Evaluation of Prevalence of Weak D Antigen among Rhesus-Negative Patients in Tertiary Care Hospitals in Bangladesh: A Multicenter Study

Global Journal of Transfusion Medicine

article

Afroz, Tamanna¹  Rahman, Manjuma²  Naznin, Bepasha³  Islam, Ashadul⁴  Saleh, Abu Jafar Mohammed¹ 

[1] Department of Transfusion Medicine, Evercare Hospital;Department of Transfusion Medicine, Square Hospitals Limited;Department of Transfusion Medicine, Asgar Ali Hospital;Department of Transfusion Medicine and Additional Registrar, Bangabandhu Sheikh Mujib Medical University

关键词: Chemical intolerance;    comorbid disease;    idiopathic environmental intolerance;    latent class;    multiple chemical sensitivity;    Quick Environmental Exposure and Sensitivity Inventory;   

DOI  :  10.4103/ed.ed_18_21

学科分类：社会科学、人文和艺术（综合）

来源: Wolters Kluwer Medknow Publications

【 摘 要 】

Background:  Chemical intolerance (CI) is characterized by multisystem symptoms initiated by a one-time high-dose or a persistent low-dose exposure to environmental toxicants. Prior studies have investigated symptom clusters rather than defined comorbid disease clusters. We use a latent class modeling approach to determine the number and type of comorbid disease clusters associated with CI. Methods:  Two hundred respondents with and without CI were recruited to complete the Quick Environmental Exposure and Sensitivity Inventory (QEESI), and a 17-item comorbid disease checklist. A logistic regression model was used to predict the odds of comorbid disease conditions between groups. A latent class analysis was used to inspect the pattern of dichotomous item responses from the 17 comorbid diseases. Results:  Those with the highest QEESI scores had significantly greater probability of each comorbid disease compared to the lowest scoring individuals (P < 0.0001). Three latent class disease clusters were found. Class 1 (17% of the sample) was characterized by a cluster consisting of irritable bowel syndrome (IBS), arthritis, depression, anxiety, fibromyalgia, and chronic fatigue. The second class (53% of the sample) was characterized by a low probability of any of the co-morbid diseases. The third class (30% of the sample) was characterized only by allergy. Discussion:  We have demonstrated that several salient comorbid diseases form a unique statistical cluster among a subset of individuals with CI. Understanding these disease clusters may help physicians and other health care workers to gain a better understanding of individuals with CI. As such, assessing their patients for CI may help identify the salient initiators and triggers of their CI symptoms—therefore guide potential treatment efforts.

【 授权许可】

CC BY-NC-SA