Readmission For Myocardial Infarction Research Articles

One-year prognosis difference of MINOCA versus MI-CAD in developing countries: insights from the Moroccan experience

Abstract Introduction The debate remains open as to the difference in prevalence of mortality and occurrence of acute events in patients with Myocardial infarction with non-obstructive coronary arteries (MINOCA) and others with Myocardial infarction with coronary arteries disease (MI-CAD) (1). Purpose We carried out an analysis of the clinical characteristics and one-year prognosis of MINOCA versus MI-CAD. Methods We conducted a prospective study for patients admitted for Acute coronary syndrome (ACS) during 2-years, to analyze the clinical and prognostic characteristics of patients with MINOCA versus MI-CAD. We defined 1-year all-cause mortality as the primary outcome, and the secondary outcome as a composite of 1-year readmission for myocardial infarction or acute heart failure (AHF). The primary and secondary outcomes was studied using a Cox proportional hazards regression model to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for variables described in the literature. Results Our study included 1077 patients, 95.3% with MI-CAD and 4.7% with MINOCA. At admission, 71.1% patient were diagnosed STEMI and 28.9% with NSTEMI. The difference between the two groups was found on age (p<0.001), hypertension, diabetes with consecutive p-values of 0.007 and 0.001, as well as Ejection fraction (p<0.001). For the outcomes studied, we found, firstly before adjustment, that patients in the MINOCA group had a better prognosis than the MI-CAD group, for all-cause 1-year mortality (HR=0. 442; 95%CI 0.227-0.760; p=0.041) with a significant difference in the Kaplein Meier survival analysis with a log-rank test (p-value =0.02) (Figure 1), and a lower risk of readmission for ACS (HR=0.297; 95%CI 0.316-0.821; p=0.034), as well as for readmission for AHF (HR=0.555; 95%CI 0.329-0.836; p=0.045) also with a significant difference between the two groups in the Kaplein Meier analysis with consecutive log-rank test p-values of 0.033 and 0.035 (Figure 2). After adjustment for age, arterial hypertension, diabetes, active smoking, EF<40%, proximal LAD or LM as culprit artery, TIMI 0-I flow, CRP >300mg and cardiogenic shock during hospitalization, the results remained significantly in favor of a better prognosis for MINOCA: (HR=0. 672; 95%CI 0.376-0.872; p=0.003) for 1-year all-cause mortality, (HR=0.301; 95%CI 0.482-0.879; p=0.012) for readmission for ACS and finally (HR=0.604; 95%CI 0.309-0.812; p=0.039) for readmission for AHF. Conclusion Despite the ambiguity in the genesis of MINOCA, the short- and long-term prognosis of these patients remains generally favorable.Figure 1.Figure 2.

Safety and efficiency of implementation of high-sensitivity troponin T in the assessment of emergency department patients with cardiac chest pain.

For emergency department (ED) patients with cardiac chest pain, introduction of high-sensitivity troponin (hsTnT) pathways has been associated with reductions in length of stay of less than 1h. At two urban Canadian sites, we introduced hsTnT on January 26, 2016. While the prior diagnostic algorithm required troponin testing at 0 and 6h, serial hsTnT serial testing was conducted at 0 and 3h. We identified consecutive patients who presented with cardiac chest pain from January 1, 2015, to March 31, 2017, along with 30-day outcomes. The primary outcome was a missed 30-day major adverse cardiac event, (MACE) defined as death, revascularization, or readmission for myocardial infarction occurring in a patient-discharged home with a minimizing diagnosis and without cardiac-specific follow-up. Secondary outcomes included admission rate, ED length of stay, and MACE. We compared pre- and post- implementation periods using descriptive methods and repeated this analysis in patients with noncardiac chest pain. We collected 5585 patients with cardiac chest pain, (2678 pre- and 2907 post-introduction) and 434 had (7.8%, 95% CI 7.1 to 8.5%) MACE, with 1 missed MACE. (0.2%, 95% CI 0.04 to 1.3%). Admission rate was stable at 24.1% pre- and 23.7% while median length of stay decreased from 464 to 285 min, a difference of 179 min. (95% CI 61 to 228 min). For 11,611 patients with noncardiac chest pain, admission rate (9%) and length of stay (191 versus 193 min) remained constant. Implementation of hsTnT for evaluation of ED chest pain patients was safe and associated with a 3-h decrease in length of stay.

One-Year Prognosis Difference of Myocardial Infarction With or Without Coronary Obstruction in Developing Countries: Insights From the Moroccan Experience.

The debate remains open as to the difference in prevalence of mortality and occurrence of acute events in patients with Myocardial infarction with non-obstructive coronary arteries (MINOCA) and others with Myocardial infarction with coronary arteries disease (MI-CAD). We conducted a 2-year retrospective study for patients admitted for Acute coronary syndrome (ACS) to analyze the clinical and prognostic characteristics of patients with MINOCA versus MI-CAD. We defined 1-year all-cause mortality as the primary outcome, and the secondary outcome as a composite of 1-year readmission for myocardial infarction or acute heart failure (AHF). Our study included 1077 patients, 95.3% with MI-CAD and 4.7% with MINOCA. At admission, 71.1% patient were diagnosed STEMI and 28.9% with NSTEMI. The difference between the 2 groups was found on age (P < .001), hypertension, diabetes with consecutive P-values of .007 and .001, as well as Ejection fraction (P < .001). For the outcomes studied, the difference was significant between the 2 groups for all events, and MINOCA patients had a better prognosis than MI-CAD patients, with adjusted hazard ratios (HR) for 1-year mortality (HR = 0.601 P = .004), for readmission for ACS (HR = 0.662; P = .002) and for readmission for AHF (HR = 0.539; P = .019). Despite the ambiguity in the genesis of MINOCA, the short- and long-term prognosis of these patients remains generally favorable.

Outcomes With Intravascular Ultrasound and Optical Coherence Tomography Guidance in Percutaneous Coronary Intervention

Intracoronary imaging has become an important tool in the treatment of complex lesions with percutaneous coronary intervention (PCI). This retrospective cohort study identified 1,118,475 patients with PCI from the Nationwide Readmissions Database from 2017 to 2019. Intravascular ultrasound (IVUS) and optical coherence tomography (OCT) were identified with appropriate International Classification of Diseases, Tenth Revision codes. The primary outcome was major adverse cardiac events. The secondary outcomes include net adverse clinical events (NACEs), all-cause mortality, myocardial infarction (MI) readmission, admission for stroke, and emergency revascularization. The multivariate Cox proportional hazard regression was used to adjust for demographic and co-morbid confounders. Of 1,118,475 PCIs, 86,140 (7.7%) used IVUS guidance and 5,617 (0.5%) used OCT guidance. The median follow-up time was 184days. The primary outcome of major adverse cardiac events was significantly lower for the IVUS (6.5% vs 7.6%; hazard ratio [HR] 0.89, 95% confidence interval [CI] 0.86 to 0.91, p <0.001) and OCT (4.4% vs 7.6%; HR 0.69, 95% CI 0.61 to 0.79, p <0.001) groups. IVUS was associated with significantly lower rates of NACEs (8.4% vs 9.4%; HR 0.92, 95% CI 0.89 to 0.94, p <0.001), all-cause mortality (3.5% vs 4.3%; HR 0.85, 95% CI 0.82 to 0.88, p <0.001), readmission for MI (2.7% vs 3.0%; HR 0.95, 95% CI 0.91 to 0.99, p=0.012), and admission for stroke (0.5% vs 0.6%; HR 0.86, 95% CI 0.78 to 0.95, p=0.002). OCT was associated with significantly lower rates of NACEs (6.6% vs 9.4%; HR 0.81, 95% CI 0.73 to 0.89, p <0.001) and all-cause mortality (1.8% vs 4.3%; HR 0.51, 95% CI 0.42 to 0.63, p <0.001). Emergency revascularization was not significantly different with IVUS guidance. Readmission for MI, stroke, and emergency revascularization were not significantly different with OCT guidance. A subgroup analysis of patients with ST-elevation MI and non-ST-elevation MI showed similar results. In conclusion, the use of IVUS and OCT guidance with PCI were associated with significantly lower rates of morbidity and mortality in real-world practice.

Readmissions for Myocardial Infarction Among Survivors of COVID-19 Hospitalization: Nationwide Analysis From Pandemic Year 2020

BackgroundCOVID-19 is known to be associated with acute myocardial infarction (MI). ObjectivesThe purpose of this study was to evaluate the outcomes of 30-day readmissions for MI among survivors of COVID-19 hospitalization. Methods and ResultsWe used the U.S. Nationwide Readmission Database to identify COVID-19 admissions from April 1, 2020, to November 30, 2020, using International Classification of Diseases-10th Revision-Clinical Modification (ICD-10-CM) claims. The primary outcome was 30-day readmission incidence for MI. A total of 521,251 cases of COVID-19 were included, of which 11.6% were readmitted within 30 days of discharge. The 30-day readmission incidence for MI was 0.6%. The 30-day all-cause readmission mortality incidence was 1.3%. Patients readmitted for MI were more frequently males (61.6% vs 38.4%) and had a higher Charlson comorbidity burden score (7 vs 4). The most common diagnosis among 30-day MI readmission was type 2 MI (51.1%), followed by a diagnosis of a type 1 non-ST-segment elevation MI (41.7%). ST-segment elevation MI cases constituted 7.6% of all MI-readmission whereas 0.6% of patients had unstable angina. 30-day MI readmissions with a recurrent diagnosis of COVID-19 had higher readmission mortality and incidence of complications. Conversely, the odds of performing revascularization procedures were lower for MI with recurrent COVID-19. Furthermore, MI readmissions with recurrent COVID-19 had a higher length of stay (7 vs 5 days) and cost of hospitalization ($18,398 vs $16,191) when compared with non-COVID-19 MI readmissions. ConclusionsAmong survivors of COVID-19 hospitalization, 5.2% of all-cause 30-day readmissions and 12% of all-cause readmission mortality were attributed to MI. MI-related readmissions were a significant source of mortality, morbidity, and resource utilization.

Abstract 417: Effect Of Antiplatelets, Ace-i, And Statins On Post-covid-19 Cardiovascular Complications

Post-COVID-19 patients are at increased risk of cardiovascular and stroke complications, especially the immediate period following infection. Beta-blockers, ACE-inhibitors, anticoagulants and antiplatelet agents are mainstay therapies for stroke patients and those with cardiovascular disease. This study aims to explore the potential benefit of these therapies in post-COVID-19 patients in prevention of cardiovascular and stroke complications. About 5134 cases were analyzed in this study. This study includes patients that were admitted for stroke of myocardial infarction who had history of COVID-19 infection within 4 weeks prior. These patients were then stratified based on their home medications including ACE-I, beta-blockers, antiplatelet and anticoagulant agents. Logistic regression and chi-square were used for analysis of data. There was no significant relationship between statin use and incident of readmission for myocardial infarction. Patients who were on antiplatelet agents were more likely to be readmitted for stroke at 1 and 4 weeks (odds ratio: 2.109 and 2.335, p value: 0.0204 and 0.0036). Patients who were on ACE-I were more likely to be readmitted for stroke at 1 and 4 weeks (odds ratio: 2.0331 and 1.945; p value: 0.0062 and 0.0055). The benefit of statin therapy in COVID-19 patients has been established previously. This is potentially due to two mechanisms: anti-inflammatory properties and lipid lowering. Our studies did not find significant relationship between statin use and incidence of re-admission for myocardial infarction. We deduce that this is due to the anti-inflammatory effect of statins in acute COVID-19, and not the lipid lowering effect. Patients who are on anti-platelet therapy are more likely to be readmitted for stroke. This is likely because they are at high risk for stroke, and COVID-19 increases their systemic inflammatory response and therefore increase stroke risk. Lastly, our study suggests there may be some relationship between ACE-I use and stroke post-COVID-19 infection.

Abstract 10757: Machine-Learning Models Based on Real-World Data to Predict Rehospitalization or Death After Acute Myocardial Infarction

Introduction: Prospectively identifying patient characteristics associated with myocardial infarction (MI) readmission would help target patients at high risk of recurrent events for improved clinical management. This study aimed to build and evaluate machine learning models based solely on real world data to identify predictors of rehospitalization or death within one year following acute MI. Methods: The study population consisted of adult patients who experienced a first hospitalization for MI between January 1, 2013 and December 31, 2017 in the Optum® Clinformatics® Data Mart, an administrative health claims database from a large US national managed care company. Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), and Deep Neural Network (DNN) models were developed and tested. Model variables included patient demographics, clinical characteristics, and specific treatments. Variable importance for model prediction was ranked. Results: Among 96,244 patients who had an initial MI, 15,925 (16.5%) had rehospitalization/death within a year. The LR, XGBoost, and DNN models performed similarly (area under the curve 0.762, 0.774, and 0.785 respectively). The XGBoost was selected as the primary model to assess the relative importance of the variables in predicting MI rehospitalization/death. Of the most impactful variables, older age, higher Charlson Comorbidity Index, presence of chronic kidney disease (all stages), previous heart failure, and no previous coronary arterial bypass graft were highly predictive of MI rehospitalization/death (Figure). Conclusions: The machine learning models developed in this study can be implemented within clinical systems to identify patients at high risk for MI readmission to improve care and decision-making. However, these models require external validation in other datasets. Furthermore, performance of the models might be improved by including information such as LDL-C levels and PCSK9 inhibitor use.

Utilization Rate and Outcomes of Intravascular Imaging in Elderly Patients Presenting With ST-Elevation Myocardial Infarction

BackgroundElderly patients presenting with ST-elevation myocardial infarction (STEMI) represent a vulnerable population with comorbid conditions and complex coronary anatomy. We aimed to describe the utilization rate and outcomes of intravascular imaging to guide percutaneous coronary intervention (PCI) in this population. MethodsThe Nationwide Readmissions Database was queried for all hospitalizations for STEMI involving PCI from 2018 to 2019. Hospitalizations were stratified by patient age into a younger cohort <75 years (mean age 58.7 ± 9.5 years) and an older cohort ≥75 years. Propensity score-weighed regression analysis was used to identify the association of intravascular imaging with in-hospital mortality, 90-day all-cause readmission, and readmission for myocardial infarction (MI). ResultsA total of 299,619 STEMI PCI hospitalizations were included. Intravascular imaging was utilized less frequently in the older cohort (6.8 % vs 7.8 %, odds ratio [OR] 0.87, 95 % CI 0.82–0.92, p < 0.001). In both cohorts, intravascular imaging was more likely to be used with anterior STEMI, complex PCI, mechanical support, and thrombectomy. Propensity score analysis showed the use of intravascular imaging was associated with lower in-hospital mortality in both cohorts (OR 0.60, 95 % CI 0.52–0.68, p < 0.001 in the younger cohort and OR 0.61, 95 % CI 0.51–0.72, p < 0.001 in the older cohort). There was no difference in 90-day all-cause readmission or readmission for MI with intravascular imaging. ConclusionsIntravascular imaging during STEMI PCI is associated with lower in-hospital mortality regardless of age. Further studies are needed to understand the low utilization rates especially among elderly patients.

Treatment gaps, 1-year readmission and mortality following myocardial infarction by diabetes status, sex and socioeconomic disadvantage

AimsWe evaluated variation in treatment for, and outcomes following, myocardial infarction (MI) by diabetes status, sex and socioeconomic disadvantage.MethodsWe included all people aged ≥30 years who were discharged alive from...

Abstract 10400: The Role of Patient, Community, and Healthcare System Factors in Variability of Hospital Readmissions After Myocardial Infarction

Introduction: The Hospital Readmissions Reduction Program (HRRP) penalizes hospitals by reducing Medicare (CMS) reimbursement for those institutions with higher rates of readmissions following hospitalizations for myocardial infarction (MI). Understanding the contributors to readmission following MI hospitalization can identify meaningful areas for intervention. We examine whether community and patient or healthcare system factors contribute more to variability in MI readmissions. Methods: We compiled CMS hospital data on MI readmissions, CMS physician reimbursement data, and 2020-21 County Health Rankings (Credit: University of Wisconsin). The outcome was the ratio of a hospital’s MI readmissions to MI discharges. Physician/healthcare system factors included total number of cardiac subspecialists, presence of all subspecialties, and the mean proportion of reimbursed charges. Patient and community factors included mean Hierarchical Condition Category (HCC) risk score (quantifies expected healthcare costs for CMS beneficiaries based on ICD-10 coding), median household income, the proportion of residents reporting no physical activity, and access to food stores. Models were created using linear regression. Model of best fit was determined using R 2 , AIC, BIC in model training data and mean absolute prediction error (MAPE) and root mean square prediction error (RMSE) in test data. Results: The linear regression model incorporating community and patient factors explained greater variability in MI readmission rates and performed with greater accuracy in the test data (R 2 0.21; AIC -40.2; BIC -5.1; MAPE 0.030; RMSE 0.042) than the model incorporating physician/healthcare system factors (R 2 0.04; AIC 170.0; BIC 195.0; MAPE 0.033; RMSE 0.045). HCC score, level of physical activity, median household income, and number of cardiac specialists were associated with significant effect sizes on the outcome. Conclusions: At a county level, community and patient factors appear to contribute more to variability in hospitals’ MI readmission rates. Further analyses should explore other community, patient, and provider factors that contribute. The HRRP does not account for community or patient factors, indicating its limitations.

Abstract 10388: The Role of Patient, Community and Healthcare System Factors in the Variability of Cardiovascular Hospital Readmissions

Introduction: The Hospital Readmissions Reduction Program (HRRP) penalizes hospitals by reducing Medicare (CMS) reimbursement for institutions with higher rates of readmissions following hospitalizations for myocardial infarction (MI), coronary artery bypass grafting (CABG) and heart failure (HF). Understanding the contributors to these readmissions can identify meaningful areas for intervention. We examine whether community and patient or healthcare system factors contribute more to variability in cardiac readmissions. Methods: We compiled CMS hospital data on MI, CABG and HF readmissions, CMS physician reimbursement data, and 2020-21 County Health Rankings (Credit: University of Wisconsin). The outcome was the ratio of a hospital’s composite readmissions for MI, CABG and HF to discharges for the same conditions. Physician/healthcare system factors included total cardiac subspecialists, presence of all subspecialties, and the mean proportion of reimbursed charges. Patient and community factors included mean Hierarchical Condition Category (HCC) risk score, median household income, proportion of residents reporting no physical activity, and access to food stores. Linear regression models were compared using R 2 , AIC, BIC in model training data and mean absolute prediction error (MAPE) and root mean square prediction error (RMSE) in test data. Results: The linear regression model incorporating community and patient factors explained greater variability in readmission rates in training data and performed with greater accuracy in the test data (R 2 0.35; AIC -1839; BIC -1811; MAPE 0.017; RMSE 0.022) than the model incorporating physician/healthcare system factors (R 2 0.04; AIC - 1685; BIC - 1664; MAPE 0.022; RMSE 0.027). HCC score, level of physical activity, and number of cardiac specialists were associated with the largest effect sizes on the outcome. Conclusions: At a county level, community and patient factors appear to contribute more to variability in hospitals’ MI, CABG and and HF readmission rates. Further analyses should explore other community, patient, and provider factors that may contribute. The HRRP does not account for community/patient factors, indicating its limitations.

Cumulative prognostic effect of diabetes and myocardial injury in patients attended in the emergency room

Abstract Background Diabetes and myocardial injury are clinical conditions associated with cardiovascular events and increased mortality during follow-up. It is not known to what extent both conditions enhance their prognostic effect in patients seen in the emergency room with cardiac troponin determination. Purpose This study aims to evaluate the prognostic implication of diabetes and myocardial injury in patients attended in the emergency room with cardiac troponin determination. Methods Retrospective observational cohorts study, in which all the patients attended the emergency room from January 2012 and December 2013 with a troponin determination. The sample was categorized according to the diabetes mellitus condition and myocardial injury (troponin below 99 th), studying four groups: non-diabetic without myocardial injury (G1), diabetic without myocardial injury (G2), non-diabetic with myocardial injury (G3), and diabetic with myocardial injury (G4). Baseline clinic characteristics and prognostic data were studied with a four years follow-up. Results A total of 3622 patients were studied; 924 (25'55%) diabetics. Three hundred seventy-one diabetic patients (40% of all diabetic patients) had an elevated troponin determination, while six hundred seventy-eights non-diabetic patients had elevated troponin (25'13% from all non-diabetics). Diabetic patients were significantly older (mean age 74 vs. 67 years). They had more frequently history of hypertension (81'9% vs 53'2%), acute myocardial infarction (31'6% vs 15'8%), heart failure (11'1% vs 5'7%), peripheral vascular disease (11'1% vs 5'2%), cerebrovascular disease (11'4% vs 6'6%), chronic pulmonary disease (23'3% vs 16'2%) and renal impairment (16'8% vs 5'2%). At four years of follow-up, G2, G3 and G4 had higher mortality than G1 (HR (95IC): 1,352 (1,080–1,693), 2,896 (2,896–3,477), and 3,441 (2,809–4,216), respectively). A multivariate competing risk model was used to obtain the HRs for readmission for myocardial infarction and heart failure between G2, G3 and G4 in relation to G1 (HR (IC 95%) 2,511 (1,592–3,96), 2,682 (1,739–4,138) and 5,036 (3,221–7,876), respectively for myocardial infarction, and 2,663 (1,825–3,886), 2,562 (1,753–3,744) and 4,292 (2,936–6,274) respectively for heart failure). Conclusions Both conditions, myocardial injury, and diabetes have a prognostic impact at a long-term follow-up with a cumulative effect, being the troponin elevation, a better prognostic marker of death risk, and similar to diabetes history for the risk of myocardial infarction and heart failure. Funding Acknowledgement Type of funding sources: None. ICC hospitalization cumulativeincidenceIAM cumulative incidence

Clinical characteristics and prognostic implications of diabetes and myocardial injury in patients admitted to the emergency room

BackgroundThis study aimed to investigate the clinical features and prognosis of diabetes and myocardial injury in patients admitted to the emergency department.MethodsWe analyzed the clinical data of all consecutive patients admitted to the emergency department during the years 2012 and 2013 with at least 1 cardiac Troponin I (cTnI Ultra Siemens, Advia Centaur) determination, and were classified according to the status of diabetes mellitus (DM) and myocardial injury (MI). Clinical events were evaluated in a 4-year follow-up.ResultsA total of 3622 patients were classified according to the presence of DM (n = 924 (25.55%)) and MI (n = 1049 (28.96%)). The proportion of MI in patients with DM was 40% and 25% in patients without DM. Mortality during follow-up was 10.9% in non-DM patients without MI, 21.3% in DM patients without MI, 40.1% in non-DM patients with MI, and 52.8% in DM patients with MI. A competitive risk model was used to obtain the Hazard Ratio (HR) for readmission for myocardial infarction or heart failure. There was a similar proportion of readmission for myocardial infarction and heart failure at a four-year follow-up in patients with DM or MI, which was much higher when DM was associated with MI, with respect to patients without DM or MI. The HR (95% Coefficient Interval) for myocardial infarction in the DM without MI, non-DM with MI, and DM with MI groups with respect to the non-DM without MI group was 2511 (1592–3960), 2682 (1739–4138), and 5036 (3221–7876), respectively. The HR (95% CI) for the risk of readmission for heart failure in the DM without MI, non-DM with MI, and DM with MI groups with respect to the non-DM without MI group was 2663 (1825–3886), 2562 (1753–3744) and 4292 (2936–6274), respectively.ConclusionsThe association of DM and MI in patients treated in an Emergency Service identifies patients at very high risk of mortality and cardiovascular events.

Effect of Diabetes Mellitus on 30 and 90-Day Readmissions of Patients With Heart Failure

The prevalence of diabetes mellitus (DM) in hospitalized heart failure (HF) patients is increasing over time. However, the effect of DM on short-term readmissions for HF is not well established. We investigated the effects of DM on readmissions of HF patients. All adult hospitalizations with a primary diagnosis of HF were identified in the National Readmission Database (NRD) for 2018 and were categorized into those with and without a secondary diagnosis of DM. The primary outcome was to assess risk difference in 30 and 90-day all-cause readmissions. Multivariate Cox survival analysis and multivariate Cox regression were performed to estimate the readmission risk difference in HF patients with and without DM. Of 925,637 HF hospitalizations that met the inclusion criteria, 441,295 (47.6%) had concomitant DM. Diabetics hospitalized for HF had higher prevalence of obesity (37.3% vs 19.5%), kidney disease (58.4% vs 29.2%) and coronary disease (61.1% vs 51.0%), compared to HF hospitalizations without DM. In adjusted analyses, DM was associated with higher hazards for all-cause [hazards ratio (HR), 30 days: 1.04 (1.02-1.06); 90 days: 1.07 (1.05-1.09)], HF [HR, 30 days: 1.05 (1.02-1.07); 90 days: 1.08 (1.05-1.10)] and myocardial infarction (MI) [HR, 30 days: 1.26 (1.12-1.41); 90 days: 1.38 (1.25-1.52)] readmissions. In conclusion, in patients with HF-related hospitalizations, the presence of DM was associated with a higher risk of 30 and 90-day all-cause, HF and MI readmissions.

972-P: Trends in Rehospitalisation Rates for Myocardial Infarction, Heart Failure, and Stroke in People with and without Diabetes in Australia from 2012-2018

Contemporary estimates of readmission rates and trends over time following cardiovascular events are required to prioritise clinical care. We estimated the incidence of readmission for myocardial infarction (MI) and heart failure (HF) following an MI, and of readmission for stroke following a stroke, stratified by diabetes status. We included everyone who was discharged from a hospital following an MI or stroke between 1 July 2012 and 30 June 2017 in Victoria, Australia (n=102323). Individuals were followed from discharge following an MI until readmission for MI or HF, or followed from discharge after a stroke until readmission for stroke, censoring at death or 1 year of follow-up. The incidence (per 100 person-years) of readmission for MI decreased in both people with and without diabetes (from 28.9 [95% CI: 27.4, 30.5] to 27.0 [25.6, 28.5] and from 18.5 [17.8, 19.3] to 15.2 [14.5, 16.0] from 2012 to 2016 [years beginning 1 July] in people with and without diabetes, respectively), but the incidence of readmission for HF only improved in people without diabetes (from 23.4 [22.0, 24.9] to 22.5 [21.1, 23.9] and 4.5 [4.1, 4.9] to 3.2 [2.9, 3.5]), and the incidence of readmission for stroke did not change (from 11.0 [9.5, 12.9] to 10.6 [9.2, 12.2] and 10.3 [9.3, 11.3] to 11.2 [10.3, 12.2]). However, the incidence rate ratio for people with vs. without diabetes increased for readmission for MI and HF. The excess risk for readmission for MI and HF for people with diabetes persisted after adjustment for age, sex, socioeconomic status, polypharmacy, comorbidity, and the competing risk of death: with subhazard ratios of 1.32 (1.28, 1.37) for MI and 3.77 (3.57, 3.98) for HF. The effect of diabetes on readmission for MI, but not HF or stroke, was stronger for women than men. Thus, improvements in rates of readmission for MI and HF were greater in people without diabetes than people with diabetes, therefore the excess risk for people with diabetes worsened from 2012-2018. Disclosure J. I. Morton: None. J. Ilomaki: Consultant; Self; AstraZeneca, Research Support; Self; Amgen Inc., Research Support; Spouse/Partner; GlaxoSmithKline plc. S. J. Wood: None. D. J. Magliano: None. J. E. Shaw: Advisory Panel; Self; Eli Lilly and Company, Merck Sharp &amp; Dohme Corp., Pfizer Inc., Research Support; Self; AstraZeneca, Speaker’s Bureau; Self; AstraZeneca, Eli Lilly and Company, Novo Nordisk. Funding Australian Government Research Training Program (to J.I.M.); Monash University (to J.I.M.)

Risk of thrombotic events after respiratory infection requiring hospitalization

Thrombosis is a major concern in respiratory infections. Our aim was to investigate the magnitude and duration of risk for arterial and venous thrombosis following discharge after respiratory infection. Patients with respiratory infections were identified using the United States Nationwide Readmission Database from 2012 to 2014. Patients admitted with asthma or cellulitis served as comparators. Readmissions for acute myocardial infarction (MI) and venous thromboembolism (VTE) were evaluated at 30 to 180 days. The likelihood of a first thrombotic event after discharge was compared with a 30-day period prior to hospitalization. Among 5,271,068 patients discharged after a respiratory infection, 0.56% and 0.78% were readmitted within 30-days with MI and VTE, respectively. Relative to asthma and cellulitis, respiratory infection was associated with a greater age and sex-adjusted hazard of 30-day readmission for MI (adjusted HR [aHR] 1.48 [95% CI 1.42–1.54] vs. asthma; aHR 1.36 [95% CI 1.31–1.41] vs. cellulitis) and VTE (aHR 1.28 [95% CI 1.24–1.33] vs. asthma; aHR 1.26, [95% CI 1.22–1.30] vs. cellulitis). Risks of MI and VTE attenuated over time. In a crossover-cohort analysis, the odds of MI (OR 1.68 [95% CI 1.62–1.73]) and VTE (OR 3.30 [95% 3.19–3.41]) were higher in the 30 days following discharge after respiratory infection than during the 30-day baseline period. Hospitalization for respiratory infection was associated with increased risks of thrombosis that were highest in the first 30-days after discharge and declined over time.

Patient Characteristics and Clinical Outcomes of Type 1 Versus Type 2 Myocardial Infarction

BackgroundType 2 myocardial infarction (MI) patients may have different characteristics and outcomes when compared with type 1 MI. ObjectivesThe purpose of this study was to compare patients with type 1 MI to those with type 2 MI in the United States. MethodsUsing the Nationwide Readmissions Database, MI patients were categorized over the 3 months following the introduction of an International Classification of Diseases-10th Revision code specific for type 2 MI. Baseline characteristics and inpatient and post-discharge outcomes among both cohorts were compared. ResultsThere were 216,657 patients with type 1 MI, 37,765 patients with type 2 MI, and 1,525 patients with both type 1 and 2 MI. Patients with type 2 MI were older (71 years vs. 69 years; p < 0.001), were more likely to be women (47.3% vs. 40%; p < 0.001), and had higher prevalence of heart failure (27.9% vs. 10.9%; p < 0.001), kidney disease (35.7% vs. 25.7%; p < 0.001), and atrial fibrillation (31% vs. 21%; p < 0.001). Rates of coronary angiography (10.9% vs. 57.3%; p < 0.001), percutaneous coronary intervention (1.7% vs. 38.5%; p < 0.001), and coronary artery bypass grafting (0.4% vs. 7.8%; p < 0.001) were lower among type 2 MI patients. Patients with type 2 MI had lower risk of in-hospital mortality (adjusted odds ratio: 0.57 [95% confidence interval: 0.54 to 0.60]) and 30-day MI readmission (adjusted odds ratio: 0.46 [95% confidence interval: 0.35 to 0.59]). There was no difference in risk of 30-day all-cause or heart failure readmission. ConclusionsPatients with type 2 MI have a unique cardiovascular phenotype when compared with type 1 MI, and are managed in a heterogenous manner. Validated management strategies for type 2 MI are needed.

Abstract 13288: Risk of Thrombotic Events After Respiratory Infection Requiring Hospitalization

Background: Thrombosis is a major concern in respiratory infections such as influenza and now COVID-19. We investigated the magnitude and duration of risk for arterial and venous thrombosis following discharge after respiratory infections. Methods: Patients with respiratory infections were identified using the United States Nationwide Readmission Database from 2012-2014. Patients admitted with asthma or cellulitis served as comparators. Readmissions for myocardial infarction (MI) and venous thromboembolism (VTE) were evaluated at 30 to 180 days. The likelihood of a thrombotic event after hospital discharge was compared with a 30-day period prior to hospitalization using conditional logistic regression. Results: Among 5,271,068 patients discharged after a respiratory infection, 0.56% and 0.78% were readmitted within 30-days with MI and VTE, respectively. Relative to asthma and cellulitis, respiratory infection was associated with a greater age and sex-adjusted hazard of 30-day readmission for MI (adjusted HR [aHR] 1.58 [95% CI 1.52-1.64] vs. asthma; aHR 1.43 [95% CI 1.38-1.48] vs. cellulitis) and VTE (aHR 1.65 [95% CI 1.60-1.69] vs. asthma; aHR 1.45, [95% CI 1.41-1.50] vs. cellulitis). Risks of MI and VTE after respiratory infection attenuated over time, yet remained higher than asthma and cellulitis over 90 and 180 days (Figure). In a crossover-cohort analysis, the odds of MI (OR 1.68 [95% CI 1.62-1.73]) and VTE (OR 3.30 [95% 3.19-3.41]) were higher in the 30 days following discharge after respiratory infection than during the baseline period. The odds of MI (OR 2.44 [95% CI 1.95-3.05]) and VTE (OR 4.49 [95% 3.50-5.76]) at 30-days appeared highest when a viral respiratory pathogen was identified. Conclusions: Hospitalization for respiratory infection, particularly when of viral etiology, was associated with an increased risk of myocardial infarction and venous thrombosis that was highest in the first 30-days after discharge and declined over time.

Abstract 245: Risk of Readmission With Recurrent Myocardial Infarction After Index Myocardial Infarction

Background: Recurrent Myocardial Infarction (MI) after an index MI is a cause for considerable morbidity and mortality. However, the underlying factors that precipitate patients for a recurrent MI remain unclear. We aimed to assess the effect of index MI treatment strategy on the risk of developing a recurrent MI. Methods: We reviewed all cases of MI at a single quaternary care medical center from January 1 st , 2010 to January 1 st , 2017 and identified all cases of recurrent MI within 90 days after index MI. Readmissions were further stratified depending on the treatment strategy undertaken during index MI into medically managed and revascularized patients. The instantaneous risk of readmission following each of these treatment strategies was estimated by the parametric method. Results: We identified 6,626 patients admitted with an index MI, of which 168 patients were readmitted with a recurrent MI within 90 days. Among the index admissions, 4354 (66%) patients underwent revascularization and 2272 (34%) patients underwent medical management. Time-varying instantaneous risk of readmission analysis showed an early peaking risk followed by a late increasing risk in the revascularization group whereas, in the medically managed group, the analysis yielded an early peaking followed by a late almost constant risk of readmission for MI. Conclusion: Patients with acute MI who are medically treated are at a higher risk of developing a recurrent MI than patients who undergo revascularization. Defining the characteristics and underlying factors contributing to these readmissions can be pivotal in improving patient outcomes.

Association of a Novel Protocol for Rapid Exclusion of Myocardial Infarction With Resource Use in a US Safety Net Hospital

High-sensitivity cardiac troponin T (hs-cTnT) protocols for the evaluation of chest pain in the emergency department (ED) may reduce unnecessary resource use and overcrowding. To determine whether the implementation of a novel hs-cTnT protocol, which incorporated troponin values drawn at 0, 1, and 3 hours after ED presentation and the modified HEART score (history, electrocardiogram, age, risk factors), was associated with improvements in resource use while maintaining safety. This retrospective cohort study from Parkland Health and Hospital System, a large safety net hospital in Dallas, Texas, included data on 31 543 unique ED encounters in which patients underwent electrocardiographic and troponin testing from January 1, 2017, to October 16, 2018. The hs-cTnT protocol was implemented in December 2017. Resource use outcomes included trends in ED dwell time, troponin to disposition decision time (the difference between the first troponin draw time and the time an order was placed for inpatient admission, admission to observation, or discharge), and final patient disposition. Safety outcomes included readmission for myocardial infarction and death. In 31 543 encounters, mean (SD) patient age was 54 (14.4) years and 14 675 patients (48%) were female. Department dwell time decreased by a mean of -1.09 (95% CI, -2.81 to 0.64) minutes per month in the preintervention period. The decline was steeper after the intervention (-4.69 [95% CI, -9.05 to -0.33] minutes per month) (P for interaction = .007). The troponin to disposition time was increasing in the preintervention period by 1.72 (95% CI, 1.08 to 2.36) minutes per month; postintervention, the mean difference increased more slowly (0.37 [95% CI, -1.25 to 1.99 minutes per month; P value for interaction = .007]). The proportion of patients discharged from the ED increased after the intervention (48% vs 54%, P < .001). Thirty-day major adverse cardiac event rates were low and did not differ before and after the intervention. Implementation of a novel protocol incorporating serial hs-cTnT measurements over 3 hours with the Modified HEART Score was associated with reduction in ED dwell times and attenuation of temporal increases in time from troponin measurement to disposition. This or similar protocols to rule out myocardial infarction have the potential to reduce ED overcrowding and improve health care quality while maintaining safety.