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Original Article

Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study

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Article: 1646024 | Received 18 Jan 2019, Accepted 17 Jun 2019, Published online: 05 Sep 2019

Figures & data

Box 1. ACF preparation, procedures, and coordination.

Table 1. Algorithms used for active case finding in Cambodia, by target group, between 25 August 2014 and 31 March 2016.

Table 2. Characteristics of clients tested for TB after a positive symptom screen in the community, between 25 August 2014 and 31 March 2016, in Cambodia.

Figure 1. Flowchart showing uptake of diagnostic algorithms during TB active case finding, between 25 August 2014 and 31 March 2016, in Cambodia.

TB: tuberculosis.
a Clients with presumptive TB were allocated in the ‘high-risk group’ if they had an additional ‘high-risk factor’, which included presumptive HIV infection (identification of opportunistic infections or self-reported previous HIV diagnosis), history of TB, and household contact with a TB patient. Clients with presumptive TB but without an additional risk-factor were grouped in the ‘moderate-risk group’.
Figure 1. Flowchart showing uptake of diagnostic algorithms during TB active case finding, between 25 August 2014 and 31 March 2016, in Cambodia.

Table 3. Number needed to test (after a positive symptom screen) to diagnose one TB case, by algorithm, between 25 August 2014 and 31 March 2016, in Cambodia.

Table 4. Predictors of TB diagnosis, during active case finding in the community, between 25 August 2014 and 31 March 2016, in Cambodia.

Table 5. Same-day treatment initiation and diagnostic lost to follow-up during active case finding in the community, between 25 August 2014 and 31 March 2016, in Cambodia.