Symptom clusters in patients presenting to the emergency department with possible acute coronary syndrome differ by sex, age, and discharge diagnosis

Rosenfeld, Anne G.; Knight, Elizabeth P.; Steffen, Alana; Burke, Larisa A.; Daya, Mohamud; DeVon, Holli A.

doi:10.1016/j.hrtlng.2015.05.008

Cited by 32 publications

(41 citation statements)

References 36 publications

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“…Another recent study that recruited patients from the emergency department found that women with an acute CHD event were likely to present without chest pain (Rosenfeld et al, 2015). Awareness of these prodromal and acute non-chest symptoms is critical for all clinicians.…”

Section: Discussionmentioning

confidence: 99%

Using the McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey to Predict the Occurrence of Short-Term Coronary Heart Disease Events in Women

McSweeney

Cleves

Fischer

et al. 2017

Women's Health Issues

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Background Few instruments capture symptoms that predict cardiac events in the short-term. Aims To examine the ability of the McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey to predict acute cardiac events within three months of administration and to identify the prodromal symptoms most associated with short-term risk in women without known coronary heart disease. Methods The McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey was administered to 1097 women referred to a cardiologist for initial coronary heart disease evaluation. Logistic regression models were used to examine prodromal symptoms individually and in combination to identify the subset of symptoms most predictive of an event within three months. Results Fifty-one women had an early cardiac event. In bivariate analyses, four of 30 prodromal symptoms were significantly associated with event occurrence within 90 days. In adjusted analyses, women reporting arm pain/discomfort and unusual fatigue were more likely (OR=4.67; 95% CI=2.08, 10.48) to have a cardiac event than women reporting neither. Conclusions The McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey may assist in predicting short-term coronary heart disease events in women without known coronary heart disease.

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Section: Discussionmentioning

confidence: 99%

Using the McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey to Predict the Occurrence of Short-Term Coronary Heart Disease Events in Women

McSweeney

Cleves

Fischer

et al. 2017

Women's Health Issues

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“…Ryan et al (2006) were the first to apply cluster analysis to symptoms of acute coronary syndrome, identifying five clusters of acute myocardial infarction symptoms. Acute coronary syndrome continues to be the focus of study in the cardiovascular cluster analysis nursing literature with multiple publications in the current decade (McSweeney, Cleves, Zhao, Lefler, & Yang, 2010; Riegel et al, 2010; Rosenfeld et al, 2015). …”

Section: Cluster Analysismentioning

confidence: 99%

Cluster Analysis in Nursing Research: An Introduction, Historical Perspective, and Future Directions

et al. 2017

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The use of cluster analysis in the nursing literature is limited to the creation of classifications of homogeneous groups and the discovery of new relationships. As such, it is important to provide clarity regarding its use and potential. The purpose of this article is to provide an introduction to distance-based, partitioning-based, and model-based cluster analysis methods commonly utilized in the nursing literature, provide a brief historical overview on the use of cluster analysis in nursing literature, and provide suggestions for future research. An electronic search included three bibliographic databases, PubMed, CINAHL and Web of Science. Key terms were cluster analysis and nursing. The use of cluster analysis in the nursing literature is increasing and expanding. The increased use of cluster analysis in the nursing literature is positioning this statistical method to result in insights that have the potential to change clinical practice.

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“…The two primary approaches for optimizing ACS patient outcomes are to reduce treatment delay and to minimize total ischemic time, defined as time of symptom onset to reperfusion of culprit arteries (Hicks et al, 2015; O’Gara et al, 2013). ACS symptoms trigger patient care seeking behaviors and inform providers’ choice of diagnostic testing; yet symptoms are often ambiguous (Rosenfeld et al, 2015). If symptoms are neither identified nor recognized, patients may be at risk for increased prehospital delay, delayed diagnosis, and increased mortality and morbidity (Doggen et al, 2016; Fanaroff, Rymer, Goldstein, Simel, & Newby, 2015; Menees et al, 2013; O’Gara et al, 2013; Wu, Moser, Riegel, McKinley, & Doering, 2011).…”

Section: Introductionmentioning

confidence: 99%

Patient‐reported symptoms improve prediction of acute coronary syndrome in the emergency department

Zègre‐Hemsey

Burke

DeVon

2018

Research in Nursing & Health

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Early diagnosis is critical in the management of patients with acute coronary syndrome (ACS), particularly ST-elevation myocardial infarction (STEMI), because effective therapies are time-dependent. Aims of this secondary analysis were to determine: (i) the prognostic value of symptoms for an ACS diagnosis in conjunction with electrocardiographic (ECG) and troponin results; and (ii) if any of 13 symptoms were associated with prehospital delay in those presenting to the emergency department (ED) with potential ACS. Patients receiving a cardiac evaluation in the ED were eligible for the study. Thirteen patient-reported symptoms were assessed in triage. Prehospital delay time was calculated as the time from symptom onset until registration in the ED. A total of 1,064 patients were enrolled in five EDs. The sample was 62% male, 70% white, and had a mean age of 60.2 years. Of 474 participants diagnosed with ACS, 118 (25%) had STEMI; 251 (53%) had non-ST elevation myocardial infarction (NSTEMI); and 105 (22%) had unstable angina. Sweating (OR = 1.42 CI [1.01, 2.00]) and shoulder pain (OR = 1.64 CI [1.13, 2.38]) added to the predictive value of an ACS diagnosis when combined with ECG and troponin results. Shortness of breath (OR = 0.71 CI [0.50, 1.00]) and unusual fatigue (OR = 0.60 CI [0.42, 0.84]) were predictive of a non-ACS diagnosis. Sweating predicted shorter prehospital delay (HR = 1.35, CI [1.10, 1.67]); shortness of breath (HR = 0.73 CI [0.60, 0.89]) and unusual fatigue (HR = 0.72, CI [0.57, 0.90]) were associated with longer prehospital delay. Patient-reported symptoms are significantly associated with ACS diagnoses and prehospital delay. Sweating and shoulder pain combined with ECG signs of ischemia may improve the timely detection of ACS in the ED.

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Symptom clusters in patients presenting to the emergency department with possible acute coronary syndrome differ by sex, age, and discharge diagnosis

Cited by 32 publications

References 36 publications

Using the McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey to Predict the Occurrence of Short-Term Coronary Heart Disease Events in Women

Using the McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey to Predict the Occurrence of Short-Term Coronary Heart Disease Events in Women

Cluster Analysis in Nursing Research: An Introduction, Historical Perspective, and Future Directions

Patient‐reported symptoms improve prediction of acute coronary syndrome in the emergency department

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