Use of Imaging-guided Decongestion for Reducing Heart Failure Readmission and Death in High-risk Patients: A Multi-site Randomized Trial of a Nurse-led Strategy at the Point of Care.

BACKGROUND: Nurse-led disease management programs (DMPs) decrease readmission after acute decompensated heart failure (HF). We sought whether readmissions could be further reduced by lung ultrasound (LUS)-guided decongestion before discharge and during DMP. METHODS AND RESULTS: Of 290 patients hospitalized with acute decompensated HF, 122 at high risk for readmission or mortality were randomized to receive usual care (UC) (n = 64) or UC plus intervention (DMP-Plus) (n = 58), comprising LUS-guided management before discharge and during at-home follow-up. Residual congestion was identified by ≥10 B-lines detected in 8 lung zones. The outcomes included a composite of readmission and/or mortality at 30 and 90 days, and 90-day HF readmission. Residual congestion was detected equally among the patient groups. The 30-day composite outcome occurred in 28% DMP-plus patients and 22% UC patients (odd ratio [OR], 1.36; 95% confidence interval [CI], 0.59-3.1; P = .5) and the 90-day HF readmission outcome occurred in 22% and 31%, respectively (odds ratio, 0.63; 95% CI, 0.28-1.43; P = .3). Residual congestion, identified at predischarge LUS examination in high-risk patients, was associated with early (<14-day) HF readmission (relative risk, 1.19; 95% CI, 1.06-1.32; P = .002) and multiple (≥2) readmissions over 90 days of follow-up (relative risk, 1.09; 95% CI, 1.01-1.16; P = .012), independent of demographics and comorbidities. CONCLUSIONS: Readmission in patients with incomplete decongestion before discharge occurs within the first 2 weeks. However, our DMP-plus strategy did not improve the primary outcome.

A novel approach to accurately measuring the burden of hospitalisations for cardiovascular disease in people with diabetes: A pilot study.

AIM: To determine the reliability of hospital discharge codes for heart failure (HF), acute myocardial infarction (AMI) and stroke compared with adjudicated diagnosis, and to pilot a scalable approach to adjudicate records on a population-based sample. METHODS: A population-based sample of 685 people with diabetes admitted (1274 admissions) to one of three Australian hospitals during 2018-2020 were randomly selected for this study. All medical records were reviewed and adjudicated. RESULTS: Cardiovascular diseases were the most common primary reason for hospitalisation in people with diabetes, accounting for ~17% (215/1274) of all hospitalisations, with HF as the leading cause. ICD-10 codes substantially underestimated HF prevalence and had the lowest agreement with the adjudicated diagnosis of HF (Kappa = 0.81), compared with AMI and stroke (Kappa ≥ 0.91). While ICD-10 codes provided suboptimal sensitivity (72%) for HF, the performance was better for AMI (sensitivity 84%; specificity 100%) and stroke (sensitivity 85%; specificity 100%). A novel approach to screen possible HF cases only required adjudicating 8% (105/1274) of records, correctly identified 78/81 of HF admissions and yielded 96% sensitivity and 98% specificity. CONCLUSIONS: While ICD-10 codes appear reliable for AMI or stroke, a more complex diagnosis such as HF benefits from a two-stage process to screen for suspected HF cases that need adjudicating. The next step is to validate this novel approach on large multi-centre studies in diabetes.

Hospital admissions among people with diabetes: A systematic review.

OBJECTIVE: To describe the reasons for hospital admission among people with diabetes. METHODS: We searched Emcare, Embase, Medline and Google Scholar databases for population-based studies describing the causes of hospitalisation among people with diabetes. We included articles published in English from 1980 to 2022. For each study, we determined the most frequent reasons for admission. Studies were assessed for quality using the Newcastle Ottawa quality assessment tool. RESULTS: 6920 research articles were retrieved from the search of all sources. After screening the titles and abstracts of these, we reviewed the full text of 135 papers and finally included data from 42 studies. Admissions among the total diabetes were reported in 25 papers: 5 articles reported type 1 diabetes alone, 10 articles reported type 2 diabetes alone and the remaining 2 articles reported type 1 and type 2 diabetes separately. Among the 25 total and type 2 diabetes studies that reported the distribution of hospitalisations in broad categories, cardiovascular diseases (CVD) were the leading cause of admission in 19/25 (76%) of studies. Among the 19 studies that reported CVD admissions by subcategories, ischaemic or coronary heart disease was the leading subtype of CVD in 58% of studies. The other common causes of admissions were infections, renal disorders, endocrine, nutritional, metabolic and immunity disorders. In people with type 1 diabetes, acute diabetes complications were the leading cause of admission. CONCLUSION: CVD are the leading cause of hospital admission for people with diabetes, with ischaemic or coronary heart disease as the predominant subtype.

Use of clinical scores in young Australian adults for prediction of atherosclerosis in middle age.

We sought to apply a simple cardiovascular health tool not requiring laboratory tests (the Fuster-BEWAT score, FBS) to predict subclinical atherosclerosis. This study included 2657 young adults (< 40 years of age). In the prognostic group (n = 894, followed for 13 years until aged 40-50 years at follow-up), the primary outcome was presence of carotid plaque measured by carotid ultrasound at follow-up. Of these 894 participants, 86 (9.6%) had unilateral, and 23 participants (2.6%) had bilateral, carotid plaques at follow-up. The baseline FBS was predictive of carotid plaque at follow-up [odds ratio OR = 0.86 (95% CI 0.77-0.96) per 1-SD increase in FBS], similar to prediction from Pooled Cohort Equation [PCE, OR = 0.72 (0.61-0.85) per 1-SD decrease in PCE]. Risk scores at baseline predicted outcomes more strongly than those at follow-up, and did so independently of any changes over 13 years of follow-up. Similar discrimination for predicting carotid plaque after 13 years was found for both baseline FBS [C-statistic = 0.68 (95% CI 0.62-0.74)] and PCE [C-statistic = 0.69 (95% CI 0.63-0.75)]. Application of this FBS prognostic information to a contemporary cohort of 1763 young adults anticipates the future development of plaque in 305 (17.3%), especially in the 1494 participants (85%) with ≤ 2 metrics of ideal health. In conclusions, FBS measured in young adulthood predicted atherosclerosis 13 years later in middle age, independent of score changes over the follow-up period, emphasizing the importance of early damage to vascular health. FBS may be a simple and feasible risk score for engaging low-risk young people with reduction of future cardiovascular risk.

Associations between symptoms and functional capacity in patients after COVID-19 infection and community controls.

BACKGROUND: Post-acute sequelae of COVID-19 (PASC or 'long COVID') reflect ongoing symptoms, but these are non-specific and common in the wider community. Few reports of PASC have been compared with a control group. AIMS: To compare symptoms and objective impairment of functional capacity in patients with previous COVID-19 infection with uninfected community controls. METHODS: In this community-based, cross-sectional study of functional capacity, 562 patients from Western Melbourne who had recovered from COVID-19 infections in 2021 and 2022 were compared with controls from the same community and tested for functional capacity pre-COVID-19. Functional impairment (<85% of the predicted response) was assessed using the Duke Activity Status Index (DASI) and 6-min walk distance (6MWD) test. A subgroup underwent cardiopulmonary exercise testing before and after exercise training. RESULTS: Of 562 respondents (age 54 ± 12 years, 69% women), 389 were symptomatic. Functional impairment (<85% predicted metabolic equivalent of tasks) was documented by DASI in 149 participants (27%), and abnormal 6MWD (<85% predicted) was observed in 14% of the symptomatic participants. Despite fewer risk factors and younger age, patients with COVID-19 had lower functional capacity by 6MWD (P < 0.001) and more depression (P < 0.001) than controls. In a pilot group of seven participants (age 58 ± 12 years, two women, VO2 18.9 ± 5.7 mL/kg/min), repeat testing after exercise training showed a 20% increase in peak workload. CONCLUSIONS: Although most participants (69%) had symptoms consistent with long COVID, significant subjective functional impairment was documented in 27% and objective functional impairment in 14%. An exercise training programme might be beneficial for appropriately selected patients.

Cognitive Dysfunction in Heart Failure: Pathophysiology and Implications for Patient Management.

PURPOSE OF REVIEW: There is increasing recognition of the prevalence and impact of cognitive dysfunction (CD) in heart failure (HF) patients. This contemporary review appraises the evidence for epidemiological association, direct pathophysiological links and emerging pharmacological and non-pharmacological interventions. Furthermore, we present evidence for care models that aim to mitigate the morbidity and poor quality of life associated with these dual processes and propose future work to improve outcomes. RECENT FINDINGS: CD disproportionately affects heart failure patients, even accounting for known comorbid risk factors, and this may extend to subclinical left ventricular dysfunction. Neuroimaging studies now provide evidence of anatomical and functional differences which support previously postulated mechanisms of reduced cerebral blood flow, micro-embolism and systemic inflammation. Interventions such as multidisciplinary ambulatory HF care, education and memory training improve HF outcomes perhaps to a greater degree in those with comorbid CD. Additionally, optimisation of standard heart failure care (cardiac rehabilitation, pharmacological and device therapy) may lead to additional cognitive benefits. Epidemiological, neuroimaging and intervention studies provide evidence for the causal association between HF and CD, although evidence for Alzheimer's dementia is less certain. Specific reporting of cognitive outcomes in HF trials and evaluation of targeted interventions is required to further guide care provision.

Metformin treatment in heart failure with preserved ejection fraction: a systematic review and meta-regression analysis.

BACKGROUND: Observational series suggest a mortality benefit from metformin in the heart failure (HF) population. However, the benefit of metformin in HF with preserved ejection fraction (HFpEF) has yet to be explored. We performed a systematic review and meta-analysis to identify whether variation in EF impacts mortality outcomes in HF patients treated with metformin. METHODS: MEDLINE and EMBASE were searched up to October 2019. Observational studies and randomised trials reporting mortality in HF patients and the proportion of patients with an EF > 50% at baseline were included. Other baseline variables were used to assess for heterogeneity in treatment outcomes between groups. Regression models were used to determine the interaction between metformin and subgroups on mortality. RESULTS: Four studies reported the proportion of patients with a preserved EF and were analysed. Metformin reduced mortality in both preserved or reduced EF after adjustment with HF therapies such as angiotensin converting enzyme inhibitors (ACEi) and beta-blockers (ß = - 0.2 [95% CI - 0.3 to - 0.1], p = 0.02). Significantly greater protective effects were seen with EF > 50% (p = 0.003). Metformin treatment with insulin, ACEi and beta-blocker therapy were also shown to have a reduction in mortality (insulin p = 0.002; ACEi p < 0.001; beta-blocker p = 0.017), whereas female gender was associated with worse outcomes (p < 0.001). CONCLUSIONS: Metformin treatment is associated with a reduction in mortality in patients with HFpEF.

Coronary artery calcium scoring in cardiovascular risk assessment of people with family histories of early onset coronary artery disease.

OBJECTIVES: To assess the predictive value of the Australian absolute cardiovascular disease risk (ACVDR) calculator and other assessment tools for identifying Australians with family histories of early onset coronary artery disease (CAD) who have coronary artery calcification. DESIGN, SETTING, PARTICIPANTS: People without known CAD were recruited at seven Australian hospitals, October 2016 - January 2019. Participants were aged 40-70 years, had a family history of early onset CAD, and a 5-year ACVDR of 2-15%. MAIN OUTCOME MEASURES: CT coronary artery calcium score greater than zero (any coronary calcification) or greater than 100 (calcification warranting lipid therapy). RESULTS: 1059 participants were recruited; 477 (45%) had non-zero coronary artery calcium scores (median 5-year ACVDR, 4.8% [IQR, 2.9-7.6%]; median coronary artery calcium score, 41.7 [IQR, 8-124]); 582 (55%) did not (median 5-year ACVDR, 3.2% [IQR, 2.0-4.6%]). Of 151 participants with calcium scores of 100 or more, 116 (77%) were deemed to be at low cardiovascular risk by Australian guidelines, while 14 of 75 participants at intermediate risk (19%) had zero calcium scores. The sensitivity of the ACVDR calculator for identifying people with non-zero calcium scores (area under receiver operator curve [AUC], 0.674) was lower than that of the pooled cohort equation (AUC, 0.711; P < 0.001). ACVDR (10-year)- and Multi-Ethnic Study of Atherosclerosis (MESA)-predicted risk categories concurred for 511 participants (48%); classifications were concordant for 925 participants (87%) when the ACVDR was supplemented by calcium scores. CONCLUSIONS: Coronary artery calcium scoring should be considered as part of the heart health check for patients at intermediate ACVDR risk and with family histories of early onset CAD. Alternative risk calculators may better select such patients for further diagnostic testing and primary prevention therapy. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN 12614001294640; 11 December 2014 (prospective).

Independence of coronary artery disease to subclinical left ventricular dysfunction.

OBJECTIVE: Epicardial atherosclerosis and heart failure while distinct clinical entities share common pathophysiological features including endothelial dysfunction and inflammation. Presence of subclinical disease could lead to early diagnosis and intervention in the other. The aim of our study was to assess the association between coronary calcium score (CCS), conventional cardiovascular risk factors, and echocardiographic markers of subclinical left ventricular dysfunction (S-LVD). METHODS: One hundred and fifty-nine participants aged 40-70 years with intermediate risk of coronary artery disease (5-year risk of 2%-15%) were identified. Computed tomography (CT) CCS and 2-D transthoracic echocardiography were performed. Main outcomes included presence of subclinical left ventricular dysfunction defined by reduced average global longitudinal strain, left atrial volume enlargement, and elevated E/e'. RESULTS: Fifteen participants had evidence of subclinical LV dysfunction (8 with systolic dysfunction and 7 with diastolic dysfunction) and 85 participants had CCS > 0. CCS > 0 was present in 10 participants with S-LVD compared to 75 participants without S-LVD (67% vs 53%, P = .47). There was no significant difference between in mean GLS (19.2 vs 19.5, P = .14), E/e' (7.2 vs 7.5 P = .33) in those without or with coronary artery calcium. Elevated CCS was also not associated with a higher tertiles of indexed LV mass (OR 1.15, P = .49) or index left atrial volume (OR 1.15, P = .49). CONCLUSIONS: In an asymptomatic, low-intermediate-risk group, mechanistic processes that lead to atherosclerosis are not directly associated with subclinical LV dysfunction.

Influence of Risk on Reduction of Readmission and Death by Disease Management Programs in Heart Failure.

OBJECTIVE: Disease management programs (DMPs) may reduce short-term readmission or death after heart failure (HF) hospitalization. We sought to determine if targeting of DMP to the highest-risk patients could improve efficiency. METHODS AND RESULTS: Patients (n = 412) admitted with HF were randomized to usual care or an intensive DMP including optimizing intravascular volume status at discharge, increased self-care education, exercise guidance, closer home surveillance, and increased intensity of HF nurse follow-up. Both treatment groups were similar in demographics, medication use, Charlson comorbidity index, ejection fraction, and left ventricular and atrial volumes. Readmission or death occurred in 74/197 (37%) usual care and 50/215 (23%) DMP patients within 30 days (relative risk [RR] 0.62, 95% confidence interval [CI] 0.46-0.84), and 113/197 (57%) usual care and 78/215 (36%) DMP patients within 90 days, (RR 0.63, 9%% CI 0.51-0.78). The predicted risk of death and readmission (estimated from our previously developed risk score) was similar between treatment groups (mean predicted risk 38.6 ± 22.2% vs 39.4 ± 21.9%; P = .73) and similar across categories of predicted risk between the treatment groups. For 30-day readmission or death, patients from the 2 highest risk quintiles showed a benefit from intervention, and there was an interaction between intervention and predicted risk (P = .02). For 90-day readmission or death, most patients-other than those in the lowest-risk quintile-benefited from the intervention. CONCLUSIONS: Use of a risk score may permit targeting of DMP to reduce HF admission. Intensive DMP may reduce short-term readmission or death, particularly in high-risk patients.

Effects of post-discharge management on rates of early re-admission and death after hospitalisation for heart failure.

OBJECTIVES: To investigate whether enrolment of patients in management programs after hospitalisation for heart failure (HF) reduces the likelihood of post-hospital adverse outcomes. DESIGN: Cohort study in which associations between adverse outcomes at 30 and 90 days for people hospitalised for HF and baseline clinical, socio-demographic and blood pathology factors, and with post-discharge management strategies, were assessed. Setting, participants: 906 patients with HF were prospectively enrolled in five Australian states at cardiology departments with expertise in treating people with HF. MAIN OUTCOME MEASURES: All-cause re-admissions and deaths at 30 and 90 days after discharge from the index admission. RESULTS: 58% of patients were men; the mean age was 72.5 years (SD, 13.9 years). By hospital, 30-day re-admission rates ranged from 17% to 33%, and 90-day rates from 40% to 55%; 30-day mortality rates were 0-13%, 90-day rates 4-24%. Factors associated with increased odds of re-admission or death at 30 or 90 days included living alone, cognitive impairment, depression, NYHA classification, left atrial volume index, and Charlson index score. Nurse-led disease management programs and reviews within 7 days were associated with reduced odds of re-admission (but not of death) at 30 and 90 days; exercise programs were associated with reduced odds at 90 days. Significant between-hospital differences in re-admission rates were reduced after adjustment for post-discharge management programs, and abolished by further adjustment for echocardiography findings. Between-hospital differences in mortality were largely explained by differences in echocardiographic findings. CONCLUSIONS: Differences in early re-admission rates after hospitalisation for HF are primarily explained by differences in post-discharge management.

Roles of nonclinical and clinical data in prediction of 30-day rehospitalization or death among heart failure patients.

BACKGROUND: Selecting heart failure (HF) patients for intensive management to reduce readmissions requires effective targeting. However, available prediction scores are only modestly effective. We sought to develop a prediction score for 30-day all-cause rehospitalization or death in HF with the use of nonclinical and clinical data. METHODS AND RESULTS: This statewide data linkage included all patients who survived their 1st HF admission (with either reduced or preserved ejection fraction) to a Tasmanian public hospital during 2009-2012. Nonclinical data (n = 1,537; 49.5% men, median age 80 y) included administrative, socioeconomic, and geomapping data. Clinical data before discharge were available from 977 patients. Prediction models were developed and internally and externally validated. Within 30 days of discharge, 390 patients (25.4%) died or were rehospitalized. The nonclinical model (length of hospital stay, age, living alone, discharge during winter, remoteness index, comorbidities, and sex) had fair discrimination (C-statistic 0.66 [95% confidence interval (CI) 0.63-0.69]). Clinical data (blood urea nitrogen, New York Heart Association functional class, albumin, heart rate, respiratory rate, diuretic use, angiotensin-converting enzyme inhibitor use, arrhythmia, and troponin) provided better discrimination (C-statistic 0.72 [95% CI 0.68-0.76]). Combining both data sources best predicted 30-day rehospitalization or death (C-statistic 0.76 [95% CI 0.72-0.80]). CONCLUSIONS: Clinical data are stronger predictors than nonclinical data, but combining both best predicts 30-day rehospitalization or death among HF patients.

Declining Prevalence of Tobacco Smoking in Vietnam.

INTRODUCTION: To supplement limited information on tobacco use in Vietnam, data from a nationally-representative population-based survey was used to estimate the prevalence of smoking among 25-64 year-olds. METHODS: This study included 14,706 participants (53.5% females, response proportion 64%) selected by multi-stage stratified cluster sampling. Information was collected using the World Health Organization STEPwise approach to surveillance of risk factors for non-communicable disease (STEPS) questionnaire. Smoking prevalence was estimated with stratification by age, calendar year, and birth year. RESULTS: Prevalence of ever-smoking was 74.9% (men) and 2.6% (women). Male ever-smokers commenced smoking at median age of 19.0 (interquartile range [IQR]: 17.0, 21.0) years and smoked median quantities of 10.0 (IQR: 7.0, 20.0) cigarettes/day. Female ever-smokers commenced smoking at median age of 20.0 (IQR: 18.0, 26.0) years and smoked median quantities of 6.0 (IQR: 4.0, 10.0) cigarettes/day. Prevalence has decreased in recent cohorts of men (p = .001), and its inverse association with years of education (p < .001) has strengthened for those born after 1969 (interaction p < .001). At 60 years of age, 53.0% of men who had reached that age were current smokers and they had accumulated median exposures of 39.0 (IQR: 32.0, 42.0) years of smoking and 21.0 (IQR: 11.5, 36.0) pack-years of cigarettes. The proportion of ever-smokers has decreased consistently among successive cohorts of women (p < .001). CONCLUSIONS: Smoking prevalence is declining in recent cohorts of men, and continues to decline in successive cohorts of women, possibly in response to anti-tobacco initiatives commencing in the 1990s. Low proportions of quitters mean that Vietnamese smokers accumulate high exposures despite moderate quantities of cigarettes smoked per day.

Exposure to parental smoking in childhood or adolescence is associated with increased carotid intima-media thickness in young adults: evidence from the Cardiovascular Risk in Young Finns study and the Childhood Determinants of Adult Health Study.

AIM: Recent evidence suggests that the exposure of children to their parents' smoking adversely effects endothelial function in adulthood. We investigated whether the association was also present with carotid intima-media thickness (IMT) up to 25 years later. METHODS AND RESULTS: The study comprised participants from the Cardiovascular Risk in Young Finns Study (YFS, n = 2401) and the Childhood Determinants of Adult Health (CDAH, n = 1375) study. Exposure to parental smoking (none, one, or both) was assessed at baseline by questionnaire. B-mode ultrasound of the carotid artery determined IMT in adulthood. Linear regression on a pooled dataset accounting for the hierarchical data and potential confounders including age, sex, parental education, participant smoking, education, and adult cardiovascular risk factors was conducted. Carotid IMT in adulthood was greater in those exposed to both parents smoking than in those whose parents did not smoke [adjusted marginal means: 0.647 mm ± 0.022 (mean ± SE) vs. 0.632 mm ± 0.021, P = 0.004]. Having both parents smoke was associated with vascular age 3.3 years greater at follow-up than having neither parent smoke. The effect was independent of participant smoking at baseline and follow-up and other confounders and was uniform across categories of age, sex, adult smoking status, and cohort. CONCLUSIONS: These results show the pervasive effect of exposure to parental smoking on children's vascular health up to 25 years later. There must be continued efforts to reduce smoking among adults to protect young people and to reduce the burden of cardiovascular disease across the population.

Impact of adiposity on cardiac structure in adult life: the Childhood Determinants of Adult Health (CDAH) study.

BACKGROUND: We have examined the association between adiposity and cardiac structure in adulthood, using a life course approach that takes account of the contribution of adiposity in both childhood and adulthood. METHODS: The Childhood Determinants of Adult Health study (CDAH) is a follow-up study of 8,498 children who participated in the 1985 Australian Schools Health and Fitness Survey (ASHFS). The CDAH follow-up study included 2,410 participants who attended a clinic examination. Of these, 181 underwent cardiac imaging and provided complete data. The measures were taken once when the children were aged 9 to 15 years, and once in adult life, aged 26 to 36 years. RESULTS: There was a positive association between adult left ventricular mass (LVM) and childhood body mass index (BMI) in males (regression coefficient (ß) 0.41; 95% confidence interval (CI): 0.14 to 0.67; p = 0.003), and females (ß = 0.53; 95% CI: 0.34 to 0.72; p < 0.001), and with change in BMI from childhood to adulthood (males: ß = 0.27; 95% CI: 0.04 to 0.51; p < 0.001, females: ß = 0.39; 95% CI: 0.20 to 0.58; p < 0.001), after adjustment for confounding factors (age, fitness, triglyceride levels and total cholesterol in adulthood). After further adjustment for known potential mediating factors (systolic BP and fasting plasma glucose in adulthood) the relationship of LVM with childhood BMI (males: ß = 0.45; 95% CI: 0.19 to 0.71; p = 0.001, females: ß = 0.49; 95% CI: 0.29 to 0.68; p < 0.001) and change in BMI (males: ß = 0.26; 95% CI: 0.04 to 0.49; p = 0.02, females: ß = 0.40; 95% CI: 0.20 to 0.59; p < 0.001) did not change markedly. CONCLUSIONS: Adiposity and increased adiposity from childhood to adulthood appear to have a detrimental effect on cardiac structure.

Use of Clinical and Echocardiographic Evaluation to Assess the Risk of Heart Failure.

BACKGROUND: Clinical and echocardiographic features predict incident heart failure (HF), but the optimal strategy for combining them is unclear. OBJECTIVES: This study sought to define an effective means of using echocardiography in HF risk evaluation. METHODS: The same clinical and echocardiographic evaluation was obtained in 2 groups with HF risk factors: a training group (n = 926, followed to 7 years) and a validation group (n = 355, followed to 10 years). Clinical risk was categorized as low, intermediate, and high using 4-year ARIC (Atherosclerosis Risk In Communities) HF risk score cutpoints of 9% and 33%. A risk stratification algorithm based on clinical risk and echocardiographic markers of stage B HF (SBHF) (abnormal global longitudinal strain [GLS], diastolic dysfunction, or left ventricular hypertrophy) was developed using a classification and regression tree analysis and was validated. RESULTS: HF developed in 12% of the training group, including 9%, 18%, and 73% of low-, intermediate-, and high-risk patients. HF occurred in 8.6% of stage A HF and 19.4% of SBHF (P < 0.001), but stage A HF with clinical risk of ≥9% had similar outcome to SBHF. Abnormal GLS (HR: 2.92 [95% CI: 1.95-4.37]; P < 0.001) was the strongest independent predictor of HF. Normal GLS and diastolic function reclassified 61% of the intermediate-risk group into the low-risk group (HF incidence: 12%). In the validation group, 11% developed HF over 4.5 years; 4%, 17%, and 39% of low-, intermediate-, and high-risk groups. Similar results were obtained after exclusion of patients with known coronary artery disease. The echocardiographic parameters also provided significant incremental value to the ARIC score in predicting new HF admission (C-statistic: 0.78 [95% CI: 0.71-0.84] vs 0.83 [95% CI: 0.77-0.88]; P = 0.027). CONCLUSIONS: Clinical risk assessment is adequate to classify low and high HF risk. Echocardiographic evaluation reclassifies 61% of intermediate-risk patients.

Prognostication and Interventional Guidance Using Acceleration-Ejection Time Ratio in Undifferentiated Paradoxical Low-Flow Low-Gradient Aortic Stenosis.

BACKGROUND: Studies in paradoxical low-flow low-gradient aortic stenosis (PLFAS) have demonstrated conflicting outcomes with variable survival advantage from aortic valve replacement (AVR). PLFAS is a heterogeneous composition of patients with uncertainty regarding true stenosis severity that continues to confound decision-making for AVR. OBJECTIVES: The purpose of this study was to investigate the utility of the Doppler acceleration (AT) to ejection (ET) time ratio (AT:ET) for prediction of prognosis and benefit from AVR in undifferentiated PLFAS. METHODS: Patients with echocardiographic findings of PLFAS (aortic valve area <1.0 cm2 or indexed aortic valve area <0.6 cm2/m2, mean gradient <40 mm Hg, indexed stroke volume <35 mL/m2, and left ventricular ejection fraction ≥50%) were identified and grouped according to an AT:ET cutoff of 0.35. The primary outcome was a 5-year composite of cardiac mortality or AVR. Secondary outcomes included the individual components of the primary endpoint and all-cause mortality at 5 years. Effect of AVR was analyzed in the AT:ET <0.35 and ≥0.35 groups. RESULTS: A total of 171 PLFAS patients (median age 77.0 years, 57% women) were followed for a median of 8.9 years. AT:ET ≥0.35 was an independent predictor of the primary outcome (HR: 4.77 [95% CI: 2.94-7.75]; P < 0.001) with incremental value over standard indices of stenosis severity (net reclassification improvement: 0.57 [95% CI: 0.14-0.84]). AT:ET ≥0.35 also remained predictive of increased cardiac death (HR: 2.91 [95% CI: 1.47-5.76]; P = 0.002) and AVR (HR: 8.45 [95% CI: 4.16-17.1]; P < 0.001), respectively, following competing risk analysis. No difference in all-cause mortality was observed. AVR in the AT:ET ≥0.35 group was associated with significant reductions in 5-year cardiac (HR: 0.09 [95% CI: 0.02-0.36]; P < 0.001) and all-cause mortality (HR: 0.16 [95% CI: 0.07-0.38]; P < 0.001). No improvement in survival from AVR was demonstrated in AT:ET <0.35 patients. CONCLUSIONS: AT:ET ≥0.35 in PLFAS predicts poorer outcomes and/or need for AVR. In undifferentiated PLFAS patients, AT:ET may have a potential role in improving patient selection for prognostic AVR.

Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis.

BACKGROUND: Adverse outcomes from moderate aortic stenosis (AS) may be caused by progression to severe AS or by the effects of comorbidities. In the absence of randomized trial evidence favoring aortic valve replacement (AVR) in patients with moderate AS, phenotyping patients according to risk may assist decision making. OBJECTIVES: This study sought to identify and validate clusters of moderate AS that may be used to guide patient management. METHODS: Unsupervised clustering algorithms were applied to demographics, comorbidities, and echocardiographic parameters in a training data set in patients with moderate AS (n = 2,469). External validation was obtained by assigning the defined clusters to an independent group with moderate AS (n = 1,358). The primary outcome, a composite of cardiac death, heart failure hospitalization, or aortic valve (AV) intervention after 5 years, was assessed between clusters in both data sets. RESULTS: Four distinct clusters-cardiovascular (CV)-comorbid, low-flow, calcified AV, and low-risk-with significant outcomes (log-rank P < 0.0001 in both data sets) were identified and replicated. The highest risk was in the CV-comorbid cluster (validation HR: 2.00 [95% CI: 1.54-2.59]; P < 0.001). The effect of AVR on cardiac death differed among the clusters. There was a significantly lower rate of outcomes after AVR in the calcified AV cluster (validation HR: 0.21 [95% CI: 0.08-0.57]; P = 0.002), but no significant effect on outcomes in the other 3 clusters. These analyses were limited by the low rate of AVR. CONCLUSIONS: Moderate AS has several phenotypes, and multiple comorbidities are the key drivers of adverse outcomes in patients with moderate AS. Outcomes of patients with noncalcified moderate AS were not altered by AVR in these groups. Careful attention to subgroups of moderate AS may be important to define treatable risk.

Prognostic Signals From Moderate Valve Disease in Big Data: An Artefact of Digital Imaging and Communications in Medicine Structured Reporting?

BACKGROUND: Recent studies have identified an association between moderate aortic stenosis (AS) and outcome. We assessed whether Digital Imaging and Communications in Medicine (DICOM) structured reporting (SR), which captures and inserts echocardiographic measurements and text data directly into radiological reports, may lead to misclassifying patients with severe AS as moderate. METHODS: Moderate or severe AS cases were filtered from an echocardiography data set based on aortic valve area (AVA) < 1.5 cm2, indexed AVA (AVAi) ≤ 0.85 cm2/m2, mean pressure gradient ≥ 25 mm Hg, dimensionless severity index (DSI) ≤ 0.5, or peak velocity > 3 m/sec. Data validation was conducted by verification of each parameter. All echocardiographic parameters and definitions of AS were compared pre- and postvalidation by taking differences in measurements. Misclassification rates were assessed by determining the percentage of cases that changed AS severity classification and impact on outcomes. Patients were followed over 4.3 ± 1.5 years. RESULTS: Of 2,595 validated echocardiograms with AS, up to 36% of the echocardiographic parameters for AS criteria had a >10% difference between DICOM-SR and manual validation, the highest with mean pressure gradient (36%) and the lowest with DSI (6.5%). The validation process changed the reported degree of AS in up to 20.6% of echocardiograms with resultant changes in AS severity and its association with mortality or heart failure-related hospitalizations. In contrast to multiple quantitative metrics in DICOM-SR after manual validation, clinicians' evaluation of AS severity was unable to distinguish composite outcomes over 3 years between moderate and severe AS. The risk of composite outcomes was significantly increased when severe AS was evidenced by at least 1 echocardiographic parameter of severe AS (hazard ratio = 1.24; 95% CI, 1.12-1.37; P < .001). The greatest hazard was based on DSI only (hazard ratio = 1.26; 95% CI, 1.10-1.44; P < .001), which was higher after manual validation compared to DICOM-SR. Averaging of repeated echo measures including invalid values contributed the most to erroneous data. CONCLUSIONS: Nonpeak data in DICOM-SR led to incorrect categorization of a high proportion of patients based on AS severity definitions. Standardization of data fields and curation to ensure that only peak values are imported from DICOM-SR data are essential.