Abstract
Background
The World Health Organization (WHO) recommends stool as an alternative respiratory sample (RS) for diagnosing pulmonary tuberculosis (PTB) in children <10 years. This study assessed stool-Xpert-Ultra diagnostic performance against microbiologically confirmed (MC-PTB) cases identified based on the composite reference standard (CRS) in children <15 years, stratified by age and nutritional status.
Methods
Children <15 years with presumptive PTB were assessed at 2 tertiary-care hospitals in Pakistan. Stools and RS were tested using Xpert MTB/RIF-Ultra (Xpert-Ultra) and culture. Using the CRS, PTB cases were MC-PTB or clinically confirmed. Nutritional status was classified using WHO criteria. Stool-Xpert-Ultra diagnostic performance was assessed against MC-PTB or positive RS-Xpert-Ultra. Logistic regression identified predictors of microbiological yields.
Results
Among 650 children, we obtained 587 RS, 258 stool and 195 both stool and RS. Of 650, 264 (41%) had MC and 136 (21%) had clinically confirmed PTB. Stool-Xpert-Ultra had sensitivity, specificity, and accuracy of 47%, 88%, 77%, and 72%, 73%, 72% against MC-PTB in children <10 and ≥10, respectively. Stool-Xpert-Ultra performed similarly against RS-Xpert-Ultra in each age group. Stool-Xpert-Ultra detected 11% additional MC-PTB cases when RS was negative or unavailable. Stool-Xpert-Ultra had high sensitivity (64%) in severely acute malnourished (SAM) children. Age ≥10, female, SAM and TB-consistent chest X-rays were strongly associated with stool and RS microbiological positivity.
Conclusions
Stool-Xpert-Ultra demonstrated moderate sensitivity against MC-PTB in <10. It identified additional MC-PTB cases when RS was unavailable or/negative, making it a valuable noninvasive alternative, especially in children ≥10 and with SAM, where it missed fewer cases.
Keywords: childhood pulmonary TB, respiratory samples, severe acute malnutrition, stools, Xpert-Ultra
Stool-Xpert-Ultra demonstrated moderate sensitivity and high specificity for pediatric pulmonary TB, with improved performance in children ≥10 years and those with malnutrition. It identified 11% additional cases, supporting its role as a noninvasive diagnostic tool in resource-limited settings.
Childhood tuberculosis (TB) remains a significant global health challenge, contributing to high morbidity and mortality [1]. In 2023, an estimated 1.25 million children aged <15 had TB, accounting for 12% of global TB cases [1]. Childhood TB results in approximately 166 000 deaths annually, representing 15% of all TB-related deaths [1]. However, 96% of these childhood TB-related deaths globally occur in those who remain untreated, and more than 40% of these deaths happen in the first 5 years of their life [2]. Pakistan ranks among the top 5 countries for TB burden, with child mortality rates from TB surpassing global averages, particularly in children under 5 (5.6% vs 2.7%) [1, 3].
Early diagnosis and treatment are crucial, as childhood TB is curable [1]. However, diagnosis remains challenging due to the nonspecific symptoms and low bacillary load [4]. While culture is the diagnostic gold standard for pulmonary TB (PTB), it has low yields, takes 4 to 6 weeks, and is not widely accessible [4]. Smear microscopy is more available but has a very low diagnostic yield in children [4]. Cartridge-based nucleic acid amplification tests, such as the Xpert MTB/RIF assay (Xpert) and Xpert MTB/RIF-Ultra (Xpert-Ultra), show promising results in adults [5], but have varying sensitivities in children based on the sample type [4]. TB diagnostic algorithms have been developed for children, but without microbiological confirmation (MC), they have limited specificity, leading to false-positive diagnoses and unnecessary anti-TB treatment (ATT) [4].
Sputum is the main sample for MC-PTB. However, younger children cannot produce sputum, necessitating invasive procedures such as gastric aspirates (GAs) or bronchoalveolar lavage [4]. These procedures are resource-intensive, invasive, and often unavailable in low-resource settings. Thus, there is a need for noninvasive alternatives to support wider use of Xpert-Ultra. The World Health Organization (WHO) recommends stool as an alternative to respiratory samples (RS) for PTB diagnosis in children <10 [6]. This study assessed stool-Xpert-Ultra diagnostic performance against MC-PTB identified based on the composite reference standard (CRS) criteria [7], and compared the performance with any RS-Xpert-Ultra (GA and/or sputum) in children <15, stratified by age and nutritional status. Furthermore, we determined the association of demographic factors, nutritional status and chest X-Ray findings consistent with TB with positive yield of stool-Xpert-Ultra and any RS-Xpert-Ultra/culture in our study population.
METHODS
Study Design, Setting and Population
In this prospective cohort study, we screened children <15 years with presumptive PTB at 2 tertiary care hospitals, Gulab Devi Teaching Hospital and the University of Child Health Sciences, Children Hospital, Lahore, Pakistan, from December 2022 to April 2024. These hospitals collaborate with the Provincial TB Control Program in Punjab and provide WHO-endorsed TB diagnostic and treatment facilities. Children with presumptive PTB were enrolled if at least 1 stool or RS was collected, and written informed consent was obtained from a parent/guardian. Presumptive PTB was defined as the presence of persistent cough >2 weeks, fever, weight loss, or failure to thrive (Supplementary Table 1). Exclusion criteria included children already receiving ATT or who had received it in the past 12 months, or those whose parents/guardians did not give consent. For the current analysis, we excluded children with extrapulmonary TB without pulmonary involvement.
Procedure
We trained a data collection team to collect information using electronic case report forms with unique study identification numbers. We consecutively enrolled eligible children and assessed them for PTB and nutritional status using standard methods [8]. Based on the WHO criteria, nutritional status was classified as severe acute malnutrition (SAM), moderate acute malnutrition (MAM), or normal [8]. Chest X-ray were performed in the anteroposterior and posteroanterior views for children <2 and ≥2 years, respectively, and interpreted by a radiologist using the WHO criteria [6] (Supplementary Table 1).
Sputum samples (n = 159) were collected when possible. If sputum was unavailable, children underwent GA (n = 414) collection after fasting for at least 4 hours. Stools (n = 63), as a single sample, were obtained if RS were not collected. Furthermore, we collected both stools and RS (n = 195) from a subset of children, based on the sample size calculation as outlined below. The stool sample was collected randomly from among all enrolled children with RS. We provided labeled containers and instructed parents to collect and return stools within 24 hours. Xpert-Ultra, culture and smear microscopy for acid-fast bacilli were performed on both RS and stool samples. A standard laboratory process for Xpert-Ultra was used [9]. The WHO-recommended Simple 1-step stool processing method (SOS) was used to analyze stools at the Microbiology Laboratory of Gulab Devi Teaching Hospital [10](Supplementary Panel 1). Moreover, for this study, we defined any RS-Xpert-Ultra as inclusion of any one of these—sputum-Xpert-Ultra, GA-Xpert-Ultra, bronchial wash-Xpert-Ultra, pleural effusion-Xpert-Ultra. Auramine O-stained smears were examined using a fluorescence microscope with light-emitting diode illumination [11]. For culture, Lowenstein-Jensen medium and a Mycobacteria Growth Indicator Tube (MGIT) 960TM from Becton Dickinson, Sparks, MD, USA, were used [12].
Classification
Definitions of all terms, including presumptive PTB, criteria for identification of PTB according to the composite reference standard (CRS) [7] and site and disease severity according to the WHO criteria [6], are provided in Supplementary Table 1. Children with presumptive PTB were classified as confirmed PTB, unconfirmed PTB, or unlikely PTB based on the CRS [7]. Confirmed and unconfirmed PTB cases started ATT and were reassessed at 2, 4, and 8 weeks. We defined “PTB cases” as either “microbiologically confirmed PTB” (MC-PTB) or “clinically confirmed PTB” with clinical confirmation established after 8 weeks of ATT response according to the CRS criteria [7]. Further, children with unlikely TB were also followed up at 8 weeks to reassess their health status and reconfirm the diagnosis.
Sample Size
The sample size was calculated to estimate the sensitivity of stool-Xpert-Ultra for PTB diagnosis in children <15 years. An expected sensitivity of 50% [6], a 95% confidence level, and a desired precision of ±10% were assumed. Using the standard formula for estimating proportions [13], the required sample size was 96 children with stool-Xpert-Ultra. To ensure sufficient power for stratified analyzes (age and nutritional status), this sample size was doubled.
Statistical Analysis
We analyzed data using Stata MP 13.0 (StataCorp LLC, College Station, Texas 77845 USA). Descriptive statistics summarized demographic and clinical characteristics, and we performed the Chi-square test to determine the difference between the 2 age groups—age <10 and ≥10 years. We evaluated the positive rates of various diagnostic tests across different samples, including stool-Xpert-Ultra, as a single sample, in PTB cases and culture-confirmed TB cases, stratified by age. We used the composite reference standard criteria [7], which categorized children into 3 categories—MC-PTB, clinically confirmed or no TB. However, for the diagnostic performance of stool-Xpert-Ultra, we classified children (based on CRS) into 2 categories: MC-PTB and clinically confirmed/no TB. Further, we also performed diagnostic performance of stool-Xpert-Ultra against any RS-Xpert-Ultra, GA-Xpert-Ultra, or sputum-Xpert-Ultra. We calculated sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy along with 95% confidence intervals (95% CI), stratified by age (<10 and ≥10) and nutritional status (normal, MAM or SAM). When using CRS as the reference standard to calculate the diagnostic performance of stool-Xpert-Ultra, stool samples, single and paired samples with RS, were combined. However, when using any RS-, GA-, or sputum-Xpert-Ultra as a reference standard to calculate diagnostic performance of stool-Xpert-Ultra, only paired stool samples, collected concurrently (within 24 hours) with the specific RS (for example, sputum or GA), were included to ensure temporal alignment for diagnostic performance comparisons. We performed multivariate logistic regression models to analyze associations between age groups, sex, nutritional status, and chest X-ray findings with positive microbiological yields (dependent variable: positive stool-Xpert-Ultra or positive RS-Xpert-Ultra/culture), reporting adjusted odds ratios (OR) with 95% CI.
Ethics
The institutional review boards of both hospitals (No. 591/UCHS, CHL, AAMC/IRB/35/2022) and the regional Committee for Medical Research Ethics in Norway (2023/532676/REK Vest) approved the study. After explaining the study in local languages, written informed consent was obtained from parents/caregivers. For illiterate participants, thumb impressions were collected in the presence of 2 witnesses, and assent was obtained from children >12 years.
RESULTS
Among 751 children with presumptive PTB, we obtained 845 samples to diagnose TB from 650 (87%) children (Figure 1). Of 845 samples, 587 were RS (392 only RS and 195 as paired samples along with stool), and 258 were stool samples (63 only stool and 195 samples paired with RS). We observed 41% and 35% positivity when only RS (162/392) or only stool samples (22/63) were obtained, respectively. Among 195 children with paired samples (stool as well as RS), 40 (20%), 32 (16%) and 8 (4%) were positive on both (stool as well as RS), only on RS, and only on stool samples, respectively. Among 650 children with at least 1 sample based on CRS, 400 (62%) were classified as PTB cases, 264/400 (66%) MC-PTB, 136/400 (34%) clinically confirmed, and 250 (38%) were unlikely TB. Of 264 MC-PTB cases, 74% (n = 194) were positive only on RS, 15% (n = 40) on both (stool and RS) and 11% (n = 30) only on the stool sample.
Figure 1.
Study flow diagram.
Table 1 depicts the comparison of baseline characteristics of children <10 and ≥10. Of 650 children, 339 (52%) were <10 years. Females notably outnumbered males in children ≥10 (68% vs 32%) compared to those <10 (45% vs 55%). GA was collected from 71% and 53%, and sputum from 13% and 37% in children <10 and ≥10, respectively. The chest X-ray findings consistent with TB were significantly higher in ≥10 compared to <10 (58% vs 45%, P-value = .0005). Among PTB cases (n = 400), MC-PTB cases were significantly higher in ≥10 than <10 (72% vs 59%, P-value = .005). The majority of children had severe disease in both age groups (69% and 72%).
Table 1.
Demographic Features, Nutritional Status, and Samples Obtained From Children With Presumptive Pulmonary TB by Age Category (n = 650)
| Characteristic | Age <10 y | Age ≥10 y | P Valuec |
|---|---|---|---|
| (N = 339), n (%) | (N = 311), n (%) | ||
| Sex | <0.0001 | ||
| Female | 152 (45) | 211 (68) | |
| Male | 187 (55) | 100 (32) | |
| Nutritional statusa | 0.091 | ||
| Normal | 144 (42) | 120 (39) | |
| Moderate acute malnutrition (MAM) | 86 (25) | 67 (21) | |
| Severe acute malnutrition (SAM) | 109 (32) | 124 (40) | |
| Sample | 0.538 | ||
| Stools, as a single sample | 45 (13) | 18 (6) | |
| Gastric aspirate | 239 (71) | 164 (53) | |
| Sputum (induced/expectorated) | 45 (13) | 114 (37) | |
| Pleural fluid | 9 (3) | 14 (4) | |
| Bronchial wash | 1 (<1) | 1 (<1) | |
| Stools as a paired sampleb | 137 (40) | 58 (19) | |
| Chest-X-rayd | 0.93 | ||
| Normal | 64 (19) | 46 (15) | |
| Other abnormal findings | 23 (7) | 20 (6) | |
| Consistent with TB | 151 (45) | 181 (58) | |
| No radiograph performed | 101 (30) | 64 (21) | |
| Diagnosis based on the composite reference standard | 0.001 | ||
| Microbiologically confirmed TB | 103 (30) | 161 (52) | |
| Clinically confirmed TB | 73 (22) | 63 (20) | |
| Unlikely TB | 163 (48) | 87 (28) | |
| Pulmonary TB severity | 0.436 | ||
| Non-severe | 55 (31) | 62 (28) | |
| Severe | 121 (69) | 162 (72) |
aClassified according to WHO criteria: Weight for Height/Length (WFH/L) >−3 = SAM, WFH/L −2 to −3 = MAM, WFH/L >−2 = Normal.
bMutually not exclusive.
c P-value for the difference between children <10 y and ≥10 y of age.
dChest X-ray consistent with TB defined as the presence of any one of the following: opacity, cavity, enlarged lymph nodes, miliary pattern, or effusion. Other abnormal findings are defined as abnormalities other than those consistent with TB.
Within PTB cases (n = 400), Xpert-Ultra was performed on 38 stool samples collected as the only sample (Table 2). Among these 38 children, stool-Xpert-Ultra showed an overall positive rate of 58% (missing 42% PTB cases), with 48% in <10 (missing 52% PTB cases) and 77% in ≥10 (missing 23% PTB cases). Similarly, among 400 PTB cases, Xpert-Ultra was performed on 342 any RS, and the overall positive rate was 65%, while it was 60% and 69% in <10 and ≥10, respectively. The overall highest positive rate was with sputum (75%, 73/93), while the lowest was with stool when obtained as a paired sample along with RS (40%, 48/119) among PTB cases. Culture and smear showed a lower positivity compared to Xpert-Ultra; however, when culture was used as the gold standard, Xpert-Ultra demonstrated 93%–100% sensitivity across all samples.
Table 2.
Positive Results of Different Diagnostic Tests Performed on the Stools and Respiratory Samples of Children With Pulmonary TB and Culture-confirmed TB by Age category
| Reference Standards | Samples | Xpert-Ultra, n/N (%) | Culture n/N (%) | Smear n/N (%) | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| < 10 y | ≥10 y | Overall | <10 y | ≥10 y | Overall | <10 y | ≥10 y | Overall | ||
| PTB cases (n = 400) | Stools as a single samplea | 12/25 (48) | 10/13 (77) | 22/38 (58) | 2/10(20) | 1/9 (11) | 3/19 (16) | 1/21 (4) | 1/9 (11) | 2/30 (7) |
| Any respiratory sample | 82/136 (60) | 142/206 (69) | 224/342 (65) | 27/110 (24) | 88/169 (52) | 115/280(41) | 12/133(9) | 61/200(0.3) | 73/333(22) | |
| Gastric aspirate | 61/104 (59) | 81/125 (65) | 142/229 (62) | 15/86 (17) | 55/107 (51) | 70/193 (36) | 6/102(6) | 33/122 (27) | 39/224 (17) | |
| Sputum | 16/24 (67) | 57/73 (78) | 73/97 (75) | 11/19 (58) | 33/54 (61) | 44/73 (60) | 5/24(21) | 28/70 (40) | 33/94 (35) | |
| Pleural fluid | 4/7 (8) | 4/8 (50) | 8/15 (53) | 1/4 (25)0 | 0/8 (0) | 1/13 (8) | 0/6 (0) | 0/8 (0) | 0/14 (0) | |
| Bronchial wash | 1/1 (100) | 0/0 (0.0) | 1/1 (100) | 0/1 (0) | 0/0 (0.0) | 0/1 (0) | 1/1 (100) | 0/0 (0.0) | 1/1 (100) | |
| Stools as paired samplea | 26/77 (34) | 22/42 (52) | 48/119 (40) | 3/62(4) | 1/34 (3) | 4/96 (4) | 1/35 (3) | 2/27 (7) | 3/60 (5) | |
| Culture-confirmed TB (n = 120) | Stools as a single sampleb | 2/2(100) | 1/1 (100) | 3/3 (100) | … | … | … | 1/2 (50) | 0/1 (0) | 1/3 (33) |
| Gastric aspirate | 14/14 (100) | 52/55 (95) | 66/69 (96) | … | … | … | 3/14 (21) | 23/54 (43) | 26/68 (38) | |
| Sputum | 9/10 (90) | 31/33 (94) | 40/43 (93) | … | … | … | 5/11(45) | 21/33 (64) | 26/44 (59) | |
| Pleural fluid | 1/1 (100) | 0/0 (0.0) | 1/1 (100) | … | … | … | 0/1 (0) | 0/0 (0.0) | 0/1 (0) | |
| Stools as paired sampleb | 3/3 (100) | 1/1 (100) | 4/4 (100) | … | … | … | 1/2 (50) | 1/1 (100) | 2/3 (67) | |
Abbreviations: n, number of positive cases; N, total number of test performed.
Xpert-Ultra was performed on all samples, whereas culture and smear were not performed on all samples, therefore, N is different.
aOf 157 PTB cases, 70 (45%) were positive on any stool sample.
bOf 7 culture confirmed PTB cases, all (100%) were positive on any stool sample.
Table 3 presents findings of diagnostic accuracy of stool-Xpert-Ultra against CRS (MC-PTB) and any RS-Xpert-Ultra (GA and sputum) positive results stratified by age and nutritional status. Among the 258 children with stool-Xpert-Ultra (single or paired samples), the overall sensitivity was 56% (95%CI 43%–67%) against MC-PTB, missing 44% cases. Among <10 and ≥10, stool-Xpert-Ultra showed sensitivity of 47% and 72%, respectively, while it was 65% in children with SAM. Among 180 positive results on any RS-Xpert-Ultra, stool-Xpert-Ultra showed an overall sensitivity of 56% (95%CI 43%–68%), missing 44% of any RS-Xpert-Ultra positive cases. However, its sensitivity was 47% and 72% against positive results on any RS-Xpert-Ultra in <10 and ≥10, respectively. Stool-Xpert-Ultra showed 58% sensitivity against GA-Xpert-Ultra with the highest sensitivity (80%) in children ≥10. The stool-Xpert-Ultra showed the highest diagnostic accuracy (91%) and 100% specificity against sputum-Xpert-Ultra while the sensitivity was highest in children > 10 (67%) as compared to children < 10 (50%).
Table 3.
Diagnostic Accuracy of Stool Xpert-Ultra Against Different Reference standards
| References | Stratification Criteria | Sensitivity, n/N, % (95% CI) | Specificity, n/N, % (95% CI) | PPV, n/N, % (95% CI) | NPV, n/N, % (95% CI) | Accuracy, n/N, % (95% CI) | |
|---|---|---|---|---|---|---|---|
| CRS based classification (n = 258) a | Age category (y) | <10 | 22/47, 47 (32–62) | 119/135, 88 (81–93) | 22/38, 58 (44–70) | 119/144, 83 (78–86) | 141/182, 77 (71–83) |
| ≥10 | 18/25, 72 (51–88) | 37/51, 73 (58–84) | 18/32, 56 (44–68) | 37/44, 84 (73–91) | 55/76, 72 (61–82) | ||
| Nutritional status | Normal | 12/24, 50 (29–71) | 74/82, 47 (21–73) | 12/20, 60 (45–74) | 74/86, 37 (23–53) | 86/106, 49 (32–65) | |
| MAM | 6/14, 43 (18–71) | 43/50, 86 (73–94) | 6/13, 46 (25–68) | 43/51, 84 (77–90) | 49/64, 77 (64–86) | ||
| SAM | 22/34, 65 (47–80) | 39/54, 72 (58–83) | 22/37, 59 (47–71) | 39/51, 76 (67–84) | 61/88, 69 (59–79) | ||
| Overall | 40/72, 56 (43–67) | 156/186, 84 (78–89) | 40/70, 57 (47–66) | 156/188, 83 (79–86) | 196/258, 76 (70–81) | ||
| Any RS-Xpert-Ultra for confirmation (n = 180)b | Age category (y) | <10 | 20/43, 46 (31–62) | 76/80, 95 (88–99) | 20/24, 83 (65–93) | 76/99, 77 (71–81) | 96/123, 78 (70–85) |
| ≥10 | 18/25, 72 (51–88) | 28/32, 87 (71–96) | 18/22, 82 (63–92) | 28/35, 80 (68–88) | 46/57, 81 (68–90) | ||
| Nutritional status | Normal | 12/23, 52 (31–73) | 52/55, 94 (85–99) | 12/15, 80 (55–93) | 52/63, 82 (75–88) | 64/78, 82 (72–90) | |
| MAM | 5/12, 42 (15–72) | 29/31, 94 (79–99) | 5/7, 71 (36–92) | 29/36, 81 (72–87) | 34/43, 79 (64, 90) | ||
| SAM | 21/23, 64 (45–80) | 23/26, 88 (70–98) | 21/24, 87 (70–95) | 23/35, 66 (54–75) | 44/59, 75 (62–85) | ||
| Overall | 38/68, 56 (43–68) | 104/112, 93 (86–97) | 38/46, 83 (70–90) | 104/134, 78 (72–82) | 142/180, 79 (72–85) | ||
| GA-Xpert-Ultra (n = 137)c | Age category (y) | <10 | 17/37, 46 (30–63) | 60/64, 94 (85–98) | 17/21, 81 (61–92) | 60/80, 75 (69–80) | 77/101, 76 (67–84) |
| ≥10 | 16/20, 80 (56–94) | 14/16, 87 (62–98) | 16/18, 89 (68–97) | 14/18, 78 (59–90) | 30/36, 83 (67–94) | ||
| Nutritional status | Normal | 10/20, 50 (27–73) | 40/42, 95 (84–99) | 10/12, 83 (55–95) | 40/50, 80 (72–86) | 50/62, 81 (69–90) | |
| MAM | 4/10, 40 (12–74) | 19/20, 95 (75–100) | 4/5, 80 (34–97) | 19/25, 76 (65–84) | 23/31, 77 (58–90) | ||
| SAM | 19/27, 70 (50–86) | 15/18, 83 (59–96) | 19/22, 86 (69–95) | 15/23, 65 (50–78) | 34/45, 76 (60–87) | ||
| Overall | 33/57, 58 (44–71) | 74/80,92 (84–97) | 33/39, 85 (72–92) | 74/98, 75 (69–81) | 107/137, 78 (70–85) | ||
| Sputum-Xpert-Ultra (n = 32)d | Age category (y) | <10 | 2/4, 50 (7–93) | 12/12, 100 (73–100) | 2/2, 100 (16–100) | 12/14, 86 (69–94) | 14/16, 87 (62–98) |
| ≥10 | 2/3, 67 (9–99) | 13/13, 100 (75–100) | 2/2, 100 (16–100) | 13/14, 93 (72–98) | 15/16, 94 (70–100) | ||
| Nutritional status | Normal | 2/2, 100 (16–100) | 9/9, 100 (66–100) | 2/2, 100 (16–100) | 9/9, 100 (66–100) | 11/11, 100 (71–100) | |
| MAM | 1/1, 100 (2–100) | 8/8, 100 (63–100) | 1/1, 100 (2–100) | 8/8, 100 (63–100) | 9/9, 100 (66–100) | ||
| SAM | 1/4, 25 (1–81) | 8/8, 100 (63–100) | 1/1, 100 (2–100) | 8/11, 72 (60–82) | 9/12, 75 (43–94) | ||
| Overall | 4/7, 57 (18–90) | 25/25, 100 (86–100) | 4/4, 100 (40–100) | 25/28, 89 (78–95) | 29/32, 91 (75–98) | ||
Abbreviations: PPV, positive predictive value; NPV, negative predictive value; MAM, Moderate acute malnutrition; SAM, Severe acute malnutrition; CI, confidence interval; CRS, Composite Reference Standard; RS, Respiratory Sample.
aStool samples were combined (single and paired samples) for this analysis, and their results were not included in the MC-PTB definition. Of 258, 72 were MC-PTB on RS and 186 were clinically confirmed or unlikely PTB using the CRS.
bChildren in whom we obtained both stool and any RS were selected for this analysis. Of 180, 68 had positive results on any RS-Xpert-Ultra, while 112 were negative on any RS-Xpert-Ultra.
cChildren in whom we obtained both stool and GA samples were selected for this analysis. Of 137, 57 had positive results on GA-Xpert-Ultra, while 80 were negative on GA-Xpert-Ultra.
dChildren in whom we obtained both stool and sputum samples were selected for this analysis. Of 32, 7 had positive results on sputum-Xpert-Ultra, while 25 were negative on sputum-Xpert-Ultra.
Figure 2 presents the results of multivariate logistic regression for (1) positive stool-Xpert-Ultra and (2) positive RS-Xpert-Ultra/culture. We found that age ≥10 years, female sex, SAM, and chest X-ray consistent with TB showed a strong association with positive stool-Xpert-Ultra. Apart from age ≥10 years, female sex, SAM, and chest X-ray consistent with TB were also strongly associated with positive RS-Xpert-Ultra/culture.
Figure 2.
Factors associated with a positive microbiological yield on Xpert-Ultra and/or culture on (A) stool sample (n = 258) and (B) respiratory sample (n = 587): multivariate logistic regression model. *Chest X-ray—consistent with TB defined as the presence of any one of the following: opacity, cavity, enlarged lymph nodes, miliary pattern, or effusion(World Health Organization 2022). Other abnormal findings are defined as abnormalities other than those consistent with TB. **Multivariate logistic regression model was constructed by including age category, sex, nutritional status and chest radiograph variables. OR, Odd ratio; CI, confidence interval; MAM, Moderate acute malnutrition; SAM, Severe acute malnutrition.
DISCUSSION
This study evaluated the diagnostic performance of stool-Xpert-Ultra for childhood PTB in routine care at 2 tertiary-care hospitals in Pakistan. Stool-Xpert-Ultra showed moderate sensitivity and high specificity against MC-PTB. Moreover, stool-Xpert-Ultra contributed a few additional MC-PTB cases when the RS were negative or unavailable. Further, we observed that 3 out of 4 stool-Xpert-Ultra tests were positive in children ≥10, and a strong association was found in children with SAM, and those with chest X-ray consistent with TB, making it a feasible alternative sample for these children. These findings are helpful for clinicians and program managers to upscale stool as an alternate to RS-Xpert-Ultra for diagnosing PTB, especially in resource-limited settings.
The moderate sensitivity (56%) of stool-Xpert-Ultra for childhood PTB aligns with systematic reviews reporting 50%–60% sensitivity in children <16 years [4, 14, 15]. The moderate sensitivity could be due to several reasons, such as the presence of paucibacillary primary TB in children, poor sputum production limits gastrointestinal Mycobacterium tuberculosis (MTB) transmission, and variable sample quality and processing methods [4, 6, 14, 16]. Moreover, we have observed that the positive stool-Xpert-Ultra was strongly associated with chest X-ray consistent with TB in all children <16 years of age reported in other studies [17–20]. This important finding suggests the use of stool in primary care settings where chest radiographs are usually unavailable. The value of stool-Xpert-Ultra was further enhanced in our study, as it identified 11% additional MC-PTB cases when RS was negative or not available in children <16 years, consistent with prior studies [14, 21–23]. Hence, with moderate sensitivity, strong association with chest X-ray findings and ability to identify additional MC-PTB cases, the stool as a noninvasive test can play a pivotal role in improving the current TB diagnostic access in resource-limited settings.
Interestingly, in the current study, stool Xpert-Ultra shows low sensitivity (48%) in children <10, which is consistent with other studies in similar age groups [4, 6, 24, 25]. The low yield probably indicates that primary TB is common in this age group, which is paucibacillary and leads to less MTB transmission to the gastrointestinal tract through swallowed sputum [21]. Pathological features in the lungs, such as hilar or mediastinal lymphadenopathy, subtle alveolar consolidations, miliary lesions, or pleural effusions, are common in this age group [26–29] and are associated with a lower bacterial burden and reduced microbiological yield as compared to cavitation on chest-X-ray in older children [17, 19, 20, 29]. However, a study conducted in Ethiopia found higher sensitivity (77%), possibly due to the inclusion of children from primary care facilities with different disease characteristics [25].
On the other hand, we observed a high sensitivity (77%) of stool Xpert-Ultra in children ≥10 years, closely matching sputum Xpert-Ultra and aligning with findings in adults [30, 31]. This comparable performance is likely due to adult-type, post-primary TB in this age group, characterized by higher bacterial loads and cavitary lesions, which increase MTB presence in both sputum and swallowed sputum, reaching the gastrointestinal tract [26].
The noninvasive nature of the stool sample addresses logistical barriers like limited sputum collection facilities in high-burden settings [6]. WHO recommends repeat Xpert-Ultra testing for high-suspicion cases [32] and targeted stool sampling could optimize diagnostic cost-effectively [33]. Compared to invasive GA, the practicality of stool samples supports its integration into Pakistan's TB guidelines, mirroring increased case detection in other high-burden countries [33, 34]. However, its moderate sensitivity in younger children indicates it cannot replace RS-Xpert-Ultra, which remains the preferred sample. Clinicians should prioritize RS collection and use stools as an adjunct or alternative when RS are unobtainable.
Nutritional status stratification in our cohort showed that the sensitivity was highest in children with SAM as reported by others [4, 17]. SAM was also associated with high microbiological yields with RS and stool samples. SAM-related immune suppression and a higher MTB burden enhance stool yield through swallowed secretions or gastrointestinal involvement. Gut barrier dysfunction and altered microbiota may further improve detection [35]. The lower yield compared to sputum likely reflects poor expectoration in SAM or differences in disease site or bacillary load between the gastrointestinal and lower respiratory compartments.
The strengths of the study include its prospective cohort design in high TB-burden areas, a diverse range of sample types and an appropriate sample size to conduct stratified analyzes. We followed up on all enrolled cases and monitored their response to treatment to verify their TB status, improving diagnostic accuracy. We used multiple reference standards to minimize the risk of bias in interpreting Xpert-Ultra sensitivity [14]. However, this study has several limitations. First, it was conducted in tertiary-care settings, where most children had severe disease, and expertise for invasive GA sampling was available, limiting generalizability to primary and secondary care healthcare centers. Second, we did not control for factors that may affect sample quality, such as the timing of the collection or intervals between samples. Lastly, chest X-rays were not performed for all cases.
CONCLUSIONS
In conclusion, our findings support stool-Xpert-Ultra as a noninvasive diagnostic tool for pediatric PTB, especially in children with SAM and ≥10 years. While stool-Xpert-Ultra cannot replace RS-Xpert-Ultra due to moderate to low sensitivity in younger children, particularly those with a low organism burden, it provides valuable diagnostic yield for additional PTB cases when RS is negative or unfeasible. Given noninvasive sampling and the potential to expand access to sampling types for PTB, stool-based diagnostics should be scaled up alongside efforts to improve RS collection in high-burden countries like Pakistan. Despite these promising results, young children with low positive rates with Xpert-Ultra warrant further research to refine diagnostic protocols.
Supplementary Material
Notes
Acknowledgments. We appreciate the data collectors (Dr Ayesha Riaz, Hafsa Nazeer, Dr Romeeza Zahid, Nadia Ameer Hamza, Farwa Farooq, Nayyab Shahid) for their contributions to data and sample collection, and processing. We also appreciate the assistance of Sadia Khan, Wardah Shams, and Mohammad Sajid Mustafa with data monitoring. We also thank the staff of the Gulab Devi Teaching Hospital and the University of Child Health Sciences, the Children's Hospital, Lahore, for their contributions to this research project. Finally, we would like to thank the children and their families for participating in this study.
Author contributions . B. A.: conceptualization, formal analysis, investigation, data curation, visualization, project administration, writing–original draft, writing–review and editing. A. A.: conceptualization, investigation, project administration, review and editing. I. B.: investigation, review and editing. H. S.: investigation, data curation, project administration, review and editing. A. S.: investigation, review and editing. Z. R.: investigation, data curation, project administration, writing–review and editing. U. A.: investigation, data curation, review and editing. Y. B. N.: conceptualization, formal analysis, visualization, writing–review and editing. T. M.: conceptualization, formal analysis, investigation, data curation, visualization, project administration, writing–original draft, writing–review and editing, funding acquisition.
Financial support. This work was partially supported by the HelseVest and the Norwegian Agency for International Cooperation and Quality Enhancement in Higher Education through the NORPART program [NORPART-2021/10348].
Data availability. Data that support the findings of the study is not publicly available and can be made available on request to the corresponding author.
Declaration of artificial intelligence. During the preparation of this work, the authors used AI tools for the correction of language.
Disclaimer. The study sponsors had no role in the analysis and interpretation of data, in the writing of the report, and in the decision to submit the article for publication. YBN is staff member of the World Health Organization. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated.
Contributor Information
Brekhna Aurangzeb, Centre of International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway; Children's Hospital, Pakistan Institute of Medical Sciences, Islamabad, Pakistan.
Atiqa Ambreen, Department of Microbiology, Gulab Devi Teaching Hospital, Lahore, Pakistan.
Iqbal Bano, Department of Pediatric Pulmonology, University of Child Health Sciences, the Children's Hospital, Lahore, Pakistan.
Huda Sarwar, Department of Health Sciences, University of York, York, UK.
Aneela Shaheen, Department of Pediatric Medicine, Gulab Devi Teaching Hospital, Lahore, Pakistan.
Zunaira Rao, Department of Microbiology, Gulab Devi Teaching Hospital, Lahore, Pakistan; Department of Primary and Secondary Health Care, Provincial TB Control Program Punjab, Lahore, Pakistan.
Muhammad Usama, Department of Microbiology, Gulab Devi Teaching Hospital, Lahore, Pakistan.
Zaheer Akhtar, Department of Pulmonology, Gulab Devi Teaching Hospital, Lahore, Pakistan.
Yasir Bin Nisar, Department of Maternal, Newborn, Child and Adolescent Health and Ageing, World Health Organization, Geneva, Switzerland.
Tehmina Mustafa, Centre of International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway; Department of Thoracic Medicine, Haukeland University Hospital, Bergen, Norway.
Supplementary Data
Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
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