Firefighters have twice as many cardiovascular deaths as police officers and 4 times as many as emergency medical responders. The etiology for this high rate of mortality remains unknown. The electrocardiogram (ECG) is a widely used tool to screen populations at risk, yet there are no available on-duty, high-resolution ECG recordings from firefighters.
We sought to evaluate the prevalence of clinical and ECG risk factors among on-duty professional firefighters during 12-lead ECG holter monitoring and exercise stress testing.
Firefighters were recruited from Surveying & Assessing Firefighters Fitness & Electrocardiogram (SAFFE) study. This descriptive study recruited firefighters from 7 firehouses across Upstate New York who completed on-duty 24-hour Holter ECG monitoring and a standard exercise stress test. All analyses were completed by a reviewer blinded to all clinical data.
A total of 112 firefighters (mean [SD] age, 44  years; mostly white men) completed the study. Although all firefighters were in normal sinus rhythm, more than half of them had at least 1 high-risk ECG risk factor present, including abnormal sympathetic tone (elevated heart rate, 54%), abnormal repolarization (wide QRS-T angle, 25%), myocardial scarring (fragmented QRS, 24%), and myocardial ischemia (ST depression, 24%). Most firefighters tolerated the treadmill exercise stress test well (metabolic equivalent tasks, 11.8 + 2.5]); however, almost one-third had abnormal results of stress tests that required further evaluation to rule out subclinical coronary artery disease.
Among on-duty professional firefighters, high-risk ECG markers of fatal cardiac events and abnormal stress test results that warrant further evaluation are prevalent. Annual physical checkups with routine 12-lead ECG can identify those who might benefit from preventive cardiovascular services.
Salah S. Al-Zaiti, PhD, RN, CRNP Assistant Professor, School of Nursing, University of Pittsburgh, Pennsylvania.
Mary G. Carey, PhD, RN, CNS, FAHA Associate Director, Clinical Nursing Research Center, Strong Memorial Hospital, and Associate Professor, School of Nursing, University of Rochester Medical Center, New York.
This study was supported by National Institutes of Health Grant 1 R21 NR011077.
This paper was presented at the 2010 Computing in Cardiology Conference, Belfast, United Kingdom. Some of the contents were released in a conference preceding of which the authors own the copyrights on that content.
The authors have no conflicts of interest to disclose.
Correspondence Mary G. Carey, PhD, RN, CNS, FAHA, Clinical Nursing Research Center, Strong Memorial Hospital, School of Nursing, University of Rochester Medical Center, 601 Elmwood Ave, Box 619-7, Rochester, NY 14642 (mary_carey@URMC.rochester.edu).