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. 2024 Jun 12;19(9):783-793.
doi: 10.2217/fmb-2024-0025. Epub 2024 Apr 9.

Novel automated AIMLAM for diagnosis of Mycobacterium tuberculosis

Liang Ruixia  1 , Li Jiankang  1 , Shi Hongmei  1 , Wu Han  1 , Zhao Chang  1
Affiliations

Novel automated AIMLAM for diagnosis of Mycobacterium tuberculosis

Liang Ruixia et al. Future Microbiol. .

Abstract

Aim: A rapid and precise diagnostic method is crucial for timely intervention and management of tuberculosis. The present study compared the diagnostic accuracy of a novel lipoarabinomannan (LAM) antigen test, AIMLAM, for tuberculosis in urine samples. Methodology: The study subjected 106 TB suspects to smear microscopy, MGIT, GeneXpert and AIMLAM. Results: Among 106, smear microscopy identified 36 as positive (33%) (sensitivity; 70.93%, 95% CI (60.14-80.22%), while MGIT showed 38 positive (36.8%). GeneXpert detected 59 positives (sensitivity; 96.83, 95% CI (89.00-99.61%)). AIMLAM declared 61 as positive (57.5%) (sensitivity; 100.00, 95% CI (94.13-100.00%) and 45 as negative (42.5%). Conclusion: Overall, AIMLAM demonstrated better diagnostic accuracy than GeneXpert Assay, smear microscopy and MGIT liquid culture in urine samples.

Keywords: AIMLAM; Mycobacterium tuberculosis; TB; lipoarabinomannan.

Plain language summary

This study describes a new way to detect tuberculosis, called AIMLAM. Unlike traditional methods that use sputum or blood, AIMLAM tests urine samples and bodily fluids. It is automated and uses easily accessible samples to identify a tuberculosis infection, so may be a convenient and noninvasive option for healthcare providers. The test shows promising results in terms of accuracy and sensitivity.

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Conflict of interest statement

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Figures

Figure 1.
Figure 1.
Flowchart methodology of AIMLAM samples processing and detection. The time required for each step has been provided. The maximum time needed for detection is 2 h and 40 min.
Figure 2.
Figure 2.
Study participants gender-wise and age groups. Light blue: number of samples, orange: percentage of samples. *M: Male. F: Female, G1, G2, G3, G4, G5 and G6 (age groups). G1 (age 1–16 years). G2 (age 16–30 years), G3 (age 31–45 years), G4 (age 46–60 years), G5 (age 61–75 years), G6 (age >75; years).
Figure 3.
Figure 3.
Positivity comparison of AIMLAM with other diagnostic procedures in different age groups. G1 (1–15 years), NR (not released). Total positivity has been shown in all groups. Blue: AIMLAM, orange: GeneXpert assay, light black: smear, yellow: MGIT culture, dark blue: culture NR (not released results). G1, G2, G3, G4, G5 and G6 (age groups). G1 (age 1–16 years). G2 (age 16–30 years), G3 (age 31–45 years), G4 (age 46–60 years), G5 (age 61–75 years), G6 (age >75 years).
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