Literature DB >> 22409097

Identifying symptom profiles of depression and anxiety in patients with an acute coronary syndrome using latent class and latent transition analysis.

Mayra Tisminetzky1, Bethany C Bray, Ruben Miozzo, Onesky Aupont, Thomas J McLaughlin.   

Abstract

OBJECTIVE: To identify symptom profiles of depression and anxiety in patients with an acute coronary syndrome (ACS), to examine changes in symptom profiles over time, and finally, to examine the effects of age and sex on patients' symptom profiles.
METHODS: One hundred ACS patients with mild to severe symptoms of depression and/or anxiety at 1 month post-hospital discharge were enrolled in a randomized trial of cognitive behavioral therapy. Latent class and latent transition analyses were used to identify symptom profiles and describe change over the time in profile membership.
RESULTS: A two-class solution was selected to describe depression and anxiety symptom profiles. Class I (76% of patients at baseline) was labeled "depression and some anxiety symptoms." Class II (24% of patients at baseline) was labeled "anxiety and some depression symptoms." Approximately 25% of patients in the treatment condition transitioned from the depression and some anxiety symptoms class to the anxiety and some depression symptoms class at follow-up compared to 10% of patients in the control condition at follow-up; nearly 50% of patients in the control condition showed worsening of symptoms as compared to 28% in the treatment condition. Results suggested age differences in the probabilities of transitioning between the classes; older patients were more likely to continue having depression and some anxiety symptoms at the time of follow-up.
CONCLUSIONS: Identifying symptom profiles of depression and anxiety in patients with an ACS may improve diagnostic practices and help to design tailored interventions.

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Year:  2011        PMID: 22409097      PMCID: PMC3712857          DOI: 10.2190/PM.42.2.g

Source DB:  PubMed          Journal:  Int J Psychiatry Med        ISSN: 0091-2174            Impact factor:   1.210


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