Development and Validation of a Risk Prediction Model for 1-Year Readmission Among Young Adults Hospitalized for Acute Myocardial Infarction.
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SUBMITTER: Dreyer RP
PROVIDER: S-EPMC8649501 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Sex differences are known to exist in the management of older patients presenting with acute myocardial infarction (AMI). Few studies have examined the incidence and risk factors of AMI among young patients, or whether clinical management differs by sex. METHODS:The Atherosclerosis Risk in Communities (ARIC) Surveillance study conducts hospital surveillance of AMI in 4 US communities (MD, MN, MS, and NC). AMI was classified by physician review, using a validated algorithm. Medications and procedures were abstracted from the medical record. Our study population was limited to young patients aged 35 to 54 years. RESULTS:From 1995 to 2014, 28?732 weighted hospitalizations for AMI were sampled among patients aged 35 to 74 years. Of these, 8737 (30%) were young. The annual incidence of AMI hospitalizations increased for young women but decreased for young men. The overall proportion of AMI admissions attributable to young patients steadily increased, from 27% in 1995 to 1999 to 32% in 2010 to 2014 ( P for trend=0.002), with the largest increase observed in young women. History of hypertension (59% to 73%, P for trend<0.0001) and diabetes mellitus (25% to 35%, P for trend<0.0001) also increased among young AMI patients. Compared to young men, young women presenting with AMI were more often black and had a greater comorbidity burden. In adjusted analyses, young women had a lower probability of receiving lipid-lowering therapies (relative risk [RR]=0.87; 95% confidence interval [CI], 0.80-0.94), nonaspirin antiplatelets (RR=0.83; 95% CI, 0.75-0.91), beta blockers (RR=0.96; 95% CI, 0.91-0.99), coronary angiography (RR=0.93; 95% CI, 0.86-0.99) and coronary revascularization (RR = 0.79; 95% CI, 0.71-0.87). However, 1-year all-cause mortality was comparable for women versus men (HR=1.10; 95% CI, 0.83-1.45). CONCLUSIONS:The proportion of AMI hospitalizations attributable to young patients increased from 1995 to 2014 and was especially pronounced among women. History of hypertension and diabetes among young patients admitted with AMI increased over time as well. Compared with young men, young women presenting with AMI had a lower likelihood of receiving guideline-based AMI therapies. A better understanding of factors underlying these changes is needed to improve care of young patients with AMI.
| S-EPMC6380926 | biostudies-literature
Project description:BackgroundEarly readmissions among older adults hospitalized for acute myocardial infarction (AMI) are costly and difficult to predict. Aging-related functional impairments may inform risk prediction but are unavailable in most studies. Our objective was to, therefore, develop and validate an AMI readmission risk model for older patients who considered functional impairments and was suitable for use before hospital discharge.Methods and resultsSILVER-AMI (Comprehensive Evaluation of Risk in Older Adults with AMI) is a prospective cohort study of 3006 patients of age ≥75 years hospitalized with AMI at 94 US hospitals. Participants underwent in-hospital assessment of functional impairments including cognition, vision, hearing, and mobility. Other variables plausibly associated with readmissions were also collected. The outcome was all-cause readmission at 30 days. We used backward selection and Bayesian model averaging to derive (N=2004) a risk model that was subsequently validated (N=1002). Mean age was 81.5 years, 44.4% were women, and 10.5% were nonwhite. Within 30 days, 547 participants (18.2%) were readmitted. Readmitted participants were older, had more comorbidities, and had a higher prevalence of functional impairments, including activities of daily living disability (17.0% versus 13.0%; P=0.013) and impaired functional mobility (72.5% versus 53.6%; P<0.001). The final risk model included 8 variables: functional mobility, ejection fraction, chronic obstructive pulmonary disease, arrhythmia, acute kidney injury, first diastolic blood pressure, P2Y12 inhibitor use, and general health status. Functional mobility was the only functional impairment variable retained but was the strongest predictor. The model was well calibrated (Hosmer-Lemeshow P value >0.05) with moderate discrimination (C statistics: 0.65 derivation cohort and 0.63 validation cohort). Functional mobility significantly improved performance of the risk model (net reclassification improvement index =20%; P<0.001).ConclusionsIn our final risk model, functional mobility, previously not included in readmission risk models, was the strongest predictor of 30-day readmission among older adults after AMI. The modest discrimination indicates that much of the variability in readmission risk among this population remains unexplained by patient-level factors.Clinical trial registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT01755052.
| S-EPMC6481309 | biostudies-literature
Project description:ImportanceIn the US, more than 600 000 adults will experience an acute myocardial infarction (AMI) each year, and up to 20% of the patients will be rehospitalized within 30 days. This study highlights the need for consideration of calibration in these risk models.ObjectiveTo compare multiple machine learning risk prediction models using an electronic health record (EHR)-derived data set standardized to a common data model.Design, setting, and participantsThis was a retrospective cohort study that developed risk prediction models for 30-day readmission among all inpatients discharged from Vanderbilt University Medical Center between January 1, 2007, and December 31, 2016, with a primary diagnosis of AMI who were not transferred from another facility. The model was externally validated at Dartmouth-Hitchcock Medical Center from April 2, 2011, to December 31, 2016. Data analysis occurred between January 4, 2019, and November 15, 2020.ExposuresAcute myocardial infarction that required hospital admission.Main outcomes and measuresThe main outcome was thirty-day hospital readmission. A total of 141 candidate variables were considered from administrative codes, medication orders, and laboratory tests. Multiple risk prediction models were developed using parametric models (elastic net, least absolute shrinkage and selection operator, and ridge regression) and nonparametric models (random forest and gradient boosting). The models were assessed using holdout data with area under the receiver operating characteristic curve (AUROC), percentage of calibration, and calibration curve belts.ResultsThe final Vanderbilt University Medical Center cohort included 6163 unique patients, among whom the mean (SD) age was 67 (13) years, 4137 were male (67.1%), 1019 (16.5%) were Black or other race, and 933 (15.1%) were rehospitalized within 30 days. The final Dartmouth-Hitchcock Medical Center cohort included 4024 unique patients, with mean (SD) age of 68 (12) years; 2584 (64.2%) were male, 412 (10.2%) were rehospitalized within 30 days, and most of the cohort were non-Hispanic and White. The final test set AUROC performance was between 0.686 to 0.695 for the parametric models and 0.686 to 0.704 for the nonparametric models. In the validation cohort, AUROC performance was between 0.558 to 0.655 for parametric models and 0.606 to 0.608 for nonparametric models.Conclusions and relevanceIn this study, 5 machine learning models were developed and externally validated to predict 30-day readmission AMI hospitalization. These models can be deployed within an EHR using routinely collected data.
| S-EPMC7846941 | biostudies-literature
Project description:BackgroundHospitals are subject to federal financial penalties for excessive 30-day hospital readmissions for acute myocardial infarction (AMI). Prospectively identifying patients hospitalized with AMI at high risk for readmission could help prevent 30-day readmissions by enabling targeted interventions. However, the performance of AMI-specific readmission risk prediction models is unknown.Methods and resultsWe systematically searched the published literature through March 2017 for studies of risk prediction models for 30-day hospital readmission among adults with AMI. We identified 11 studies of 18 unique risk prediction models across diverse settings primarily in the United States, of which 16 models were specific to AMI. The median overall observed all-cause 30-day readmission rate across studies was 16.3% (range, 10.6%-21.0%). Six models were based on administrative data; 4 on electronic health record data; 3 on clinical hospital data; and 5 on cardiac registry data. Models included 7 to 37 predictors, of which demographics, comorbidities, and utilization metrics were the most frequently included domains. Most models, including the Centers for Medicare and Medicaid Services AMI administrative model, had modest discrimination (median C statistic, 0.65; range, 0.53-0.79). Of the 16 reported AMI-specific models, only 8 models were assessed in a validation cohort, limiting generalizability. Observed risk-stratified readmission rates ranged from 3.0% among the lowest-risk individuals to 43.0% among the highest-risk individuals, suggesting good risk stratification across all models.ConclusionsCurrent AMI-specific readmission risk prediction models have modest predictive ability and uncertain generalizability given methodological limitations. No existing models provide actionable information in real time to enable early identification and risk-stratification of patients with AMI before hospital discharge, a functionality needed to optimize the potential effectiveness of readmission reduction interventions.
| S-EPMC5858710 | biostudies-literature
Project description:To examine overall and decade-long trends (1999-2009), characteristics, treatment practices, and hospital outcomes in individuals aged 65 and older hospitalized for acute myocardial infarction (AMI) and to describe how these factors varied in the youngest, middle, and oldest-old individuals.Retrospective cohort study.Population-based Worcester Heart Attack Study.Analyses were conducted to examine the sociodemographic and clinical characteristics, cardiac treatments, and hospital outcomes of older adults in three age strata (65-74, 75-84, ?85).The study sample consisted of 3,851 individuals aged 65 and older hospitalized with AMI every other year between 1999 and 2009; 32% were aged 65 to 74, 43% aged 75 to 84, and 25% aged 85 and older.Advancing age was inversely associated with receipt of evidence-based cardiac therapies. After multivariable adjustment, the odds of dying during hospitalization was 1.46 times as high in participants aged 75 to 84 and 1.78 times as high in those aged 85 and older as in those aged 65 to 74. The oldest-old participants had approximately 25% lower odds of a prolonged hospital stay (>3 days) than those aged 65 to 74. Decade-long trends in the principal study outcomes were also examined. Although the oldest-old participants hospitalized for AMI were at the greatest risk of dying, persistent age-related differences were observed in hospital treatment practices. Similar results were observed after excluding participants with a do-not-resuscitate order in their medical records.Although there are persistent disparities in the care and outcomes of older adults hospitalized with AMI, additional studies are needed to delineate the extent to which less-aggressive care reflects individual preferences and appropriate implementation of palliative care approaches.
| S-EPMC4135447 | biostudies-other
Project description:BackgroundReducing hospital readmission after acute myocardial infarction (AMI) has the potential to both improve quality and reduce costs. As such, readmission after AMI has been a target of financial penalties through Medicare. However, substantial concern exists about potential adverse effects and efficacious readmission-reduction strategies are not well validated.Methods and resultsWe started an AMI readmissions reduction program in November 2017. Between July 2016 and February 2019, hospital billing data were queried to detect all inpatient hospitalizations at the Massachusetts General Hospital for AMI. Thirty-day readmission was identified through hospital billing data, and mortality was extracted from our electronic health record. The data set was merged with claims data for patients in accountable care organizations to detect readmission at other hospitals. We performed segmented linear regression, adjusting for secular trend and case mix, to assess the independent association of our program on both outcome variables. After inclusion and exclusion criteria were applied, the study population included 2020 patients. The overall 30-day readmission rate was higher before the intervention than after the intervention (15.5% versus 10.7%, P=0.002). The overall 30-day mortality rate was similar in both time periods (1.8% versus 1.4%, P=0.457). The program was associated with initial reduction in 30-day readmission (-9.8%, P=0.0002) and 30-day mortality (-2.6%, P=0.041). The program did not change trend in 30-day readmission (+0.19% readmissions/mo, P=0.554) and trend in 30-day mortality (-0.21% deaths/mo, P=0.119).ConclusionsAn AMI readmissions reduction program that increases outpatient and emergency department (ED) access to cardiology care is associated with reduced 30-day readmission and 30-day mortality. Similar statistical techniques can be used to conduct a rigorous, mechanistic program evaluation of other quality improvement initiatives.
| S-EPMC7237309 | biostudies-literature
Project description:ObjectiveTo examine prevalence and characteristics of newly diagnosed diabetes (NDD) in younger adults hospitalised with acute myocardial infarction (AMI) and investigate whether NDD is associated with health status and clinical outcomes over 12-month post-AMI.MethodsIn individuals (18-55 years) admitted with AMI, without established diabetes, we defined NDD as (1) baseline or 1-month HbA1c≥6.5%; (2) discharge diabetes diagnosis or (3) diabetes medication initiation within 1 month. We compared baseline characteristics of NDD, established diabetes and no diabetes, and their associations with baseline, 1-month and 12-month health status (angina-specific and non-disease specific), mortality and in-hospital complications.ResultsAmong 3501 patients in Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients study, 14.5% met NDD criteria. Among 508 patients with NDD, 35 (6.9%) received discharge diagnosis, 91 (17.9%) received discharge diabetes education and 14 (2.8%) initiated pharmacological treatment within 1 month. NDD was more common in non-White (OR 1.58, 95% CI 1.23 to 2.03), obese (OR 1.72, 95% CI 1.39 to 2.12), financially stressed patients (OR 1.27, 95% CI 1.02 to 1.58). Compared with established diabetes, NDD was independently associated with better disease-specific health status and quality of life (p≤0.04). No significant differences were found in unadjusted in-hospital mortality and complications between NDD and established or no diabetes.ConclusionsNDD was common among adults≤55 years admitted with AMI and was more frequent in non-White, obese, financially stressed individuals. Under 20% of patients with NDD received discharge diagnosis or initiated discharge diabetes education or pharmacological treatment within 1 month post-AMI. NDD was not associated with increased risk of worse short-term health status compared with risk noted for established diabetes.Trial registration numberNCT00597922.
| S-EPMC8005796 | biostudies-literature
Project description:Background:Older adults with acute myocardial infarction (AMI) have higher prevalence of functional impairments, including deficits in cognition, strength, and sensory domains, than their younger counterparts. Objective:To develop and evaluate the prognostic utility of a risk model for 6-month post-AMI mortality in older adults that incorporates information about functional impairments. Design:Prospective cohort study. (ClinicalTrials.gov: NCT01755052). Setting:94 hospitals throughout the United States. Participants:3006 persons aged 75 years or older who were hospitalized with AMI and discharged alive. Measurements:Functional impairments were assessed during hospitalization via direct measurement (cognition, mobility, muscle strength) or self-report (vision, hearing). Clinical variables associated with mortality in prior risk models were ascertained by chart review. Seventy-two candidate variables were selected for inclusion, and backward selection and Bayesian model averaging were used to derive (n = 2004 participants) and validate (n = 1002 participants) a model for 6-month mortality. Results:Participants' mean age was 81.5 years, 44.4% were women, and 10.5% were nonwhite. There were 266 deaths (8.8%) within 6 months. The final risk model included 15 variables, 4 of which were not included in prior risk models: hearing impairment, mobility impairment, weight loss, and lower patient-reported health status. The model was well calibrated (Hosmer-Lemeshow P > 0.05) and showed good discrimination (area under the curve for the validation cohort = 0.84). Adding functional impairments significantly improved model performance, as evidenced by category-free net reclassification improvement indices of 0.21 (P = 0.008) for hearing impairment and 0.26 (P < 0.001) for mobility impairment. Limitation:The model was not externally validated. Conclusion:A newly developed model for 6-month post-AMI mortality in older adults was well calibrated and had good discriminatory ability. This model may be useful in decision making at hospital discharge. Primary Funding Source:National Heart, Lung, and Blood Institute of the National Institutes of Health.
| S-EPMC7695040 | biostudies-literature
Project description:BACKGROUND:Acute myocardial infarction (AMI) is a major cardiovascular complication of noncardiac surgery. We aimed to evaluate the frequency, causes, and outcomes of 30-day hospital readmission after perioperative AMI. METHODS:Patients who were diagnosed with AMI during hospitalization for major noncardiac surgery were identified using the 2014 US Nationwide Readmission Database. Rates, causes, and costs of 30-day readmissions after noncardiac surgery with and without perioperative AMI were identified. RESULTS:Among 3?807?357 hospitalizations for major noncardiac surgery, 8085 patients with perioperative AMI were identified. A total of 1135 patients (14.0%) with perioperative AMI died in-hospital during the index admission. Survivors of perioperative AMI were more likely to be readmitted within 30 days than surgical patients without perioperative AMI (19.1% versus 6.5%, P<0.001). The most common indications for 30-day rehospitalization were management of infectious complications (30.0%), cardiovascular complications (25.3%), and bleeding (10.4%). In-hospital mortality during hospital readmission in the first 30 days after perioperative AMI was 11.3%. At 6 months, the risk of death was 17.6% and ?1 hospital readmission was 36.2%. CONCLUSIONS:Among patients undergoing noncardiac surgery who develop a perioperative MI, ?1 in 3 suffer from in-hospital death or hospital readmission in the first 30 days after discharge. Strategies to improve outcomes of surgical patients early after perioperative AMI are warranted.
| S-EPMC5995321 | biostudies-literature
Project description:Background Readmission after myocardial infarction ( MI ) is a publicly reported quality metric with hospital reimbursement linked to readmission rates. We describe the timing and pattern of readmission by cause within the first year after MI in consecutive patients, regardless of revascularization strategy, payer status, or age. Methods and Results We identified patients discharged after an MI from April 2008 to June 2012. Readmission within 12 months was the primary end point. Readmissions were classified into 4 groups: MI related, other cardiovascular, noncardiovascular, and planned. A total of 3069 patients were discharged after an MI (average age, 65±13 years; and 1941 [63%] men). A total of 655 patients (21.3%) were readmitted at least once (897 total readmissions). A total of 147 patients (4.8%) were readmitted ≥2 times, accounting for 389 readmissions (43%). The instantaneous risk of all-cause readmission was highest (15 readmissions/100 patients per month; 95% confidence interval, 12-19 readmissions/100 patients per month) immediately after discharge, decreased by almost half (8.1 readmissions/100 patients per month; 95% confidence interval, 7.2-9.0 readmissions/100 patients per month) within 15 days, and was substantially lower and relatively constant (1.4 readmissions/100 patients per month; 95% confidence interval, 1.2-1.6 readmissions/100 patients per month) out to 1 year. Cardiovascular causes of readmission were more common early after discharge. Conclusions Most patients with MI are never readmitted, whereas a small minority (≈5%) account for nearly half of 1-year readmissions. The readmission pattern after MI is characterized by an early peak (first 15 days) of cardiovascular readmissions, followed by a middle period (months 1-4) of noncardiovascular readmissions, and ending with a low-risk period (>4 months) during which the risk appears independent of cause.
| S-EPMC6404216 | biostudies-literature