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Different Features of Cholera in Malnourished and Non-Malnourished Children: Analysis of 20 Years of Surveillance Data from a Large Diarrheal Disease Hospital in Urban Bangladesh.

Sharika NuzhatMd Iqbal HossainNusrat Jahan ShalyRafiqul IslamSoroar Hossain KhanAbu Syed Golam FaruquePradip Kumar BardhanAzharul Islam KhanMohammod Jobayer ChistiTahmeed Ahmed
Published in: Children (Basel, Switzerland) (2022)
Malnourished children are more prone to infectious diseases including severe diarrhea compared to non-malnourished children. However, data are scarce on differences in the presentation in such children. We aimed to identify clinical differentials among children with cholera with or without malnutrition. Data were extracted from the diarrheal disease surveillance system (DDSS) of Dhaka Hospital of International Centre for Diarrheal Disease Research, Bangladesh (icddr,b) from January 2001 to December 2020. Among children under five in DDSS, cholera positive (culture confirmed) malnourished children (WAZ, WL/HZ or L/HAZ ˂ -2) were considered as cases ( n = 920) and children with cholera but non-malnourished (WAZ, WL/HZ or L/HAZ ≥-2.00 to ≤+2.00) were controls ( n = 586). After adjusting for potential confounders such as maternal illiteracy, day labor fathers, maternal employment, slum dwelling, non-sanitary latrine use, use of untreated water, and history of cough, it was revealed that malnourished cholera children significantly more often presented in hospital during evening hours (6 p.m. to 12 mid-night) ( p < 0.05), had illiterate fathers ( p < 0.05), >24 h history of diarrheal duration ( p < 0.05), dehydrating diarrhea ( p < 0.05), and had longer hospitalization ( p < 0.05). The study results underscore the importance of understanding of basic differences in the presentation of severity of cholera in malnourished children for prompt identification and subsequent management of these vulnerable children.
Keyphrases
  • young adults
  • public health
  • pregnant women
  • mental health
  • machine learning
  • depressive symptoms
  • body mass index
  • early onset
  • big data
  • mental illness