Diagnostic Accuracy of Clinical Diagnostic Scoring Systems for Childhood Tuberculosis: A Systematic Review and Meta-analysis.

Background: Diagnosis of childhood tuberculosis (TB) poses several challenges. Therefore, point-based scoring systems and diagnostic algorithms have been developed to improve the diagnostic yields in this population. However, there are no updated systematic reviews of the existing childhood TB scoring systems and algorithms. Hence, we systematically reviewed the diagnostic accuracy of the childhood TB diagnostic scoring systems and algorithms. Methods: We systematically searched PubMed, CINAHL, Embase, Scopus, and Google Scholar databases for relevant articles published until 30 March 2023. QUADAS-2 was used to assess their study quality. Diagnostic accuracy measures (ie, sensitivity, specificity, diagnostic odds ratio, positive and negative likelihood ratios) were pooled using a random-effects model. Results: We included 15 eligible studies, with a total of 7327 study participants aged <15 years, with 10 evaluations of childhood TB diagnostic scoring systems and algorithms. Among these algorithms and scoring systems, only 3 were evaluated more than once. These were the Keith Edwards scoring system with 5 studies (sensitivity, 81.9%; specificity, 81.2%), Kenneth Jones criteria with 3 studies (sensitivity, 80.1%; specificity, 45.7%), and the Ministry of Health-Brazil algorithm with 3 studies (sensitivity, 79.9%; specificity, 73.2%). Conclusions: We recommend using the Keith Edwards scoring system because of its high sensitivity and specificity. Further research is necessary to assess the effectiveness of scoring systems and algorithms in identifying TB in children with HIV and malnutrition.

Diagnostic accuracy of chest ultrasound scan in the diagnosis of childhood tuberculosis.

Chest Ultrasound Scan (CUS) has been utilized in place of CXR in the diagnosis of adult pneumonia with similar or higher sensitivity and specificity to CXR. However, there is a paucity of data on the use of CUS for the diagnosis of childhood TB. This study aimed to determine the diagnostic accuracy of CUS for childhood TB. This cross-sectional study was conducted at the Mulago National Referral Hospital in Uganda. Eighty children up to 14 years of age with presumptive TB were enrolled. They all had CUS and CXR performed and interpreted independently by radiologists. The radiologist who performed the CXR was blinded to the CUS findings, and vice versa. Radiologists noted whether TB was likely or unlikely. A two-by-two table was developed to compare the absolute number of children as either TB likely or TB unlikely on CXR or CUS. This was used to calculate the sensitivity and specificity of CUS when screening for TB in children, with a correction to accommodate the use of CXR as a reference test. The sensitivity of CUS was 64% (95% CI 48.5%-77.3%), while its specificity was 42.7% (95% CI 25.5%-60.8%). Both the CUS and CXR found 29 children with a likelihood of TB, and 27 children unlikely to have TB. CUS met the sensitivity target set by the WHO TPP for Triage, and it had a sensitivity and specificity comparable to that of CXR.

Diagnostic accuracy of clinical diagnostic scoring systems for childhood tuberculosis: a systematic review and meta-analysis protocol.

INTRODUCTION: Diagnosis of childhood tuberculosis (TB) poses several challenges. Therefore, clinical signs and symptoms, radiological studies, laboratory examinations, point-based scoring systems or diagnostic algorithms have been developed to improve diagnostic yields in this population. However, there are limited data on the diagnostic test accuracy of paediatric TB scoring systems. Therefore, this systematic review and meta-analysis aims to synthesise the available evidence on the diagnostic accuracy of childhood TB diagnostic scoring systems. METHODS AND ANALYSIS: This protocol describes a systematic review, developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses of Diagnostic Test Accuracy. We will conduct a comprehensive literature search for relevant articles in the following databases: PubMed, CINAHL, Embase, Scopus and Cochrane Databases. The eligibility criteria for studies will be formulated based on the Participants (Population), Index Test, Comparator Test and Target Condition criteria for the review question. The index test will be defined as any attempt to diagnose childhood TB using either a scoring system or a diagnostic algorithm, whereas a composite reference standard will be used as a reference standard. This will include any attempt to confirm diagnosis of TB. Where bacteriological confirmation is not obtained and there are at least two of the following features: chest radiograph consistent with TB, immunological evidence of Mycobacterium tuberculosis infection and/or positive response to TB treatment will also be considered. The QUADAS-2 Tool will be used to assess the quality of the studies. The diagnostic accuracy measures (ie, sensitivity, specificity, negative predictive and positive predictive values) will be pooled with the random-effects or fixed-effects models, as appropriate. All statistical analyses will be performed using the Review Manager V.5.4. ETHICS AND DISSEMINATION: This research is exempt from ethics approval given that this is a protocol for a systematic review, which uses published data. The findings from this review will be disseminated through peer-reviewed publications and scientific conferences. PROSPERO REGISTRATION NUMBER: CRD42022367049.

Comparison of tests done, and tuberculosis cases detected by Xpert® MTB/RIF and Xpert® MTB/RIF-Ultra in Uganda.

BACKGROUND: Uganda introduced Xpert® MTB/RIF assay into its TB diagnostic algorithm in January 2012. In July 2018, this assay was replaced with Xpert® MTB/RIF Ultra assay. We set out to compare the tests done and tuberculosis cases detected by Xpert® MTB/RIF and Xpert® MTB/RIF Ultra assay in Uganda. METHODS: This was a before and after study, with the tests done and TB cases detected between Jan-June 2019 when using Xpert® MTB/RIF Ultra assay compared to those done between Jan-June 2018 while using Xpert® MTB/RIF assay. This data was analyzed using Stata version 13, it was summarized into measures of central tendency and the comparison between Xpert® MTB/RIF Ultra and Xpert® MTB/RIF was explored using a two-sided T-test which was considered significant if p <0.05. RESULTS: One hundred and twelve (112) GeneXpert sites out of a possible 239 were included in the study. 128,476 (M: 1147.11, SD: 842.88) tests were performed with Xpert® MTB/RIF Ultra assay, with 9693 drug-susceptible TB (DS-TB) cases detected (M: 86.54, SD: 62.12) and 144 (M: 1.28, SD: 3.42) Rifampicin Resistant TB cases (RR-TB). Whilst 107, 890 (M: 963.30, SD: 842.88) tests were performed with Xpert® MTB/RIF assay between, 8807 (M: 78.63, SD: 53.29) DS-TB cases were detected, and 147 (M: 1.31, SD: 2.39) RR-TB cases. The Number Need to Test (NNT) to get one TB case was 12 for Xpert® MTB/RIF and 13 for Xpert ®MTB/RIF Ultra. On comparing the two assays in terms of test performance (p = 0.75) and case detection both susceptible TB (p = 0.31) and RR-TB (p = 0.95) were not found statistically significant. CONCLUSIONS: This study found no significant difference in test performance and overall detection of DS-TB and RR-TB when using Xpert® MTB/RIF Ultra and Xpert® MTB/RIF assays. The health systems approach should be used to elucidate all the probable potential of Xpert® MTB/RIF Ultra.

Community intervention for child tuberculosis active contact investigation and management: study protocol for a parallel cluster randomized controlled trial.

BACKGROUND: There are major gaps in the management of pediatric tuberculosis (TB) contact investigation for rapid identification of active tuberculosis and initiation of preventive therapy. This study aims to evaluate the impact of a community-based intervention as compared to facility-based model for the management of children in contact with bacteriologically confirmed pulmonary TB adults in low-resource high-burden settings. METHODS/DESIGN: This multicenter parallel open-label cluster randomized controlled trial is composed of three phases: I, baseline phase in which retrospective data are collected, quality of data recording in facility registers is checked, and expected acceptability and feasibility of the intervention is assessed; II, intervention phase with enrolment of index cases and contact cases in either facility- or community-based models; and III, explanatory phase including endpoint data analysis, cost-effectiveness analysis, and post-intervention acceptability assessment by healthcare providers and beneficiaries. The study uses both quantitative and qualitative analysis methods. The community-based intervention includes identification and screening of all household contacts, referral of contacts with TB-suggestive symptoms to the facility for investigation, and household initiation of preventive therapy with follow-up of eligible child contacts by community healthcare workers, i.e., all young (< 5 years) child contacts or older (5-14 years) child contacts living with HIV, and with no evidence of TB disease. Twenty clusters representing TB diagnostic and treatment facilities with their catchment areas are randomized in a 1:1 ratio to either the community-based intervention arm or the facility-based standard of care arm in Cameroon and Uganda. Randomization was stratified by country and constrained on the number of index cases per cluster. The primary endpoint is the proportion of eligible child contacts who initiate and complete the preventive therapy. The sample size is of 1500 child contacts to identify a 10% difference between the arms with the assumption that 60% of children will complete the preventive therapy in the standard of care arm. DISCUSSION: This study will provide evidence of the impact of a community-based intervention on household child contact screening and management of TB preventive therapy in order to improve care and prevention of childhood TB in low-resource high-burden settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT03832023 . Registered on 6 February 2019.

A yield and cost comparison of tuberculosis contact investigation and intensified case finding in Uganda.

INTRODUCTION: Resource constraints in Low and Middle-Income Countries (LMICs) limit tuberculosis (TB) contact investigation despite evidence its benefits could outweigh costs, with increased efficiency when compared with intensified case finding (ICF). However, there is limited data on yield and cost per TB case identified. We compared yield and cost per TB case identified for ICF and Tuberculosis-Contact Investigation (TB-CI) in Uganda. METHODS: A retrospective cohort study based on data from 12 Ugandan hospitals was done between April and September 2017. Two methods of TB case finding (i.e. ICF and TB-CI) were compared. Regarding ICF, patients either self-reported their signs and symptoms or were prompted by health care workers, while TB-CI was done by home-visiting and screening contacts of TB patients. Patients who were presumed to have tuberculosis were requested to produce a sample for examination. TB yield was defined as a ratio of diagnoses to tests, and this was computed per method of diagnosis. The cost per TB case identified (medical, personnel, transportation and training) for each diagnosis method were computed using the activity-based approach, from the health care perspective. Cost data were analyzed using Windows Excel. RESULTS: 454 index TB cases and 2,707 of their household contacts were investigated. Thirty-one per cent of contacts (840/2707) were found to be presumptive TB cases. A total of 7,685 tests were done, 6,967 for ICF and 718 for TB-CI. The yields were 18.62% (1297/6967) and 5.29% (38/718) for ICF and TB-CI, respectively. It cost US$ 120.60 to diagnose a case of TB using ICF compared to US$ 877.57 for TB-CI. CONCLUSION: The yield of TB-CI was found to be four-times lower and seven-times costlier compared to ICF. These findings suggest that ICF can improve TB case detection at a low cost, particularly in high TB prevalent settings.

A comparision of the yield of three tuberculosis screening modalities among people living with HIV: a retrospective quasi-experiemental study.

BACKGROUND: The Intensified Case Finding (ICF) tool was approved for TB screening in 2011; however there is still paucity of robust data comparing yields of the different ICF screening modalities. We compared yields of three different screening modalities for TB among Patients Living with HIV (PLHIV) in Uganda in order to inform National TB Programs on the most effective TB screening method. METHODS: This was a retrospective quasi-experimental study conducted at an Out-Patient HIV/AIDS clinic in Uganda. We set out to determine yields of three different TB screening modalities at three time periods: 2006/07 where Passive Case Finding (PCF) was used. Here, no screening questions were administered; the clinician depended on the patient's self report. In 2008/09 embedded Intensified Case Finding Tool (e-ICF) was used; here a data capture field was added to the patient clinical encounter forms to compel clinicians to screen for TB symptoms. In 2010/11 Independent Intensified Case Finding Tool (i-ICF) was used; here a screening data collection form, was used, it had the same screening questions as e-ICF. Routine clinical data, including TB status, were collected and entered into an electronic clinical care database. Analysis was done in STATA and the main outcome estimated was the proportional yield of TB cases for each screening modality. RESULTS: The overall yield of TB cases was 11.18 % over the entire period of the study (2006 - 2011). The intervention-specific yields were 1.86 % for PCF, 14.95 % for e-ICF and 12.47 % for i-ICF. Use of either e-ICF (OR: 9.2, 95 % CI: 4.81-17.73) or i- ICF (OR: 7.7, 95 % CI: 4.02-14.78) significantly detected more TB cases compared to PCF (P <0.001). While the yields of the Active Case Finding modalities (e-ICF & i-ICF) were not significantly different (OR: 0.98, 95 % CI 0.76-1.27, P = 0.89). CONCLUSION: The active screening modalities (e-ICF & i-ICF) had a comparable TB yield and were eight to nine times more efficient in identifying TB cases when compared to the PCF. Cost effectiveness studies would be informative.