Young Women With Acute Myocardial Infarction: Risk Prediction Model for 1-Year Hospital Readmission.

Background: Although young women ( aged ≤ 55 years) are at higher risk than similarly aged men for hospital readmission within 1 year after an acute myocardial infarction (AMI), no risk prediction models have been developed for them. The present study developed and internally validated a risk prediction model of 1-year post-AMI hospital readmission among young women that considered demographic, clinical, and gender-related variables. Methods: We used data from the US Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients (VIRGO) study (n = 2007 women), a prospective observational study of young patients hospitalized with AMI. Bayesian model averaging was used for model selection and bootstrapping for internal validation. Model calibration and discrimination were respectively assessed with calibration plots and area under the curve. Results: Within 1-year post-AMI, 684 women (34.1%) were readmitted to the hospital at least once. The final model predictors included: any in-hospital complication, baseline perceived physical health, obstructive coronary artery disease, diabetes, history of congestive heart failure, low income ( < $30,000 US), depressive symptoms, length of hospital stay, and race (White vs Black). Of the 9 retained predictors, 3 were gender-related. The model was well calibrated and exhibited modest discrimination (area under the curve = 0.66). Conclusions: Our female-specific risk model was developed and internally validated in a cohort of young female patients hospitalized with AMI and can be used to predict risk of readmission. Whereas clinical factors were the strongest predictors, the model included several gender-related variables (ie, perceived physical health, depression, income level). However, discrimination was modest, indicating that other unmeasured factors contribute to variability in hospital readmission risk among younger women.

Contexte: Bien que les femmes jeunes (≤ 55 ans) présentent un risque plus élevé que les hommes du même âge de réadmission à l'hôpital dans l'année suivant un infarctus aigu du myocarde (IAM), il n'existe pas de modèle de prédiction des risques conçu spécialement pour elles. Dans le cadre de la présente étude, on a créé et validé à l'interne un modèle de prédiction des risques de réadmission à l'hôpital dans l'année suivant un IAM chez les femmes jeunes en tenant compte de variables démographiques, cliniques et associées au genre. Méthodologie: Nous avons utilisé les données de l'étude américaine VIRGO (variation du rétablissement : le rôle du genre dans les résultats des jeunes patientes ayant subi un IAM) (n = 2007 femmes), une étude observationnelle prospective menée auprès de jeunes patientes hospitalisées pour un IAM. Un modèle bayésien d'établissement de la moyenne a été utilisé pour la sélection du modèle et la méthode bootstrap a été utilisée pour la validation interne. L'étalonnage et la discrimination du modèle ont été évalués respectivement au moyen des courbes d'étalonnage et de la surface sous la courbe. Résultats: Dans l'année suivant l'IAM, 684 femmes (34,1 %) ont été réadmises à l'hôpital au moins une fois. Les facteurs prédictifs finaux du modèle sont notamment : toute complication survenue à l'hôpital, l'état de santé physique perçu au départ, la coronaropathie obstructive, le diabète, les antécédents d'insuffisance cardiaque congestive, le faible revenu (< 30 000 $ US), les symptômes dépressifs, la durée du séjour à l'hôpital et l'ethnie (blanc par rapport à noir). Parmi les neuf facteurs prédictifs retenus, trois sont associés au genre. Le modèle est bien étalonné et présente une discrimination modeste (surface sous la courbe = 0,66). Conclusions: Notre modèle de risque propre aux femmes a été conçu et validé à l'interne auprès d'une cohorte de femmes jeunes hospitalisées pour un IAM et peut être utilisé pour prédire le risque de réadmission. Bien que les facteurs cliniques soient les facteurs prédictifs les plus puissants, le modèle inclut plusieurs variables liées au genre (p. ex., état de santé physique perçu, dépression, revenu). Cependant, la discrimination étant modeste, d'autres facteurs non mesurés contribuent à la variabilité du risque de réadmission à l'hôpital chez les femmes plus jeunes.

Association of Sociodemographic Characteristics With 1-Year Hospital Readmission Among Adults Aged 18 to 55 Years With Acute Myocardial Infarction.

Importance: Among younger adults, the association between Black race and postdischarge readmission after hospitalization for acute myocardial infarction (AMI) is insufficiently described. Objectives: To examine whether racial differences exist in all-cause 1-year hospital readmission among younger adults hospitalized for AMI and whether that difference retains significance after adjustment for cardiac factors and social determinants of health (SDOHs). Design, Setting, and Participants: The VIRGO (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients) study was an observational cohort study of younger adults (aged 18-55 years) hospitalized for AMI with a 2:1 female-to-male ratio across 103 US hospitals from January 1, 2008, to December 31, 2012. Data analysis was performed from August 1 to December 31, 2021. Main Outcomes and Measures: The primary outcome was all-cause readmission, defined as any hospital or observation stay greater than 24 hours within 1 year of discharge, identified through medical record abstraction and clinician adjudication. Logistic regression with sequential adjustment evaluated racial differences and potential moderation by sex and SDOHs. The Blinder-Oaxaca decomposition quantified how much of any racial difference was explained and not explained by covariates. Results: This study included 2822 participants (median [IQR] age, 48 [44-52] years; 1910 [67.7%] female; 2289 [81.1%] White and 533 [18.9%] Black; 868 [30.8%] readmitted). Black individuals had a higher rate of readmission than White individuals (210 [39.4%] vs 658 [28.8%], P < .001), particularly Black women (179 of 425 [42.1%]). After adjustment for sociodemographic characteristics, cardiac factors, and SDOHs, the odds of readmission were 34% higher among Black individuals (odds ratio [OR], 1.34; 95% CI, 1.06-1.68). The association between Black race and 1-year readmission was positively moderated by unemployment (OR, 1.68; 95% CI, 1.09- 2.59; P for interaction = .02) and fewer number of working hours per week (OR, 1.01; 95% CI, 1.00-1.02; P for interaction = .01) but not by sex. Decomposition indicates that 79% of the racial difference in risk of readmission went unexplained by the included covariates. Conclusions and Relevance: In this multicenter study of younger adults hospitalized for AMI, Black individuals were more often readmitted in the year following discharge than White individuals. Although interventions to address SDOHs and employment may help decrease racial differences in 1-year readmission, more study is needed on the 79% of the racial difference not explained by the included covariates.

Development and Validation of a Risk Prediction Model for 1-Year Readmission Among Young Adults Hospitalized for Acute Myocardial Infarction.

Background Readmission over the first year following hospitalization for acute myocardial infarction (AMI) is common among younger adults (≤55 years). Our aim was to develop/validate a risk prediction model that considered a broad range of factors for readmission within 1 year. Methods and Results We used data from the VIRGO (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients) study, which enrolled young adults aged 18 to 55 years hospitalized with AMI across 103 US hospitals (N=2979). The primary outcome was ≥1 all-cause readmissions within 1 year of hospital discharge. Bayesian model averaging was used to select the risk model. The mean age of participants was 47.1 years, 67.4% were women, and 23.2% were Black. Within 1 year of discharge for AMI, 905 (30.4%) of participants were readmitted and were more likely to be female, Black, and nonmarried. The final risk model consisted of 10 predictors: depressive symptoms (odds ratio [OR], 1.03; 95% CI, 1.01-1.05), better physical health (OR, 0.98; 95% CI, 0.97-0.99), in-hospital complication of heart failure (OR, 1.44; 95% CI, 0.99-2.08), chronic obstructive pulmomary disease (OR, 1.29; 95% CI, 0.96-1.74), diabetes mellitus (OR, 1.23; 95% CI, 1.00-1.52), female sex (OR, 1.31; 95% CI, 1.05-1.65), low income (OR, 1.13; 95% CI, 0.89-1.42), prior AMI (OR, 1.47; 95% CI, 1.15-1.87), in-hospital length of stay (OR, 1.13; 95% CI, 1.04-1.23), and being employed (OR, 0.88; 95% CI, 0.69-1.12). The model had excellent calibration and modest discrimination (C statistic=0.67 in development/validation cohorts). Conclusions Women and those with a prior AMI, increased depressive symptoms, longer inpatient length of stay and diabetes may be more likely to be readmitted. Notably, several predictors of readmission were psychosocial characteristics rather than markers of AMI severity. This finding may inform the development of interventions to reduce readmissions in young patients with AMI.

Bayesian Model Averaging for Selection of a Risk Prediction Model for Death within Thirty Days of Discharge: The SILVER-AMI Study.

We describe a selection process for a multivariable risk prediction model of death within 30 days of hospital discharge in the SILVER-AMI study. This large, multi-site observational study included observational data from 2000 persons 75 years and older hospitalized for acute myocardial infarction (AMI) from 94 community and academic hospitals across the United States and featured a large number of candidate variables from demographic, cardiac, and geriatric domains, whose missing values were multiply imputed prior to model selection. Our objective was to demonstrate that Bayesian Model Averaging (BMA) represents a viable model selection approach in this context. BMA was compared to three other backward-selection approaches: Akaike information criterion, Bayesian information criterion, and traditional p-value. Traditional backward-selection was used to choose 20 candidate variables from the initial, larger pool of five imputations. Models were subsequently chosen from those candidates using the four approaches on each of 10 imputations. With average posterior effect probability ≥ 50% as the selection criterion, BMA chose the most parsimonious model with four variables, with average C statistic of 78%, good calibration, optimism of 1.3%, and heuristic shrinkage of 0.93. These findings illustrate the utility and flexibility of using BMA for selecting a multivariable risk prediction model from many candidates over multiply imputed datasets.

Design and rationale of the comprehensive evaluation of risk factors in older patients with AMI (SILVER-AMI) study.

BACKGROUND: While older adults (age 75 and over) represent a large and growing proportion of patients with acute myocardial infarction (AMI), they have traditionally been under-represented in cardiovascular studies. Although chronological age confers an increased risk for adverse outcomes, our current understanding of the heterogeneity of this risk is limited. The Comprehensive Evaluation of Risk Factors in Older Patients with AMI (SILVER-AMI) study was designed to address this gap in knowledge by evaluating risk factors (including geriatric impairments, such as muscle weakness and cognitive impairments) for hospital readmission, mortality, and health status decline among older adults hospitalized for AMI. METHODS/DESIGN: SILVER-AMI is a prospective cohort study that is enrolling 3000 older adults hospitalized for AMI from a recruitment network of approximately 70 community and academic hospitals across the United States. Participants undergo a comprehensive in-hospital assessment that includes clinical characteristics, geriatric impairments, and health status measures. Detailed medical record abstraction complements the assessment with diagnostic study results, in-hospital procedures, and medications. Participants are subsequently followed for six months to determine hospital readmission, mortality, and health status decline. Multivariable regression will be used to develop risk models for these three outcomes. DISCUSSION: SILVER-AMI will fill critical gaps in our understanding of AMI in older patients. By incorporating geriatric impairments into our understanding of post-AMI outcomes, we aim to create a more personalized assessment of risk and identify potential targets for interventions. TRIAL REGISTRATION NUMBER: NCT01755052 .

Patient expectations from implantable defibrillators to prevent death in heart failure.

BACKGROUND: Indications for implantable cardioverter-defibrillators (ICDs) in heart failure (HF) are expanding and may include more than 1 million patients. This study examined patient expectations from ICDs for primary prevention of sudden death in HF. METHODS AND RESULTS: Study participants (n = 105) had an EF <35% and symptomatic HF, without history of ventricular tachycardia/fibrillation or syncope. Subjects completed a written survey about perceived ICD benefits, survival expectations, and circumstances under which they might deactivate defibrillation. Mean age was 58, LVEF 21%, 40% were New York Heart Association Class III-IV, and 65% already had a primary prevention ICD. Most patients anticipated more than10 years survival despite symptomatic HF. Nearly 54% expected an ICD to save >or=50 lives per 100 during 5 years. ICD recipients expressed more confidence that the device would save their own lives compared with those without an ICD (P < .001). Despite understanding the ease of deactivation, 70% of ICD recipients indicated they would keep the ICD on even if dying of cancer, 55% even if having daily shocks, and none would inactivate defibrillation even if suffering constant dyspnea at rest. CONCLUSIONS: HF patients anticipate long survival, overestimate survival benefits conferred by ICDs, and express reluctance to deactivate their devices even for end-stage disease.

Thresholds of physical activity and life expectancy for patients considering destination ventricular assist devices.

BACKGROUND: Current implantable left ventricular assist devices (LVAD) improve survival and function for patients with very late stage heart failure (HF) but may also offer benefit before inotrope dependence. Debate continues about selection of HF patients for LVAD therapy. We sought to determine what level of personal risk and disability HF patients thought would warrant LVAD therapy. METHODS: The study included 105 patients with symptomatic HF and an LV ejection fraction (EF) < 35% who were given a written paragraph about LVADs and asked about circumstances under which they would consider such a device. New York Heart Association (NYHA) functional class, time trade-off utility, and patient-assessed functional score were determined. RESULTS: Participants (mean age, 58 years) had an LVEF of 21%. The median duration of HF was 5 years, and 65% had a primary prevention implantable cardioverter defibrillator. Presented with a scenario of bed-ridden HF, 81% stated they would definitely or probably want an LVAD; 50% would consider LVAD to prolong survival if HF survival were predicted to be < 1 year and 75% if < 6 months. Meanwhile, 44% would consider LVAD if they could only walk < 1 block and 64% if they could not dress without stopping. Anticipated thresholds did not differ by NYHA class, time trade-off, or functional score. CONCLUSIONS: Patient thresholds for LVAD insertion parallel objective survival and functional data. HF patients would be receptive to referral for discussion of LVAD by the time expected mortality is within 6 to 12 months and activity remains limited to less than 1 block.

The association between high-dose diuretics and clinical stability in ambulatory chronic heart failure patients.

OBJECTIVE: In chronic heart failure (HF), diuretic doses increase as the disease progresses, often after hospitalization for instability, and have been associated with worsening renal function and increased mortality. METHODS AND RESULTS: A prospective observational analysis of 183 patients in an advanced HF clinic stratified at baseline by diuretic dose (low dose < or = 80 mg, high dose > 80 mg furosemide equivalent) was performed. All patients were followed for 1 year, and the primary outcome was a combined HF event of admission for HF, cardiac transplant, mechanical cardiac support, or death. Compared with patients taking low-dose diuretics (n = 113), patients taking high-dose diuretics (n = 70) had more markers of increased cardiovascular risk and were more likely to have a history of recent instability (33% vs 4.4% in low dose, P < .001). High doses of diuretics were a strong univariate predictor of subsequent HF events (hazard ratio 3.83, 95% confidence interval 1.82-8.54); however, after adjustment for clinical stability, diuretic dose no longer remained significant (hazard ratio 1.53, 95% confidence interval 0.58-4.03). CONCLUSION: High-dose diuretics may be more of a marker than a cause of instability. A history of HF stability during the past 6 months is associated with an 80% lower risk of an HF event during the next year, independently of baseline diuretic dose.

Characteristics of patients who die with heart failure and a low ejection fraction in the new millennium.

BACKGROUND: Therapies for heart failure (HF) with a low ejection fraction (EF) have delayed disease progression and prolonged survival, but the implications of these therapies on the end stages of HF have not been examined. METHODS AND RESULTS: Patients seen by the Brigham and Women's cardiomyopathy service with an EF < or =35%, at least 1 outpatient visit or at least 30 days of follow-up who died between January 1, 2000, and October 20, 2003, were evaluated retrospectively. Of the 160 patients who died since 2000, 80 (50%) were outpatients. In the 6 months before death, 93% of patients had New York Heart Association (NYHA) class III or IV symptoms. The NYHA class, clinical characteristics, medications, and comorbidities differed little between inpatient and outpatient deaths. Renal insufficiency and hyponatremia were worse in the months preceding death than at the time of death (creatinine: 3.2 versus 2.3 mg/dL, P < .0001; sodium: 128 versus 135 mmol/L, P < .0001, respectively). Death was considered sudden in only 21% of patients. CONCLUSION: Deaths in the current era of HF management occur in patients with long-standing HF characterized by biventricular dysfunction and advanced symptoms. Most deaths are heralded by hyponatremia, acute on chronic renal insufficiency, and frequent hospitalizations.

Frequency and impact of delayed decisions regarding heart transplantation on long-term outcomes in patients with advanced heart failure.

OBJECTIVES: We sought to characterize decisions regarding listing of heart transplant candidates and to determine the impact of delayed listing for a transplant on survival. BACKGROUND: Evaluation and listing for heart transplantation have evolved over the past decade, with the complex decision process often extending beyond the time of initial review. Little is known about the current impact of decisions and timing of listing on outcomes. METHODS: Decisions were prospectively recorded during the initial committee discussions regarding patients referred for heart transplant evaluation. Survival and transplantation rates were assessed. RESULTS: A total of 214 patients were evaluated for heart transplantation (age 49 +/- 11 years, ejection fraction 21 +/- 9%, New York Heart Association class III +/- I, peak oxygen consumption 13 +/- 4 ml/kg/min). At the initial evaluation, 44% of patients were deemed eligible, 25% were potentially eligible, 19% were ineligible, and 12% were deferred. For eligible patients, 37% of patients were listed within 10 days of evaluation, and a total of 71% of patients were ever listed. Regardless of transplantation, the three-year survival rate in eligible patients not listed early was similar to that in patients listed immediately (85% vs. 77%, p = 0.34). Ineligible and potentially eligible patients had a higher three-year mortality rate than did eligible patients if transplantation occurred (51% vs. 17%, p < 0.001) or not (57% vs. 19%, p = 0.04). CONCLUSIONS: Using current accepted guidelines, many patients referred for transplant evaluation were not considered eligible for transplantation, and those who were eligible were not often listed immediately. Eligible patients not listed initially did well in the long term, and patients with relative contraindications had worse outcomes with or without a transplant.

Clinical assessment identifies hemodynamic profiles that predict outcomes in patients admitted with heart failure.

OBJECTIVES: This study was designed to determine the relevance of a proposed classification for advanced heart failure (HF). Profiles based on clinical assessment of congestion and perfusion at the time of hospitalization were compared with subsequent outcomes. BACKGROUND: Optimal design of therapy and trials for advanced HF remains limited by the lack of simple clinical profiles to characterize patients. METHODS: Prospective analysis was performed for 452 patients admitted to the cardiomyopathy service at the Brigham and Women's Hospital with a diagnosis of HF. Patients were classified by clinical assessment into four profiles: profile A, patients with no evidence of congestion or hypoperfusion (dry-warm, n = 123); profile B, congestion with adequate perfusion (wet-warm, n = 222); profile C, congestion and hypoperfusion (wet-cold, n = 91); and profile L, hypoperfusion without congestion (dry-cold, n = 16). Other standard predictors of outcome were included and patients were followed for the end points of death (n = 117) and death or urgent transplantation (n = 137) at one year. RESULTS: Survival analysis showed that clinical profiles predict outcomes in HF. Profiles B and C increase the risk of death plus urgent transplantation by univariate (hazard ratio [HR] 1.83, p = 0.02) and multivariate analyses (HR 2.48, p = 0.003). Moreover, clinical profiles add prognostic information even when limited to patients with New York Heart Association (NYHA) class III/IV symptoms (profile B: HR 2.23, p = 0.026; profile C: HR 2.73, p = 0.009). CONCLUSIONS: Simple clinical assessment can be used to define profiles in patients admitted with HF. These profiles predict outcomes and may be used to guide therapy and identify populations for future investigation.