Predictors of In-hospital Mortality and Acute Myocardial Infarction in Thrombotic Thrombocytopenic Purpura

2013 ◽  
Vol 126 (11) ◽  
pp. 1016.e1-1016.e7 ◽  
Author(s):  
Nivas Balasubramaniyam ◽  
Dhaval Kolte ◽  
Chandrasekar Palaniswamy ◽  
Kiran Yalamanchili ◽  
Wilbert S. Aronow ◽  
...  
Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 4290-4290
Author(s):  
Ruchika Goel ◽  
Paul Ness ◽  
Clifford M. Takemoto ◽  
Karen E. King ◽  
Aaron Tobian

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.


2014 ◽  
Vol 23 (3) ◽  
pp. 289-291 ◽  
Author(s):  
Jun Wang ◽  
Xiaomin Cai ◽  
Xunmin Cheng ◽  
Ping Song ◽  
Shisen Jiang ◽  
...  

2016 ◽  
Vol 27 (8) ◽  
pp. 948-951 ◽  
Author(s):  
Tomoko Takimoto ◽  
Mitsushige Nakao ◽  
Takuya Nakajo ◽  
Yoshiaki Chinen ◽  
Junya Kuroda ◽  
...  

CHEST Journal ◽  
2009 ◽  
Vol 136 (4) ◽  
pp. 109S
Author(s):  
Kaushang A. Gandhi ◽  
Wilbert S. Aronow ◽  
Parminder Singh ◽  
Harit Desai ◽  
Harshad Amin ◽  
...  

2018 ◽  
Vol 5 (3) ◽  
pp. 183
Author(s):  
Betül Çavuşoğlu Türker ◽  
Süleyman Ahbab ◽  
Fatih Türker ◽  
Hayriye Esra Ataoğlu

2021 ◽  
Vol 9 (27) ◽  
pp. 8104-8113
Author(s):  
Delia Lidia Șalaru ◽  
Cristina Andreea Adam ◽  
Dragos Traian Marius Marcu ◽  
Ionut Valentin Șimon ◽  
Liviu Macovei ◽  
...  

1993 ◽  
Vol 23 (3) ◽  
pp. 481
Author(s):  
Cheol Whan Lee ◽  
Jae Joong Kim ◽  
Sung Jae Myung ◽  
Ju Young Kim ◽  
Hae Hyuk Chung ◽  
...  

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
O Chehab ◽  
M Pahuja ◽  
O Adegbala ◽  
E Akintoye ◽  
P Ramia ◽  
...  

Abstract Background There is scarce evidence reflecting the clinical outcomes in patients with Idiopathic Thrombocytopenic Purpura (ITP) and Acute Myocardial Infarction (AMI). The ITP patient population is at higher risk of bleeding complications due to low platelet counts and difficulty in managing their antiplatelet and anticoagulation therapy. In our study, we sought to assess clinical outcomes of ITP patients admitted with AMI using the US national inpatient sample (NIS) database. Purpose To determine difference in in-hospital mortality, clinical complications, and length of stay (LOS) in AMI patients with and without ITP. Methods We identified adults aged ≥18 years hospitalized from 2005 to 2014 with AMI as their primary diagnosis utilizing ICD-9 codes 410.0 to 410.92. Patients with ITP were identified using ICD-9 code 287.31. The primary outcome was in-hospital mortality. Secondary outcomes included coronary revascularization procedures (PCI and CABG), and in-hospital complications including bleeding (intracranial, epistaxis, GI, and GU bleeding, hematoma, and bleeding requiring transfusion), cardiac complications, transfusions, acute ischemic stroke (AIS), and LOS. A propensity-matched cohort accounting for demographic characteristics, comorbidities, and cardiovascular risk factors, was created to compare these outcomes. Patients with secondary causes of ITP such as HIV, pregnancy, sepsis, SLE, malignancy were excluded. Results A total of 1108034 AMI admissions, of which 1002 with ITP, were identified. In the unmatched group, patients with ITP were older, and had more comorbidities (diabetes mellitus; hypothyroidism; atrial fibrillation; previous history of cardiovascular, peripheral, and end stage renal disease; all p<0.05). In the AMI population, 851 ITP and 851 non-ITP admissions were propensity-matched. Figure 1 illustrates the primary and secondary outcomes of the study among the propensity-matched study groups. Although there was no difference in short-term mortality between the ITP and non-ITP patients with AMI, patients with ITP were less likely to undergo coronary revascularization possibly because of thrombocytopenia. Patients with ITP had significantly more bleeding complications and transfusions. We observed in our study that patients with ITP had a significantly longer LOS compared to non-ITP patients (6.1 vs 5.4 days, with a mean ratio of 1.14 (95% CI: 1.05,1.23)). Conclusion In the large population of patients included in the NIS database, patients with ITP admitted with AMI, have a significantly higher rate of bleeding complications, undergo less PCI and have a longer LOS compared to AMI patients without ITP. There are no current guidelines by ACC/AHA/ESC regarding management of patients with AMI and thrombocytopenia. These results warrant further investigation through randomized controlled trials including patients with thrombocytopenia to assess long term outcomes and to define optimal management in this population.


2003 ◽  
Vol 33 (11) ◽  
pp. 1048
Author(s):  
Tae Hee Lee ◽  
Jin Hyuk Kim ◽  
Wan Jung Kim ◽  
Ji Young Park ◽  
Heung Sun Kang ◽  
...  

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