title: Predictors of in-hospital complications after pericardiectomy: a nationwide outcomes study.
abstract: OBJECTIVE
  Advances in medical care had caused a paradigm shift in the indications for pericardiectomy. We evaluated the current predictors of in-hospital complications for pericardiectomy.
  
  
  METHODS
  Patients who underwent pericardiectomy between 1998 and 2008 were identified from the US Nationwide Inpatient Sample. Risk-adjusted logistic regression model was used to analyze the predictors of surgical outcomes.
  
  
  RESULTS
  A total of 13,593 patients underwent pericardiectomy during this period. Pericardiectomy was performed for constrictive pericarditis (28%; n = 3851), pericardial calcification (15%; n = 2061), secondary malignancies (3%; n = 456), adhesive pericarditis (2%; n = 318), and other causes (40%; n = 5461). Unadjusted mortality and complication rates were approximately 8% and 48%, respectively. Fourteen percent of patients required blood transfusion. Only 62% were routinely discharged home. After risk adjustment, age, female gender, comorbidity index, and the primary diagnosis independently predicted in-hospital mortality and overall complication rates (P < .05). Calcific pericarditis was the only etiology associated with lower risk-adjusted mortality (odds ratio [OR], 0.48), operative complications (OR, 0.32), overall complications (OR, 0.32), incidence of transfusion (OR, 0.38), and highest routine discharge rates (OR, 1.84); P < .001 for all. Constrictive pericarditis had the highest requirement for cardiopulmonary bypass (OR, 6.41; P < .01) and incidence of bleeding complications (OR, 2.61; P < .01).
  
  
  CONCLUSIONS
  Morbidity remains high for pericardiectomy. In addition to age, gender, and comorbidities, attention should be given to etiology during surgical planning or referral. This significantly influences the requirement for cardiopulmonary bypass, chances of bleeding complications, and transfusion requirements.
authors.affiliation: Division of Cardiothoracic Surgery, University of Missouri-Columbia School of Medicine, Columbia, MO, USA. gopaldasr@health.missouri.edu
authors.forename: Raja R
authors.initials: RR
authors.lastname: Gopaldas
authors.forename: Tam K
authors.initials: TK
authors.lastname: Dao
authors.forename: Normand R
authors.initials: NR
authors.lastname: Caron
authors.forename: John G
authors.initials: JG
authors.lastname: Markley
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D001803:Blood Transfusion; D016009:Chi-Square Distribution; D015897:Comorbidity; D005260:Female; D006331:Heart Diseases / Q000401:mortality / Q000601:surgery*; D017052:Hospital Mortality; D006801:Humans; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D010351:Patient Discharge; D010492:Pericardiectomy / Q000009:adverse effects* / Q000401:mortality; D011183:Postoperative Complications / Q000209:etiology* / Q000401:mortality / Q000628:therapy; D019106:Postoperative Hemorrhage / Q000209:etiology / Q000628:therapy; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D013997:Time Factors; D016896:Treatment Outcome; D014481:United States