Diagnostic Challenges in Childhood Pulmonary Tuberculosis-Optimizing the Clinical Approach

Development of tuberculosis treatment decision algorithms in children below 5 years hospitalised with severe acute malnutrition in Zambia and Uganda: a prospective diagnostic cohort study

Background

In children with severe acute malnutrition (SAM) tuberculosis is common, challenging to diagnose, and often fatal. We developed tuberculosis treatment decision algorithms (TDAs) for children under the age of 5 years with SAM.

Methods

In this prospective diagnostic study, we enrolled and followed up children aged <60 months hospitalised with SAM at three tertiary hospitals in Zambia and Uganda from 4 November 2019 to 20 June 2022. We included children aged 2-59 months with SAM as defined by WHO and hospitalised following the WHO clinical criteria. We excluded children with current or history of antituberculosis treatment within the preceding 3 months. They underwent tuberculosis symptom screening, clinical assessment, chest X-ray, abdominal ultrasound, Xpert MTB/RIF Ultra (Ultra) and culture on respiratory and stool samples with 6 months follow-up. Tuberculosis was retrospectively defined using the 2015 standard case definition for childhood tuberculosis. We used logistic regression to develop diagnostic prediction models for a one-step diagnosis and a two-step screening and diagnostic approaches. We derived scores from models using WHO-recommended thresholds for sensitivity and proposed TDAs. This study is registered with ClinicalTrials.gov, NCT04240990.

Findings

Of 1906 children hospitalised with SAM during the study period, 1230 were screened, 1152 were eligible and 603 were enrolled. Of the 603 children enrolled-median age 15 (inter-quartile range (IQR): 11-20) months and 65 (11.0%) living with HIV-114 (18.9%) were diagnosed with tuberculosis, including 51 (8.5%) with microbiological confirmation and 104 (17.2%) initiated treatment at a median of 6(IQR: 2-10) days after inclusion. 108 children were retrospectively classified as having tuberculosis resulting in a prevalence of 17.9% (95% confidence intervals (CI): 15.1; 21.2). 75 (69.4%) children with tuberculosis reported cough of any duration, 32 (29.6%) cough ≥2 weeks and 11 (10.2%) tuberculosis contact history. 535 children had complete data and were included in the diagnostic prediction model. The one-step diagnostic model had 15 predictors, including Ultra, clinical, radiographic, and abdominal features, an area under the receiving operating curve (AUROC) of 0.910, and derived TDA sensitivity of 86.14% (95% CI: 78.07-91.56) and specificity of 80.88% (95% CI: 76.91-84.30). The two-step model had AUROCs of 0.750 and 0.912 for screening and diagnosis, respectively, and derived combined TDA sensitivity of 79.21% (95% CI: 70.30-85.98) and a specificity of 83.64% (95% CI: 79.87-86.82).

Interpretation

Tuberculosis prevalence was high among hospitalised children with SAM, with atypical clinical features. TDAs achieved satisfactory diagnostic accuracy and could be used to improve diagnosis in this vulnerable group.

Funding

Unitaid.

Global, regional, and national age-specific progress towards the 2020 milestones of the WHO End TB Strategy: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Global evaluations of the progress towards the WHO End TB Strategy 2020 interim milestones on mortality (35% reduction) and incidence (20% reduction) have not been age specific. We aimed to assess global, regional, and national-level burdens of and trends in tuberculosis and its risk factors across five separate age groups, from 1990 to 2021, and to report on age-specific progress between 2015 and 2020.

METHODS

We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD 2021) analytical framework to compute age-specific tuberculosis mortality and incidence estimates for 204 countries and territories (1990-2021 inclusive). We quantified tuberculosis mortality among individuals without HIV co-infection using 22 603 site-years of vital registration data, 1718 site-years of verbal autopsy data, 825 site-years of sample-based vital registration data, 680 site-years of mortality surveillance data, and 9 site-years of minimally invasive tissue sample (MITS) diagnoses data as inputs into the Cause of Death Ensemble modelling platform. Age-specific HIV and tuberculosis deaths were established with a population attributable fraction approach. We analysed all available population-based data sources, including prevalence surveys, annual case notifications, tuberculin surveys, and tuberculosis mortality, in DisMod-MR 2.1 to produce internally consistent age-specific estimates of tuberculosis incidence, prevalence, and mortality. We also estimated age-specific tuberculosis mortality without HIV co-infection that is attributable to the independent and combined effects of three risk factors (smoking, alcohol use, and diabetes). As a secondary analysis, we examined the potential impact of the COVID-19 pandemic on tuberculosis mortality without HIV co-infection by comparing expected tuberculosis deaths, modelled with trends in tuberculosis deaths from 2015 to 2019 in vital registration data, with observed tuberculosis deaths in 2020 and 2021 for countries with available cause-specific mortality data.

FINDINGS

We estimated 9·40 million (95% uncertainty interval [UI] 8·36 to 10·5) tuberculosis incident cases and 1·35 million (1·23 to 1·52) deaths due to tuberculosis in 2021. At the global level, the all-age tuberculosis incidence rate declined by 6·26% (5·27 to 7·25) between 2015 and 2020 (the WHO End TB strategy evaluation period). 15 of 204 countries achieved a 20% decrease in all-age tuberculosis incidence between 2015 and 2020, eight of which were in western sub-Saharan Africa. When stratified by age, global tuberculosis incidence rates decreased by 16·5% (14·8 to 18·4) in children younger than 5 years, 16·2% (14·2 to 17·9) in those aged 5-14 years, 6·29% (5·05 to 7·70) in those aged 15-49 years, 5·72% (4·02 to 7·39) in those aged 50-69 years, and 8·48% (6·74 to 10·4) in those aged 70 years and older, from 2015 to 2020. Global tuberculosis deaths decreased by 11·9% (5·77 to 17·0) from 2015 to 2020. 17 countries attained a 35% reduction in deaths due to tuberculosis between 2015 and 2020, most of which were in eastern Europe (six countries) and central Europe (four countries). There was variable progress by age: a 35·3% (26·7 to 41·7) decrease in tuberculosis deaths in children younger than 5 years, a 29·5% (25·5 to 34·1) decrease in those aged 5-14 years, a 15·2% (10·0 to 20·2) decrease in those aged 15-49 years, a 7·97% (0·472 to 14·1) decrease in those aged 50-69 years, and a 3·29% (-5·56 to 9·07) decrease in those aged 70 years and older. Removing the combined effects of the three attributable risk factors would have reduced the number of all-age tuberculosis deaths from 1·39 million (1·28 to 1·54) to 1·00 million (0·703 to 1·23) in 2020, representing a 36·5% (21·5 to 54·8) reduction in tuberculosis deaths compared to those observed in 2015. 41 countries were included in our analysis of the impact of the COVID-19 pandemic on tuberculosis deaths without HIV co-infection in 2020, and 20 countries were included in the analysis for 2021. In 2020, 50 900 (95% CI 49 700 to 52 400) deaths were expected across all ages, compared to an observed 45 500 deaths, corresponding to 5340 (4070 to 6920) fewer deaths; in 2021, 39 600 (38 300 to 41 100) deaths were expected across all ages compared to an observed 39 000 deaths, corresponding to 657 (-713 to 2180) fewer deaths.

INTERPRETATION

Despite accelerated progress in reducing the global burden of tuberculosis in the past decade, the world did not attain the first interim milestones of the WHO End TB Strategy in 2020. The pace of decline has been unequal with respect to age, with older adults (ie, those aged >50 years) having the slowest progress. As countries refine their national tuberculosis programmes and recalibrate for achieving the 2035 targets, they could consider learning from the strategies of countries that achieved the 2020 milestones, as well as consider targeted interventions to improve outcomes in older age groups.

FUNDING

Bill & Melinda Gates Foundation.

Culture-Free Whole Genome Sequencing of Mycobacterium tuberculosis Using Ligand-Mediated Bead Enrichment Method

Background

Direct whole genome sequencing (WGS) of Mycobacterium tuberculosis (Mtb) can be used as a tool to study drug resistance, mixed infections, and within-host diversity. However, WGS is challenging to obtain from clinical samples due to low number of bacilli against a high background.

Methods

We prospectively collected 34 samples (sputum, n = 17; bronchoalveolar lavage, n = 13; and pus, n = 4) from patients with active tuberculosis (TB). Prior to DNA extraction, we used a ligand-mediated magnetic bead method to enrich Mtb from clinical samples and performed WGS on Illumina platform.

Results

Mtb was definitively identified based on WGS from 88.2% (30/34) of the samples, of which 35.3% (12/34) were smear negative. The overall median genome coverage was 15.2% (interquartile range [IQR], 7.7%-28.2%). There was a positive correlation between load of bacilli on smears and genome coverage (P < .001). We detected 58 genes listed in the World Health Organization mutation catalogue in each positive sample (median coverage, 85% [IQR, 61%-94%]), enabling the identification of mutations missed by routine diagnostics. Mutations causing resistance to rifampicin, isoniazid, streptomycin, and ethambutol were detected in 5 of 34 (14.7%) samples, including the rpoB S441A mutation that confers resistance to rifampicin, which is not covered by Xpert MTB/RIF.

Conclusions

We demonstrate the feasibility of magnetic bead-based enrichment for culture-free WGS of Mtb from clinical specimens, including smear-negative samples. This approach can also be integrated with low-cost sequencing workflows such as targeted sequencing for rapid detection of Mtb and drug resistance.

Pediatric Tuberculosis: A Review of Evidence-Based Best Practices for Clinicians and Health Care Providers

Advances in pediatric TB care are promising, the result of decades of advocacy, operational and clinical trials research, and political will by national and local TB programs in high-burden countries. However, implementation challenges remain in linking policy to practice and scaling up innovations for prevention, diagnosis, and treatment of TB in children, especially in resource-limited settings. There is both need and opportunity to strengthen clinician confidence in making a TB diagnosis and managing the various manifestations of TB in children, which can facilitate the translation of evidence to action and expand access to new tools and strategies to address TB in this population. This review aims to summarize existing guidance and best practices for clinicians and health care providers in low-resource, TB-endemic settings and identify resources with more detailed and actionable information for decision-making along the clinical cascade to prevent, find, and cure TB in children.

Patient characteristics and predictors of mortality among children hospitalised with tuberculosis: A six-year case series study in Uganda

BACKGROUND

The high case-fatality rates among children with tuberculosis (TB) are reportedly driven by in-hospital mortality and severe forms of TB. Therefore, there is need to better understand the predictors of mortality among children hospitalised with TB. We examined the patient clinical profiles, length of hospital stay from date of admission to date of final admission outcome, and predictors of mortality among children hospitalised with TB at two tertiary hospitals in Uganda.

METHODS

We conducted a case-series study of children below 15 years of age hospitalised with TB, from January 1st, 2016, to December 31st, 2021. Convenience sampling was done to select TB cases from paper-based medical records at Mulago National Referral Hospital (MNRH) in urban Kampala, and Fort Portal Regional Referral Hospital (FRRH) in rural Fort Portal. We fitted linear and logistic regression models with length of stay and in-hospital mortality as key outcomes.

RESULTS

Out of the 201 children hospitalised with TB, 50 were at FRRH, and 151 at MNRH. The male to female ratio was 1.5 with median age of 2.6 years (Interquartile range-IQR 1-6). There was a high prevalence of HIV (67/171, 39%), severe malnutrition reported as weight-for-age Z-score <-3SD (51/168, 30%). Among children with pulmonary TB who initiated anti-tuberculosis therapy (ATT) either during hospitalisation or within seven days prior to hospitalisation; cough (134/143, 94%), fever (111/143, 78%), and dyspnoea (78/143, 55%) were common symptoms. Children with TB meningitis commonly presented with fever (17/24, 71%), convulsions (14/24 58%), and cough (13/24, 54%). The median length of hospital stay was 8 days (IQR 5-15). Of the 199 children with known in-hospital outcomes, 34 (17.1%) died during hospitalisation. TB meningitis was associated with in-hospital mortality (aOR = 3.50, 95% CI = 1.10-11.17, p = 0.035), while male sex was associated with reduced mortality (aOR = 0.33, 95% CI = 0.12-0.95, p = 0.035). Hospitalisation in the urban hospital predicted a 0.48-day increase in natural log-transformed length of hospital stay (ln-length of stay) (95% CI 0.15-0.82, p = 0.005), but not age, sex, HIV, malnutrition, or TB meningitis.

CONCLUSIONS

In-hospital mortality was high, and significantly driven almost four times higher by TB meningitis, with longer hospital stay among children in urban hospitals. The high in-hospital mortality and long hospital stay may be reduced by timely TB diagnosis and treatment initiation among children.

Risk factors identification of COVID-19 patients with chronic obstructive pulmonary disease: A retrospective study in Punjab-Pakistan

BACKGROUND

Accessibility to the immense collection of studies on noncommunicable diseases related to coronavirus disease of 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an immediate focus of researchers. However, there is a scarcity of information about chronic obstructed pulmonary disease (COPD), which is associated with a high rate of infection in COVID-19 patients. Moreover, by combining the effects of the SARS-CoV-2 on COPD patients, we may be able to overcome formidable obstacles factors, and diagnosis influencers.

MATERIALS AND METHODS

A retrospective study of 280 patients was conducted at DHQ Hospital Muzaffargarh in Punjab, Pakistan. Negative binomial regression describes the risk of fixed successive variables. The association is described by the Cox proportional hazard model and the model coefficient is determined through log-likelihood observation. Patients with COPD had their survival and mortality plotted on Kaplan-Meier curves.

RESULTS

The increased risk of death in COPD patients was due to the effects of variables such as cough, lower respiratory tract infection (LRTI), tuberculosis (TB), and body-aches being 1.369, 0.693, 0.170, and 0.217 times higher at (95% confidence interval [CI]: 0.747-1.992), (95% CI: 0.231-1.156), (95% CI: 0.008-0.332), and (95% CI: -0.07 to 0.440) while it decreased 0.396 in normal condition.

CONCLUSION

We found that the symptoms of COPD (cough, LRTI, TB, and bodyaches) are statistically significant in patients who were most infected by SARS-CoV-2.

Monocyte, Lymphocyte and Neutrophil Ratios - Easy-to-Use Biomarkers for the Diagnosis of Pediatric Tuberculosis

BACKGROUND

The neutrophil-to-lymphocyte-ratio (NLR), neutrophil-to-monocyte-plus-lymphocyte-ratio (NMLR) and monocyte-to-lymphocyte-ratio (MLR) may have diagnostic potential for tuberculosis (TB).

METHODS

Data of two prospective multicenter studies in Switzerland were used, which included children <18 years with TB exposure, infection or disease or with febrile non-TB lower-respiratory-tract infection (nTB-LRTI).

RESULTS

Of the 389 children included 25 (6.4%) had TB disease, 12 (3.1%) TB infection, 28 (7.2%) were healthy TB exposed and 324 (83.3%) nTB-LRTI. Median (IQR) NLR was highest with 2.0 (1.2, 2.2) in children with TB disease compared to TB exposed [0.8 (0.6, 1.3); P = 0.002] and nTB-LRTI [0.3 (0.1, 1.0); P < 0.001]. Median (IQR) NMLR was highest with 1.4 (1.2, 1.7) in children with TB disease compared to healthy exposed [0.7 (0.6, 1.1); P = 0.003] and children with nTB-LRTI [0.2 (0.1, 0.6); P < 0.001). Receiver operating characteristic curves to detect TB disease compared to nTB-LRTI for NLR and NMLR had an area under the curve of 0.82 and 0.86, the sensitivity of 88% and 88%, and specificity of 71% and 76%, respectively.

CONCLUSION

NLR and NMLR are promising, easy-to-obtain diagnostic biomarkers to differentiate children with TB disease from other lower respiratory tract infections. These results require validation in a larger study and in settings with high and low TB endemicity.

Advancing personalized medicine for tuberculosis through the application of immune profiling

While early and precise diagnosis is the key to eliminating tuberculosis (TB), conventional methods using culture conversion or sputum smear microscopy have failed to meet demand. This is especially true in high-epidemic developing countries and during pandemic-associated social restrictions. Suboptimal biomarkers have restricted the improvement of TB management and eradication strategies. Therefore, the research and development of new affordable and accessible methods are required. Following the emergence of many high-throughput quantification TB studies, immunomics has the advantages of directly targeting responsive immune molecules and significantly simplifying workloads. In particular, immune profiling has been demonstrated to be a versatile tool that potentially unlocks many options for application in TB management. Herein, we review the current approaches for TB control with regard to the potentials and limitations of immunomics. Multiple directions are also proposed to hopefully unleash immunomics' potential in TB research, not least in revealing representative immune biomarkers to correctly diagnose TB. The immune profiles of patients can be valuable covariates for model-informed precision dosing-based treatment monitoring, prediction of outcome, and the optimal dose prediction of anti-TB drugs.