Français
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Circulation 2010-Jul

Comprehensive peroxidase-based hematologic profiling for the prediction of 1-year myocardial infarction and death.

Seuls les utilisateurs enregistrés peuvent traduire des articles
Se connecter S'inscrire
Le lien est enregistré dans le presse-papiers
Marie-Luise Brennan
Anupama Reddy
W H Wilson Tang
Yuping Wu
Danielle M Brennan
Amy Hsu
Shirley A Mann
Peter L Hammer
Stanley L Hazen

Mots clés

Abstrait

BACKGROUND

Recognition of biological patterns holds promise for improved identification of patients at risk for myocardial infarction (MI) and death. We hypothesized that identifying high- and low-risk patterns from a broad spectrum of hematologic phenotypic data related to leukocyte peroxidase-, erythrocyte- and platelet-related parameters may better predict future cardiovascular risk in stable cardiac patients than traditional risk factors alone.

RESULTS

Stable patients (n=7369) undergoing elective cardiac evaluation at a tertiary care center were enrolled. A model (PEROX) that predicts incident 1-year death and MI was derived from standard clinical data combined with information captured by a high-throughput peroxidase-based hematology analyzer during performance of a complete blood count with differential. The PEROX model was developed using a random sampling of subjects in a derivation cohort (n=5895) and then independently validated in a nonoverlapping validation cohort (n=1474). Twenty-three high-risk (observed in > or =10% of subjects with events) and 24 low-risk (observed in > or =10% of subjects without events) patterns were identified in the derivation cohort. Erythrocyte- and leukocyte (peroxidase)-derived parameters dominated the variables predicting risk of death, whereas variables in MI risk patterns included traditional cardiac risk factors and elements from all blood cell lineages. Within the validation cohort, the PEROX model demonstrated superior prognostic accuracy (78%) for 1-year risk of death or MI compared with traditional risk factors alone (67%). Furthermore, the PEROX model reclassified 23.5% (P<0.001) of patients to different risk categories for death/MI when added to traditional risk factors.

CONCLUSIONS

Comprehensive pattern recognition of high- and low-risk clusters of clinical, biochemical, and hematologic parameters provided incremental prognostic value in stable patients having elective diagnostic cardiac catheterization for 1-year risks of death and MI.

Rejoignez notre
page facebook

La base de données d'herbes médicinales la plus complète soutenue par la science

  • Fonctionne en 55 langues
  • Cures à base de plantes soutenues par la science
  • Reconnaissance des herbes par image
  • Carte GPS interactive - étiquetez les herbes sur place (à venir)
  • Lisez les publications scientifiques liées à votre recherche
  • Rechercher les herbes médicinales par leurs effets
  • Organisez vos intérêts et restez à jour avec les nouvelles recherches, essais cliniques et brevets

Tapez un symptôme ou une maladie et lisez des informations sur les herbes qui pourraient aider, tapez une herbe et voyez les maladies et symptômes contre lesquels elle est utilisée.
* Toutes les informations sont basées sur des recherches scientifiques publiées

Google Play badgeApp Store badge