Journal Article > CommentaryFull Text
Lancet Child Adolesc Health. 2018 October 5; Volume 2 (Issue 12); DOI:10.1016/S2352-4642(18)30284-0
Umphrey L, Brown AL, Hiffler L, Lafferty N, Garcia DM, et al.
Lancet Child Adolesc Health. 2018 October 5; Volume 2 (Issue 12); DOI:10.1016/S2352-4642(18)30284-0
Journal Article > CommentaryFull Text
Lancet Child Adolesc Health. 2020 December 1; Volume 4 (Issue 12); 855-857.; DOI:10.1016/S2352-4642(20)30273-X
Nash M, Perrin C, Seddon JA, Furin J, Hauser J, et al.
Lancet Child Adolesc Health. 2020 December 1; Volume 4 (Issue 12); 855-857.; DOI:10.1016/S2352-4642(20)30273-X
Journal Article > CommentaryFull Text
Lancet Child Adolesc Health. 2023 September 11; Volume 7 (Issue 10); 675-677.; DOI:10.1016/S2352-4642(23)00217-1
Deborggraeve S, Casenghi M, Hewison CCH, Ditekemena J, Ditiu L, et al.
Lancet Child Adolesc Health. 2023 September 11; Volume 7 (Issue 10); 675-677.; DOI:10.1016/S2352-4642(23)00217-1
Journal Article > CommentaryFull Text
Lancet Child Adolesc Health. 2023 November 1; Volume 7 (Issue 11); 751-753.; DOI:10.1016/S2352-4642(23)00214-6
May T, Babirekere-Iriso E, Traoré M, Berbain E, Ahmed M, et al.
Lancet Child Adolesc Health. 2023 November 1; Volume 7 (Issue 11); 751-753.; DOI:10.1016/S2352-4642(23)00214-6
Journal Article > ResearchFull Text
Lancet Child Adolesc Health. 2023 March 13; Online ahead of print; DOI:10.1016/S2352-4642(23)00004-4
Gunasekera KS, Marcy O, Muñoz J, Lopez-Varela E, Sekadde MP, et al.
Lancet Child Adolesc Health. 2023 March 13; Online ahead of print; DOI:10.1016/S2352-4642(23)00004-4
BACKGROUND
Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres.
METHODS
For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings.
FINDINGS
Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms.
INTERPRETATION
We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance.
Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres.
METHODS
For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings.
FINDINGS
Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms.
INTERPRETATION
We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance.
Journal Article > ReviewFull Text
Lancet Child Adolesc Health. 2021 August 17; Volume S2352-4642 (Issue 21); 00194-2.; DOI: 10.1016/S2352-4642(21)00194-2
Corona Maioli S, Bhabha J, Wickramage K, Wood LCN, Erragne L, et al.
Lancet Child Adolesc Health. 2021 August 17; Volume S2352-4642 (Issue 21); 00194-2.; DOI: 10.1016/S2352-4642(21)00194-2
The global population of unaccompanied minors-children and adolescents younger than 18 years who migrate without their legal guardians is increasing. However, as data are not systematically collected in any region, if collected at all, little is known about this diverse group of young people. Compared with adult migrants, unaccompanied minors are at greater risk of harm to their health and integrity because they do not have the protection provided by a family, which can affect their short-term and long-term health. This Review summarises evidence regarding the international migration and health of unaccompanied minors. Unaccompanied minors are entitled to protection that should follow their best interests as a primary consideration; however, detention, sometimes under the guise of protection, is a widespread practice. If these minors are provided with appropriate forms of protection, including health and psychosocial care, they can thrive and have good long-term outcomes. Instead, hostile immigration practices persist, which are not in the best interests of the child.
Journal Article > CommentaryFull Text
Lancet Child Adolesc Health. 2020 November 1; Volume 4 (Issue 11); 804-805.; DOI:10.1016/S2352-4642(20)30321-7
García-Mingo A, Abbara A, Basu Roy R
Lancet Child Adolesc Health. 2020 November 1; Volume 4 (Issue 11); 804-805.; DOI:10.1016/S2352-4642(20)30321-7
Journal Article > Short ReportAbstract
Lancet Child Adolesc Health. 2019 September 11; Volume 3; DOI:10.1016/S2352-4642(19)30244-5
Wells JCK, Briend A, Boyd EM, Berkely JA, Hall A, et al.
Lancet Child Adolesc Health. 2019 September 11; Volume 3; DOI:10.1016/S2352-4642(19)30244-5
Child undernutrition refers broadly to the condition in which food intake is inadequate to meet a child's needs for physiological function, growth, and the capacity to respond to illness. Since the 1970s, nutritionists have categorised undernutrition in two major ways, either as wasted (ie, low weight for height, or small mid-upper arm circumference) or stunted (ie, low height for age). This approach, although useful for identifying populations at risk of undernutrition, creates several problems: the focus is on children who have already become undernourished, and this approach draws an artificial distinction between two idealised types of undernourished children that are widely interpreted as indicative of either acute or chronic undernutrition. This distinction in turn has led to the separation of programmatic approaches to prevent and treat child undernutrition. In the past 3 years, research has shown that individual children are at risk of both conditions, might be born with both, pass from one state to the other over time, and accumulate risks to their health and life through their combined effects. The current emphasis on identifying children who are already wasted or stunted detracts attention from the larger number of children undergoing the process of becoming undernourished. We call for a major shift in thinking regarding how we assess child undernutrition, and how prevention and treatment programmes can best address the diverse causes and dynamic biological processes that underlie undernutrition.
Journal Article > Case Report/SeriesFull Text
Lancet Child Adolesc Health. 2020 December 1; Volume 4 (Issue 12); 884-888.; DOI:10.1016/S2352-4642(20)30278-9
Ottoni MP, Ricciardone JD, Nadimpalli A, Singh SN, Katsomya AM, et al.
Lancet Child Adolesc Health. 2020 December 1; Volume 4 (Issue 12); 884-888.; DOI:10.1016/S2352-4642(20)30278-9
Background
Few fetuses survive childbirth when the mother is positive for Ebola virus, with almost all being miscarried or stillborn, or dying shortly after birth. Before 2019, only two infants had been reported surviving past 28 days, of whom one tested positive for Ebola virus and subsequently received experimental therapies. Little is understood regarding the care of surviving neonates born to Ebola virus-positive mothers in the postnatal period and how novel anti-Ebola virus therapies might affect neonatal outcomes.
Methods
In this case series, we report on two neonates liveborn during the 2018–20 North Kivu Ebola epidemic in the Democratic Republic of the Congo who, along with their Ebola virus-positive mothers, received investigational monoclonal antibody treatment (mAB114 or REGN-EB3) as part of a randomised controlled trial (NCT03719586).
Findings
Both infants were born Ebola-negative and progressed well while in the Ebola Treatment Centre. Neither neonate developed evidence of Ebola virus disease during the course of the admission, and both were Ebola-negative at 21 days and remained healthy at discharge.
Interpretation
To our knowledge these neonates are the first documented as Ebola virus-negative at birth after being born to Ebola virus-positive mothers, and only the third and fourth neonates ever documented to have survived into infancy. Although no conclusions can be drawn from this small case series, and further research is required to investigate the neonatal effects of antibody therapies, these cases warrant review regarding whether post-delivery antibody therapy should be considered for all liveborn neonates of Ebola virus-positive mothers. In the context of a low resource setting, where survival of low-birthweight infants is poor, these cases also highlight the importance of adequate neonatal care.
Few fetuses survive childbirth when the mother is positive for Ebola virus, with almost all being miscarried or stillborn, or dying shortly after birth. Before 2019, only two infants had been reported surviving past 28 days, of whom one tested positive for Ebola virus and subsequently received experimental therapies. Little is understood regarding the care of surviving neonates born to Ebola virus-positive mothers in the postnatal period and how novel anti-Ebola virus therapies might affect neonatal outcomes.
Methods
In this case series, we report on two neonates liveborn during the 2018–20 North Kivu Ebola epidemic in the Democratic Republic of the Congo who, along with their Ebola virus-positive mothers, received investigational monoclonal antibody treatment (mAB114 or REGN-EB3) as part of a randomised controlled trial (NCT03719586).
Findings
Both infants were born Ebola-negative and progressed well while in the Ebola Treatment Centre. Neither neonate developed evidence of Ebola virus disease during the course of the admission, and both were Ebola-negative at 21 days and remained healthy at discharge.
Interpretation
To our knowledge these neonates are the first documented as Ebola virus-negative at birth after being born to Ebola virus-positive mothers, and only the third and fourth neonates ever documented to have survived into infancy. Although no conclusions can be drawn from this small case series, and further research is required to investigate the neonatal effects of antibody therapies, these cases warrant review regarding whether post-delivery antibody therapy should be considered for all liveborn neonates of Ebola virus-positive mothers. In the context of a low resource setting, where survival of low-birthweight infants is poor, these cases also highlight the importance of adequate neonatal care.
Journal Article > CommentaryFull Text
Lancet Child Adolesc Health. 2021 March 1; Volume 5 (Issue 3); 159-161.; DOI:10.1016/S2352-4642(21)00003-1
Mohr-Holland E, Douglas-Jones B, Apolisi I, Ngambu N, Mathee S, et al.
Lancet Child Adolesc Health. 2021 March 1; Volume 5 (Issue 3); 159-161.; DOI:10.1016/S2352-4642(21)00003-1