Research Article - Biomedical Research (2017) Volume 28, Issue 4

Assessment of quality of life in Chinese patients with thyroid associated orbitopathy

Objective: To examine the quality of life (QOL) of Chinese people with thyroid-associated orbitopathy by employing TAO-QOL Questionnaire, to test compliance of questionnaire, and to evaluate the correlation between TAO-QOL and various classifications of TAO.

Design: Prospective and cross-sectional.

Participants: Total 182 patients with TAO and Grave’s disease enrolled in the present study.

Methodology: The original TAO-QOL was translated into Chinese language for the present study. In our study the findings were compared using various clinical severity grading systems such as CASs, modified NOSPECS score, VISA classification, EUGOGO classification, and Gorman diplopia scale.

Results: Clinical scores demonstrating inflammation and strabismus in study subjects with TAO are positively associated with overall and visual function-linked QOL (Spearman coefficient 0.03-0.38) p<0.05). Clinical measures related with appearance are positively associated with appearance-associated QOL (Spearman coefficient 0.25-0.26, p<0.05). The multivariate analysis of the present study revealed, motility disorder of VISA classification and age, soft tissue inflammation, motility disorder of modified NOSPECS exhibited positive correlation with overall and function-related QOL. Similarly, soft-tissue inflammation, proptosis, gender of modified NOSPECS, and appearance of VISA classification had correlation with appearance-related QOL. Moreover, rationality of TAO-QOL was verified adequately based on the findings of patient surveys and correlation between the subscales of TAO-QOL.

Conclusion: TAO-QOL displayed substantial compliance with various objective clinical measures of TAO. TAO-QOL was a lucid and convenient tool for quick assessment of QOL in daily outpatient wards, which is an easily translatable into several languages and extensively applicable to various inhabitants of different geographical regions.

Author(s): Lifang Han, Haimei Wang, Xia Li, Jing Li, Guizhen Lin, Jun Yan

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