Literature DB >> 17182133

Patient-dependent variables affecting treatment and prediction of acute coronary syndrome are age-related. A study performed in Israel.

Oleg Gorelik1, Dorit Almoznino-Sarafian, Israel Yarovoi, Irena Alon, Miriam Shteinshnaider, Irma Tzur, David Modai, Natan Cohen.   

Abstract

BACKGROUND: Acute coronary syndrome (ACS) prevails in older patients and is associated with higher morbidity and mortality. Little is known about patient-related variables that may affect course and treatment of ACS in older vs. younger with acute chest pain.
METHODS: Situational, circumstantial, and other patient-related variables were assessed in 1000 unselected consecutive older (> or =70 years) and younger (<70 years) patients admitted with chest pain and possible ACS.
RESULTS: In 182 older vs. 818 younger patients, prevalence of females, those not speaking the local language, living alone, lower education level, non-smokers, diabetes, hypertension, preexisting coronary artery disease, and attempting some form of self-treatment before seeking medical help were significantly greater (P<0.001). Interval from chest pain onset to emergency department arrival was longer (P=0.05), and a higher proportion of the older considered hospitalization mandatory, suspecting ACS (P<0.001). ACS eventually developed in 19.1% of younger and 39% of older patients (P<0.001). On multivariate analysis, most predictive of ACS in the younger group were: preexisting coronary artery disease (OR 5.27; 95% CI 3.44-8.07, P<0.001), current smoking (OR 1.78; 95% CI 1.16-2.75, P=0.002), male sex (OR 1.57; 95% CI 1.0-2.59, P=0.07), and older age (OR 1.25; 95% CI 1.11-1.42, P=0.005). In the older group, these were: not speaking the local language (OR 2.39; 95% CI 1.19-4.79, P=0.005), preexisting coronary artery disease (OR 1.95; 95% CI 1.0-3.87, P=0.026), direct emergency department arrival (OR 1.9; 95% CI 1.0-3.77, P=0.066), and diabetes (OR 1.84; 95% CI 1.0-3.56, P=0.079).
CONCLUSIONS: We defined age-associated differences in patient-related variables that may predict ACS and affect treatment negatively. These variables might improve risk stratification upon hospitalization.

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Year:  2006        PMID: 17182133     DOI: 10.1016/j.ijcard.2006.10.027

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  2 in total

1.  Classifying subgroups of patients with symptoms of acute coronary syndromes: A cluster analysis.

Authors:  Holli A DeVon; Catherine J Ryan; Sally H Rankin; Bruce A Cooper
Journal:  Res Nurs Health       Date:  2010-10       Impact factor: 2.228

2.  Coronary heart disease in primary care: accuracy of medical history and physical findings in patients with chest pain--a study protocol for a systematic review with individual patient data.

Authors:  Jörg Haasenritter; Marc Aerts; Stefan Bösner; Frank Buntinx; Bernard Burnand; Lilli Herzig; J André Knottnerus; Girma Minalu; Staffan Nilsson; Walter Renier; Carol Sox; Harold Sox; Norbert Donner-Banzhoff
Journal:  BMC Fam Pract       Date:  2012-08-09       Impact factor: 2.497

  2 in total

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