Validation of community health workers' assessment of neonatal illness in rural Bangladesh.
Objective To estimate the validity (sensitivity, specificity, and positive and negative predictive values) of a clinical algorithm as used by community health workers (CHWs) to detect and classify neonatal illness during routine household visits in rural Bangladesh. Methods CHWs evaluated breastfeed...
| Publicado en: | Bulletin of the World Health Organization Vol. 87; no. 1; pp. 12 - 20 |
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| Autores principales: | , , , , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
World Health Organization
Jan2009
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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=105629378&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105629378 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00429686 BUW jtl: Bulletin of the World Health Organization issn: 00429686 maglogo: N pubinfo: dt: Jan2009 vid: 87 iid: 1 pid: 437 pub: World Health Organization artinfo: ui: 105629378 105629378 2010169431 10.2471/blt.07.050666 NLM19197400 105629378 ppf: 12 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Validation of community health workers' assessment of neonatal illness in rural Bangladesh. aug: au: Darmstadt GL Baqui AH Choi Y Bari S Rahman SM Mannan I Ahmed ASM Saha SK Rahman R Chang S Winch PJ Black R Santosham M El Arifeen S sug: subj: Community Health Workers Evaluation Infant, Newborn, Diseases Diagnosis Patient Assessment Evaluation Bangladesh Breast Feeding Evaluation Data Analysis Software Data Analysis, Statistical Descriptive Statistics Funding Source Infant, Newborn kappa Statistic Pearson's Correlation Coefficient Predictive Value of Tests Prospective Studies Sensitivity and Specificity Human Infant, Newborn: birth-1 month ab: Objective To estimate the validity (sensitivity, specificity, and positive and negative predictive values) of a clinical algorithm as used by community health workers (CHWs) to detect and classify neonatal illness during routine household visits in rural Bangladesh. Methods CHWs evaluated breastfeeding and symptoms and signs of illness in 395 neonates selected randomly from neonatal illness surveillance during household visits on postnatal days 0, 2, 5 and 8. Neonates classified with very severe disease (VSD) were referred to a community-based hospital. Within 12 hours of CHW assessments, physicians independently evaluated all neonates seen in a given day by one CHW, randomly chosen from among 36 project CHWs. Physicians recorded symptoms and signs of illness, classified the illness, and determined whether the newborn needed referral-level care at the hospital. Physicians' identification and classification were used as the gold standard in determining the validity of CHWs' identification of symptoms and signs of illness and its classification. Findings CHWs' classification of VSD showed a sensitivity of 73%, a specificity of 98%, a positive predictive value of 57% and a negative predictive value of 99%. A maternal report of any feeding problem as ascertained by physician questioning was significantly associated (P < 0.001) with 'not sucking at all' and 'not attached at all' or 'not well attached' as determined clinically by CHWs during feeding assessment. Conclusion CHWs identified with high validity the neonates with severe illness needing referral-level care. Home-based illness recognition and management, including referral of neonates with severe illness by CHWs, is a promising strategy for improving neonatal health and survival in low-resource developing country settings. Copyright © 2008 World Health Organization pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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