Monique Gainey1, Kexin Qu2, Stephanie C Garbern3, Meagan A Barry3, John Austin Lee3, Sabiha Nasrin4, Mahmuda Monjory4, Eric J Nelson5, Rochelle Rosen6, Nur H Alam4, Christopher H Schmid2, Adam C Levine3. 1. Rhode Island Hospital, Providence, RI, USA. 2. Department of Biostatistics, Brown University School of Public Health, Providence, RI, USA. 3. Department of Emergency Medicine, Alpert Medical School, Brown University, Providence, RI, USA. 4. International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh. 5. Departments of Pediatrics and Environmental and Global Health, Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA. 6. Department of Behavioral and Social Sciences, School of Public Health, Brown University, Providence, RI, USA.
Abstract
OBJECTIVE: Accurately assessing dehydration severity is a critical step in reducing mortality from diarrhoea, but is complicated by cholera and undernutrition. This study seeks to assess the accuracy of two clinical diagnostic models for dehydration among patients over five years with cholera and undernutrition and compare their respective performance to the World Health Organization (WHO) algorithm. METHODS: In this secondary analysis of data collected from the NIRUDAK study, accuracy of the full and simplified NIRUDAK models for predicting severe and any dehydration was measured using the area under the Receiver Operator Characteristic curve (AUC) among patients over five with/without cholera and with/without wasting. Bootstrap with 1000 iterations was used to compare the m-index for each NIRUDAK model to that of the WHO algorithm. RESULTS: A total of 2,139 and 2,108 patients were included in the nutrition and cholera subgroups respectively with an overall median age of 35 years (IQR = 42) and 49.6% female. All subgroups had acceptable discrimination in diagnosing severe or any dehydration (AUC > 0.60); though the full NIRUDAK model performed best among patients without cholera, with an AUC of 0.82 (95%CI:0.79, 0.85) and among patients without wasting, with an AUC of 0.79 (95%CI:0.76, 0.81). Compared with the WHO's algorithm, both the full and simplified NIRUDAK models performed significantly better in terms of their m-index (p < 0.001) for all comparisons, except for the simplified NIRUDAK model in the wasting group. CONCLUSIONS: Both the full and simplified NIRUDAK models performed less well in patients over five years with cholera and/or wasting; however, both performed better than the WHO algorithm.
OBJECTIVE: Accurately assessing dehydration severity is a critical step in reducing mortality from diarrhoea, but is complicated by cholera and undernutrition. This study seeks to assess the accuracy of two clinical diagnostic models for dehydration among patients over five years with cholera and undernutrition and compare their respective performance to the World Health Organization (WHO) algorithm. METHODS: In this secondary analysis of data collected from the NIRUDAK study, accuracy of the full and simplified NIRUDAK models for predicting severe and any dehydration was measured using the area under the Receiver Operator Characteristic curve (AUC) among patients over five with/without cholera and with/without wasting. Bootstrap with 1000 iterations was used to compare the m-index for each NIRUDAK model to that of the WHO algorithm. RESULTS: A total of 2,139 and 2,108 patients were included in the nutrition and cholera subgroups respectively with an overall median age of 35 years (IQR = 42) and 49.6% female. All subgroups had acceptable discrimination in diagnosing severe or any dehydration (AUC > 0.60); though the full NIRUDAK model performed best among patients without cholera, with an AUC of 0.82 (95%CI:0.79, 0.85) and among patients without wasting, with an AUC of 0.79 (95%CI:0.76, 0.81). Compared with the WHO's algorithm, both the full and simplified NIRUDAK models performed significantly better in terms of their m-index (p < 0.001) for all comparisons, except for the simplified NIRUDAK model in the wasting group. CONCLUSIONS: Both the full and simplified NIRUDAK models performed less well in patients over five years with cholera and/or wasting; however, both performed better than the WHO algorithm.
Authors: Ben Van Calster; Vanya Van Belle; Yvonne Vergouwe; Dirk Timmerman; Sabine Van Huffel; Ewout W Steyerberg Journal: Stat Med Date: 2012-06-26 Impact factor: 2.373
Authors: James A Platts-Mills; Sudhir Babji; Ladaporn Bodhidatta; Jean Gratz; Rashidul Haque; Alexandre Havt; Benjamin Jj McCormick; Monica McGrath; Maribel Paredes Olortegui; Amidou Samie; Sadia Shakoor; Dinesh Mondal; Ila Fn Lima; Dinesh Hariraju; Bishnu B Rayamajhi; Shahida Qureshi; Furqan Kabir; Pablo P Yori; Brenda Mufamadi; Caroline Amour; J Daniel Carreon; Stephanie A Richard; Dennis Lang; Pascal Bessong; Esto Mduma; Tahmeed Ahmed; Aldo Aam Lima; Carl J Mason; Anita Km Zaidi; Zulfiqar A Bhutta; Margaret Kosek; Richard L Guerrant; Michael Gottlieb; Mark Miller; Gagandeep Kang; Eric R Houpt Journal: Lancet Glob Health Date: 2015-07-19 Impact factor: 26.763
Authors: Karen L Kotloff; James P Nataro; William C Blackwelder; Dilruba Nasrin; Tamer H Farag; Sandra Panchalingam; Yukun Wu; Samba O Sow; Dipika Sur; Robert F Breiman; Abu Sg Faruque; Anita Km Zaidi; Debasish Saha; Pedro L Alonso; Boubou Tamboura; Doh Sanogo; Uma Onwuchekwa; Byomkesh Manna; Thandavarayan Ramamurthy; Suman Kanungo; John B Ochieng; Richard Omore; Joseph O Oundo; Anowar Hossain; Sumon K Das; Shahnawaz Ahmed; Shahida Qureshi; Farheen Quadri; Richard A Adegbola; Martin Antonio; M Jahangir Hossain; Adebayo Akinsola; Inacio Mandomando; Tacilta Nhampossa; Sozinho Acácio; Kousick Biswas; Ciara E O'Reilly; Eric D Mintz; Lynette Y Berkeley; Khitam Muhsen; Halvor Sommerfelt; Roy M Robins-Browne; Myron M Levine Journal: Lancet Date: 2013-05-14 Impact factor: 79.321
Authors: Lee Hooper; Asmaa Abdelhamid; Natalie J Attreed; Wayne W Campbell; Adam M Channell; Philippe Chassagne; Kennith R Culp; Stephen J Fletcher; Matthew B Fortes; Nigel Fuller; Phyllis M Gaspar; Daniel J Gilbert; Adam C Heathcote; Mohannad W Kafri; Fumiko Kajii; Gregor Lindner; Gary W Mack; Janet C Mentes; Paolo Merlani; Rowan A Needham; Marcel G M Olde Rikkert; Andreas Perren; James Powers; Sheila C Ranson; Patrick Ritz; Anne M Rowat; Fredrik Sjöstrand; Alexandra C Smith; Jodi J D Stookey; Nancy A Stotts; David R Thomas; Angela Vivanti; Bonnie J Wakefield; Nana Waldréus; Neil P Walsh; Sean Ward; John F Potter; Paul Hunter Journal: Cochrane Database Syst Rev Date: 2015-04-30