Community-based validation of assessment of newborn illnesses by trained community health workers in Sylhet district of Bangladesh.
Objectives: To validate trained community health workers' recognition of signs and symptoms of newborn illnesses and classification of illnesses using a clinical algorithm during routine home visits in rural Bangladesh.Methods: Between August 2005 and May 2006, 288 newborns were assessed independent...
| Publicado en: | Tropical Medicine & International Health Vol. 14; no. 12; pp. 1448 - 1457 |
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| Autores principales: | , , , , , , , , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
Dec2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105259868&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105259868 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13602276 1YC jtl: Tropical Medicine & International Health issn: 13602276 maglogo: Y pubinfo: dt: Dec2009 vid: 14 iid: 12 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 105259868 NLM19807901 2010498737 10.1111/j.1365-3156.2009.02397.x NLM19807901 PMC2929169 105259868 ppf: 1448 ppct: 9 formats: tig: atl: Community-based validation of assessment of newborn illnesses by trained community health workers in Sylhet district of Bangladesh. aug: au: Baqui AH Arifeen SE Rosen HE Mannan I Rahman SM Al-Mahmud AB Hossain D Das MK Begum N Ahmed S Santosham M Black RE Darmstadt GL Baqui, Abdullah H Arifeen, Shams E Rosen, Heather E Mannan, Ishtiaq Rahman, Syed M Al-Mahmud, Arif Billah Hossain, Daniel affil: Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA sug: subj: Algorithms Allied Health Personnel Standards Infant, Newborn, Diseases Diagnosis Neonatal Assessment Standards Adolescence Adult Allied Health Personnel Education Bangladesh Female Human Infant, Newborn Middle Age Nursing Assessment Methods Sensitivity and Specificity Surveys Young Adult Adolescent: 13-18 years Adult: 19-44 years Infant, Newborn: birth-1 month Middle Aged: 45-64 years Female ab: Objectives: To validate trained community health workers' recognition of signs and symptoms of newborn illnesses and classification of illnesses using a clinical algorithm during routine home visits in rural Bangladesh.Methods: Between August 2005 and May 2006, 288 newborns were assessed independently by a community health worker and a study physician. Based on a 20-sign algorithm, sick neonates were classified as having very severe disease, possible very severe disease or no disease. The physician's assessment was considered as the gold standard.Results: Community health workers correctly classified very severe disease in newborns with a sensitivity of 91%, specificity of 95% and kappa value of 0.85 (P < 0.001). Community health workers' recognition showed a sensitivity of more than 60% and a specificity of 97-100% for almost all signs and symptoms.Conclusion: Community health workers with minimal training can use a diagnostic algorithm to identify severely ill newborns with high validity. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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