Severe Pain Profiles And Associated Sociodemographic And Clinical Characteristics In Individuals With Sickle Cell Disease

CLINICAL JOURNAL OF PAIN(2021)

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摘要
Objective: The aim of this study was to identify classes of individuals with sickle cell disease (SCD) who share distinct severe pain profiles and evaluate differences in demographic, clinical, and psychosocial characteristics between classes. Methods: This exploratory, cross-sectional study used data collected for the SCD Implementation Consortium Research Registry at Duke University. Using Adult Sickle Cell Quality of Life-Measurement System pain-item data from 291 adults with SCD, latent class analysis was used to determine classes of individuals sharing distinct severe pain profiles. Bivariate analyses and logistic regression models were used to assess the relationships between pain profile classes and demographic, clinical, and psychosocial characteristics. Results: Three classes sharing distinct severe pain profiles were identified: Low Frequency and Impact class (n=73), Moderate Frequency and Impact class (n=94), and High Frequency and Impact class (n=124). When compared with the Low Frequency and Impact class and controlling for age and sex, individuals in the Moderate Frequency and Impact class were more likely to: be female (P=0.031) and unemployed (P=0.013); report worse sleep (P=0.005) and social functioning (P=0.005); have less emotional distress (P=0.004); describe pain as "sore" (P=0.002); and have previous SCD-related lung complications (P=0.016). When compared with the Low Frequency and Impact class, individuals in the High Frequency and Impact class: had worse social functioning (P<0.001) and previous SCD-related lung complications (P=0.006); described pain as "sore" (P<0.001); and were taking pain medication daily for SCD (P=0.001). Discussion: Severe pain experiences in SCD are complex; however, there are subgroups of people who report similar experiences of severe pain.
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关键词
pain, sickle cell disease, patient-reported outcomes, latent class analysis, quality of life
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