U.S. flag An official website of the United States government.
Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

i

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

Supporting Files
File Language:
English


Details

  • Alternative Title:
    Int J Tuberc Lung Dis
  • Personal Author:
  • Description:
    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.

  • Subjects:
  • Keywords:
  • Source:
    Int J Tuberc Lung Dis. 25(7):547-553
  • Pubmed ID:
    34183099
  • Pubmed Central ID:
    PMC8609420
  • Document Type:
  • Funding:
  • Place as Subject:
  • Volume:
    25
  • Issue:
    7
  • Collection(s):
  • Main Document Checksum:
    urn:sha256:f9b2635075e90b50b9ebda0512f59a63e1830c4c2f1d1c63450acbb290741b5b
  • Download URL:
  • File Type:
    Filetype[PDF - 270.60 KB ]
File Language:
English
ON THIS PAGE
 Was this page helpful?
 Found an issue?
Send us an email at:
CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners.

As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.