Acute Myocardial Infarction Due to Eltrombopag Therapy in a Patient with Immune Thrombocytopenic Purpura

Abstract Background: Immune Thrombocytopenic Purpura (ITP) is an autoimmune disorder characterized by low platelet counts and mucocutaneous bleeding. Antiplatelet agents are an essential component in the treatment of acute myocardial infarction (MI). Patients with ITP are not exempt from succumbing to acute myocardial infarction. Myocardial infraction in these patients is rare but poses a significant management challenge. The outcomes of hospitalized patients with ITP and acute MI have not been previously described and may help identify risk factors associated with adverse outcomes in this unique patient population. Methods: The International Classification of Diseases, 9th Edition, Clinical Modification codes were used to identify patients with ITP who were admitted with acute myocardial infarction. All data regarding such hospitalization was extracted from the National Inpatient Database for the years 2000 to 2014. Patient demographics of age, race and gender; hospital characteristics such as geographical location, teaching status, rural vs. urban location and bed size, medical comorbidities such as hypertension, hyperlipidemia, diabetes and coronary artery disease were studied. The Chi square test was used to determine associations with statistical significance and logistic regression was used to determine independent predictors of mortality. Results: A total of 753,732 hospitalized patients with ITP were identified over the time period of 2000 to 2014 of which 37695 patients had both ITP and acute MI. There were more females with ITP in general (60% females vs 40% males), but more males with ITP and acute MI (55.8% males vs 44.2% females; p =0.0000). Caucasians were affected the most (5.5%) amongst all races and the age group of 65-79 years had the highest percentage of patients with ITP and MI (7.3%). While hospitals located in the Northeast region of the country had the highest prevalence of MI in ITP, there was no statistical difference between prevalence in hospitals of different sizes (small vs. medium vs. large). A majority of patients with MI and ITP were covered by Medicare and were discharged home. 5572 patients received a stent and 3353 patients underwent coronary artery bypass grafting. The classical risk factors of hypertension, hyperlipidemia, and diabetes were also noted to be highly prevalent in patients with ITP and MI. 10.05% of patients with ITP and acute MI died during hospitalization, while 4% of all patients with ITP died during hospitalization (p<0.05). Multiple regression showed that stent placement, female gender, blood transfusions, platelet transfusion, 80+ age group and higher Charlson's score were independent predictors of mortality in patients with ITP who have MI (ORs: 0.3, 0.8, 1.9, 1.3, 5.9 and 5.5 respectively). Conclusions: ITP patients with MI have poor outcomes. Known risk factors for acute MI in the general population are also applicable to patients with ITP. Acute MI is associated with an increased rate of in-hospital death in patients with ITP. Both blood transfusions and platelet transfusions adversely affect outcomes and should be considered in the management of MI in ITP patients. Disclosures Kota: Novartis: Honoraria; Xcenda: Honoraria; Incyte: Honoraria; BMS: Honoraria; Pfizer: Honoraria.

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Recurrent Acute Myocardial Infarction in Patients with Immune Thrombocytopenic Purpura

Journal of Patient-Centered Research and Reviews ◽

10.17294/2330-0698.1010 ◽

2014 ◽

Vol 1 (1) ◽

pp. 41-45 ◽

Cited By ~ 1

Author(s):

Fengyi Shen ◽

Tonga Nfor ◽

Tanvir Bajwa

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Immune Thrombocytopenic Purpura ◽

Thrombocytopenic Purpura

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Primary PCI for Acute Myocardial Infarction in a Patient with Idiopathic Thrombocytopenic Purpura

Herz ◽

10.1007/s00059-010-3262-1 ◽

2010 ◽

Vol 35 (1) ◽

pp. 43-49 ◽

Cited By ~ 13

Author(s):

Aleksandar N. Neskovic ◽

Ivan Stankovic ◽

Predrag Milicevic ◽

Aleksandar Aleksic ◽

Alja Vlahovic-Stipac ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Idiopathic Thrombocytopenic Purpura ◽

Primary Pci ◽

Thrombocytopenic Purpura

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Risk-Predictors of Mortality in Hospitalized Patients with Thrombotic Thrombocytopenic Purpura: Nationally Representative Data from 2007-2011

Blood ◽

10.1182/blood.v124.21.4290.4290 ◽

2014 ◽

Vol 124 (21) ◽

pp. 4290-4290

Author(s):

Ruchika Goel ◽

Paul Ness ◽

Clifford M. Takemoto ◽

Karen E. King ◽

Aaron Tobian

Keyword(s):

Risk Factors ◽

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Logistic Regression ◽

Thrombotic Thrombocytopenic Purpura ◽

Arterial Thrombosis ◽

Hospitalized Patients ◽

Thrombocytopenic Purpura ◽

Plasma Infusion ◽

Multivariable Logistic Regression

Abstract Introduction: Survivors of Thrombotic Thrombocytopenic Purpura (TTP) hospitalizations have been proposed to be at higher risk for long term poor clinical outcomes and premature death. Patients with TTP have a high risk for in-hospital morbidity and mortality as well. However, there is a paucity of data on the predictors of adverse outcomes including death in hospitalized patients with TTP. Methods: A weighted analysis of 5 years (2007-2011) using data from the Nationwide Inpatient Sample, a stratified probability sample of 20% of all hospital discharges among community hospitals in the United States (approximately 1100 hospitals/year), was performed. Hospitalizations with TTP as the primary admitting diagnoses were identified using the ICD-9 discharge code 446.6. Univariate and stepwise multivariable logistic regression analyses with elimination were used for statistical analysis. Based on results of univariate analysis, the significant variables were added in a stepwise manner in a multivariable model. All variables selected for the multivariable model were tested for interaction with a significance threshold level of p<0.2. Except for this, all hypothesis testing was two tailed and p<0.05 was considered significant. Receiver Operator Characteristics (ROC) curve was constructed using risk factors on multivariate analysis. Results: The all-cause mortality rate was 8.7% (918/10615) among admissions with primary diagnosis of TTP (0.5% pediatric, 65.9% female, 58.2% Caucasian, 27.2% African-American). Table 1 lists the risk factors by univariate analysis and includes a) factors with significantly higher odds of mortality and b) other putative factors which were not statistically significant predictors. Table 2: In stepwise multivariable logistic regression analysis: arterial thrombosis (adjOR 5.1 95%CI=1.1-31.7), acute myocardial infarction (adjOR 2.8, 95%CI=1.6-4.9), non-occurrence of either intervention: plasmapheresis or fresh frozen plasma infusion (adjOR 2.0, 95% CI=1.4-2.9) 4) requirement of platelet transfusions during hospitalization (adjOR 2.0, 95%CI= 1.3-3.2) and every ten year increase in age (OR 1.4 95%CI=1.3-1.6) were independently predictive of mortality in TTP patients (area under the curve for ROC 74%, Figure 1). Conclusion: We present a set of independent risk factors that may potentially be used in a predictive model of mortality in TTP. Early and targeted aggressive therapy based on these factors should guide the management of hospitalized patients with TTP for improved outcomes. Table 1.Unadjusted odds of in-hospital mortality.Significant predictors of mortality for TTP on univariate analysisOdds Ratio95% Confidence LimitsArterial Thrombosis 10.92.254.6AMI 3.72.16.2STROKE 4.93.07.9Platelet Transfusion 2.31.53.6Bleeding event 1.71.12.6Plasmapheresis (No vs. Yes)1.61.22.3plasmapheresis or plasma infusion (not performed)2.21.53.1Every 10 years increase in age1.51.31.6PRBC transfusion1.71.22.3Caucasian versus African American1.91.32.8Asian versus African American3.31.29.1V ariables not significant predictors of mortality for TTP on univariate analysis.Odds Ratio95% Confidence LimitsVenous Thrombosis/Thromboembolism1.90.84.4FEMALE versus male gender1.00.71.4Hypertension Yes vs. no0.90.61.2Diabetes Yes vs. no0.90.61.4Chronic Kidney Disease Yes vs. No1.40.92.2End Stage Renal Disease Yes vs. No0.90.41.9Overweight/Obese Yes vs. No0.70.41.5Variables meeting criteria for inclusion in multiple logistic regression model are in boldface type. Table 2. Multivariable Predictors for In Hospital Mortality in patients with primary diagnosis of TTP Adjusted Odds Ratio 95% Confidence Limits Arterial Thrombosis 6.0 1.2 30.5 Acute myocardial infarction 2.8 1.6 4.8 No Plasmapheresis/Plasma infusion 2.0 1.4 2.9 Platelet Transfusion 2.1 1.4 3.2 Age (per 10 year higher) 1.4 1.3 1.6 Female versus Male 1.2 0.8 1.7 TTP = Thrombotic Thrombocytopenic Purpura Step 0: Using arterial thrombosis Figure 1: Receiver- Operator-Characteristic Curve (ROC) overlay curve for the stepwise multivariable logistic regression risk prediction showing incremental AUC with addition of each risk factor for hospital patients with TTP. Figure 1:. Receiver- Operator-Characteristic Curve (ROC) overlay curve for the stepwise multivariable logistic regression risk prediction showing incremental AUC with addition of each risk factor for hospital patients with TTP. Step 1: Adding acute myocardial infarction Step 2: Adding plasmapheresis /fresh frozen plasma infusion Step 3: Adding platelet transfusions Final model: Adding every ten year increase in age. Disclosures Ness: Terumo BCT: Consultancy.

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