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Intensive Care Medicine

, Volume 36, Issue 9, pp 1579–1586 | Cite as

APACHE-II score and Killip class for patients with acute myocardial infarction

  • Juan Mercado-Martínez
  • Ricardo Rivera-Fernández
  • Eduardo Aguilar-Alonso
  • Ángel García-Alcántara
  • Andrés Estivill-Torrull
  • Agustín Aranda-León
  • María Consuelo Guia-Rambla
  • Mari Paz Fuset-Cabanes
  • GRUPO ARIAM
Original

Abstract

Objective

To analyse the influence on the prognosis of intensive care unit (ICU) patients with acute myocardial infarction (AMI): prognostic index score, Killip class, AMI site, thrombolysis and other variables that might improve prognostic capacity and functioning of the APACHE-II index.

Design

Cohort study using prospectively gathered ARIAM project data.

Setting

ICUs from 129 Spanish hospitals.

Patients

ICU-admitted AMI patients in ARIAM database during 4-year period were retrospectively studied.

Measurements and main results

The sample comprised 6,458 patients, 76.8% males, age 64.97 ± 12.56 years, APACHE-II score 9.49 ± 7.03 points and ICU mortality 8.9%. Mortality was higher for females (p < 0.001), anterior AMI site (p < 0.001), previous AMI (p < 0.001), delay-to-hospital arrival >180 min (p = 0.003) and non-receipt of thrombolysis (p = 0.015). ICU mortality was related to age (p < 0.001) and APACHE-II score (p < 0.001). In multivariate analysis, it was related to APACHE-II (OR 1.16), age (OR 1.05), gender (OR 1.64), previous AMI (OR 1.57), anterior AMI (OR 2.05) and delay >180 min (OR 1.37). Killip class, gathered in 1,893 patients, was significantly associated with ICU mortality, and two predictive models were constructed for this group using multivariate analysis. Area under ROC curve was 0.94 in one (Killip class, age, gender, APACHE-II) versus 0.92 in the other (same variables without APACHE-II).

Conclusions

APACHE-II score and Killip class are useful for assessing the severity of patients with AMI and are complementary. Each can be used with a few commonly gathered clinical variables to construct prognostic models to assess severity. Their joint application yields a model with excellent discrimination capacity.

Keywords

Intensive care Myocardial infarction Severity of illness index Outcome and process assessment Mortality prediction Acute physiology and chronic health evaluation (APACHE) Killip class 

Supplementary material

134_2010_1832_MOESM1_ESM.doc (42 kb)
Supplementary material (DOC 41.5 kb)

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Copyright information

© Copyright jointly held by Springer and ESICM 2010

Authors and Affiliations

  • Juan Mercado-Martínez
    • 1
  • Ricardo Rivera-Fernández
    • 2
  • Eduardo Aguilar-Alonso
    • 3
  • Ángel García-Alcántara
    • 4
  • Andrés Estivill-Torrull
    • 1
  • Agustín Aranda-León
    • 1
  • María Consuelo Guia-Rambla
    • 5
  • Mari Paz Fuset-Cabanes
    • 6
  • GRUPO ARIAM
  1. 1.Santa Ana HospitalMotrilSpain
  2. 2.Hospital Universitario Puerta del MarCadizSpain
  3. 3.Infanta Margarita HospitalCabraSpain
  4. 4.Virgen de la Victoria HospitalMalagaSpain
  5. 5.Hospital Parc TauliSabadellSpain
  6. 6.Hospital La FeValenciaSpain

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