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

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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Outcomes of Hospitalized Patients with Myocardial Infarction and Immune Thrombocytopenic Purpura: A Cross Sectional Study over 15 Years

Blood ◽

10.1182/blood-2018-99-116966 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4977-4977

Author(s):

Chisom Onuoha ◽

Marcus Weldon ◽

Vamsi Kota ◽

Achuta Kumar Guddati

Keyword(s):

Risk Factors ◽

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Coronary Artery ◽

Immune Thrombocytopenic Purpura ◽

Hospitalized Patients ◽

Blood Transfusions ◽

Age Group ◽

Thrombocytopenic Purpura ◽

Acute Mi

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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In-hospital gastrointestinal bleeding in patients with acute myocardial infarction: incidence, outcomes and risk factors analysis from China Acute Myocardial Infarction Registry

BMJ Open ◽

10.1136/bmjopen-2020-044117 ◽

2021 ◽

Vol 11 (9) ◽

pp. e044117

Author(s):

Wence Shi ◽

Xiaoxue Fan ◽

Jingang Yang ◽

Lin Ni ◽

Shuhong Su ◽

...

Keyword(s):

Risk Factors ◽

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Logistic Regression ◽

Gastrointestinal Bleeding ◽

Secondary Outcome ◽

Multivariate Logistic Regression ◽

Independent Risk Factors ◽

Receptor Inhibitor

ObjectiveTo investigate the incidence of gastrointestinal bleeding (GIB) in patients with acute myocardial infarction (AMI), clarify the association between adverse clinical outcomes and GIB and identify risk factors for in-hospital GIB after AMI.DesignRetrospective cohort study.Setting108 hospitals across three levels in China.ParticipantsFrom 1 January 2013 to 31 August 2014, after excluding 2659 patients because of incorrect age and missing GIB data, 23 794 patients with AMI from 108 hospitals enrolled in the China Acute Myocardial Infarction Registry were divided into GIB-positive (n=282) and GIB-negative (n=23 512) groups and were compared.Primary and secondary outcome measuresMajor adverse cardiovascular and cerebrovascular events (MACCEs) are a composite of all-cause death, reinfarction and stroke. The association between GIB and endpoints was examined using multivariate logistic regression and Cox proportional hazards models. Independent risk factors associated with GIB were identified using multivariate logistic regression analysis.ResultsThe incidence of in-hospital GIB in patients with AMI was 1.19%. GIB was significantly associated with an increased risk of MACCEs both in-hospital (OR 2.314; p<0.001) and at 2-year follow-up (HR 1.407; p=0.0008). Glycoprotein IIb/IIIa (GPIIb/IIIa) receptor inhibitor, percutaneous coronary intervention (PCI) and thrombolysis were novel independent risk factors for GIB identified in the Chinese AMI population (p<0.05).ConclusionsGIB is associated with both in-hospital and follow-up MACCEs. Gastrointestinal prophylactic treatment should be administered to patients with AMI who receive primary PCI, thrombolytic therapy or GPIIb/IIIa receptor inhibitor.Trial registration numberNCT01874691.

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Integrin Polymorphisms as Risk Factors for Thrombosis

Thrombosis and Haemostasis ◽

10.1055/s-0037-1615851 ◽

1999 ◽

Vol 82 (08) ◽

pp. 337-344 ◽

Cited By ~ 32

Author(s):

Paul Bray

Keyword(s):

Risk Factors ◽

Myocardial Infarction ◽

Coronary Artery Disease ◽

Acute Myocardial Infarction ◽

Coronary Artery ◽

Arterial Thrombosis ◽

Protein C ◽

Integrin Αiibβ3 ◽

Coronary Syndromes ◽

Artery Disease

IntroductionBy the year 2020, ischemic heart disease will become the number one public health problem on the planet, surpassing lower respiratory infections, diarrheal disease, perinatal problems, and unipolar major depression.1 Acute myocardial infarction, the most feared complication of coronary artery disease, results from the formation of an occlusive thrombus at the site of a ruptured atherosclerotic plaque. The 1990s have seen an increased awareness of the contribution of inherited disorders of hemostasis as risks for coronary thrombosis. Consideration for potential hypercoagulable states in patients with these disorders would seem justified, since, for example, the risk for an acute coronary event is considerably greater with an abnormally elevated fibrinogen level than with an elevated total cholesterol level.2,3 The clinical benefit of thrombolytic therapy in acute myocardial infarction provides further support for the importance of fibrin formation or dissolution in this setting.4,5 An appropriate hypercoagulable evaluation of an unusual arterial thrombosis, particularly in a young patient, would include assays for hyperhomocysteinemia, the lupus anticoagulant, anticardiolipin antibodies, as well as assays for fibrinogen and plasminogen activator inhibitor-1. Currently, less evidence exists to support measurements of tissue plasminogen activator, von Willebrand factor (vWF), factors VII or XIII, or those factors associated with venous thrombosis, such as activated protein C resistance/factor V Leiden or deficiencies of antithrombin III, protein C, or protein S.There is also abundant evidence that platelet thrombi play a crucial role in the development of acute myocardial infarction. In 1974, Chandler et al summarized a series of pathologic studies examining coronary arteries of patients with acute myocardial infarction and reaffirmed the basic understanding that coronary artery thrombi can cause acute ischemia and myocardial infarction.6 DeWood et al provided in vivo evidence to corroborate pathologic data,7 and Trip et al correlated platelet hyperreactivity with coronary events and mortality in patients with established coronary artery disease.8 The clinical arena has also provided additional support for the central role of platelets in the acute ischemic coronary syndromes, myocardial infarction, and unstable angina. Antiplatelet therapy with aspirin, ticlopidine, clopidogrel, and inhibitors of integrin αIIbβ3 (e.g., abciximab and integrilin) has demonstrated beneficial effects in a number of coronary artery disease settings.9-11 Platelet physiology is arbitrarily divided into phases of adhesion, activation, secretion, and aggregation. When arterial subendothelium is exposed, vWF molecules are rapidly localized to these areas, and the initial platelet contact with the wound is a tethering to this insoluble form of vWF via glycoprotein (GP) Ibα.12,13 Stable adhesion and platelet activation is then mediated through integrin α2β1 binding to exposed collagen and integrin αIIbβ3 binding to vWF and fibrinogen.14 Fibrinogen has multiple αIIbβ3 binding sites, and an expanding thrombus ensues when platelets aggregate via the intercellular bridging of fibrinogen and vWF binding to the activated conformation of αIIbβ3. Three platelet membrane glycoprotein receptors, αIIbβ3, α2β1, and GP Ib-IX, have highly interactive and additive adhesive effects, ultimately resulting in stable thrombus formation.Attempts to educate both physicians and the lay public about the so-called “traditional” risk factors for coronary artery disease and acute ischemic coronary syndromes have been successful,15 and there are now established preventive therapies, such as blood pressure control, cessation of cigarette smoking, and cholesterol lowering. Genetic variations confer a potent risk for coronary artery disease in many families, and, although these risks fall outside the domain of preventive medicine, an emerging concept in the field is that targeted genetic testing may be used to direct therapeutic decisions. Although inherited alterations of hemostatic factors are believed to be important in the development of acute ischemic coronary syndromes, until recently, inherited platelet risk factors had not been considered. This review will focus on the potential link between the genetic and platelet components of arterial thrombosis, in particular, coronary artery disease.

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