Prevalence of electrocardiographic unrecognized myocardial infarction and its association with mortality

Sex and ethnic differences in unrecognized myocardial infarctions: Observations on recognition and preventive therapies from the multiethnic population-based HELIUS cohort

Background

Epidemiological studies suggest sex differences in the prevalence and characteristics of unrecognized and recognized myocardial infarction (uMI, rMI). Despite increasingly diverse populations, observations are limited in multiethnic contexts. Gaining better understanding may inform policy makers and healthcare professionals on populations at risk of uMI who could benefit from preventive measures.

Methods

We used baseline data from the multiethnic population-based HELIUS cohort (2011-2015; Amsterdam, the Netherlands). Using logistic regressions, we studied sex differences in the prevalence and proportion of uMIs across ethnic groups. Next, we studied whether symptoms, clinical parameters, and sociocultural factors were associated with uMIs. Finally, we compared secondary preventive therapies in women and men with a uMI or rMI. We relied on pathological Q-waves on a resting electrocardiogram as the electrocardiographic signature for (past) MI.

Results

Overall, and in Turkish and Moroccan subgroups, the prevalence of uMIs was higher in men than women. The proportion of uMIs was similar in women (21.0%) and men (18.4%), yet varied by ethnicity. In women and men, symptoms (chest pain, dyspnea) and clinical parameters (hypertension, hypercholesterolemia), and in women also lower educational level and diabetes were associated with lower odds of uMIs. Women (0.0%) and men (3.6%) with uMI were unlikely to receive secondary preventive therapies compared to those with rMI (28.1-40.9%).

Conclusions

The prevalence of uMIs was higher in men than women, and sex differences in the proportion of uMIs varied somewhat across ethnic groups. People with uMIs did not receive adequate preventative medications, posing a risk for recurrent events.

Relative fat mass and prediction of incident atrial fibrillation, heart failure and coronary artery disease in the general population

BACKGROUND

Relative fat mass (RFM) is an emerging marker of obesity that estimates body fat percentage using a sex-specific formula containing height and waist circumference (WC). We studied the association of RFM with incident atrial fibrillation (AF), heart failure (HF), and coronary artery disease (CAD) and explored RFM cutoffs for cardiovascular disease (CVD) prediction.

METHODS

We studied 95,003 participants (age 45 ± 13 years, 59% women) without prevalent AF, HF or CAD from the population-based Lifelines study. Outcomes were ascertained using electrocardiography and self-reported questionnaire data. We used logistic regression to study the association of RFM with individual outcomes and a composite outcome (incident AF, HF, and/or CAD). Multivariable models were adjusted for components of the SCORE risk model (age, sex, systolic blood pressure, cholesterol, and smoking). Optimal cutoffs were determined using the Youden index.

RESULTS

During a median follow-up of 3.8 (3.0-4.6) years, 224 (0.2%) participants developed AF, 1003 (1.1%) HF and 657 (0.7%) CAD. After multivariable adjustment, RFM was significantly associated with all outcomes (standardised OR 1.26, 95% CI 1.18-1.34 for the composite outcome). Optimal RFM cutoffs ( ≥26 for men, ≥38 for women) were lower than previously proposed RFM cutoffs ( ≥30 for men, ≥40 for women). In general, overall discriminative ability of RFM and its cutoffs was at least similar (in women) or better (in men) compared to BMI and WC. Since RFM was substantially correlated with age, we additionally determined age-specific cutoffs, which ranged from 23 to 27 in men and 33 to 43 in women.

CONCLUSIONS

RFM is associated with incident AF, HF, and CAD and may be used as a simple and intuitive marker of obesity and cardiovascular risk in the general population. This study provides potential RFM cutoffs for CVD prediction that may be used by future studies or preventive strategies targeting obesity and cardiovascular risk.

Prevalence, predictors, and outcomes of clonal hematopoiesis in individuals aged ≥80 years

Clonal hematopoiesis (CH), characterized by a fraction of peripheral blood cells carrying an acquired genetic variant, emerges with age. Although in general CH is associated with increased mortality and morbidity, no higher risk of death was observed for individuals ≥80 years. Here, we investigated CH in 621 individuals aged ≥80 years from the population-based LifeLines cohort. Sensitive error-corrected sequencing of 27 driver genes at a variant allele frequency ≥1% revealed CH in the majority (62%) of individuals, independent of gender. The observed mutational spectrum was dominated by DNMT3A and TET2 variants, which frequently (29%) displayed multiple mutations per gene. In line with previous results in individuals ≥80 years, the overall presence of CH did not associate with a higher risk of death (hazard ratio, 0.91; 95% confidence interval, 0.70-1.18; P = .48). Being able to assess the causes of death, we observed no difference between individuals with or without CH, except for deaths related to hematological malignancies. Interestingly, comparison of mutational spectra confined to DNMT3A and TET2 vs spectra containing other mutated genes, showed a higher risk of death when mutations other than DNMT3A or TET2 were present (hazard ratio, 1.48; 95% confidence interval, 1.06-2.08; P = .025). Surprisingly, no association of CH with cardiovascular morbidity was found, irrespective of clone size. Further, CH associated with chronic obstructive pulmonary disease. Data on estimated exposure to DNA damaging toxicities (ie, smoking, a history of cancer [as a proxy for previous genotoxic therapy], and job-related pesticide exposure) showed an association with spliceosome and ASXL1 variants, but not with DNMT3A and TET2 variants.

Erythrocytosis in the general population: clinical characteristics and association with clonal hematopoiesis

Erythrocytosis is a common reason for referral to hematology services and is usually secondary in origin. The aim of this study was to assess clinical characteristics and clonal hematopoiesis (CH) in individuals with erythrocytosis in the population-based Lifelines cohort (n = 147 167). Erythrocytosis was defined using strict (World Health Organization [WHO] 2008/British Committee for Standards in Hematology) and wide (WHO 2016) criteria. Individuals with erythrocytosis (strict criteria) and concurrent leukocytosis and/or thrombocytosis were 1:2 matched with individuals with isolated erythrocytosis and analyzed for somatic mutations indicative of CH (≥5% variant allele frequency). One hundred eighty five males (0.3%) and 223 females (0.3%) met the strict criteria, whereas 4868 males (7.6%) and 309 females (0.4%) met the wide criteria. Erythrocytosis, only when defined using strict criteria, was associated with cardiovascular morbidity (odds ratio [OR], 1.8; 95% confidence interval [CI], 1.2-2.6), cardiovascular mortality (hazard ratio [HR], 2.2; 95% CI, 1.0-4.6), and all-cause mortality (HR, 1.7; 95% CI, 1.2-2.6), independent of conventional risk factors. Mutations were detected in 51 of 133 (38%) evaluable individuals, with comparable frequencies between individuals with and without concurrent cytosis. The JAK2 V617F mutation was observed in 7 of 133 (5.3%) individuals, all having concurrent cytosis. The prevalence of mutations in BCOR/BCORL1 (16%) was high, suggesting aberrant epigenetic regulation. Erythrocytosis with CH was associated with cardiovascular morbidity (OR, 9.1; 95% CI, 1.2-68.4) in a multivariable model. Our data indicate that only when defined using strict criteria erythrocytosis is associated with cardiovascular morbidity (especially in the presence of CH), cardiovascular mortality, and all-cause mortality.

Association of Recognized and Unrecognized Myocardial Infarction With Depressive and Anxiety Disorders in 125,988 Individuals: A Report of the Lifelines Cohort Study

OBJECTIVE

No previous study has focused on recognition of myocardial infarction (MI) and the presence of both depressive and anxiety disorders in a large population-based sample. The aim of this study was to investigate the association of recognized MI (RMI) and unrecognized MI (UMI) with depressive and anxiety disorders.

METHODS

Analyses included 125,988 individuals enrolled in the Lifelines study. Current mental disorders according to the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) were assessed with the Mini-International Neuropsychiatric Interview. UMI was detected using electrocardiogram in participants who did not report a history of MI. The classification of RMI was based on self-reported MI history together with the use of either antithrombotic medications or electrocardiogram signs of MI. Analyses were adjusted for age, sex, smoking, somatic comorbidities, and physical health-related quality of life as measured by the RAND 36-Item Health Survey in different models.

RESULTS

Participants with RMI had significantly higher odds of having any depressive and any anxiety disorder as compared with participants without MI (depressive disorder: odds ratio [OR] = 1.86, 95% confidence interval [CI] = 1.38-2.52; anxiety disorder: OR = 1.60, 95% CI = 1.32-1.94) after adjustment for age and sex. Participants with UMI did not differ from participants without MI (depressive disorder: OR = 1.60, 95% CI = 0.96-2.64; anxiety disorder: OR = 0.73, 95% CI = 0.48-1.11). After additional adjustment for somatic comorbidities and low physical health-related quality of life, the association between RMI with any depressive disorder was no longer statistically significant (OR = 1.18; 95% CI =0.84-1.65), but the association with any anxiety disorder remained (OR = 1.27, 95% CI = 1.03-1.57).

CONCLUSIONS

Recognition of MI seems to play a major role in the occurrence of anxiety, but not depressive, disorders.

Proactive screening for symptoms: A simple method to improve early detection of unrecognized cardiovascular disease in primary care. Results from the Lifelines Cohort Study

Cardiovascular disease (CVD) often goes unrecognized, despite symptoms frequently being present. Proactive screening for symptoms might improve early recognition and prevent disease progression or acute cardiovascular events. We studied the diagnostic value of symptoms for the detection of unrecognized atrial fibrillation (AF), heart failure (HF), and coronary artery disease (CAD) and developed a corresponding screening questionnaire. We included 100,311 participants (mean age 52 ± 9 years, 58% women) from the population-based Lifelines Cohort Study. For each outcome (unrecognized AF/HF/CAD), we built a multivariable model containing demographics and symptoms. These models were combined into one 'three-disease' diagnostic model and questionnaire for all three outcomes. Results were validated in Lifelines participants with chronic obstructive pulmonary disease (COPD) and diabetes mellitus (DM). Unrecognized CVD was identified in 1325 participants (1.3%): AF in 131 (0.1%), HF in 599 (0.6%), and CAD in 687 (0.7%). Added to age, sex, and body mass index, palpitations were independent predictors for unrecognized AF; palpitations, chest pain, dyspnea, exercise intolerance, health-related stress, and self-expected health worsening for unrecognized HF; smoking, chest pain, exercise intolerance, and claudication for unrecognized CAD. Area under the curve for the combined diagnostic model was 0.752 (95% CI 0.737-0.766) in the total population and 0.757 (95% CI 0.734-0.781) in participants with COPD and DM. At the chosen threshold, the questionnaire had low specificity, but high sensitivity. In conclusion, a short questionnaire about demographics and symptoms can improve early detection of CVD and help pre-select people who should or should not undergo further screening for CVD.

Sex-Based Differences in Unrecognized Myocardial Infarction

Background

Myocardial infarction is an important cause of morbidity and mortality in both men and women. Atypical or the absence of symptoms, more prevalent among women, may contribute to unrecognized myocardial infarctions and missed opportunities for preventive therapies. The aim of this research is to investigate sex‐based differences of undiagnosed myocardial infarction in the general population.

Methods and Results

In the Lifelines Cohort Study, all individuals ≥18 years with a normal baseline ECG were followed from baseline visit till first follow‐up visit (≈5 years, n=97 203). Individuals with infarct‐related changes between baseline and follow‐up ECGs were identified. The age‐ and sex‐specific incidence rates were calculated and sex‐specific cardiac symptoms and predictors of unrecognized myocardial infarction were determined. Follow‐up ECG was available after a median of 3.8 (25th and 75th percentile: 3.0–4.6) years. During follow‐up, 198 women experienced myocardial infarction (incidence rate 1.92 per 1000 persons‐years) compared with 365 men (incidence rate 3.30; P<0.001 versus women). In 59 (30%) women, myocardial infarction was unrecognized compared with 60 (16%) men (P<0.001 versus women). Individuals with unrecognized myocardial infarction less often reported specific cardiac symptoms compared with individuals with recognized myocardial infarction. Predictors of unrecognized myocardial infarction were mainly hypertension, smoking, and higher blood glucose level.

Conclusions

A substantial proportion of myocardial infarctions are unrecognized, especially in women. Opportunities for secondary preventive therapies remain underutilized if myocardial infarction is unrecognized.

Myocardial infarction evaluation from stopping time decision toward interoperable algorithmic states in reinforcement learning

BACKGROUND

The Elliot wave principle commonly characterizes the impulsive and corrective wave trends for both financial market trends and electrocardiograms. The impulsive wave trends of electrocardiograms can annotate several wave components of heart-beats including pathological heartbeat waveforms. The stopping time inquires which ordinal element satisfies the assumed mathematical condition within a numerical set. The proposed work constitutes several algorithmic states in reinforcement learning from the stopping time decision, which determines the impulsive wave trends. Each proposed algorithmic state is applicable to any relevant algorithmic state in reinforcement learning with fully numerical explanations. Because commercial electrocardiographs still misinterpret myocardial infarctions from extraordinary electrocardiograms, a novel algorithm needs to be developed to evaluate myocardial infarctions. Moreover, differential diagnosis for right ventricle infarction is required to contraindicate a medication such as nitroglycerin.

METHODS

The proposed work implements the stopping time theory to impulsive wave trend distribution. The searching process of the stopping time theory is equivalent to the actions toward algorithmic states in reinforcement learning. The state value from each algorithmic state represents the numerically deterministic annotated results from the impulsive wave trend distribution. The shape of the impulsive waveform is evaluated from the interoperable algorithmic states via least-first-power approximation and approximate entropy. The annotated electrocardiograms from the impulsive wave trend distribution utilize a structure of neural networks to approximate the isoelectric baseline amplitude value of the electrocardiograms, and detect the conditions of myocardial infarction. The annotated results from the impulsive wave trend distribution consist of another reinforcement learning environment for the evaluation of impulsive waveform direction.

RESULTS

The accuracy to discern myocardial infarction was found to be 99.2754% for the data from the comma-separated value format files, and 99.3579% for those containing representative beats. The clinical dataset included 276 electrocardiograms from the comma-separated value files and 623 representative beats.

CONCLUSIONS

Our study aims to support clinical interpretation on 12-channel electrocardiograms. The proposed work is suitable for a differential diagnosis under infarction in the right ventricle to avoid contraindicated medication during emergency. An impulsive waveform that is affected by myocardial infarction or the electrical direction of electrocardiography is represented as an inverse waveform.

Prognosis of unrecognised myocardial infarction determined by electrocardiography or cardiac magnetic resonance imaging: systematic review and meta-analysis

OBJECTIVE

To evaluate the prognosis of unrecognised myocardial infarction determined by electrocardiography (UMI-ECG) or cardiac magnetic resonance imaging (UMI-CMR).

DESIGN

Systematic review and meta-analysis of prospective studies.

DATA SOURCES

Electronic databases, including PubMed, Embase, and Google Scholar.

STUDY SELECTION

Prospective cohort studies were included if they reported adjusted relative risks, odds ratios, or hazard ratios and 95% confidence intervals for all cause mortality or cardiovascular outcomes in participants with unrecognised myocardial infarction compared with those without myocardial infarction.

DATA EXTRACTION AND SYNTHESIS

The primary outcomes were composite major adverse cardiac events, all cause mortality, and cardiovascular mortality associated with UMI-ECG and UMI-CMR. The secondary outcomes were the risks of recurrent coronary heart disease or myocardial infarction, stroke, heart failure, and atrial fibrillation. Pooled hazard ratios and 95% confidence intervals were reported. The heterogeneity of outcomes was compared in clinically recognised and unrecognised myocardial infarction.

RESULTS

The meta-analysis included 30 studies with 253 425 participants and 1 621 920 person years of follow-up. UMI-ECG was associated with increased risks of all cause mortality (hazard ratio 1.50, 95% confidence interval 1.30 to 1.73), cardiovascular mortality (2.33, 1.66 to 3.27), and major adverse cardiac events (1.61, 1.38 to 1.89) compared with the absence of myocardial infarction. UMI-CMR was also associated with increased risks of all cause mortality (3.21, 1.43 to 7.23), cardiovascular mortality (10.79, 4.09 to 28.42), and major adverse cardiac events (3.23, 2.10 to 4.95). No major heterogeneity was observed for any primary outcomes between recognised myocardial infarction and UMI-ECG or UMI-CMR. The absolute risk differences were 7.50 (95% confidence interval 4.50 to 10.95) per 1000 person years for all cause mortality, 11.04 (5.48 to 18.84) for cardiovascular mortality, and 27.45 (17.1 to 40.05) for major adverse cardiac events in participants with UMI-ECG compared with those without myocardial infarction. The corresponding data for UMI-CMR were 32.49 (6.32 to 91.58), 37.2 (11.7 to 104.20), and 51.96 (25.63 to 92.04), respectively.

CONCLUSIONS

UMI-ECG or UMI-CMR is associated with an adverse long term prognosis similar to that of recognised myocardial infarction. Screening for unrecognised myocardial infarction could be useful for risk stratification among patients with a high risk of cardiovascular disease.

Electrocardiographic screening in primary care for cardiovascular disease risk and atrial fibrillation

Electrocardiograms (ECGs) are frequently recorded in primary care for screening purposes. An ECG is essential in diagnosing atrial fibrillation, and ECG abnormalities are associated with cardiovascular events. While recent studies show that ECGs adequately reclassify a proportion of patients based on the clinical risk score calculations, there are no data to support that this also results in improved health outcomes. When applied for screening for atrial fibrillation, more cases are found with routine care, but this would be undone when physicians would perform systematic pulse palpation. In most studies, the harms of routine ECG use (such as unnecessary diagnostic testing, emotional distress, increased health expenses) were poorly documented. As such, the routine performing of ECGs in asymptomatic primary care patients, whether it is for cardiovascular disease risk assessment or atrial fibrillation, cannot be recommended.

Missed Acute Myocardial Infarction (MAMI) in a rural and regional setting

Background

Delay in treatment and/or failure to provide reperfusion in ST-segment elevation myocardial infarction (STEMI) impacts on morbidity and mortality. This occurs more often outside metropolitan areas yet the reasons for this are unclear. This study aimed to describe factors associated with missed diagnosis of acute myocardial infarction (MAMI) in a rural and regional setting.

Methods

Using a retrospective cohort design, patients who presented with STEMI and failed to receive reperfusion therapy within four hours were identified as MAMI. Univariate analyses were undertaken to identify differences in clinical characteristics between the treated STEMI group and the MAMI group. Mortality, 30-day readmission rates and length of hospital stay are reported.

Results

Of 100 patients identified as MAMI (70 male, 30 female), 24 died in hospital. Demographics and time from symptom onset were similar in the treated STEMI and MAMI groups. Of the MAMI patients who died, rural hospitals recorded the highest inpatient mortality (69.6% p = 0.008). MAMI patients compared to treated STEMI patients had higher 30 day readmission (31.6% vs 3.3%, p = 0.001) and longer length of stay (5.5 vs 4.3 days p = 0.029). Inaccurate identification of STEMI on electrocardiogram (72%) and diagnostic uncertainty (65%) were associated with MAMI. The Glasgow algorithm to identify STEMI was utilised on 57% of occasions, with 93% accuracy.

Conclusion

Mortality following MAMI is high particularly in smaller rural hospitals. MAMI results in increased length of stay and readmission rate. Electrocardiogram interpretation and diagnostic accuracy require improvement to determine if this improves patient outcomes.

Electrocardiographic unrecognized myocardial infarction does not improve prediction of cardiovascular events beyond traditional risk factors. The Tromsø Study

Background Unrecognized myocardial infarction (MI) is a frequent and intriguing entity associated with a similar risk of death as recognized MI. Previous studies have not fully addressed whether the poor prognosis is explained by traditional cardiovascular risk factors. We investigated whether electrocardiographically detected unrecognized MI was independently associated with cardiovascular events and death and whether it improved prediction for future MI in a general population. Design Prospective cohort study. Methods We studied 5686 women and men without clinically recognized MI at baseline in 2007-2008. We assessed the risk of future MI, stroke and all-cause mortality in persons with unrecognized MI compared with persons with no MI during 31,051 person-years of follow-up. Results In the unadjusted analyses, unrecognized MI was associated with increased risk of future recognized MI (hazard ratio 1.84, 95% confidence interval (CI) 1.15-2.96) and all-cause mortality (hazard ratio 1.78, 95% CI 1.21-2.61), but not stroke (hazard ratio 1.09, 95% CI 0.56-2.17). The associations did not remain significant after adjustment for traditional risk factors (hazard ratio 1.25, 95% CI 0.76-2.06 and hazard ratio 1.38, 95% CI 0.93-2.05) for MI and all-cause mortality respectively. Unrecognized MI did not improve risk prediction for future recognized MI using the Framingham Risk Score ( p = 0.96) or the European Systematic COronary Risk Evaluation ( p = 0.65). There was no significant sex interaction regarding any of the endpoints. Conclusion Electrocardiographic unrecognized MI was not significantly associated with future risk of MI, stroke or all-cause mortality in the general population after adjustment for the traditional cardiovascular risk factors, and it did not improve prediction of future MI.