Random glucose sampling as screening tool for diabetes among disadvantaged tuberculosis patients residing in urban slums in India. Issue 1 (11th March 2019)

• Record Type: Journal Article
• Authors: Gröschel, Matthias I.; Luz, Christian F.; Batra, Sonali; Ahuja, Sandeep; Batra, Shelly; Kranzer, Katharina; van der Werf, Tjip S.
• Is Part Of: ERJ open research. Volume 5:Issue 1(2019)
• Publication Date: 2019-03-11
• Subjects: Respiratory organs -- Diseases -- Periodicals; Respiration -- Periodicals; Respiration; Respiratory organs -- Diseases; Respiratory organs -- Diseases -- Treatment; Respiratory Tract Diseases; Electronic journals; Fulltext; Internet Resources; Periodicals; Periodical; 616.2005
• DOI: 10.1183/23120541.00025-2019
• Languages: English
• ISSNs: 2312-0541

Abstract

Noncommunicable diseases like diabetes are increasingly recognised as important risk factors for tuberculosis (TB) and poor treatment outcomes [1]. While the link between TB and diabetes was described many decades ago, several recent epidemiological studies and systematic reviews have confirmed the association of diabetes with a three-fold increased risk of developing TB [2]. Since 2011, the World Health Organization has recommended bidirectional screening of all TB patients for diabetes [3]. However, it is currently unclear at which point in treatment one should screen and which diagnostic tools should be used. Following the American Diabetes Association, diabetes is diagnosed by a fasting plasma glucose ≥7 mmol·L −1, a 2-h plasma glucose value ≥11.1 mmol·L −1 during the oral glucose tolerance test, glycated haemoglobin (HbA1C) ≥48 mmol·mol −1 or a random plasma glucose value ≥11.1 mmol·L −1 in patients with classic symptoms of hyperglycaemia [4]. The Concurrent Tuberculosis and Diabetes Mellitus (TANDEM) consortium recently suggested a simplified two-step diagnostic algorithm where all patients with random plasma glucose levels >6.1 mmol·L −1 receive point-of-care HbA1C testing [4]. With laboratory-based HbA1C as the gold standard, this two-step combination resulted in a sensitivity and specificity of >90% to detect diabetes. Here, we evaluate the feasibility of diabetes screening by random glucose sampling among disadvantaged TB patients residing in urban slums in New Delhi, India. Recently, a two-step diagnostic algorithm to diagnose diabetes among TB patients was proposed comprising random glucose and point-of-care HbA1c. This study evaluates the first part of this algorithm among disadvantaged TB patients. http://ow.ly/UI7d30nK1UN