Exploring Psychoneurological Symptom Clusters in Acute Stroke Patients: A Latent Class Analysis

Purpose: To identify latent classes of acute stroke patients with distinct experiences with the symptom clusters of depression, anxiety, fatigue, sleep disturbance, and pain symptoms and assess, if the selected variables determine a symptom-cluster experience in acute stroke patients. Participants and Methods: A sample of 690 participants were collected from July 2020 to December 2020 in a cross-sectional descriptive study. Latent class analysis was conducted to distinguish different clusters of acute stroke participants who experienced five patient-reported symptoms. Furthermore, multinomial logistic regression was selected to verify the influencing indicators of each subgroup, with selected socio-demographic variables, clinical characteristics, self-efficacy, and perceived social support as independent variables and the different latent classes as the dependent variable. Results: Three latent classes, named all high symptom, high psychological disorder, and all low symptom, were identified, accounting for 9.6%, 26.3%, and 64.1% of symptom clusters, respectively. Patients in the all high symptom and high psychological disorder classes reported significantly lower quality of life (F=40.21, p <0.05). Female gender, younger age, higher National Institutes of Health Stroke Scale scores, and lower self-efficacy and perceived social support were risk factors associated with the high psychological disorder class. Younger patients with lower self-efficacy and perceived social support were more likely to be in the all high symptom class. Conclusion: This study identified latent classes of acute stroke patients that can be used in predicting symptom-cluster experiences following a stroke. Also, the ability to characterize subgroups of patients with distinct symptom experiences helps identify high-risk patients. Focusing on symptom clusters in clinical practice can inspire us to create effective targeted interventions for subgroups of stroke patients suffering from the same symptom cluster.

Automated summary

This study identified latent classes of acute stroke patients with distinct experiences of symptom clusters. Three classes, including all high symptom, high psychological disorder, and all low symptom, were identified. The results can help identify high-risk patients and create effective targeted interventions for stroke patients with different symptom clusters.