19 October-1 December 2020
The 51st Union World Conference On Lung Health


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Channel 1
OA-39-The Union/CDC late-breaker session on TB
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mic English
OA-39-The Union/CDC late-breaker session on TB
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15:00 - 15:05: Introduction

15:05 - 15:13: LB-2112-24-Diagnostic accuracy, clinical impact and antimicrobial resistance consequences of using trial-of-antibiotics for TB diagnosis: a randomised controlled trial in Malawi (ACT-TB study) Antibiotics, commonly used during tuberculosis (TB) diagnosis, have unknown diagnostic accuracy and effectiveness. This three-arm randomised trial in Malawi (azithromycin versus amoxycillin versus standard of care) showed modest, increased specificity with immediate antibiotics, but no other clinical benefit on missed TB diagnosis, hospitalisation or death. Trial-of-antibiotics, therefore, offers only limited benefit.

Titus Divala

15:13 - 15:21: LB-2087-24-Xpert performance evaluation for linkage to TB care (XPEL TB): a cluster randomised trial An ultra-pragmatic cluster randomised trial was conducted to evaluate the effectiveness of a streamlined tuberculosis (TB) diagnostic strategy, centred around onsite Xpert testing at 20 health centres in Uganda. This intervention increased 14-day TB treatment initiation by 56% and improved quality metrics along the entire TB diagnostic evaluation cascade of care.

Achilles Katamba

15:21 - 15:29: LB-2110-24-Comparable diagnostic performance of the T-SPOT TB test, using manual density gradient cell isolation, versus automated positive selection with the T-Cell TM Kit This prospective study aimed to compare the T-SPOT tuberculosis (TB) test, using peripheral blood mononuclear cells (PBMCs) isolated via manual density gradient separation (reference) performed between 0-8 hours after blood collection, versus automated positive selection with magnetic bead isolation with the T-Cell TM Kit performed between 0-55 hours post collection.

Shu-Hua Wang

15:29 - 15:37: LB-2070-24-Deep learning algorithm classifies active TB from normal - and other abnormal - chest X-rays with high accuracy on large scale dataset An artificial intelligence algorithm, trained and tested on a large scale dataset, can classify active tuberculosis (TB) from normal - and other abnormal - chest X-rays with high accuracy. It can be applied in TB screening programmes where a large amount of population are evaluated in a short period of time with limited radiologists.

Yuan Li

15:37 - 15:45: LB-2127-24-Tool to assess willingness to prescribe TB preventative therapy among healthcare workers in rural South Africa A tool to assess healthcare worker willingness to prescribe tuberculosis preventative therapy (TPT), in rural South Africa, was derived using exploratory factor and regression analyses. Such a tool is relevant as TPT initiation rates have decreased among people living with HIV despite South Africa's initial successful TPT roll out.

Amiya Ahmed

15:45 - 15:53: LB-2056-24-Shorter treatment for minimal TB in children: main findings from the SHINE trial SHINE was an open-label treatment shortening trial in children with minimal (non-severe and smear-negative), symptomatic drug-susceptible tuberculosis (TB). One thousand, two hundred and four children in Africa and India were randomised to four-month versus six-month treatment, using World Health Organization-recommended paediatric fixed-dose formulations, and followed for 18 months. Here we will be presenting the main trial results.

Eric Wobudeya

15:53 - 16:01: LB-2046-24-Temporal non-adherence and TB treatment outcomes? ‘O art of subtlety and secrecy!’ When adherence to anti-tuberculosis medication is considered, adherence levels are frequently reduced to binary categorisations (above 80/90% is ‘good’), ignoring their temporal subtleties and the intricacies of the adherence-outcome relationship. We sought to determine this relationship in detail, including the dynamics of adherence between the initiation and continuation phases.

Helen R. Stagg

16:01 - 16:20: Q&A

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