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Development of clinical sign based algorithms for community based assessment of omphalitis

L C Mullany1, G L Darmstadt, J Katz

  • 1Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street, Suite W5021, Baltimore, MD 21211, USA. lmullany@jhsph.edu

Insights

Community health workers can reliably identify newborn omphalitis (umbilical cord infection) using simple sign-based definitions. Algorithms focusing on pus and redness improve diagnosis accuracy, reducing newborn morbidity and mortality in developing countries.

Area of Science:

  • Neonatal Health
  • Infectious Disease Epidemiology
  • Global Health

Background:

  • Newborn omphalitis is a major cause of illness and death in developing nations.
  • Standardized clinical definitions are crucial for community-based omphalitis management.

Purpose of the Study:

  • To develop optimal sign-based algorithms for diagnosing omphalitis in community settings.
  • To assess the reliability and validity of non-specialist health worker assessments of umbilical cord infection signs.

Main Methods:

  • Digital umbilical cord images were analyzed by community health workers for signs of infection (pus, redness, swelling).
  • Intra- and inter-worker agreement was assessed.
  • Sensitivity and specificity were compared against a physician-determined gold standard.

Main Results:

  • High sensitivity (90%) and specificity (96%) were found for detecting pus.
  • Moderate sensitivity (57%) and high specificity (95%) were observed for redness.
  • A composite definition using pus and redness, excluding swelling, demonstrated the best diagnostic performance.

Conclusions:

  • Two sign-based algorithms are recommended for community omphalitis diagnosis.
  • Focusing on redness extending to the surrounding skin identifies moderate to severe cases.
  • Requiring both pus and redness offers high specificity and moderate-to-high sensitivity for diagnosing omphalitis.
Abstract

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