Use of quantitative molecular diagnostic methods to assess the aetiology, burden, and clinical characteristics of diarrhoea in children in low-resource settings: a reanalysis of the MAL-ED cohort study
Optimum management of childhood diarrhoea in low-resource settings has been hampered by insufficient data on aetiology, burden, and associated clinical characteristics. We used quantitative diagnostic methods to reassess and refine estimates of diarrhoea aetiology from the Etiology, Risk Factors, an...
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Published in | The Lancet global health Vol. 6; no. 12; pp. e1309 - e1318 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier Ltd
01.12.2018
Elsevier |
Subjects | |
Online Access | Get full text |
ISSN | 2214-109X 2214-109X |
DOI | 10.1016/S2214-109X(18)30349-8 |
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Abstract | Optimum management of childhood diarrhoea in low-resource settings has been hampered by insufficient data on aetiology, burden, and associated clinical characteristics. We used quantitative diagnostic methods to reassess and refine estimates of diarrhoea aetiology from the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) cohort study.
We re-analysed stool specimens from the multisite MAL-ED cohort study of children aged 0–2 years done at eight locations (Dhaka, Bangladesh; Vellore, India; Bhaktapur, Nepal; Naushero Feroze, Pakistan; Venda, South Africa; Haydom, Tanzania; Fortaleza, Brazil; and Loreto, Peru), which included active surveillance for diarrhoea and routine non-diarrhoeal stool collection. We used quantitative PCR to test for 29 enteropathogens, calculated population-level pathogen-specific attributable burdens, derived stringent quantitative cutoffs to identify aetiology for individual episodes, and created aetiology prediction scores using clinical characteristics.
We analysed 6625 diarrhoeal and 30 968 non-diarrhoeal surveillance stools from 1715 children. Overall, 64·9% of diarrhoea episodes (95% CI 62·6–71·2) could be attributed to an aetiology by quantitative PCR compared with 32·8% (30·8–38·7) using the original study microbiology. Viral diarrhoea (36·4% of overall incidence, 95% CI 33·6–39·5) was more common than bacterial (25·0%, 23·4–28·4) and parasitic diarrhoea (3·5%, 3·0–5·2). Ten pathogens accounted for 95·7% of attributable diarrhoea: Shigella (26·1 attributable episodes per 100 child-years, 95% CI 23·8–29·9), sapovirus (22·8, 18·9–27·5), rotavirus (20·7, 18·8–23·0), adenovirus 40/41 (19·0, 16·8–23·0), enterotoxigenic Escherichia coli (18·8, 16·5–23·8), norovirus (15·4, 13·5–20·1), astrovirus (15·0, 12·0–19·5), Campylobacter jejuni or C coli (12·1, 8·5–17·2), Cryptosporidium (5·8, 4·3–8·3), and typical enteropathogenic E coli (5·4, 2·8–9·3). 86·2% of the attributable incidence for Shigella was non-dysenteric. A prediction score for shigellosis was more accurate (sensitivity 50·4% [95% CI 46·7–54·1], specificity 84·0% [83·0–84·9]) than current guidelines, which recommend treatment only of bloody diarrhoea to cover Shigella (sensitivity 14·5% [95% CI 12·1–17·3], specificity 96·5% [96·0–97·0]).
Quantitative molecular diagnostics improved estimates of pathogen-specific burdens of childhood diarrhoea in the community setting. Viral causes predominated, including a substantial burden of sapovirus; however, Shigella had the highest overall burden with a high incidence in the second year of life. These data could improve the management of diarrhoea in these low-resource settings.
Bill & Melinda Gates Foundation. |
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AbstractList | Background: Optimum management of childhood diarrhoea in low-resource settings has been hampered by insufficient data on aetiology, burden, and associated clinical characteristics. We used quantitative diagnostic methods to reassess and refine estimates of diarrhoea aetiology from the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) cohort study. Methods: We re-analysed stool specimens from the multisite MAL-ED cohort study of children aged 0–2 years done at eight locations (Dhaka, Bangladesh; Vellore, India; Bhaktapur, Nepal; Naushero Feroze, Pakistan; Venda, South Africa; Haydom, Tanzania; Fortaleza, Brazil; and Loreto, Peru), which included active surveillance for diarrhoea and routine non-diarrhoeal stool collection. We used quantitative PCR to test for 29 enteropathogens, calculated population-level pathogen-specific attributable burdens, derived stringent quantitative cutoffs to identify aetiology for individual episodes, and created aetiology prediction scores using clinical characteristics. Findings: We analysed 6625 diarrhoeal and 30 968 non-diarrhoeal surveillance stools from 1715 children. Overall, 64·9% of diarrhoea episodes (95% CI 62·6–71·2) could be attributed to an aetiology by quantitative PCR compared with 32·8% (30·8–38·7) using the original study microbiology. Viral diarrhoea (36·4% of overall incidence, 95% CI 33·6–39·5) was more common than bacterial (25·0%, 23·4–28·4) and parasitic diarrhoea (3·5%, 3·0–5·2). Ten pathogens accounted for 95·7% of attributable diarrhoea: Shigella (26·1 attributable episodes per 100 child-years, 95% CI 23·8–29·9), sapovirus (22·8, 18·9–27·5), rotavirus (20·7, 18·8–23·0), adenovirus 40/41 (19·0, 16·8–23·0), enterotoxigenic Escherichia coli (18·8, 16·5–23·8), norovirus (15·4, 13·5–20·1), astrovirus (15·0, 12·0–19·5), Campylobacter jejuni or C coli (12·1, 8·5–17·2), Cryptosporidium (5·8, 4·3–8·3), and typical enteropathogenic E coli (5·4, 2·8–9·3). 86·2% of the attributable incidence for Shigella was non-dysenteric. A prediction score for shigellosis was more accurate (sensitivity 50·4% [95% CI 46·7–54·1], specificity 84·0% [83·0–84·9]) than current guidelines, which recommend treatment only of bloody diarrhoea to cover Shigella (sensitivity 14·5% [95% CI 12·1–17·3], specificity 96·5% [96·0–97·0]). Interpretation: Quantitative molecular diagnostics improved estimates of pathogen-specific burdens of childhood diarrhoea in the community setting. Viral causes predominated, including a substantial burden of sapovirus; however, Shigella had the highest overall burden with a high incidence in the second year of life. These data could improve the management of diarrhoea in these low-resource settings. Funding: Bill & Melinda Gates Foundation. Optimum management of childhood diarrhoea in low-resource settings has been hampered by insufficient data on aetiology, burden, and associated clinical characteristics. We used quantitative diagnostic methods to reassess and refine estimates of diarrhoea aetiology from the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) cohort study. We re-analysed stool specimens from the multisite MAL-ED cohort study of children aged 0-2 years done at eight locations (Dhaka, Bangladesh; Vellore, India; Bhaktapur, Nepal; Naushero Feroze, Pakistan; Venda, South Africa; Haydom, Tanzania; Fortaleza, Brazil; and Loreto, Peru), which included active surveillance for diarrhoea and routine non-diarrhoeal stool collection. We used quantitative PCR to test for 29 enteropathogens, calculated population-level pathogen-specific attributable burdens, derived stringent quantitative cutoffs to identify aetiology for individual episodes, and created aetiology prediction scores using clinical characteristics. We analysed 6625 diarrhoeal and 30 968 non-diarrhoeal surveillance stools from 1715 children. Overall, 64·9% of diarrhoea episodes (95% CI 62·6-71·2) could be attributed to an aetiology by quantitative PCR compared with 32·8% (30·8-38·7) using the original study microbiology. Viral diarrhoea (36·4% of overall incidence, 95% CI 33·6-39·5) was more common than bacterial (25·0%, 23·4-28·4) and parasitic diarrhoea (3·5%, 3·0-5·2). Ten pathogens accounted for 95·7% of attributable diarrhoea: Shigella (26·1 attributable episodes per 100 child-years, 95% CI 23·8-29·9), sapovirus (22·8, 18·9-27·5), rotavirus (20·7, 18·8-23·0), adenovirus 40/41 (19·0, 16·8-23·0), enterotoxigenic Escherichia coli (18·8, 16·5-23·8), norovirus (15·4, 13·5-20·1), astrovirus (15·0, 12·0-19·5), Campylobacter jejuni or C coli (12·1, 8·5-17·2), Cryptosporidium (5·8, 4·3-8·3), and typical enteropathogenic E coli (5·4, 2·8-9·3). 86·2% of the attributable incidence for Shigella was non-dysenteric. A prediction score for shigellosis was more accurate (sensitivity 50·4% [95% CI 46·7-54·1], specificity 84·0% [83·0-84·9]) than current guidelines, which recommend treatment only of bloody diarrhoea to cover Shigella (sensitivity 14·5% [95% CI 12·1-17·3], specificity 96·5% [96·0-97·0]). Quantitative molecular diagnostics improved estimates of pathogen-specific burdens of childhood diarrhoea in the community setting. Viral causes predominated, including a substantial burden of sapovirus; however, Shigella had the highest overall burden with a high incidence in the second year of life. These data could improve the management of diarrhoea in these low-resource settings. Bill & Melinda Gates Foundation. Optimum management of childhood diarrhoea in low-resource settings has been hampered by insufficient data on aetiology, burden, and associated clinical characteristics. We used quantitative diagnostic methods to reassess and refine estimates of diarrhoea aetiology from the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) cohort study.BACKGROUNDOptimum management of childhood diarrhoea in low-resource settings has been hampered by insufficient data on aetiology, burden, and associated clinical characteristics. We used quantitative diagnostic methods to reassess and refine estimates of diarrhoea aetiology from the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) cohort study.We re-analysed stool specimens from the multisite MAL-ED cohort study of children aged 0-2 years done at eight locations (Dhaka, Bangladesh; Vellore, India; Bhaktapur, Nepal; Naushero Feroze, Pakistan; Venda, South Africa; Haydom, Tanzania; Fortaleza, Brazil; and Loreto, Peru), which included active surveillance for diarrhoea and routine non-diarrhoeal stool collection. We used quantitative PCR to test for 29 enteropathogens, calculated population-level pathogen-specific attributable burdens, derived stringent quantitative cutoffs to identify aetiology for individual episodes, and created aetiology prediction scores using clinical characteristics.METHODSWe re-analysed stool specimens from the multisite MAL-ED cohort study of children aged 0-2 years done at eight locations (Dhaka, Bangladesh; Vellore, India; Bhaktapur, Nepal; Naushero Feroze, Pakistan; Venda, South Africa; Haydom, Tanzania; Fortaleza, Brazil; and Loreto, Peru), which included active surveillance for diarrhoea and routine non-diarrhoeal stool collection. We used quantitative PCR to test for 29 enteropathogens, calculated population-level pathogen-specific attributable burdens, derived stringent quantitative cutoffs to identify aetiology for individual episodes, and created aetiology prediction scores using clinical characteristics.We analysed 6625 diarrhoeal and 30 968 non-diarrhoeal surveillance stools from 1715 children. Overall, 64·9% of diarrhoea episodes (95% CI 62·6-71·2) could be attributed to an aetiology by quantitative PCR compared with 32·8% (30·8-38·7) using the original study microbiology. Viral diarrhoea (36·4% of overall incidence, 95% CI 33·6-39·5) was more common than bacterial (25·0%, 23·4-28·4) and parasitic diarrhoea (3·5%, 3·0-5·2). Ten pathogens accounted for 95·7% of attributable diarrhoea: Shigella (26·1 attributable episodes per 100 child-years, 95% CI 23·8-29·9), sapovirus (22·8, 18·9-27·5), rotavirus (20·7, 18·8-23·0), adenovirus 40/41 (19·0, 16·8-23·0), enterotoxigenic Escherichia coli (18·8, 16·5-23·8), norovirus (15·4, 13·5-20·1), astrovirus (15·0, 12·0-19·5), Campylobacter jejuni or C coli (12·1, 8·5-17·2), Cryptosporidium (5·8, 4·3-8·3), and typical enteropathogenic E coli (5·4, 2·8-9·3). 86·2% of the attributable incidence for Shigella was non-dysenteric. A prediction score for shigellosis was more accurate (sensitivity 50·4% [95% CI 46·7-54·1], specificity 84·0% [83·0-84·9]) than current guidelines, which recommend treatment only of bloody diarrhoea to cover Shigella (sensitivity 14·5% [95% CI 12·1-17·3], specificity 96·5% [96·0-97·0]).FINDINGSWe analysed 6625 diarrhoeal and 30 968 non-diarrhoeal surveillance stools from 1715 children. Overall, 64·9% of diarrhoea episodes (95% CI 62·6-71·2) could be attributed to an aetiology by quantitative PCR compared with 32·8% (30·8-38·7) using the original study microbiology. Viral diarrhoea (36·4% of overall incidence, 95% CI 33·6-39·5) was more common than bacterial (25·0%, 23·4-28·4) and parasitic diarrhoea (3·5%, 3·0-5·2). Ten pathogens accounted for 95·7% of attributable diarrhoea: Shigella (26·1 attributable episodes per 100 child-years, 95% CI 23·8-29·9), sapovirus (22·8, 18·9-27·5), rotavirus (20·7, 18·8-23·0), adenovirus 40/41 (19·0, 16·8-23·0), enterotoxigenic Escherichia coli (18·8, 16·5-23·8), norovirus (15·4, 13·5-20·1), astrovirus (15·0, 12·0-19·5), Campylobacter jejuni or C coli (12·1, 8·5-17·2), Cryptosporidium (5·8, 4·3-8·3), and typical enteropathogenic E coli (5·4, 2·8-9·3). 86·2% of the attributable incidence for Shigella was non-dysenteric. A prediction score for shigellosis was more accurate (sensitivity 50·4% [95% CI 46·7-54·1], specificity 84·0% [83·0-84·9]) than current guidelines, which recommend treatment only of bloody diarrhoea to cover Shigella (sensitivity 14·5% [95% CI 12·1-17·3], specificity 96·5% [96·0-97·0]).Quantitative molecular diagnostics improved estimates of pathogen-specific burdens of childhood diarrhoea in the community setting. Viral causes predominated, including a substantial burden of sapovirus; however, Shigella had the highest overall burden with a high incidence in the second year of life. These data could improve the management of diarrhoea in these low-resource settings.INTERPRETATIONQuantitative molecular diagnostics improved estimates of pathogen-specific burdens of childhood diarrhoea in the community setting. Viral causes predominated, including a substantial burden of sapovirus; however, Shigella had the highest overall burden with a high incidence in the second year of life. These data could improve the management of diarrhoea in these low-resource settings.Bill & Melinda Gates Foundation.FUNDINGBill & Melinda Gates Foundation. |
Author | Ahmed, Imran Silapong, Sasikorn Houpt, Eric R Vasquez, Angel Orbe Kabir, Furqan Bauck, Aubrey Ross, A Catharine Jennifer, M. Steffi Petri, William A Bodhidatta, Ladaporn Sundaram, Shanmuga Liu, Jie Svensen, Erling Medeiros, Pedro HQS Yarrot, Ladislaus Murray-Kolb, Laura E Olotegui, Maribel Paredes Patil, Crystal L Page, Nicola Guerrant, Richard L Roshan, Reeba Flores, Julian Torres Yori, Pablo P Rayamajhi, Bishnu Bahadur Barrett, Leah Moraes, Milena Muliyil, Jayaprakash Ammu, Geetha Maciel, Bruna LL Nahar, Baitun Shrestha, Prakash Sunder Kaki, Shiny Leite, Jose Paulo Raju, Sophy Hariraju, Dinesh Gratz, Jean Pan, William K Dillingham, Rebecca Filho, José Quirino Roberts, James H Lazarus, Robin P Kiwelu, Ireen Havt, Alexandre Hossain, Md Iqbal Ahmed, Tahmeed Benny, Blossom Rajendiran, Revathi Gottlieb, Michael Lang, Dennis Trigoso, Dixner Rengifo Shrestha, Rita Schaefer, Barbara Mota, Francisco S Lertsethtakarn, Paphavee Nshama, Rosemary Bose, Anuradha Mduma, Estomih R Turab, Ali Schulze, Kerry McGrath, Monica Mvungi, Regisiana Leite, Álvaro M Lima |
AuthorAffiliation | g Christian Medical College, Vellore, India o Foundation for the National Institutes of Health, Bethesda, MD, USA m Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA b Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA h University of Venda, Thohoyandou, South Africa i Haydom Global Health Institute, Haydom, Tanzania q Walter Reed/AFRIMS Research Unit, Nepal, Kathmandu, Nepal d Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok, Thailand c Aga Khan University, Karachi, Pakistan f International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh a Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA, USA e Asociación Benéfica PRISMA, Iquitos, Peru r University of Bergen, Bergen, Norway k Federal University of Ceara, Fortaleza, Brazil l Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil p National Institute for Communicable Diseases, Johannesburg, South Africa |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30287127$$D View this record in MEDLINE/PubMed |
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ContentType | Journal Article |
Contributor | Ahmed, Imran Vasquez, Angel Orbe Maciel, Bruna Ll Bauck, Aubrey Ross, A Catharine Petri, William A Sundaram, Shanmuga Svensen, Erling Medeiros, Pedro Hqs Ahmed, Am Shamsir Yarrot, Ladislaus Murray-Kolb, Laura E Olotegui, Maribel Paredes Roshan, Reeba Flores, Julian Torres Rayamajhi, Bishnu Bahadur Barrett, Leah Moraes, Milena Muliyil, Jayaprakash Ammu, Geetha Nahar, Baitun Shrestha, Prakash Sunder Kaki, Shiny Raju, Sophy Hariraju, Dinesh Pan, William K Dillingham, Rebecca Filho, José Quirino Lazarus, Robin P Hossain, Md Iqbal Trigoso, Dixner Rengifo Shrestha, Rita Schaefer, Barbara Mota, Francisco S Bose, Anuradha Turab, Ali Schulze, Kerry Mvungi, Regisiana Leite, Álvaro M Simons, Suzanne Mondal, Dinesh Rose, Anuradha Chandyo, Ram Krishna Ramanujam, Karthikeyan Oriá, Reinaldo B Karunakaran, Priyadarshani Psaki, Stephanie Caulfield, Laura Lee, Gwenyth Ramachandran, Anup Ramadas, Rakhi Soofi, Sajid Zaidi, Anita Km Shrestha, Binob Koshy, Beena Knobler, Stacey Amour, Caroline Bayyo, Eliwaza Lima, Noélia L Di Moura, Alessandra Scharf, Rebecca Strand, |
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Snippet | Optimum management of childhood diarrhoea in low-resource settings has been hampered by insufficient data on aetiology, burden, and associated clinical... Background: Optimum management of childhood diarrhoea in low-resource settings has been hampered by insufficient data on aetiology, burden, and associated... |
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SubjectTerms | Asia, Western - epidemiology Brazil - epidemiology Child, Preschool Cohort Studies Diarrhea - epidemiology Diarrhea - etiology Health Resources - supply & distribution Humans Incidence Infant Infant, Newborn Molecular Diagnostic Techniques Peru - epidemiology Real-Time Polymerase Chain Reaction South Africa - epidemiology Tanzania - epidemiology |
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Title | Use of quantitative molecular diagnostic methods to assess the aetiology, burden, and clinical characteristics of diarrhoea in children in low-resource settings: a reanalysis of the MAL-ED cohort study |
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