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DOI 10.5588/ijtld.21.0013

Медицинская библиотека · The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2021

Evaluation of point-of-care algorithms to detect diabetes during screening for latent TB infection.

Largen A, Ayala A, Khurana R, Katz D J, Venkatappa T K, Brostrom R

СтатьяПоддержка службы здравоохранения СШАПеревод пока не подготовлен

Аннотация

BACKGROUND

Individuals with both diabetes mellitus (DM) and TB infection are at higher risk of progressing to TB disease.

OBJECTIVE

To determine DM prevalence in populations at high risk for latent TB infection (LTBI) and to identify the most accurate point-of-care (POC) method for DM screening.

METHODS

Adults aged ≥25 years were recruited at health department clinics in Hawaii and Arizona, USA, and screened for LTBI and DM. Screening methods for DM included self-report, random blood glucose (RBG), and POC hemoglobin A1c (HbA1c). Using HbA1c ≥6.5% or self-reported history as the gold standard for DM, we compared test strategies to determine the most accurate method while keeping test costs low.

RESULTS

Of 472 participants, 13% had DM and half were unaware of their diagnosis. Limiting HbA1c testing to ages ≥30 years with a RBG level of 120-180 mg/dL helped identify most participants with DM (sensitivity 85%, specificity 99%) at an average test cost of US$2.56 per person compared to US$9.56 per person using HbA1c for all patients.

CONCLUSION

Self-report was insufficient to determine DM status because many participants were previously undiagnosed. Using a combination of POC RBG and HbA1c provided an inexpensive option to assess DM status in persons at high risk for LTBI.

Для цитирования: Largen A, Ayala A, Khurana R, Katz D J, Venkatappa T K, Brostrom R. Evaluation of point-of-care algorithms to detect diabetes during screening for latent TB infection.. The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease. 2021. DOI: 10.5588/ijtld.21.0013.

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