, 95% CI 0.9-1.1). CONCLUSIONS: CHiP numbers have steadily increased in NSCs. NSC patients were older and had a higher prevalence of cardiovascular risks than SC patients. Mortality and major bleeding odds were significantly lower in those cases undertaken in NSCs, although MACCE odds were not different between the groups.

Wait-times Benchmarks for risk-based prioritization in Transcatheter Aortic Valve Implantation: a simulation study.

BACKGROUND: Demand for transcatheter aortic valve implantation (TAVI) has increased in the last decade, resulting in prolonged wait-times and undesirable health outcomes in many health systems. Risk-based prioritization and wait-times benchmarks can improve equitable access to patients. METHODS: We used simulation models to follow-up a synthetic population of 50,000 individuals from referral to completion of TAVI. Based on their risk of adverse events, patients could be classified as "low-", "medium-" and "high-risk", and shorter wait-times were assigned for the higher risk groups. We assessed the impacts of the size and wait-times for each risk group on waitlist mortality, hospitalization and urgent TAVIs. All scenarios had the same resource constraints, allowing us to explore the trade-offs between faster access for prioritized patients and deferred access for non-prioritized groups. RESULTS: Increasing the proportion of patients categorized as high-risk, and providing more rapid access to the higher-risk groups achieved the greatest reductions in mortality, hospitalizations and urgent TAVIs (relative reductions of up to 29%, 23% and 38%, respectively). However, this occurs at the expense of excessive wait-times in the non-prioritized low-risk group (up to 25 weeks). We propose wait-times of up to 3 weeks for high-risk patients and 7 weeks for medium-risk patients. CONCLUSIONS: Prioritizing higher-risk patients with faster access leads to better health outcomes, however this also results in unacceptably long wait-times for the non-prioritized groups in settings with limited capacity. Decision-makers must be aware of these implications when developing and implementing waitlist prioritization strategies.