Development of clinical sign based algorithms for community based assessment of omphalitis.
BACKGROUND
In developing countries, newborn omphalitis contributes significantly to morbidity and mortality. Community based identification and management of omphalitis will require standardised clinical sign based definitions.


OBJECTIVE
To identify optimal sign based algorithms to define omphalitis in the community and to evaluate the reliability and validity of cord assessments by non-specialist health workers for clinical signs of omphalitis.


METHODS
Within a trial of the impact of topical antiseptics on umbilical cord infection in rural Nepal, digital images of the umbilical cord were collected. Workers responsible for in-home examinations of the umbilical cord evaluated the images for signs of infection (pus, redness, swelling). Intraworker and interworker agreement was evaluated, and sensitivity and specificity compared with a physician generated gold standard ranking were estimated.


RESULTS
Sensitivity and specificity of worker evaluations were high for pus (90% and 96% respectively) and moderate for redness (57% and 95% respectively). Swelling was the least reliably identified sign. Measures of observer agreement were similar to that previously recorded between experts evaluating subjective skin conditions. A composite definition for omphalitis that combined pus and redness without regard to swelling was the most sensitive and specific.


CONCLUSIONS
Two sign based algorithms for defining omphalitis are recommended for use in the community. Focusing on redness extending to the skin around the base of the stump will identify cases of moderate and high severity. Requiring both the presence of pus and redness will result in a definition with very high specificity and moderate to high sensitivity.
Mullany
L C
LC
Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street, Suite W5021, Baltimore, MD 21211, USA. lmullany@jhsph.edu
Darmstadt
G L
GL
Katz
J
J
Khatry
S K
SK
LeClerq
S C
SC
Adhikari
R K
RK
Tielsch
J M
JM
D000465:Algorithms; D001424:Bacterial Infections / Q000175:diagnosis* / Q000473:pathology; D003153:Community Health Services; D003150:Community Health Workers; D003906:Developing Countries; D004890:Erythema / Q000175:diagnosis / Q000382:microbiology / Q000473:pathology; D006801:Humans; D007231:Infant, Newborn; D009390:Nepal; D015588:Observer Variation; D010781:Photography; D019035:Rural Health Services; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D013492:Suppuration / Q000382:microbiology / Q000473:pathology; D014470:Umbilical Cord / Q000382:microbiology* / Q000473:pathology