HOMEPRODUCTSCOMPANYCONTACTFAQResearchDictionaryPharmaSign Up FREE or Login

Predictors of in-hospital mortality and acute myocardial infarction in thrombotic thrombocytopenic purpura.

AbstractBACKGROUND:
Despite the widespread availability of plasmapheresis as a therapy, thrombotic thrombocytopenic purpura is associated with significant morbidity and mortality. There is a paucity of data on the predictors of poor clinical outcome in this population. Acute myocardial infarction is a recognized complication of thrombotic thrombocytopenic purpura. Little is known about the magnitude of this problem, its risk factors, and its influence on mortality in patients hospitalized with thrombotic thrombocytopenic purpura.
METHODS:
We used the 2001-2010 Nationwide Inpatient Sample database to identify patients aged ≥18 years with the diagnosis of thrombotic thrombocytopenic purpura (International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] code 446.6) who also received therapeutic plasmapheresis (ICD-9-CM code 99.71) during the hospitalization. Patients with acute myocardial infarction were identified using the Healthcare Cost and Utilization Project Clinical Classification Software code 100. Stepwise logistic regression was used to determine independent predictors of in-hospital mortality and acute myocardial infarction in thrombotic thrombocytopenic purpura patients.
RESULTS:
Among the 4032 patients (mean age 47.5 years, 67.7% women, and 36.9% white) with thrombotic thrombocytopenic purpura who also underwent plasmapheresis, in-hospital mortality was 11.1%. Independent predictors of increased in-hospital mortality were older age (odds ratio [OR] 1.03; 95% confidence interval [CI], 1.02-1.04; P <.001), acute myocardial infarction (OR 1.89; 95% CI, 1.24-2.88; P = .003), acute renal failure (OR 2.75; 95% CI, 2.11-3.58; P <.001), congestive heart failure (OR 1.66; 95% CI, 1.17-2.34; P = .004), acute cerebrovascular disease (OR 2.68; 95% CI, 1.87-3.85; P <.001), cancer (OR 2.49; 95% CI, 1.83-3.40; P <.001), and sepsis (OR 2.59; 95% CI, 1.88-3.59; P <.001). Independent predictors of acute myocardial infarction were older age (OR 1.03; 95% CI, 1.02-1.04; P <.001), smoking (OR 1.60; 95% CI, 1.14-2.24; P = .007), known coronary artery disease (OR 2.59; 95% CI, 1.76-3.81; P <.001), and congestive heart failure (OR 2.40; 95% CI, 1.71-3.37; P <.001).
CONCLUSION:
In this large national database, patients with thrombotic thrombocytopenic purpura had an in-hospital mortality rate of 11.1% and an acute myocardial infarction rate of 5.7%. Predictors of in-hospital mortality were older age, acute myocardial infarction, acute renal failure, congestive heart failure, acute cerebrovascular disease, cancer, and sepsis. Predictors of acute myocardial infarction were older age, smoking, known coronary artery disease, and congestive heart failure.
AuthorsNivas Balasubramaniyam, Dhaval Kolte, Chandrasekar Palaniswamy, Kiran Yalamanchili, Wilbert S Aronow, John A McClung, Sahil Khera, Sachin Sule, Stephen J Peterson, William H Frishman
JournalThe American journal of medicine (Am J Med) Vol. 126 Issue 11 Pg. 1016.e1-7 (Nov 2013) ISSN: 1555-7162 [Electronic] United States
PMID23993262 (Publication Type: Journal Article)
CopyrightCopyright © 2013 Elsevier Inc. All rights reserved.
Topics
  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Databases, Factual
  • Female
  • Hospital Mortality
  • Hospitalization
  • Humans
  • Incidence
  • Kaplan-Meier Estimate
  • Logistic Models
  • Male
  • Middle Aged
  • Myocardial Infarction (epidemiology, etiology, mortality)
  • Plasmapheresis
  • Prognosis
  • Purpura, Thrombotic Thrombocytopenic (complications, mortality, therapy)
  • Retrospective Studies
  • Risk Factors
  • Young Adult

Join CureHunter, for free Research Interface BASIC access!

Take advantage of free CureHunter research engine access to explore the best drug and treatment options for any disease. Find out why thousands of doctors, pharma researchers and patient activists around the world use CureHunter every day.
Realize the full power of the drug-disease research graph!


Choose Username:
Email:
Password:
Verify Password:
Enter Code Shown: