Prevalence and predictors of tuberculosis in adults and adolescents with sputum trace Ultra results in two high-burden clinical settings

Prevalence and predictors of tuberculosis in adults and adolescents with sputum trace Ultra results in two high-burden clinical settings | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Prevalence and predictors of tuberculosis in adults and adolescents with sputum trace Ultra results in two high-burden clinical settings View ORCID Profile Caitlin Visek , View ORCID Profile Ronit R. Dalmat , Annet Nalutaaya , Kamoga Caleb Erisa , Patrick Biché , Gabrielle Stein , Amanda Ganguloo , Robin Draper , Mariam Nantale , View ORCID Profile Adrienne E. Shapiro , Douglas Wilson , Achilles Katamba , Paul K. Drain , Emily A. Kendall doi: https://doi.org/10.1101/2025.05.16.25327787 Caitlin Visek 1 Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine , Baltimore, Maryland, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Caitlin Visek For correspondence: Cvisek1{at}jh.edu Ronit R. Dalmat 2 Department of Global Health, University of Washington , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ronit R. Dalmat Annet Nalutaaya 3 Uganda Tuberculosis Implementation Research Consortium , Walimu, Kampala, Uganda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kamoga Caleb Erisa 3 Uganda Tuberculosis Implementation Research Consortium , Walimu, Kampala, Uganda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Patrick Biché 4 Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health , Baltimore, Maryland, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gabrielle Stein 2 Department of Global Health, University of Washington , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Amanda Ganguloo 5 Umkhuseli Innovation and Research Management , Pietermaritzburg, South Africa 6 Department of Internal Medicine, Harry Gwala Regional Hospital, University of KwaZulu-Natal , Pietermaritzburg, South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Robin Draper 5 Umkhuseli Innovation and Research Management , Pietermaritzburg, South Africa 6 Department of Internal Medicine, Harry Gwala Regional Hospital, University of KwaZulu-Natal , Pietermaritzburg, South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mariam Nantale 3 Uganda Tuberculosis Implementation Research Consortium , Walimu, Kampala, Uganda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Adrienne E. Shapiro 2 Department of Global Health, University of Washington , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Adrienne E. Shapiro Douglas Wilson 5 Umkhuseli Innovation and Research Management , Pietermaritzburg, South Africa 6 Department of Internal Medicine, Harry Gwala Regional Hospital, University of KwaZulu-Natal , Pietermaritzburg, South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Achilles Katamba 3 Uganda Tuberculosis Implementation Research Consortium , Walimu, Kampala, Uganda 7 Clinical Epidemiology & Biostatistics Unit, Department of Medicine, Makerere University College of Health Sciences , Kampala, Uganda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Paul K. Drain 2 Department of Global Health, University of Washington , Seattle, Washington, USA 8 Department of Epidemiology, University of Washington , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Emily A. Kendall 1 Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine , Baltimore, Maryland, USA 4 Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health , Baltimore, Maryland, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Background Some patients who test trace-positive on Xpert MTB/RIF Ultra (“Ultra”), a highly sensitive molecular diagnostic platform, may not have tuberculosis (TB) disease. A better understanding of the prevalence of TB disease, associated clinical characteristics, and utility of additional diagnostic tests among people with trace sputum (PWTS) could aid clinical decision-making. Methods We enrolled adults and adolescents with trace-positive sputum on initial TB diagnostic evaluation in Uganda and South Africa. Participants were extensively evaluated at enrollment; those with uncertain TB status were followed off treatment, with interval reevaluations by TB clinicians, for up to three months. We assessed TB prevalence and associated patient characteristics and diagnostic results. Results Among 311 PWTS, TB was identified by sputum culture at enrollment in 20% of participants (61/311, 95% CI 15-24%). Within three months, 48% (145/301, 95% CI 43-54%) had been judged by clinicians to warrant TB treatment, and among those followed until microbiologic outcomes, 30% (68/227, 95% CI 24-36%) had positive culture and 41% (99/240, 95% CI 35-47%) had positive culture or Ultra. Having TB symptoms, advanced HIV, and no recent TB history were associated with microbiologically-confirmed TB disease, as were an abnormal chest x-ray (in those without recent TB) or elevated CRP. Conclusions Roughly half of PWTS were started on TB therapy. Given the low observed mortality rate, some low-risk people with negative results on widely available diagnostic tests could safely defer treatment. Multimodal testing, repeated evaluations, and longer follow-up duration are needed to fully assess the TB burden in PWTS. Key points: Half of patients with trace results on initial Xpert MTB/RIF Ultra diagnostic testing were diagnosed with TB within three months. Negative HIV status, lack of prior TB treatment, negative chest x-ray, and low C-reactive protein identified patients at lower risk. Background Tuberculosis (TB) detection remains a challenge globally, with an estimated 29% of cases never being formally diagnosed [ 1 ]. Expanding access to rapid molecular diagnostics is a World Health Organization (WHO) priority, as these tools allow for accurate diagnosis of TB, early detection of drug resistance, and prompt initiation of effective therapy [ 1 ]. Xpert MTB/Rif Ultra (“Ultra”; Cepheid), a widely used rapid diagnostic test, achieves sensitivity close to that of culture, partly through incorporation of multi-copy Mycobacterium tuberculosis (MTB) gene targets [ 2 , 3 ]. The lowest level of MTB detection, a category called “trace,” is reported when Ultra detects only these multi-copy targets and not the single-copy-per-genome rpoB target. Trace results have uncertain clinical significance, as the presence of MTB DNA may reflect very low disease burden or remnant material from non-viable bacilli [ 4 ]. In diagnostic evaluations of patients with presumptive pulmonary TB, the trace category has accounted for 8 to 41% of all positive Ultra results [ 5 – 8 ], and as many as 9 in 10 of these trace results have been associated with negative sputum cultures and considered false positives [ 5 ]. However, many of these studies were small and included limited diagnostic evaluations. More extensive diagnostic evaluation, as well as interval reevaluations prior to treatment, could clarify whether some trace results represent disease even when cultures are negative. In addition, while several studies have found that people previously treated for pulmonary TB are especially likely to have trace sputum results and negative cultures [ 6 , 8 , 9 ], little is known about other patient characteristics or test results that might alter the likelihood of TB disease in people with trace-positive sputum (PWTS). Given these gaps in knowledge, current WHO guidelines recommend treating all presumptive TB patients with trace results, with the narrow exception of HIV-negative adults treated for TB within the past five years [ 10 ]. Understanding when a ‘Trace’ result is most likely to indicate TB disease would allow for more nuanced treatment decisions. Therefore, we conducted a prospective cohort study in two countries to better delineate the TB disease status of PWTS during routine TB diagnostic evaluations. Following their initial trace result, participants underwent a systematic diagnostic evaluation, and if their TB status remained uncertain, treatment was deferred, and they were reassessed for evidence of TB disease one month and three months later. We estimated the proportions of patients diagnosed with TB clinically or microbiologically within three months and identified patient characteristics and ancillary diagnostic test results associated with TB disease. Methods Study design, participants, and procedures We recruited adult and adolescent PWTS from routine TB diagnostic evaluations at seven health facilities in Kampala, Uganda, from February 2022 to July 2024, and from outpatient clinics of Harry Gwala Regional Hospital and its catchment area near Pietermaritzburg, South Africa, from November 2022 to June 2024. Study members attempted to recruit and enroll all eligible PWTS. Eligible patients had not yet initiated TB treatment, did not require hospitalization, and had not received TB treatment (both sites) or preventive therapy (South Africa only) within the previous three months. Within 14 days of the initial sputum Ultra result, consenting participants underwent an extensive baseline evaluation that included a standardized interview, physical exam, digital chest x-ray (CXR), repeat sputum Ultra testing, sputum cultures (liquid and solid culture on each of two expectorated specimens), Mtb immunoreactivity testing (QuantiFERON-TB Gold+; Uganda site only), chest CT (Uganda site only), HIV testing, and serum C-reactive protein (LumiraDx [South Africa], ichroma [Uganda]; CRP) measurement. Patients with HIV also underwent urine lipoarabinomannan (LAM) testing and CD4+ T-cell count measurement. Participants who remained untreated after this baseline diagnostic evaluation (by choice or recommendation of a clinician) were reassessed at one and three months with interview, sputum Ultra, sputum culture, CRP, and (at three months) repeat CXR. Monitoring and treatment initiation At the South African site, a three-person panel of study doctors evaluated participants at each visit and determined whether to initiate or continue to defer TB treatment. At the Ugandan site, participants remained under the care of TB clinicians at the referring health facilities, who could start treatment at any time but were encouraged to await study investigations when clinically appropriate, and three-person advisory panels of pulmonologists and a radiologist reviewed new study data and made additional treatment recommendations. Although participants were enrolled to follow for a year or more, this analysis focuses on TB diagnosed within three months, a period interpreted as indicating “prevalent” disease (present at the time of the initial trace Ultra result). Outcomes and missing data Primary analyses use a composite TB reference standard: having MTB complex on sputum culture, a recommendation to start TB treatment (on any microbiological and/or clinical basis), or death attributed to tuberculosis. Sensitivity analyses use more limited microbiological (positive if MTB complex grew on sputum culture or Ultra was positive at a level greater than trace) and culture-only reference standards. All reference standards are assessed at two timepoints: at baseline (considering all tests on specimens from, and treatment decisions based on, the baseline study visit) and within three months (cumulatively). Participants are excluded from any microbiological outcome for which results are missing or uninterpretable, from all three-month outcomes if they missed the three-month visit, and from microbiological outcomes at three months if they initiated treatment before the three-month visit without microbiological confirmation ( Supplemental Table 1). Data analysis Continuous variables are summarized as median and interquartile range (IQR). Prevalence estimates are reported with 95% Wald confidence intervals. We evaluated patient characteristics associated with TB in the cohort using log-binomial and robust Poisson regression. We developed analogous models for each of the three TB reference standards, classifying by the culture-only reference at baseline (to avoid bias from earlier culture-negative TB diagnoses) and the composite and microbiological reference standards at three months. We used forward stepwise selection of patient characteristic variables for each reference standard separately, considering the following variables a priori for inclusion: age (dichotomized at 35 years), gender, country, history of tobacco smoking, recent TB (treated within the past five years), symptoms (cough, weight loss, night sweats, or fever at baseline), recent household TB contact (diagnosed within the past six months), HIV status, and CD4 count (modelled only as an interaction with HIV status and categorized as <200 cells/mm 3 , ≥200 cells/mm 3 , or unknown). All variables selected for any of the three reference standards were included in all final models. A small number of participants with missing covariate data ( Table 1 ) were excluded, except in a sensitivity analysis using multiple imputation (‘mice’ package; Supplement ). View this table: View inline View popup Download powerpoint Table 1: Patient characteristics and baseline diagnostic results for trace-positive participants To the resulting “patient characteristics” models, we subsequently added either CXR results (normal/abnormal, “CXR-added model”) or CRP results (normal/elevated using a threshold of 5 mg/L, “CRP added model”) as an additional covariate. The CXR-added model included an interaction between CXR result and recent TB. We generated receiver operating characteristic (ROC) curves for each model and calculated areas under the ROC curves (AUCs) using the ‘pROC’ package (version 1.18.5). Finally, we used our CXR-added regression model to estimate the risk of TB among a simulated cohort of patients with a specified set of low-risk features – namely, negative HIV status and normal baseline CXR – but no history of TB. Results are reported as the median and IQR of estimated individual-level risks. See Supplemental Methods for further detail. All analyses used R Statistical Software version 4.3.1 (R Core Team, 2023). Ethical approval statement The study was approved by the University of KwaZulu-Natal Biomedical Research Ethics Committee, the Makerere University School of Public Health Research and Ethics Committee, and the institutional review boards at the University of Washington and Johns Hopkins University. Results A total of 311 PWTS (170 in Uganda; 141 in South Africa) were enrolled by the analysis cutoff dates. Another 796 (59 in Uganda; 737 in South Africa) had trace results at participating facilities but were not enrolled, primarily due to distance or inability to make contact ( Figure 1 , Supplemental Figure 1 ). At one and three months, 190 and 162 participants, respectively, remained alive and untreated and completed follow-up visits. Mortality during this three-month period was 0.6% (2/311), with one of the deaths attributed to TB. Download figure Open in new tab Figure 1: Study population overview Flow diagram of patients with trace results on diagnostic evaluation, study enrollment, and visit completion, with reasons for exclusion The cohort was 50% male (155/311) with a median age of 37 ( Table 1 ). HIV prevalence was 57% (178/311), and most participants living with HIV were on antiretroviral therapy (ART) and had CD4 counts greater than 200 cells/mm 3 . Nearly a quarter (24%) had been treated for TB within the past five years, and most had one or more TB symptom. On repeat Ultra testing at baseline, most participants (215/302; 71%) tested negative, but 12% (35/302) tested trace positive (of whom 11 [31%] also had positive baseline sputum cultures) and 17% (52/302) had positive results at a level greater than trace (of whom 32 [62%] had positive cultures). Half of participants (50%; 156/310) had an elevated CRP, and 65% (196/302) had an abnormal CXR ( Table 1 ). Overall, 145 of 301 participants (48%, 95% CI 43-54%) were positive by the composite reference standard by three months ( Figure 2 ). Twenty-five (17%) of these diagnoses were based on additional data obtained during follow up. Eighty-three (57%) were confirmed by Xpert (>trace) or culture ( Supplemental Figure 2 ). Download figure Open in new tab Figure 2: TB prevalence among patients with initial trace Xpert Ultra results, by multiple definitions TB prevalence by the composite, microbiological (Xpert or culture), and sputum-culture only reference standards assessed at baseline and by three months, for the overall cohort and several subgroups. Prevalence estimates are represented as a point estimate and plotted with lines showing their 95% confidence intervals. CD4-count-stratified and symptom-stratified results are shown in Supplemental Figures 4-5 . Of those who could be evaluated using the microbiological reference standard, TB prevalence was 26% (81/311, 95% CI 21-31%) at baseline and 41% (99/240, 95% CI 35-47%) by three months ( Figure 2 ). Some patients with positive microbiological classifications (31/99 [31%] of those positive by 3 months) had positive (>Trace) Ultra results but negative cultures; 16 of these were considered falsely positive with no treatment recommended. When considering sputum culture only, TB prevalence was 20% (61/311, 95% CI 15-24%) at baseline. Among the entire cohort, 68/311 (22%) had at least one positive culture by three months, with seven participants having newly positive cultures during follow up; three-month prevalence by the culture reference standard (after excluding 84 who had started treatment without culture confirmation (72 participants) or were missing three-month culture results (12) was 30% (68/227, 95% CI 24-36%). In univariate analysis, TB was associated with male gender, HIV positivity, low or unknown CD4 count, TB symptoms, and a lack of recent TB treatment history, as well as with diagnostic results of abnormal CXR (particularly in those without recent TB) and elevated CRP ( Table 2 , Supplemental Tables 5-6 ). A positive or trace repeat Ultra was associated with a prevalence ratio (PR) of having TB of 2.2 [95% CI 1.8-2.7] for the three-month composite reference standard and 5.9 (95% CI 3.6-9.6) by the baseline culture-positive reference standard ( Supplemental Table 3 ). View this table: View inline View popup Download powerpoint Table 2: Multivariate log-binomial regression model coefficients for discriminating TB vs no TB, using composite reference standard over 3 months In multivariable regression, TB (defined by the composite reference standard by three months) remained positively associated with advanced HIV (CD4 <200 cells/mm 3 : PR 2.0 [95% CI 1.2-3.3]) and TB symptoms (PR 3.1 [95% CI 1.5-7.8]) and inversely associated with recent TB (PR 0.6 [95% CI 0.3-0.9]) ( Table 2 ). When considering additional diagnostic test results, either an abnormal CXR (in those without recent TB: PR 1.8 [95% CI 1.2-2.8]) or an elevated CRP (PR 1.7 [95% CI 1.2-2.5]) was associated with greater likelihood of having TB. Results for alternative reference standards were largely similar, though associations with TB history and CXR results were weaker when using the microbiological reference standard that classified all people with positive Ultra results as having TB ( Supplemental Tables 5-6 ). A sensitivity analysis using multiple imputation of missing data produced generally similar results ( Supplemental Table 7 ). The patient characteristics regression model classified TB status (composite reference standard, three months) with an AUC of 0.76 (95% CI 0.71-0.82) by. This AUC increased to 0.80 (95% CI 0.75-0.85) or 0.79 (95% CI 0.74-0.84) after adding CXR or CRP, respectively ( Figure 3 ). AUCs were similar for the other reference standards ( Supplemental Figure 4) . Download figure Open in new tab Figure 3: Receiver operating characteristic curves for the basic characteristics, CXR-added, and CRP-added models using the composite reference standard over 3 months When we applied the CXR-added regression model to the simulated “low-risk” cohort of HIV-negative patients with normal baseline CXRs (but no recent history of TB), the median risk of TB (by the composite reference standard) was 27% (IQR 22-30%). Discussion Our study offers a detailed look into the disease status and clinical and microbiological profiles of the largest cohort to date of patients with trace Ultra sputum diagnostic test results. More than 300 patients from multiple facilities in two high-prevalence countries were followed untreated for up to three months to clarify their TB status. Nearly half were diagnosed with TB within three months, including 41% with some microbiological confirmation. Baseline sputum culture (on which 20% of patients tested positive) did not capture the full burden of TB. Still, half of patients did not have sufficient evidence to diagnose TB despite three months of extensive testing. Across multiple TB definitions, patient characteristics associated with TB in this population included advanced HIV, TB symptoms at the time of enrollment, and having no recent history of TB treatment. Results of CXR and CRP testing further aided in risk-stratifying patients. Accurately defining TB disease is a challenge when studying TB prevalence. Sputum culture, while often the gold standard, can be insufficiently sensitive to detect active pulmonary disease with low bacillary burden [ 11 ]. TB disease burden may also wax and wane [ 12 , 13 ], limiting detection through one-time evaluations. We considered TB diagnosed within three months of a trace result, a timeframe chosen to allow for multiple reassessment opportunities and sufficient disease progression in cases of recent primary exposure, yet short enough that any TB that was identified was likely to explain the initial trace result. Using multiple TB reference standards and repeated evaluations allowed us to more fully capture active disease near the limit of detection and generally demonstrated consistent associations of patient characteristics with TB across definitions. The TB burden estimated in our trace cohort is similar or higher compared to others which have used a sputum culture reference [ 5 – 9 ]. While TB prevalence varies by definition, we take our study’s most conservative estimate of true TB burden to be 22%, the proportion of our originally enrolled cohort (68/311) with a positive culture within three months. At the upper end of plausible true prevalence, our composite (48%) and microbiological (41%) prevalence estimates may be inflated by clinical overdiagnosis and false-positive Ultra results, respectively. Still, our results may underestimate TB prevalence among all PWTS, because two excluded groups – those empirically treated for TB before test results returned, and those requiring hospitalization -- may have particularly high likelihood of having TB disease. In general, our prevalence estimates are high enough to support treatment for most PWTS in high-burden settings when further testing and follow up is not feasible. We were able to identify characteristics significantly associated with TB among PWTS. Consistent with other studies [ 6 , 8 , 9 ], we found that trace results in patients with a recent history of TB treatment were less likely to indicate current active disease. In addition, although most participants in our cohort reported TB symptoms, being asymptomatic at baseline also conferred a roughly three-fold lower risk. PWTS identified through targeted universal TB testing strategies [ 14 , 15 ] may therefore be less likely to have true TB than those identified through symptom-driven testing. Finally, we found that advanced HIV was associated with microbiologically- and culture-confirmed TB among PWTS. This finding supports current WHO guidelines’ recommendation to treat patients with HIV who have a trace result [ 10 ], not only because of their elevated risk for serious illness if TB goes untreated, but also due to a higher burden of true TB. Our results also suggest that additional diagnostic testing after a trace result can inform disease probability estimates. A normal CXR (in those without recent TB) and a normal CRP were associated with a one-and-a-half-to three-fold lower TB risk across multiple definitions, although the absolute improvement in TB status classifications (as measured by AUC) was small. In addition, where a previous review found that evidence regarding repeat Ultra testing was lacking [ 16 ], our results indicate that a negative result on a repeat Ultra test reduces TB likelihood by at least half, depending on the reference standard ( Supplemental Table 3 ). Therefore, although we were unable estimate the predictive accuracy of diagnostic results within all subgroups PWTS, our cohort-wide results suggest that a negative diagnostic result on any of several widely available diagnostic tests – CXR, CRP, and repeat Ultra – could support deferring treatment for an otherwise low-risk patient whose estimated probability of TB after the initial trace result is near a clinician’s treatment threshold ( Supplemental Table 4 ). Our study has several limitations. First, limiting enrollment to patients who had not yet initiated TB treatment may have disproportionately excluded more ill patients (especially in South Africa, where nearly 1 in 10 PWTS started treatment before they could be recruited). Therefore, our results apply primarily to patients whose TB status is sufficiently uncertain that a treating clinician would defer empiric treatment based on clinical presentation alone and await diagnostic testing. Similarly, among those enrolled, participants who were more ill were more likely to be clinically diagnosed early in follow up, limiting later opportunities to detect MTB microbiologically and potentially biasing the three-month microbiological-based prevalence estimates. In addition, there may have been differences by study site in microbiological testing sensitivity (e.g. the second sputum culture specimen was collected in the early morning in Uganda, where baseline culture-positive prevalence was higher) and in clinicians’ threshold for clinical diagnosis (particularly in the context of HIV co-infection). Notably, national guidelines in Uganda advise treatment for patients with trace results, while South African guidelines defer to clinician judgment [ 15 , 17 ]. Finally, the three-month timeframe of our current analysis could be too brief to detect slowly progressing disease. In conclusion, our study suggests that the TB prevalence among PWTS is high, but that up to half of PWTS do not have clinically or microbiologically evident TB even with three months of repeated culture, molecular testing, and clinical evaluations. While roughly half of PWTS likely warrant treatment, lower-risk characteristics, favorable diagnostic results, and low mortality rates in this observed cohort, may offer reassurance to clinicians considering treatment deferral with repeated clinical review and TB testing for select patients. Funding This work was supported by the Bill and Melinda Gates Foundation (INV-042921 to EAK and OPP1213504 to PKD) and the US National Institutes of Health (R01HL153611 to EAK). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data Availability Data available on reasonable request. Please direct such requests to Dr. Emily A. Kendall at ekendall{at}jhmi.edu and Dr. Paul K. Drain at pkdrain{at}uw.edu . Conflicts of Interest No conflicts of interest declared for any co-author. Author Contributions CV drafted the statistical analysis plan, performed the data analysis, and drafted the manuscript, with supervision from EAK. RRD contributed to the analytic approach, data curation and interpretation, and editing of the manuscript. AN, PB, and GS managed data curation. KCE and MN coordinated data acquisition in Uganda, and RD and AG conducted patient visits and data acquisition in South Africa. EAK and PKD conceptualized and supervised the study, and AS, DW, and AK all contributed to administration of the project and interpretation of results. All authors reviewed and approved the final manuscript. Acknowledgements This work would not be possible without the support of the staff of Harry Gwala Regional Hospital and referring primary health care clinics, the KwaZulu-Natal Department of Health, the South African National Health Laboratory Service, the TURN-TB research team and physician consultants, and the clinical and laboratory staff at Kitebi Health Centre, Kisugu Health Centre, Kisenyi Health Centre, Kawaala Health Centre, Kiswa Health Centre, Naguru Hospital, and Mulago Hospital Wards 5&6. 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OpenUrl Abstract / FREE Full Text 4. ↵ Planning for country transition to Xpert® MTB/RIF Ultra cartridges: Global Laboratory Initiative, Stop TB Partnership, 2017 April 2017 . 5. ↵ Chilukutu L , Mwanza W , Kerkhoff AD , Somwe P , Kagujje M , Muyoyeta M . Prevalence and interpretation of Xpert Ultra trace results among presumptive TB patients . Public Health Action 2022 ; 12 ( 1 ): 28 – 33 . OpenUrl PubMed 6. ↵ Dorman SE , Schumacher SG , Alland D , et al. Xpert MTB/RIF Ultra for detection of Mycobacterium tuberculosis and rifampicin resistance: a prospective multicentre diagnostic accuracy study . Lancet Infect Dis 2018 ; 18 ( 1 ): 76 – 84 . OpenUrl CrossRef PubMed 7. Biswas S , Uddin MKM , Paul KK , et al. Xpert MTB/RIF Ultra assay for the detection of Mycobacterium tuberculosis in people with negative conventional Xpert MTB/RIF but chest imaging suggestive of tuberculosis in Dhaka, Bangladesh . Int J Infect Dis 2022 ; 114 : 244 – 51 . OpenUrl PubMed 8. ↵ Mishra H , Reeve BWP , Palmer Z , et al. Xpert MTB/RIF Ultra and Xpert MTB/RIF for diagnosis of tuberculosis in an HIV-endemic setting with a high burden of previous tuberculosis: a two-cohort diagnostic accuracy study . Lancet Respir Med 2020 ; 8 ( 4 ): 368 – 82 . OpenUrl PubMed 9. ↵ Dowling WB , Whitelaw A , Nel P . Tracing TB: Are there predictors for active TB disease in patients with Xpert Ultra trace results? Int J Infect Dis 2022 ; 114 : 115 – 23 . OpenUrl PubMed 10. ↵ WHO operational handbook on tuberculosis: Module 3: Diagnosis – Rapid diagnostics for tuberculosis detection Geneva: World Health Organization , 2021 . 11. ↵ Coussens AK , Zaidi SMA , Allwood BW , et al. Classification of early tuberculosis states to guide research for improved care and prevention: an international Delphi consensus exercise . Lancet Respir Med 2024 ; 12 ( 6 ): 484 – 98 . 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Geneva , 2021 . 17. ↵ Uganda National Tuberculosis and Leprosy Control Programme: Manual for Management and Control of Tuberculosis and Leprosy . 4th ed: Ministry of Health , 2024 . View the discussion thread. Back to top Previous Next Posted May 18, 2025. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Prevalence and predictors of tuberculosis in adults and adolescents with sputum trace Ultra results in two high-burden clinical settings Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. 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