Burden of latent tuberculosis infection among People living with HIV in Shanghai, China: A 4-year cohort study

Burden of latent tuberculosis infection among People living with HIV in Shanghai, China: A 4-year cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Burden of latent tuberculosis infection among People living with HIV in Shanghai, China: A 4-year cohort study Lixin Rao, Kaikan Gu, Yun Yang, Boxin Le, Zhengqi Zhang, Jing Chen, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8973880/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Mycobacterium tuberculosis / human immunodeficiency virus (TB/HIV) co-infection remains a significant global public health challenge. In areas with a lower incidence of TB and HIV, how to elevate screening efficiency while maintaining cost-effectiveness worth further exploration. This study aimed to provide a suitable algorism for TB prevention and intervention among people who live with HIV (PLHIV) in Shanghai based on a cohort study. Methods A 4-year cohort study was conducted from May 2019 to December 2024, enrolling PLHIV from two districts in Shanghai. Participants underwent baseline and annual follow-up assessments using interferon-gamma release assays (IGRA) and questionnaires. Demographic, clinical, and laboratory data were collected. Results Among 963 enrolled participants, 857 completed baseline assessments. The baseline TBI prevalence was 6.8% (58/857). Older age and higher CD4 + T-cell count were associated with TBI. During a mean follow-up of 788 days among 615 participants, the IGRA conversion rate was 1.75% per person-year. One case of active TB was diagnosed (incidence rate: 84.33 per 100,000 person-years), occurring in a participant with an indeterminate baseline IGRA result. Participants with indeterminate baseline results had a significantly higher risk of subsequent IGRA conversion or active TB compared to those with negative results. Conclusion Given the low prevalence of latent TB infection and active TB among PLHIV in Shanghai, universal preventive treatment is not optimally efficient. The high rate of indeterminate IGRA results at baseline requires focused clinical assessment. A targeted screening and preventive treatment strategy based on local epidemiology and resources should be developed to enhance TB prevention in this population. TB/HIV co-infection Tuberculosis Infection Screening algorithm IGRA conversion Figures Figure 1 Figure 2 Background Tuberculosis (TB) and acquired immune deficiency syndrome (AIDS) are both chronic infectious diseases caused respectively by Mycobacterium tuberculosis (MTB) and human immunodeficiency virus (HIV), whose correlation becomes a growing global public health concern. MTB is a typical opportunistic pathogen which usually under the control of human immune system presenting as tuberculosis infection (TBI) instead of active TB. Owing to impaired immune function, HIV-positive individuals are more susceptible of TBI and are at a constant risk of progressing to active TB through reactivation of TBI[ 1 ]. Co-infection of MTB/HIV will accelerate process of both diseases and increase the risk of severe case and death. According to World Health Organization (WHO)’s Global Tuberculosis Report, 5.8% of the TB patients and 12.2% of the TB death are HIV-related in 2024[ 2 ]. Meanwhile, TB is accounted for nearly one-fourth of AIDS-related death in 2023[ 3 ]. The severe situation of MTB/HIV co-infection hinders the achievement of “End TB” goal in 2035[ 2 , 4 ]. Globally speaking, the prevalence of TB/HIV co-infection varies depending on the very different distributions of two diseases. A meta-analysis estimates the prevalence of TB/HIV co-infection ranged from 2.93% to 72.34% in countries except China. [ 5 ] Compared to other countries, China has significantly lower burden of co-infection 0.9% (95% CI: 0.6%-1.4%) of TB patients co-infected with HIV[ 6 ], and the pooled prevalence of TB is 6.0% (95% CI: 4.0%-7.0%) among people who live with HIV (PLHIV) [ 7 ]. However, the burden of TB and HIV are still serious and the uneven distribution of both diseased increases the difficulty of prevention and control especially in low-HIV burden and medium-TB burden regions such as Shanghai. Following WHO’s recommendation, Shanghai has started to screen for HIV antigen among TB patients and to systematically screen for active TB PLHIV annually among all patients since 2012[ 8 ]. After more than ten years of practice, the inspection rate has significantly improved. However, the current measures seem to reach its limit on finding more active cases. In our previous study, only 0.08% TB patients are newly confirmed with HIV, and 0.21% of PLHIV under management are diagnosed with active TB in 2020[ 9 ]. As screening for active patient has decreasing yield, we have moved our focus forward on screening for infectious individuals and provide early intervention. The question in front of us now is how to enhance the screening efficiency while also taking cost-effectiveness into account. In this study, we try to acquire the prevalence of TBI among PLHIV in Shanghai and to build up a cohort to follow-up on the changes of TBI status and the development to TB disease, in order to explore a better algorithm to identify and prevent TBI and active TB cases. Methods Study design This is a cohort study design, including PLHIV under management in two districts of Shanghai, namely Jing’an and Baoshan district, from 2019.5.1 to 2024.12.31. These two districts were selected based on their relatively higher incidence of HIV case report. All patients were examined and treated at Shanghai Public Health Clinical Center (SPHCC), which is the only designated hospital for PLHIV in Shanghai. All participants were enrolled on the premise of fully understanding of the purpose and procedure of this study. Individuals with a previous history of TB (whether pulmonary tuberculosis, tuberculous pleurisy, or extraplumonary tuberculosis) within five years or had been underwent tuberculosis preventive treatment (TPT) within five years were excluded. We provided a standardized questionnaire and an interferon-gamma release assay (IGRA) for every participant at baseline and every follow-up visit unless the former IGRA test was positive. The questionnaires were developed specifically for this study (see supplementary file 1 and 2). Both baseline and follow-up questionnaires were recorded by trained interviewers including exposure history of active TB patients, susceptible symptoms of TB (cough, hemoptysis, fever, night sweat, and weight loss), weight and height and relative test results. QuantiFREON-TB Gold In-Tube (QFT-GIT; Cellestis, Carnegie, Australia) was used for IGRA. At least 5 ml of blood is needed for QFT-GIT. All tests were performed by qualified technicians in laboratory of SPHCC. Participant with a positive IGRA test excluding clinical evidence of active TB disease is deemed as TBI. All screening and diagnose processes followed the local standard of protocol. Other tests results, such as CD4 + lymphocyte count, HIV virus load, as well as other contagious disease which includes Hepatitis B, Hepatitis C, syphilis and pneumocystis pneumonia as well as tuberculosis diagnosis records were collected from hospital information system of SPHCC. Data collection and Statistical Analysis Professionals from Jingan and Baoshan district center for disease control and prevention (CDC) are responsible for the collection and quality control of baseline and follow-up questionnaires. Data were collected by Epidata (Version 3.1) and pre-processed by Microsoft Excel (Version 2010). Statistical analysis was performed by IBM SPSS Statistics (version 20.0) and R (version 4.5.2). A P-value less than 0.05 (two-tailed) was regarded as the level of significance. Logistic regression models were used to evaluate the association between MTB infection status and socio-demographic, clinical and laboratory characteristics. All factors were included into the multivariate linear regression using an enter procedure. Multiple categorical variables were included in the model as dummy variables. Paired T-test, Chi-square, Odds ratio (OR) and 95% confidence interval (CI) were calculated. Due to different enroll and ended follow-up time, we used person day and person year to evaluate follow-up period. And a sankey diagram was plotted to demonstrate the changes in the TB infection status of the study population. Ethnics approval The study protocol was approved by the Ethical Review Committee of Shanghai Municipal Center for Disease and Prevention (Approval number: 2019-12). All participants have provided signed informed consent prior to the investigation. Results In this study, a total of 963 HIV-positive participants were enrolled. A pilot trial was performed at May 2019 and the formal enrollment initiated at September 2019. The enrollment ceased at December 2021 and the follow-up continued till December 2024. Among those participants, 560 individuals (58.2%) were from Jinan district and 403 (41.8%) were from Baoshan district. After cross-checking with previous TB patients database, one participant was found to have been diagnosed with active TB in 2018, thus was excluded from this study according to the exclusion criteria. The inclusion diagram is displayed in Fig. 1 . Demographic and epidemiological characteristics of the participants at baseline Among participants enrolled, 857 completed all the required steps at baseline thus was included in further analysis. The median age of the participants was 42.2 years old, and 92.5% of them were male. Most of the participants are previous patients with an average diagnosis time of 4.5 years. A total of 58 individuals tested positive for IGRA, accounting for 6.8% of the whole cohort. All participants underwent systematic screening for active TB and none was diagnosed. Indeterminate (15, 1.8%) and negative (784, 91.5%) results are counted as TBI negative. Baseline demographic clinical and epidemiological characteristics are displayed in Table 1 . Age and CD4 + lymphocyte count are statistically significant factors in the logistic regression. Table 1 Logistic regression of demographic, clinical and epidemiological characteristics for the participants at baseline Variables All patients ( n = 857) TBI at baseline ( n = 58) P value Adjusted OR (95% CI) Gender 0.269 1.989 (0.588–6.722) male 793(92.5) 55(94.8) female 64(7.5) 3(5.2) Age Group 0.048 1.237 (1.002–1.528) 17–30 171(20.5) 8(12.5) 31–40 296(34.8) 17(30.4) 41–50 152(17.6) 11(19.6) 51–60 139(15.5) 16(26.8) ≥ 61 99(11.6) 6(10.7) Newly Diagnosed HIV-Positive(within 1 year) 0.169 0.346 (0.076–1.569) Yes 95(11.1) 2(3.4) No 762(88.9) 56(96.6) Body Mass Index 24(overweight) 250(29.2) 14(24.1) Suspicious Symptoms 0.971 0.986 (0.466–2.086) Positive 130(15.2) 9(15.5) Negative 727(84.8) 49(84.5) CD4 + lymphocyte count 0.018 0.453 (0.235–0.873) < 400 /µl 314(36.6) 13(22.4) ≥ 400/µl 543(63.4) 45(77.6) HIV virus load 0.418 1.365 (0.642–2.903) < 20 copies 170(19.8) 10(17.2) ≥ 20 copies 687(80.2) 48(82.8) HBV 0.168 2.497 (0.680–9.171) Positive 20(2.3) 3(5.2) Negative 837(97.7) 55(94.8) HCV 0.950 1.068 (0.133–8.567) Positive 19(2.2) 1(1.7) Negative 838(97.8) 57(98.3) Syphilis 0.129 0.282 (0.055–1.446) Positive 75(8.8) 2(3.4) Negative 782(91.2) 56(96.6) Other infectious diseases 0.471 1.567 (0.462–5.315) Positive 66(7.7) 4(6.9) Negative 791(92.3) 54(93.1) Changes of TBI status and immune function during the follow-up period By the end of the follow-up (December 31, 2024), a total of 615 individuals had completed at least one follow-up, with an average follow-up period of 788 days and a follow-up rate of 71.8%. According to the protocol, 554 of the 799 baseline IGRA negative participants have accepted annually IGRA test. There are 117 (21.1%) and 46 (8.3%) participants underwent the second and the third follow-up IGRA test respectively. Among all the participants, 21 turned positive. Most conversion was detected at the first follow-up test (17, 81.0%) and none positive conversion was detected at the third follow-up period. The average time interval is 466 days for the individuals who converted at first follow-up, 975 for those at second follow-up period, and 646 days for all converted participants. The follow-up positive conversion rate for IGRA was 1.75% per person year. Follow-up indeterminate result is not regarded as a positive outcome in this study. None of the baseline TBI individual developed to active TB, while one participant has been diagnosed with pulmonary TB, whose baseline IGRA result was indeterminate. It took 505 days from the first test of IGRA to the diagnosis of active TB, with an annualized adjusted incidence density of 84.33 per 100,000. And 3 participants died before the second IGRA test was taken. The change of TBI status is shown in Fig. 2 . Statistical significance of the changes of CD4 cell count, virus load and BMI between baseline and last follow-up test were detected (Table 2 ). The overall immune related status for all participants is improved, though the degree of improvement in the positive conversion group was only slightly lower than the non-positive conversion group and the difference was not statistically significant. Table 2 Changes of CD4 count, virus load and BMI between baseline and last follow-up Pair means standard deviation T P value CD4 count Baseline 501.67 172.96 -6.54 < 0.001 Last follow-up 548.65 Virus load Baseline 8760.4 8554.51 2.66 0.008 Last follow-up 206.17 BMI Baseline 22.58 1.55 -4.95 < 0.001 Last follow-up 22.92 Notably, the indeterminate result of IGRA at baseline alerts worse follow-up outcome, which included the only TB patient found in this study and 6.7% positive conversion rate, which is significantly higher than those with baseline negative results at baseline (3.7%, χ2 = 3.20). There are 245 participants who haven’t accepted a second IGRA test due to various reasons. Although their TBI status couldn’t be directly observed by this study, we managed to obtain the information whether they were diagnosed with active TB from annual screening for PLHIV and none of them has active TB diagnose until the end of follow-up. Discussion The global challenge of managing TBI in PLHIV necessitates intensified screening and prevention, in alignment with the United Nation's 2030 targets to end TB and HIV/AIDS. This study is designed to answer the question that, what is the most suitable strategy to screening and prevent TBI among PLHIV in Shanghai, China. A total of 963 eligible participants were enrolled from Jing’an and Baoshan District. At baseline, 857 participants completed both IGRA and questionnaire. The demographic characteristics of the included participants are in line with the profile of PLHIV in Shanghai. Taking QFT positive as the TBI criterion, 58 (6.8%) TBI were identified at baseline. By multivariate analysis, we found it’s hard to separate between TBI and not infected individuals by most factors, except for age group and CD4 T lymphocyte count. Similar studies have been taken place in various regions with different demographic and epidemic background with the prevalence of TBI ranged from 4.8% to 25.2%[ 10 – 13 ], thus it is hard to compare the absolute value of the prevalence of TBI due to high heterogeneity between studies concerning local TB and HIV burden, ART coverage and immune status of sampled subjects. Still, all those studies have reached a consensus that CD4 T lymphocyte count, virus load, ART use, and age are strongly related to tuberculosis infection, which is also agreed with our findings. Especially among individuals with low level of CD4 count, their risk of TBI or active TB is doubtlessly higher but the TBI status may not be detected due to impaired immune function[ 12 , 14 ]. Thus the subgroup of low CD4 count would be facing a double risk of higher TB infection and false negative of either IGRA or TST. This should be taken into account during policy making process. In the follow-up period, 615 participants had completed at least one follow-up visit. By the end of December 31, 2024, the average follow-up period were 788 days. At the start of the follow-up, the immune levels of the participants were already higher than individuals in other regions in similar studies. However, it is encouraging to see after more than two years of follow-up, the overall immune levels of the participants have increased, proving that continuous ART has a sustained effect on the control of viral load and the improvement of CD4 lymphocyte level. There were 1 (0.2%) pulmonary TB patient and 21 (3.8%) participants turned positive among 554 baseline TBI negative or indeterminate participants during follow-up period. No active TB patient was found among IGRA positive individuals and no ex-pulmonary TB patient was found. The prevalence of active TB is 84.33 per 100,000 person year and TBI conversion rate by year is 1.75%. It should also be noted that the conversion rate could not be simply equaled to recent infection, as the special immune status of PLHIV may lead to false negative results at baseline. Another issue worth to discuss is how to treat individuals with indeterminate result. A meta-analysis shows that the pooled proportion of indeterminate results in IGRA is 3.9% (95% CI: 3.5%-4.2%) in all populations and 5.7% (95% CI: 4.8%-6.6%) in the immune compromised subgroup[ 15 ] indicating that indeterminate results are more common in PLHIV. Other than immune status, indeterminate result is also related to factors such as personal condition, co-morbid, interaction of other co-infection and laboratorial operation.[ 16 ] In our study, 11.1% of the indeterminate individuals turned to positive during follow-up, the difference is statistically significant comparing to baseline negative participants. It is suggested that long-term follow-up and comprehensive evaluation of the detection results is a strategy to deal with the indeterminate results of IGRA. In some resource limited regions with high TB/HIV co-infection prevalence, the algorism of defining both positive and indeterminate results as TBI could be adapted to avoid more test.[ 17 ] However, considering the characteristics of the epidemic situation in Shanghai and the conditions of health resources comprehensively, it is not recommended to handle the indeterminate result as IGRA positive. Overall speaking, the baseline TBI prevalence, the follow-up positive conversion rate of TBI and the incidence of active TB obtained in this study were quite different comparing to similar studies in some high TB burden areas such as Brazil[ 13 ], Mexico[ 18 ] or Ghana[ 19 ]. Even in China, the distribution of TB and HIV epidemic varies greatly. A multicentered prospective study in rural China acquired 0.87 per 100 person year after 2 years follow-up among QFT positive population[ 20 ] which indicates that even in China, a fixed policy is not an effective method of controlling TB/HIV. In the latest recommendations from WHO consolidated guidelines, it is recommended to provide universal TPT for PLHIV irrespective of the degree of immunosuppression and even if TBI testing is unavailable. [ 21 ] According to our study, this approach may not be directly applicable to China, to be more particularly, to Shanghai, where the proportion of TB patients co-infected with HIV is significantly lower (1.8% nationally, 0.35% in Shanghai) than in regions that informed the WHO guidance (12.8%–56.7%)[ 22 – 25 ]. After integrated consideration, we believe that conducting TPT on the bases of TBI status is a more suitable prevention and control strategy for Shanghai. There are certain limits of this study. First of all, a large proportion of enrolled individuals are previous diagnosed PLHIV who have been on ART for years. Most of them have already re-established a stable immune function with a relatively high CD4 T-cell level. Secondly, interpreting the results of IGRA can always be troublesome among PLHIV because the false negative rate in this population is not ignorable. Thirdly, it is also hard to differentiate recent or previous infection of MTB if participants are IGRA positive at baseline. In conclusion, in light of the low prevalence of TBI and the low incidence of active TB among PLHIV in Shanghai, the implementation of universal TPT for all PLHIV may not represent the most efficient prevention strategy in this setting. The occurrence of indeterminate IGRA results warrants intensified attention, underscoring the need for enhanced interdisciplinary interpretation during the screening process. It is therefore recommended that tailored algorithms for TBI screening and risk-stratified management be developed, taking into account local epidemiological patterns and resource availability, in order to implement a targeted TPT approach and optimize the overall effectiveness of TB prevention and care among PLHIV in Shanghai. Abbreviations TB: Tuberculosis AIDS: acquired immune deficiency syndrome MTB: Mycobacterium tuberculosis HIV: human immunodeficiency virus TBI: tuberculosis infection WHO: World Health Organization PLHIV: people who live with HIV TPT: tuberculosis preventive treatment IGRA: interferon-gamma release assays SPHCC: Shanghai Public Health Clinical Center OR: odds ratio CI: confidence interval Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the Ethical Review Committee of Shanghai Municipal Center for Disease and Prevention (Approval number: 2019-12). All participants have provided signed informed consent prior to the investigation. Clinical trial Not applicable. Consent for publication Not applicable. Availability of data and materials The data in this study were collected by questionnaires and the hospital information system of SPHCC. We would like to share statistical results of this study. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors state that they do not have any conflicts of interest. Funding The study received support from Prevention and control of emerging and major infectious diseases-national science and technology major Project (2025ZD01908500), National Key Research Project (2024YFC2311205), the Top Young Talents in Shanghai (2023) and The Public Health Personnel Training Support Project of the National Bureau of Disease Prevention and Control (2024) Author contributions Rao designed the questionnaire and the survey process, performed the statistical analysis and wrote the article. Gu was in charge of implementing the on-site survey in Jing'an District, including cohort establishment, cohort management, and follow-up retention. Yang was in charge of implementing the on-site survey in Jing'an District, including cohort management, questionnaire collection and quality control for data entry. Le was responsible for implementing the on-site survey in Baoshan District, including cohort establishment, cohort management, and follow-up retention. Zhang was responsible for implementing the on-site survey in Baoshan District, including cohort management, questionnaire collection and quality control for data entry. Chen provided technical support, including coordination of medical institutions and public health institutions. Ning provided technical support, including coordination of medical institutions, statistical analysis suggestions and quality control. Yue provided technical support, including coordination of medical institutions, statistical analysis suggestions and quality control. Zhu was responsible for coordinating laboratory testing. Shen was responsible for overall coordination and review of the paper for finalization. All authors read and approved the final version of the paper. Acknowledgement We sincerely thank Wu Bin from Shanghai Public Health Clinical Center for her support in the research process. References World Health Organization, WHO consolidated guidelines on tuberculosis Module1: Prevention-Tuberculosis preventive treatment, second edition. 2024, Geneva. World Health Organization, Global Tuberculosis Report 2025. 2025, Geneva. Joint United Nations Programme on HIV/AIDS, AIDS, crisis and the power to transform: UNAIDS Global AIDS Update 2025. 2025, Geneva. World Health Organization, The End TB Strategy. 2015, Geneva, Switzerland: WHO Document Production Services. Gao, J., P. Zheng and H. Fu, Prevalence of TB/HIV co-infection in countries except China: a systematic review and meta-analysis. PLoS One, 2013. 8(5): p. e64915. Gao, L., et al., HIV/TB co-infection in mainland China: a meta-analysis. PLoS One, 2010. 5(5): p. e10736. Qi, C., et al., Prevalence and risk factors of tuberculosis among people living with HIV/AIDS in China: a systematic review and meta-analysis. BMC Infect Dis, 2023. 23(1): p. 584. WHO Policy on Collaborative TB/HIV Activities: Guidelines for National Programmes and Other Stakeholders. WHO Guidelines Approved by the Guidelines Review Committee. 2012, Geneva: World Health Organization. Rao LX, Xiao X, Chen J, Shen X, Jiang QW, Study of screening methods of MTB／HIV co-infected patients in low TB and AIDS prevalence area. ZHONG GUO FANG LAO ZA ZHI. 2021. 43(3): 240-247R Bourgarit, A., et al., Latent Tuberculosis Infection Screening and 2-Year Outcome in Antiretroviral-Naive HIV-Infected Patients in a Low-Prevalence Country. Ann Am Thorac Soc, 2015. 12(8): p. 1138-45. Mancuso, J.D., et al., The Prevalence of Latent Tuberculosis Infection in the United States. Am J Respir Crit Care Med, 2016. 194(4): p. 501-9. Geremew, D., et al., Tuberculosis and its association with CD4(+) T cell count among adult HIV positive patients in Ethiopian settings: a systematic review and meta-analysis. BMC Infect Dis, 2020. 20(1): p. 325. Navarro, P.D.D., et al., Prevalence of latent Mycobacterium tuberculosis infection in prisoners. J Bras Pneumol, 2016. 42(5): p. 348-355. Leidl, L., et al., Relationship of immunodiagnostic assays for tuberculosis and numbers of circulating CD4+ T-cells in HIV infection. Eur Respir J, 2010. 35(3): p. 619-26. Zhou, G., et al., Indeterminate results of interferon gamma release assays in the screening of latent tuberculosis infection: a systematic review and meta-analysis. Front Immunol, 2023. 14: p. 1170579. Yun, J.W., et al., Significant reduction in rate of indeterminate results of the QuantiFERON-TB Gold In-Tube test by shortening incubation delay. J Clin Microbiol, 2014. 52(1): p. 90-4. Njagi, L.N., et al., Prevalence and predictors of tuberculosis infection among people living with HIV in a high tuberculosis burden context. BMJ Open Respir Res, 2023. 10(1). Plascencia Hernández, A., et al., A prevalence study in Guadalajara, Mexico, comparing tuberculin skin test and QuantiFERON-TB Gold In-Tube. PLoS One, 2022. 17(3): p. e0264982. Lamptey, H., et al., High prevalence of co-infections with latent tuberculosis, syphilis and hepatitis B and C among people with HIV in Ghana: a call for integrating screening into routine care. AIDS Res Ther, 2025. 22(1): p. 61. Gao, L., et al., Incidence of active tuberculosis in individuals with latent tuberculosis infection in rural China: follow-up results of a population-based, multicentre, prospective cohort study. Lancet Infect Dis, 2017. 17(10): p. 1053-1061. World Health Organization, WHO consolidated guidelines on tuberculosis Module3: Diagnosis. Tests for tuberculosis infection. 2022, Geneva. Chaisson, L.H., et al., CD4+ cell count stratification to guide tuberculosis preventive therapy for people living with HIV. AIDS, 2020. 34(1): p. 139-147. Rangaka, M.X., et al., Isoniazid plus antiretroviral therapy to prevent tuberculosis: a randomised double-blind, placebo-controlled trial. Lancet, 2014. 384(9944): p. 682-90. Danel, C., et al., A Trial of Early Antiretrovirals and Isoniazid Preventive Therapy in Africa. N Engl J Med, 2015. 373(9): p. 808-22. Badje, A., et al., Effect of isoniazid preventive therapy on risk of death in west African, HIV-infected adults with high CD4 cell counts: long-term follow-up of the Temprano ANRS 12136 trial. Lancet Glob Health, 2017. 5(11): p. e1080-e1089. Additional Declarations No competing interests reported. Supplementary Files Questionnaires.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 30 Apr, 2026 Reviews received at journal 08 Apr, 2026 Reviewers agreed at journal 24 Mar, 2026 Reviewers agreed at journal 23 Mar, 2026 Reviews received at journal 21 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers invited by journal 19 Mar, 2026 Editor assigned by journal 08 Mar, 2026 Submission checks completed at journal 07 Mar, 2026 First submitted to journal 07 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8973880","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":609732962,"identity":"ebed836e-aaac-4aad-951b-4c6254ec4e54","order_by":0,"name":"Lixin Rao","email":"","orcid":"","institution":"Shanghai Municipal Center For Disease Control Prevention","correspondingAuthor":false,"prefix":"","firstName":"Lixin","middleName":"","lastName":"Rao","suffix":""},{"id":609732968,"identity":"24baebf2-c3d5-4409-8d04-88e5baff233b","order_by":1,"name":"Kaikan Gu","email":"","orcid":"","institution":"Shanghai Jing'an District Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Kaikan","middleName":"","lastName":"Gu","suffix":""},{"id":609732972,"identity":"ffa33385-8be6-4d31-a7d9-92ef92aff27c","order_by":2,"name":"Yun Yang","email":"","orcid":"","institution":"Shanghai Jing'an District Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yun","middleName":"","lastName":"Yang","suffix":""},{"id":609732975,"identity":"a482765b-59f7-47c9-b263-0144b6fca001","order_by":3,"name":"Boxin Le","email":"","orcid":"","institution":"Shanghai Baoshan District Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Boxin","middleName":"","lastName":"Le","suffix":""},{"id":609732978,"identity":"de87df37-876e-430d-94dc-8386c54e1ffe","order_by":4,"name":"Zhengqi Zhang","email":"","orcid":"","institution":"Shanghai Baoshan District Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Zhengqi","middleName":"","lastName":"Zhang","suffix":""},{"id":609732979,"identity":"37709fb4-b606-4a24-8c0a-bf06df1e72f7","order_by":5,"name":"Jing Chen","email":"","orcid":"","institution":"Shanghai Municipal Center For Disease Control Prevention","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Chen","suffix":""},{"id":609732980,"identity":"c6c67d52-38dc-4c74-be6d-4f0f3ba74a9d","order_by":6,"name":"Zhen Ning","email":"","orcid":"","institution":"Shanghai Municipal Center For Disease Control Prevention","correspondingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Ning","suffix":""},{"id":609732987,"identity":"b0954f47-6263-4b14-8dbf-88fd588cf726","order_by":7,"name":"Qing Yue","email":"","orcid":"","institution":"Shanghai Municipal Center For Disease Control Prevention","correspondingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Yue","suffix":""},{"id":609732990,"identity":"4668c5f4-6e4c-43f8-be2a-db0a5101f293","order_by":8,"name":"Zhaoqin Zhu","email":"","orcid":"","institution":"Shanghai Public Health Clinical Center","correspondingAuthor":false,"prefix":"","firstName":"Zhaoqin","middleName":"","lastName":"Zhu","suffix":""},{"id":609732992,"identity":"b20558f3-4087-4b1e-92bd-80662222b915","order_by":9,"name":"Xin Shen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYDACCRBhwCAHJhkYDhCvxZhULQwMiQ1Ea5Gf3XzsMU/BnfT57Yc3fmD4c4eBf3YDfi0Gd46lG84weJa74UxasQRj2zMGiTsEbDKQyDGT+GBwOHeDBI8ZA2PDYaBIAgGHzcj/JpFgcDhdfgZQC8MfIrQw3MhhA9mSwHADpIWNCC0GN9LMJGcYHDYE+yWx7TCPxA2CDkt+Js3z57C8PCjEPvw5LMc/g5DDUABQMQ8p6kfBKBgFo2AU4AAAHXBB8JjHzMgAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai Municipal Center For Disease Control Prevention","correspondingAuthor":true,"prefix":"","firstName":"Xin","middleName":"","lastName":"Shen","suffix":""}],"badges":[],"createdAt":"2026-02-26 06:09:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8973880/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8973880/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105315578,"identity":"75ecf198-87ec-4cfa-a8ce-83964aa45f89","added_by":"auto","created_at":"2026-03-24 16:11:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":57772,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of enrollment\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8973880/v1/d9dae244471d59177dda6558.png"},{"id":105315564,"identity":"6e928311-ea7f-461a-b217-9cc8ded0b0f2","added_by":"auto","created_at":"2026-03-24 16:11:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":162264,"visible":true,"origin":"","legend":"\u003cp\u003eSankey diagram on the change of TBI state during follow-up period\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8973880/v1/98978b8306982decb9c39192.png"},{"id":105315694,"identity":"ef07a820-b1c3-46f7-8f35-f3cb0bc79dae","added_by":"auto","created_at":"2026-03-24 16:11:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":929905,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8973880/v1/2d94e38c-d9d0-424f-842a-08ec1bd1513f.pdf"},{"id":105315523,"identity":"15142d78-09dc-4be7-a3e5-bdb0f7311965","added_by":"auto","created_at":"2026-03-24 16:11:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":202447,"visible":true,"origin":"","legend":"","description":"","filename":"Questionnaires.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8973880/v1/177c0c25add3d6a1a09b2af1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Burden of latent tuberculosis infection among People living with HIV in Shanghai, China: A 4-year cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eTuberculosis (TB) and acquired immune deficiency syndrome (AIDS) are both chronic infectious diseases caused respectively by \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e (MTB) and human immunodeficiency virus (HIV), whose correlation becomes a growing global public health concern. MTB is a typical opportunistic pathogen which usually under the control of human immune system presenting as tuberculosis infection (TBI) instead of active TB. Owing to impaired immune function, HIV-positive individuals are more susceptible of TBI and are at a constant risk of progressing to active TB through reactivation of TBI[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Co-infection of MTB/HIV will accelerate process of both diseases and increase the risk of severe case and death. According to World Health Organization (WHO)\u0026rsquo;s Global Tuberculosis Report, 5.8% of the TB patients and 12.2% of the TB death are HIV-related in 2024[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Meanwhile, TB is accounted for nearly one-fourth of AIDS-related death in 2023[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The severe situation of MTB/HIV co-infection hinders the achievement of \u0026ldquo;End TB\u0026rdquo; goal in 2035[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGlobally speaking, the prevalence of TB/HIV co-infection varies depending on the very different distributions of two diseases. A meta-analysis estimates the prevalence of TB/HIV co-infection ranged from 2.93% to 72.34% in countries except China. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] Compared to other countries, China has significantly lower burden of co-infection 0.9% (95% CI: 0.6%-1.4%) of TB patients co-infected with HIV[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and the pooled prevalence of TB is 6.0% (95% CI: 4.0%-7.0%) among people who live with HIV (PLHIV) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, the burden of TB and HIV are still serious and the uneven distribution of both diseased increases the difficulty of prevention and control especially in low-HIV burden and medium-TB burden regions such as Shanghai. Following WHO\u0026rsquo;s recommendation, Shanghai has started to screen for HIV antigen among TB patients and to systematically screen for active TB PLHIV annually among all patients since 2012[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. After more than ten years of practice, the inspection rate has significantly improved. However, the current measures seem to reach its limit on finding more active cases. In our previous study, only 0.08% TB patients are newly confirmed with HIV, and 0.21% of PLHIV under management are diagnosed with active TB in 2020[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs screening for active patient has decreasing yield, we have moved our focus forward on screening for infectious individuals and provide early intervention. The question in front of us now is how to enhance the screening efficiency while also taking cost-effectiveness into account. In this study, we try to acquire the prevalence of TBI among PLHIV in Shanghai and to build up a cohort to follow-up on the changes of TBI status and the development to TB disease, in order to explore a better algorithm to identify and prevent TBI and active TB cases.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis is a cohort study design, including PLHIV under management in two districts of Shanghai, namely Jing\u0026rsquo;an and Baoshan district, from 2019.5.1 to 2024.12.31. These two districts were selected based on their relatively higher incidence of HIV case report. All patients were examined and treated at Shanghai Public Health Clinical Center (SPHCC), which is the only designated hospital for PLHIV in Shanghai.\u003c/p\u003e \u003cp\u003eAll participants were enrolled on the premise of fully understanding of the purpose and procedure of this study. Individuals with a previous history of TB (whether pulmonary tuberculosis, tuberculous pleurisy, or extraplumonary tuberculosis) within five years or had been underwent tuberculosis preventive treatment (TPT) within five years were excluded.\u003c/p\u003e \u003cp\u003eWe provided a standardized questionnaire and an interferon-gamma release assay (IGRA) for every participant at baseline and every follow-up visit unless the former IGRA test was positive. The questionnaires were developed specifically for this study (see supplementary file 1 and 2). Both baseline and follow-up questionnaires were recorded by trained interviewers including exposure history of active TB patients, susceptible symptoms of TB (cough, hemoptysis, fever, night sweat, and weight loss), weight and height and relative test results. QuantiFREON-TB Gold In-Tube (QFT-GIT; Cellestis, Carnegie, Australia) was used for IGRA. At least 5 ml of blood is needed for QFT-GIT. All tests were performed by qualified technicians in laboratory of SPHCC. Participant with a positive IGRA test excluding clinical evidence of active TB disease is deemed as TBI. All screening and diagnose processes followed the local standard of protocol. Other tests results, such as CD4\u0026thinsp;+\u0026thinsp;lymphocyte count, HIV virus load, as well as other contagious disease which includes Hepatitis B, Hepatitis C, syphilis and pneumocystis pneumonia as well as tuberculosis diagnosis records were collected from hospital information system of SPHCC.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection and Statistical Analysis\u003c/h3\u003e\n\u003cp\u003eProfessionals from Jingan and Baoshan district center for disease control and prevention (CDC) are responsible for the collection and quality control of baseline and follow-up questionnaires. Data were collected by Epidata (Version 3.1) and pre-processed by Microsoft Excel (Version 2010). Statistical analysis was performed by IBM SPSS Statistics (version 20.0) and R (version 4.5.2). A P-value less than 0.05 (two-tailed) was regarded as the level of significance. Logistic regression models were used to evaluate the association between MTB infection status and socio-demographic, clinical and laboratory characteristics. All factors were included into the multivariate linear regression using an enter procedure. Multiple categorical variables were included in the model as dummy variables. Paired T-test, Chi-square, Odds ratio (OR) and 95% confidence interval (CI) were calculated. Due to different enroll and ended follow-up time, we used person day and person year to evaluate follow-up period. And a sankey diagram was plotted to demonstrate the changes in the TB infection status of the study population.\u003c/p\u003e\n\u003ch3\u003eEthnics approval\u003c/h3\u003e\n\u003cp\u003e The study protocol was approved by the Ethical Review Committee of Shanghai Municipal Center for Disease and Prevention (Approval number: 2019-12). All participants have provided signed informed consent prior to the investigation.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn this study, a total of 963 HIV-positive participants were enrolled. A pilot trial was performed at May 2019 and the formal enrollment initiated at September 2019. The enrollment ceased at December 2021 and the follow-up continued till December 2024. Among those participants, 560 individuals (58.2%) were from Jinan district and 403 (41.8%) were from Baoshan district. After cross-checking with previous TB patients database, one participant was found to have been diagnosed with active TB in 2018, thus was excluded from this study according to the exclusion criteria. The inclusion diagram is displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eDemographic and epidemiological characteristics of the participants at baseline\u003c/h3\u003e\n\u003cp\u003eAmong participants enrolled, 857 completed all the required steps at baseline thus was included in further analysis. The median age of the participants was 42.2 years old, and 92.5% of them were male. Most of the participants are previous patients with an average diagnosis time of 4.5 years. A total of 58 individuals tested positive for IGRA, accounting for 6.8% of the whole cohort. All participants underwent systematic screening for active TB and none was diagnosed. Indeterminate (15, 1.8%) and negative (784, 91.5%) results are counted as TBI negative.\u003c/p\u003e \u003cp\u003eBaseline demographic clinical and epidemiological characteristics are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Age and CD4\u0026thinsp;+\u0026thinsp;lymphocyte count are statistically significant factors in the logistic regression.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression of demographic, clinical and epidemiological characteristics for the participants at baseline\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll patients\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;857)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eTBI at baseline\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.989 (0.588\u0026ndash;6.722)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e793(92.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e55(94.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64(7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3(5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.237 (1.002\u0026ndash;1.528)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171(20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e8(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e296(34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e17(30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152(17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e11(19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139(15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e16(26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99(11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e6(10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eNewly Diagnosed HIV-Positive(within 1 year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.346 (0.076\u0026ndash;1.569)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95(11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e762(88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56(96.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18(underweight)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31(3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.705 (0.406\u0026ndash;1.226)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;24(normal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e576(67.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42(72.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;24(overweight)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e250(29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSuspicious Symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.986 (0.466\u0026ndash;2.086)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130(15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e727(84.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49(84.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;lymphocyte count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.453 (0.235\u0026ndash;0.873)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;400 /\u0026micro;l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e314(36.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e13(22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;400/\u0026micro;l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e543(63.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e45(77.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV virus load\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.365 (0.642\u0026ndash;2.903)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20 copies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170(19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e10(17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;20 copies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e687(80.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e48(82.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.497 (0.680\u0026ndash;9.171)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3(5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e837(97.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e55(94.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.068 (0.133\u0026ndash;8.567)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19(2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1(1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e838(97.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e57(98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSyphilis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.282 (0.055\u0026ndash;1.446)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75(8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2(3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e782(91.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e56(96.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eOther infectious diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.567 (0.462\u0026ndash;5.315)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66(7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e791(92.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54(93.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eChanges of TBI status and immune function during the follow-up period\u003c/h2\u003e \u003cp\u003eBy the end of the follow-up (December 31, 2024), a total of 615 individuals had completed at least one follow-up, with an average follow-up period of 788 days and a follow-up rate of 71.8%. According to the protocol, 554 of the 799 baseline IGRA negative participants have accepted annually IGRA test. There are 117 (21.1%) and 46 (8.3%) participants underwent the second and the third follow-up IGRA test respectively. Among all the participants, 21 turned positive. Most conversion was detected at the first follow-up test (17, 81.0%) and none positive conversion was detected at the third follow-up period. The average time interval is 466 days for the individuals who converted at first follow-up, 975 for those at second follow-up period, and 646 days for all converted participants. The follow-up positive conversion rate for IGRA was 1.75% per person year. Follow-up indeterminate result is not regarded as a positive outcome in this study.\u003c/p\u003e \u003cp\u003eNone of the baseline TBI individual developed to active TB, while one participant has been diagnosed with pulmonary TB, whose baseline IGRA result was indeterminate. It took 505 days from the first test of IGRA to the diagnosis of active TB, with an annualized adjusted incidence density of 84.33 per 100,000. And 3 participants died before the second IGRA test was taken. The change of TBI status is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStatistical significance of the changes of CD4 cell count, virus load and BMI between baseline and last follow-up test were detected (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The overall immune related status for all participants is improved, though the degree of improvement in the positive conversion group was only slightly lower than the non-positive conversion group and the difference was not statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges of CD4 count, virus load and BMI between baseline and last follow-up\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePair\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003emeans\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4 count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e501.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLast follow-up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e548.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVirus load\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8760.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8554.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLast follow-up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e206.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLast follow-up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNotably, the indeterminate result of IGRA at baseline alerts worse follow-up outcome, which included the only TB patient found in this study and 6.7% positive conversion rate, which is significantly higher than those with baseline negative results at baseline (3.7%, χ2\u0026thinsp;=\u0026thinsp;3.20).\u003c/p\u003e \u003cp\u003eThere are 245 participants who haven\u0026rsquo;t accepted a second IGRA test due to various reasons. Although their TBI status couldn\u0026rsquo;t be directly observed by this study, we managed to obtain the information whether they were diagnosed with active TB from annual screening for PLHIV and none of them has active TB diagnose until the end of follow-up.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe global challenge of managing TBI in PLHIV necessitates intensified screening and prevention, in alignment with the United Nation's 2030 targets to end TB and HIV/AIDS. This study is designed to answer the question that, what is the most suitable strategy to screening and prevent TBI among PLHIV in Shanghai, China. A total of 963 eligible participants were enrolled from Jing\u0026rsquo;an and Baoshan District. At baseline, 857 participants completed both IGRA and questionnaire. The demographic characteristics of the included participants are in line with the profile of PLHIV in Shanghai. Taking QFT positive as the TBI criterion, 58 (6.8%) TBI were identified at baseline. By multivariate analysis, we found it\u0026rsquo;s hard to separate between TBI and not infected individuals by most factors, except for age group and CD4 T lymphocyte count.\u003c/p\u003e \u003cp\u003eSimilar studies have been taken place in various regions with different demographic and epidemic background with the prevalence of TBI ranged from 4.8% to 25.2%[\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], thus it is hard to compare the absolute value of the prevalence of TBI due to high heterogeneity between studies concerning local TB and HIV burden, ART coverage and immune status of sampled subjects. Still, all those studies have reached a consensus that CD4 T lymphocyte count, virus load, ART use, and age are strongly related to tuberculosis infection, which is also agreed with our findings. Especially among individuals with low level of CD4 count, their risk of TBI or active TB is doubtlessly higher but the TBI status may not be detected due to impaired immune function[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Thus the subgroup of low CD4 count would be facing a double risk of higher TB infection and false negative of either IGRA or TST. This should be taken into account during policy making process.\u003c/p\u003e \u003cp\u003eIn the follow-up period, 615 participants had completed at least one follow-up visit. By the end of December 31, 2024, the average follow-up period were 788 days. At the start of the follow-up, the immune levels of the participants were already higher than individuals in other regions in similar studies. However, it is encouraging to see after more than two years of follow-up, the overall immune levels of the participants have increased, proving that continuous ART has a sustained effect on the control of viral load and the improvement of CD4 lymphocyte level.\u003c/p\u003e \u003cp\u003eThere were 1 (0.2%) pulmonary TB patient and 21 (3.8%) participants turned positive among 554 baseline TBI negative or indeterminate participants during follow-up period. No active TB patient was found among IGRA positive individuals and no ex-pulmonary TB patient was found. The prevalence of active TB is 84.33 per 100,000 person year and TBI conversion rate by year is 1.75%. It should also be noted that the conversion rate could not be simply equaled to recent infection, as the special immune status of PLHIV may lead to false negative results at baseline.\u003c/p\u003e \u003cp\u003eAnother issue worth to discuss is how to treat individuals with indeterminate result. A meta-analysis shows that the pooled proportion of indeterminate results in IGRA is 3.9% (95% CI: 3.5%-4.2%) in all populations and 5.7% (95% CI: 4.8%-6.6%) in the immune compromised subgroup[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] indicating that indeterminate results are more common in PLHIV. Other than immune status, indeterminate result is also related to factors such as personal condition, co-morbid, interaction of other co-infection and laboratorial operation.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] In our study, 11.1% of the indeterminate individuals turned to positive during follow-up, the difference is statistically significant comparing to baseline negative participants. It is suggested that long-term follow-up and comprehensive evaluation of the detection results is a strategy to deal with the indeterminate results of IGRA. In some resource limited regions with high TB/HIV co-infection prevalence, the algorism of defining both positive and indeterminate results as TBI could be adapted to avoid more test.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] However, considering the characteristics of the epidemic situation in Shanghai and the conditions of health resources comprehensively, it is not recommended to handle the indeterminate result as IGRA positive.\u003c/p\u003e \u003cp\u003eOverall speaking, the baseline TBI prevalence, the follow-up positive conversion rate of TBI and the incidence of active TB obtained in this study were quite different comparing to similar studies in some high TB burden areas such as Brazil[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], Mexico[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] or Ghana[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Even in China, the distribution of TB and HIV epidemic varies greatly. A multicentered prospective study in rural China acquired 0.87 per 100 person year after 2 years follow-up among QFT positive population[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] which indicates that even in China, a fixed policy is not an effective method of controlling TB/HIV. In the latest recommendations from WHO consolidated guidelines, it is recommended to provide universal TPT for PLHIV irrespective of the degree of immunosuppression and even if TBI testing is unavailable. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] According to our study, this approach may not be directly applicable to China, to be more particularly, to Shanghai, where the proportion of TB patients co-infected with HIV is significantly lower (1.8% nationally, 0.35% in Shanghai) than in regions that informed the WHO guidance (12.8%\u0026ndash;56.7%)[\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. After integrated consideration, we believe that conducting TPT on the bases of TBI status is a more suitable prevention and control strategy for Shanghai.\u003c/p\u003e \u003cp\u003eThere are certain limits of this study. First of all, a large proportion of enrolled individuals are previous diagnosed PLHIV who have been on ART for years. Most of them have already re-established a stable immune function with a relatively high CD4 T-cell level. Secondly, interpreting the results of IGRA can always be troublesome among PLHIV because the false negative rate in this population is not ignorable. Thirdly, it is also hard to differentiate recent or previous infection of MTB if participants are IGRA positive at baseline.\u003c/p\u003e \u003cp\u003eIn conclusion, in light of the low prevalence of TBI and the low incidence of active TB among PLHIV in Shanghai, the implementation of universal TPT for all PLHIV may not represent the most efficient prevention strategy in this setting. The occurrence of indeterminate IGRA results warrants intensified attention, underscoring the need for enhanced interdisciplinary interpretation during the screening process. It is therefore recommended that tailored algorithms for TBI screening and risk-stratified management be developed, taking into account local epidemiological patterns and resource availability, in order to implement a targeted TPT approach and optimize the overall effectiveness of TB prevention and care among PLHIV in Shanghai.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eTB: Tuberculosis\u003c/p\u003e\n\u003cp\u003eAIDS: acquired immune deficiency syndrome\u003c/p\u003e\n\u003cp\u003eMTB:\u003cem\u003e\u0026nbsp;Mycobacterium tuberculosis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHIV: human immunodeficiency virus\u003c/p\u003e\n\u003cp\u003eTBI: tuberculosis infection\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u003c/p\u003e\n\u003cp\u003ePLHIV: people who live with HIV\u003c/p\u003e\n\u003cp\u003eTPT: tuberculosis preventive treatment\u003c/p\u003e\n\u003cp\u003eIGRA: interferon-gamma release assays\u003c/p\u003e\n\u003cp\u003eSPHCC: Shanghai Public Health Clinical Center\u003c/p\u003e\n\u003cp\u003eOR: odds ratio\u003c/p\u003e\n\u003cp\u003eCI: confidence interval\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the Ethical Review Committee of Shanghai Municipal Center for Disease and Prevention (Approval number: 2019-12). All participants have provided signed informed consent prior to the investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data in this study were collected by questionnaires and the hospital information system of SPHCC. We would like to share statistical results of this study. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors state that they do not have any conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received support from Prevention and control of emerging and major infectious diseases-national science and technology major Project (2025ZD01908500), National Key Research Project (2024YFC2311205), the Top Young Talents in Shanghai (2023) and The Public Health Personnel Training Support Project of the National Bureau of Disease Prevention and Control\u0026nbsp;(2024)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRao designed the questionnaire and the survey process, performed the statistical analysis and wrote the article. Gu was in charge of implementing the on-site survey in Jing'an District, including cohort establishment, cohort management, and follow-up retention. Yang was in charge of implementing the on-site survey in Jing'an District, including cohort management, questionnaire collection and quality control for data entry. Le was responsible for implementing the on-site survey in Baoshan District, including cohort establishment, cohort management, and follow-up retention. Zhang was responsible for implementing the on-site survey in Baoshan District, including cohort management, questionnaire collection and quality control for data entry. Chen provided technical support, including coordination of medical institutions and public health institutions. Ning provided technical support, including coordination of medical institutions, statistical analysis suggestions and quality control. Yue provided technical support, including coordination of medical institutions, statistical analysis suggestions and quality control. Zhu was responsible for coordinating laboratory testing. Shen was responsible for overall coordination and review of the paper for finalization.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final version of the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank Wu Bin from Shanghai Public Health Clinical Center for her support in the research process.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization, WHO consolidated guidelines on tuberculosis Module1: Prevention-Tuberculosis preventive treatment, second edition. 2024, Geneva.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization, Global Tuberculosis Report 2025. 2025, Geneva.\u003c/li\u003e\n\u003cli\u003eJoint United Nations Programme on HIV/AIDS, AIDS, crisis and the power to transform: UNAIDS Global AIDS Update 2025. 2025, Geneva.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization, The End TB Strategy. 2015, Geneva, Switzerland: WHO Document Production Services.\u003c/li\u003e\n\u003cli\u003eGao, J., P. Zheng and H. Fu, Prevalence of TB/HIV co-infection in countries except China: a systematic review and meta-analysis. PLoS One, 2013. 8(5): p. e64915.\u003c/li\u003e\n\u003cli\u003eGao, L., et al., HIV/TB co-infection in mainland China: a meta-analysis. PLoS One, 2010. 5(5): p. e10736.\u003c/li\u003e\n\u003cli\u003eQi, C., et al., Prevalence and risk factors of tuberculosis among people living with HIV/AIDS in China: a systematic review and meta-analysis. BMC Infect Dis, 2023. 23(1): p. 584.\u003c/li\u003e\n\u003cli\u003eWHO Policy on Collaborative TB/HIV Activities: Guidelines for National Programmes and Other Stakeholders. WHO Guidelines Approved by the Guidelines Review Committee. 2012, Geneva: World Health Organization.\u003c/li\u003e\n\u003cli\u003eRao LX, Xiao X, Chen J, Shen X, Jiang QW, Study of screening methods of MTB／HIV co-infected patients in low TB and AIDS prevalence area. ZHONG GUO FANG LAO ZA ZHI. 2021. 43(3): 240-247R\u003c/li\u003e\n\u003cli\u003eBourgarit, A., et al., Latent Tuberculosis Infection Screening and 2-Year Outcome in Antiretroviral-Naive HIV-Infected Patients in a Low-Prevalence Country. Ann Am Thorac Soc, 2015. 12(8): p. 1138-45.\u003c/li\u003e\n\u003cli\u003eMancuso, J.D., et al., The Prevalence of Latent Tuberculosis Infection in the United States. Am J Respir Crit Care Med, 2016. 194(4): p. 501-9.\u003c/li\u003e\n\u003cli\u003eGeremew, D., et al., Tuberculosis and its association with CD4(+) T cell count among adult HIV positive patients in Ethiopian settings: a systematic review and meta-analysis. BMC Infect Dis, 2020. 20(1): p. 325.\u003c/li\u003e\n\u003cli\u003eNavarro, P.D.D., et al., Prevalence of latent Mycobacterium tuberculosis infection in prisoners. J Bras Pneumol, 2016. 42(5): p. 348-355.\u003c/li\u003e\n\u003cli\u003eLeidl, L., et al., Relationship of immunodiagnostic assays for tuberculosis and numbers of circulating CD4+ T-cells in HIV infection. Eur Respir J, 2010. 35(3): p. 619-26.\u003c/li\u003e\n\u003cli\u003eZhou, G., et al., Indeterminate results of interferon gamma release assays in the screening of latent tuberculosis infection: a systematic review and meta-analysis. Front Immunol, 2023. 14: p. 1170579.\u003c/li\u003e\n\u003cli\u003eYun, J.W., et al., Significant reduction in rate of indeterminate results of the QuantiFERON-TB Gold In-Tube test by shortening incubation delay. J Clin Microbiol, 2014. 52(1): p. 90-4.\u003c/li\u003e\n\u003cli\u003eNjagi, L.N., et al., Prevalence and predictors of tuberculosis infection among people living with HIV in a high tuberculosis burden context. BMJ Open Respir Res, 2023. 10(1).\u003c/li\u003e\n\u003cli\u003ePlascencia Hern\u0026aacute;ndez, A., et al., A prevalence study in Guadalajara, Mexico, comparing tuberculin skin test and QuantiFERON-TB Gold In-Tube. PLoS One, 2022. 17(3): p. e0264982.\u003c/li\u003e\n\u003cli\u003eLamptey, H., et al., High prevalence of co-infections with latent tuberculosis, syphilis and hepatitis B and C among people with HIV in Ghana: a call for integrating screening into routine care. AIDS Res Ther, 2025. 22(1): p. 61.\u003c/li\u003e\n\u003cli\u003eGao, L., et al., Incidence of active tuberculosis in individuals with latent tuberculosis infection in rural China: follow-up results of a population-based, multicentre, prospective cohort study. Lancet Infect Dis, 2017. 17(10): p. 1053-1061.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization, WHO consolidated guidelines on tuberculosis Module3: Diagnosis. Tests for tuberculosis infection. 2022, Geneva.\u003c/li\u003e\n\u003cli\u003eChaisson, L.H., et al., CD4+ cell count stratification to guide tuberculosis preventive therapy for people living with HIV. AIDS, 2020. 34(1): p. 139-147.\u003c/li\u003e\n\u003cli\u003eRangaka, M.X., et al., Isoniazid plus antiretroviral therapy to prevent tuberculosis: a randomised double-blind, placebo-controlled trial. Lancet, 2014. 384(9944): p. 682-90.\u003c/li\u003e\n\u003cli\u003eDanel, C., et al., A Trial of Early Antiretrovirals and Isoniazid Preventive Therapy in Africa. N Engl J Med, 2015. 373(9): p. 808-22.\u003c/li\u003e\n\u003cli\u003eBadje, A., et al., Effect of isoniazid preventive therapy on risk of death in west African, HIV-infected adults with high CD4 cell counts: long-term follow-up of the Temprano ANRS 12136 trial. Lancet Glob Health, 2017. 5(11): p. e1080-e1089.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"TB/HIV co-infection, Tuberculosis Infection, Screening algorithm, IGRA conversion","lastPublishedDoi":"10.21203/rs.3.rs-8973880/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8973880/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e/ human immunodeficiency virus (TB/HIV) co-infection remains a significant global public health challenge. In areas with a lower incidence of TB and HIV, how to elevate screening efficiency while maintaining cost-effectiveness worth further exploration. This study aimed to provide a suitable algorism for TB prevention and intervention among people who live with HIV (PLHIV) in Shanghai based on a cohort study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA 4-year cohort study was conducted from May 2019 to December 2024, enrolling PLHIV from two districts in Shanghai. Participants underwent baseline and annual follow-up assessments using interferon-gamma release assays (IGRA) and questionnaires. Demographic, clinical, and laboratory data were collected.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 963 enrolled participants, 857 completed baseline assessments. The baseline TBI prevalence was 6.8% (58/857). Older age and higher CD4 + T-cell count were associated with TBI. During a mean follow-up of 788 days among 615 participants, the IGRA conversion rate was 1.75% per person-year. One case of active TB was diagnosed (incidence rate: 84.33 per 100,000 person-years), occurring in a participant with an indeterminate baseline IGRA result. Participants with indeterminate baseline results had a significantly higher risk of subsequent IGRA conversion or active TB compared to those with negative results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the low prevalence of latent TB infection and active TB among PLHIV in Shanghai, universal preventive treatment is not optimally efficient. The high rate of indeterminate IGRA results at baseline requires focused clinical assessment. A targeted screening and preventive treatment strategy based on local epidemiology and resources should be developed to enhance TB prevention in this population.\u003c/p\u003e","manuscriptTitle":"Burden of latent tuberculosis infection among People living with HIV in Shanghai, China: A 4-year cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 16:08:52","doi":"10.21203/rs.3.rs-8973880/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-30T09:02:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-08T18:17:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"264568175105510746738568006954598782690","date":"2026-03-24T06:34:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"289190602661874159703438251281183692391","date":"2026-03-23T11:31:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-21T04:10:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"32748415344649287530301955623677625409","date":"2026-03-20T08:54:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120926013287899833990026687353811293233","date":"2026-03-19T20:36:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214925291788177485106589365784658777960","date":"2026-03-19T15:04:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T06:29:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-09T02:59:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-07T09:16:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2026-03-07T09:12:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5fb61093-7727-4c40-a606-f5f175bdd214","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-04-30T09:02:28+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T09:26:26+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 16:08:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8973880","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8973880","identity":"rs-8973880","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}