Diagnostic and prognostic utility of urine LF-LAM assay for tuberculosis detection in advanced HIV
DOI:
https://doi.org/10.61529/idjp.v34i1.368Abstract
Background: The diagnostic tests available for TB are very accurate but samples are yield dependent. WHO recommends the use of LF LAM for diagnosis of active TB in patients with advanced HIV disease.
Material and Methods: This cross-sectional validity study was conducted at the Infectious Diseases Department of the Pakistan Institute of Medical Sciences, a large public-sector tertiary care hospital in Pakistan, from October to December 2024. A total of 113 patients with advanced HIV disease were enrolled in this study. The patients underwent Xpert MTB Ultra and LF LAM. These patients were followed for 8 weeks to assess survival.
Results: There were 99(87.6%) males and 14(12.4%) females of total 113 patients. The number of patients who survived and those who did not survive at 8 weeks was 88(77.9%), and 25 (22.1%) respectively. The LF LAM was found to have sensitivity (76.1%), Specificity (86.1%), PPV (87.27%), NPV (74.13%), and LR+ (5.42). The Discion tree analysis showed that positive LF LAM leads to the probability of 76.3% survival. The age (OR 0.946; 95%CI 0.905-0.978; p=0.012), Xpert MTB Ultra (OR 14.288; 95%CI 2.24-91.05; p=0.005), TB LAM (OR 0.416;95% CI 0.034-0.842; p=0.030) were found to be significant predictors of survival at 8 weeks.
Conclusion: LF LAM is a promising diagnostic strategy with good prognostic value in patients with HIV/TB coinfection.
Keywords: Diagnostic accuracy, Decision tree, LF LAM, Xpert MTB ultra
References
Khan S, Abbas W. HIV-1 in Pakistan: Where we stand? Where will we go? J Pak Med Assoc. 2017; 67(11): 1730–3. Available from: https://www.ncbi.nlm.nih.gov/pub med/29171569
Scott L, da Silva P, Boehme CC, Stevens W, Gilpin CM. Diagnosis of opportunistic infections: HIV co-infections - tuberculosis. Curr Opin HIV AIDS. 2017; 12(2): 129–38. DOI: https://doi.org/10.1097/coh.0000000000000345
Bayabil S, Seyoum A. Joint modeling in detecting predictors of CD4 cell count and status of tuberculosis among people living with HIV/AIDS under HAART at Felege Hiwot Teaching and Specialized Hospital, North-West Ethiopia. HIV AIDS (Auckl). 2021; 13: 527–37. DOI: https://doi.org/10.2147/hiv.s307069
Liu D, Gu L, Zhang R, Liu L, Shen Y, Shao Y, et al. Utility of urine lipoarabinomannan (LAM) in diagnosing mycobacteria infection among hospitalized HIV-positive patients. Int J Infect Dis. 2022; 118: 65–70. DOI: https://doi.org/10.1016/j.ijid.2022.02.046
Amin AG, De P, Graham B, Calderon RI, Franke MF, Chatterjee D. Urine lipoarabinomannan in HIV uninfected, smear-negative, symptomatic TB patients: effective sample pretreatment for a sensitive immunoassay and mass spectrometry. Sci Rep. 123AD; 11: 2922. DOI: https://doi.org/10.1038/s41598-021-82445-4
Åhsberg J, Puplampu P, Kwashie A, Commey JO, Ganu VJ, Omari MA, et al. Point-of-care urine lipoarabinomannan testing to guide tuberculosis treatment among severely ill inpatients with human immunodeficiency virus in real-world practice: A multicenter stepped wedge cluster-randomized trial from Ghana. Clin Infect Dis. 2023; 77 (8); 1185-93. DOI: https://doi.org/10.1093/cid/ciad316
Lateral flow urine lipoarabinomannan assay (LF-LAM) for the diagnosis of active tuberculosis in people living with HIV. Policy update 2019. Available from: https://iris.who.int/bitstream/handle/10665/329479/9789241550604-eng.pdf?sequence=1
Broger T, Koeppel L, Huerga H, Miller P, Gupta-Wright A, Blanc FX, et al. Diagnostic yield of urine lipoarabinomannan and sputum tuberculosis tests in people living with HIV: A systematic review and meta-analysis of individual participant data. Lancet Glob Health. 2023; 11(6): e903–16. Available from: http://www.thelancet.com/article/S2214109X23001353/fulltext
Shah M, Ssengooba W, Armstrong D, Nakiyingi L, Holshouser M, Ellner JJ, et al. Comparative performance of urinary lipoarabinomannan assays and Xpert MTB/RIF in HIV-infected individuals. AIDS. 2014; 28(9): 1307–14. DOI: https://doi.org/10.1097/qad.0000000000000264
Kebede W, Abebe G, Gudina EK, Van Rie A. The value of lateral flow urine lipoarabinomannan assay and empirical treatment in Xpert MTB/RIF ultra-negative patients with presumptive TB: A prospective cohort study. Sci Rep. 2021; 11(1): 24428. DOI: https://doi.org/10.1038/s41598-021-04090-1
Fekadu G, Wang Y, You JHS. Standard diagnostics with and without urine-based lipoarabinomannan testing for tuberculosis disease in HIV-infected patients in a high-burden setting-A cost-effectiveness analysis. PLoS One. 2023; 18(7): e0288605. DOI: https://doi.org/10.1371/journal.pone.0288605
Gupta-Wright A, Peters JA, Flach C, Lawn SD. Detection of lipoarabinomannan (LAM) in urine is an independent predictor of mortality risk in patients receiving treatment for HIV-associated tuberculosis in sub-Saharan Africa: a systematic review and meta-analysis. BMC Med. 2016; 14(1): 53. DOI: https://doi.org/10.1186/s12916-016-0603-9
Gupta-Wright A, Corbett EL, Wilson D, Van Oosterhout JJ, Dheda K, Huerga H, et al. Risk score for predicting mortality including urine lipoarabinomannan detection in hospital in patients with HIV-associated tuberculosis in sub-Saharan Africa: Derivation and external validation cohort study. PLoS Med. 2019; 16(4): e1002776. DOI: https://doi.org/10.1371/journal.pmed.1002776
Mangu C, Cossa M, Ndege R, Khosa C, Leukes V, de la Torre-Pérez L, et al. Expanding Xpert MTB/RIF Ultra® and LF-LAM testing for diagnosis of tuberculosis among HIV-positive adults admitted to hospitals in Tanzania and Mozambique: A randomized controlled trial (the EXULTANT trial). BMC Infect Dis. 2024; 24(1): 831. DOI: https://doi.org/10.1186/s12879-024-09651-z
Sadiq H, Akhtar N, Virk S, Virk KA, Zafar A, Meraj L. CD 4 count stratification and its accuracy in predicting the HIV-Tuberculosis co-infection. Inf Dis J Pak. 2024; 33(2): 63–8. DOI: https://doi.org/10.61529/idjp.v33i2.296
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Abeer Zafar, Nasim Akhtar, Sana Tahir virk, Kazim Abbas Virk, Malik muhammad Umair, Hina Saghir

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.