title: The coexistence of multiple cardiovascular diseases is an independent predictor of the 30-day mortality of hospitalized patients with congestive heart failure: a study in Beijing.
abstract: BACKGROUND
  Congestive heart failure (CHF) has become a major clinical and public health challenge with the aging of the population in China. However, the effect of the coexistence of multiple cardiovascular diseases on the prognosis of hospitalized patients with CHF remains unclear. A comparative analysis was performed to explore the etiology and comorbidities of CHF and in-hospital mortality in patients with CHF.
  
  
  OBJECTIVE
  The coexistence of multiple cardiovascular diseases is an independent predictor of the 30-day mortality of hospitalized patients with CHF.
  
  
  METHODS
  All 6949 patients (4344 males, 2605 females) in the database with a principal ICD-9-CM discharge diagnosis of CHF were identified and divided into 5 groups according to the number of comorbidities. Cox proportional hazards regression was used to examine the association between the number of comorbidities and in-hospital mortality in patients with CHF.
  
  
  RESULTS
  A single comorbidity was predominant in younger patients (18-39 years, P<0.001), whereas multiple comorbidities were predominant in the elderly (≥80 years, P<0.001). The most common single etiology was valvular heart disease, and the most common triple etiology was hypertension and diabetes mellitus complicated by coronary artery disease. Cox regression analysis showed a higher hospital mortality rate associated with an increased number of comorbidities (hazard ratio [HR] from 1.22 [95% CI: 0.89-1.68] to HR 3.49 [95% CI: 2.55-4.78], P<0.001).
  
  
  CONCLUSIONS
  This study demonstrates the coexistence of multiple cardiovascular diseases is an independent predictor of the 30-day mortality of hospitalized patients with CHF.
authors.affiliation: Laboratory of Geriatric Cardiology, Institute of Geriatric Cardiology, Chinese PLA General Hospital, Beijing, China.
authors.forename: Qiaoxiang
authors.initials: Q
authors.lastname: Yin
authors.forename: Yusheng
authors.initials: Y
authors.lastname: Zhao
authors.forename: Jiayue
authors.initials: J
authors.lastname: Li
authors.forename: Qiao
authors.initials: Q
authors.lastname: Xue
authors.forename: Xingli
authors.initials: X
authors.lastname: Wu
authors.forename: Lei
authors.initials: L
authors.lastname: Gao
authors.forename: Ping
authors.initials: P
authors.lastname: He
authors.forename: Mei
authors.initials: M
authors.lastname: Zhu
authors.forename: Shiwen
authors.initials: S
authors.lastname: Wang
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D044466:Asian People / Q000706:statistics & numerical data*; D002318:Cardiovascular Diseases / Q000208:ethnology / Q000401:mortality*; D016009:Chi-Square Distribution; D002681:China / Q000453:epidemiology; D015897:Comorbidity; D005260:Female; D006333:Heart Failure / Q000208:ethnology / Q000401:mortality*; D017052:Hospital Mortality; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D055815:Young Adult