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The purpose of this study was to explore the prevalence, severity, and factors associated with multidimensional fatigue in Chinese patients with newly diagnosed meningiomas. This cross-sectional study included 120 Chinese meningioma patients. Data were collected before surgery, including demographic, clinical, psychological, and sleep characteristics, as well as fatigue scores based on completion of the Multidimensional Fatigue Inventory (MFI-20). Mann–Whitney U tests, Kruskal–Wallis H tests, Spearman correlation and multiple linear regression were used to analyze the data. The results showed there was a high prevalence of severe fatigue for each dimension: general fatigue (33.3%), physical fatigue (27.5%), reduced activity (28.3%), reduced motivation (12.5%), mental fatigue (11.7%), and total fatigue (23.3%). Headache and anxiety were found to be associated with general fatigue. Depression was related with physical fatigue. The Karnofsky Performance Status (KPS) score and depression were associated with reduced activity. Depression and the Epworth Sleepiness Scale (ESS) score were correlated with reduced motivation, while the KPS score and anxiety were associated with mental fatigue. Importantly, comorbidity, the KPS score, headache, depression, sleep disturbances, and the ESS score remained strong correlates of total fatigue. Our findings indicate that newly diagnosed meningioma patients are affected by multidimensional fatigue. For patients with risk factors of fatigue, targeted interventions are advised to decrease fatigue and improve HRQoL. [ABSTRACT FROM AUTHOR]

Background. Pituitary adenomas (PAs) refers to a group of benign tumors that develop in the pituitary gland and are often characterized by fatigue. However, fatigue has not been documented in any Chinese research involving people with primary PA. The study sought to examine the prevalence, predictors, and correlation of fatigue with the quality of life (QoL) among PA patients in China. Methods. In total, 203 primary PA patients were included in this cross-sectional study. A series of questionnaires were administered, including the Multidimensional Fatigue Inventory (MFI), M. D. Anderson Symptom Inventory Brain Tumor (MDASI-BT), Short-Form 36 Health Survey (SF-36), Pittsburgh Sleep Quality Index (PSQI), and the Hospital Anxiety and Depression Scale (HADS). Data analysis was accomplished by Pearson or Spearman correlations, linear regression, and simple path analysis. Results. Severe fatigue prior to the initial diagnosis and preparation for surgery affected 50% of PA patients. Depression, sleep disturbance, and MDASI-BT symptom total scores were independently able to predict patient fatigue. Sleep disturbance mediates the influence of depression on fatigue (IE sleep = 0.296, 95% CI: LB = 0.148 to UB = 0.471). Conclusions. Chinese patients with primary PA often report experiencing fatigue. Depression and poor sleep quality were shown to be significant contributors to PA patients' fatigue. Depression affects PA patients' fatigue directly or indirectly. Medical professionals should take a proactive approach to PA patients suffering from fatigue before initial diagnosis and preoperative preparation to determine necessary interventions early, thus reducing fatigue and ultimately enhancing their QoL. [ABSTRACT FROM AUTHOR]

Background: Stigma, besides aggravating the damage caused by the disease, may also lead to unhealthy characteristics in patients and unhealthy situations in society. Individuals with acromegaly disease may suffer from stigma concerns, and the associated factors remain largely unknown. Therefore, the present cross-sectional study aimed to investigate the levels of perceived stigma in patients with acromegaly and explore the associated factors. Methods: A total of 138 patients with acromegaly were evaluated for having stigma using five previously validated scales: (i) the Stigma Scale for Chronic Illness, (ii) the Hamilton Anxiety Scale, (iii) the Rosenberg Self-Esteem Scale, (iv) the Body Image Concern scale, and (v) the Acromegaly Quality of Life scale. The potential determinants of stigma were evaluated using the univariate statistical analysis. A multivariate linear regression model was adopted to assess the predictors of stigma in patients with acromegaly. Pearson's correlation analysis was performed to analyze the relationship between stigma and the quality of life of the patients. Results: Among the 138 respondents, 102 provided consent for participation.The evaluated patients exhibited critically high levels of perceived stigma. The multiple regression analysis revealed high BMI, serious body image concerns, inferiority complex personality, and critical levels of anxiety as the potential predictors of stigma in patients with acromegaly. The overall stigma and internalized stigma were significantly correlated with QoL in these patients. Conclusion: The patients with acromegaly exhibited critically high levels of perceived stigma, which led to psychological distress and disruptions in their daily lives. This finding highlights the importance of addressing the stigma concerns and the necessity for providing additional support to these patients in this regard during follow-up sessions. Further research should focus on developing intervention strategies to decrease the levels of perceived stigma in patients with acromegaly to promote their quality of life and for the psychosocial rehabilitation of these patients. [ABSTRACT FROM AUTHOR]

Purpose: Sleep disturbance is common in meningioma patients and may lead to disease aggravation and decreases health-related quality of life (HRQoL). However, the sleep quality of meningioma patients newly diagnosed and ready for surgery has not been well clarified in China. This study aims to evaluate the prevalence, correlates, and impact of sleep disturbance among Chinese meningioma patients.Methods: In this cross-sectional study, meningioma patients were recruited from the Affiliated Hospital of Nantong University from January 2020 to November 2020. A series of questionnaires were applied: the 0-10 Numerical Rating Scale (NRS), the Hospital Anxiety and Depression Scale (HADS), the Multidimensional Fatigue Inventory (MFI-20), the Epworth Sleepiness Scale (ESS), the Short-Form 36 (SF-36), the Pittsburgh Sleep Quality Index (PSQI). Independent samples t test, Mann-Whitney U test, chi-square analysis, Pearson/Spearman correlation, and binary logistic regression were used to analyze the data.Results: One hundred meningioma patients completed the questionnaires. Sleep disturbance affected 43% of the meningioma patients and was linked to many concomitant symptoms, such as headache, fatigue, anxiety, and depression. Binary logistic regression indicated that fatigue and headache were independently associated with sleep disturbance of meningioma patients. Meanwhile, severe sleep disturbance led to lower quality of life.Conclusions: These findings demonstrated that a considerable number of meningioma patients newly diagnosed and ready for surgery suffered from sleep disturbance, potentially contributing to impair HRQoL. Medical personnel should pay more attention to meningioma patients with sleep disturbance and take effective measures to improve sleep quality, with the ultimate goal to improve their HRQoL. [ABSTRACT FROM AUTHOR]

The Gout Impact Scale (GIS) is a disease-specific health-related quality of life (HR-QoL) measurement for patients with gout. This study aimed to investigate the quality of life in Chinese patients with gout and potential risk factors for poorer HR-QoL by GIS. Adults with gout from February 2017 to February 2019 were invited to complete a questionnaire containing the GIS, social demographic characteristics, clinical information and gout-specific questions. Pearson/Spearman correlation and linear regression were used to analyze the data. A total of 413 patients were included in the analysis (mean age, 51.85 years; 96.4% male). The mean (SD) score of GIS total was 56.79 ± 15.45. Worse gout-specific HR-QoL was associated with anxiety (p <.05), depression (p <.05) and fatigue (p <.05). The effectiveness and global satisfaction of Treatment Satisfaction Questionnaire for Medication (TSQM) were negatively related to each dimension of GIS. Age (B = −0.251, p =.013), fatigue (B = 1.850, p <.001) and depression (B = 9.068, p =.042) were independent predictors of GIS total score. Gout-specific HR-QoL is impaired by social demographic and clinical characteristics, highlighting the importance of psychological factors (fatigue and depression) and patient-reported outcomes (patients' satisfaction and confidence in gout treatment). These findings suggest that more studies should focus on disease-specific HR-QoL. [ABSTRACT FROM AUTHOR]

Purpose: To assess the acceptability, reliability, validity, and responsiveness of the Chinese Asthma Quality of Life Questionnaire (C-AQLQ) in a sample of Chinese asthma patients. Methods: The C-AQLQ and Short Form 36 Health Survey (SF-36) scales were administered to patients at baseline and 3 months later. Asthma severity condition and lung function were evaluated. Necessary data were gathered to assess the psychometric properties such as the feasibility, internal consistency, test-retest reliability, structural validity, discriminant validity, convergent validity, and responsiveness of the C-AQLQ. Results: One hundred and thirty-seven patients completed the investigation. The Cronbach's alpha coefficient for the total scale was 0.96. Factor analysis yielded five factors that generally corresponded to the five proposed subscales. Patients with mild asthma reported higher scores than patients with moderate/severe asthma on all subscales other than environmental stimuli. Lung function measurement and the asthma severity score correlated significantly with domains of the C-AQOL but with fewer domains of the SF-36. The questionnaire detected within-subject changes in patients' asthma status during follow-up. Conclusions: Results indicated preliminary support that the C-AQLQ is a reliable, valid, discriminating, and responsive measure of quality of life in Chinese asthma patients. It is more sensitive than the generic SF-36 in detecting differences in asthma severity. [ABSTRACT FROM AUTHOR]