To help reduce paediatric morbidity and mortality in the developing world, WHO has developed a diagnostic and treatment algorithm that targets the principal causes of death in children, which include acute respiratory infection, malaria, measles, diarrhoeal disease, and malnutrition. With this algorithm, known as the Sick Child Charts, severely ill children are rapidly identified, through the presence of any one of 13 signs indicative of severe illness, and referred for more intensive health care. These signs are the inability to drink, abnormal mental status (abnormally sleepy), convulsions, wasting, oedema, chest wall retraction, stridor, abnormal skin turgor, repeated vomiting, stiff neck, tender swelling behind the ear, pallor of the conjunctiva, and corneal ulceration. The usefulness of these signs, both in current clinical practice and within the optimized context of the Sick Child Chart algorithm in a rural district of western Kenya, was evaluated. We found that 27% of children seen in outpatient clinics had one or more of these signs and that pallor and chest wall retraction were the signs most likely to be associated with hospital admission (odds ratio (OR) = 8.6 and 5.3, respectively). Presentation with any of these signs led to a 3.2 times increased likelihood of admission, although 54% of hospitalized children had no such signs and 21% of children sent home from the outpatient clinic had at least one sign. Among inpatients, 58% of all children and 89% of children who died had been admitted with a sign. Abnormal mental status was the sign most highly associated with death (OR = 59.6), followed by poor skin turgor (OR = 5.6), pallor (OR = 4.3), repeated vomiting (OR = 3.6), chest wall retraction (OR = 2.7), and oedema (OR = 2.4). Overall, the mortality risk associated with having at least one sign was 6.5 times higher than that for children without any sign. While these signs are useful in identifying a subset of children at high risk of death, their validation in other settings is needed. The training and supervision of health workers to identify severely ill children should continue to be given high priority because of the benefits, such as reduction of childhood mortality.
PIP: The World Health Organization (WHO) has developed a diagnostic and treatment algorithm to facilitate the rapid identification and management of severely ill children in developing countries. 13 indicators are listed on Sick Child Charts: inability to drink, abnormal mental status (e.g., sleepiness), convulsions, wasting, edema, chest wall retraction, stridor, abnormal skin turgor, repeated vomiting, stiff neck, tender swelling behind the ear, pallor of the conjunctiva, and corneal ulceration. These indicators target the principal causes of child mortality: acute respiratory infection, malaria, measles, diarrheal disease, and malnutrition. The usefulness of the WHO algorithm was evaluated in 4 clinics in western Kenya's Siaya district and in the pediatric outpatient and inpatient departments of Siaya District Hospital. 770 (28%) of the 2799 children (mean age, 13 months) seen in these rural outpatient clinics had 1 or more of the 13 signs, most frequently repeated vomiting (13%). Children with any of these signs had a 2.3 times higher odds of hospitalization than those without such signs; however, 424 admitted children (54%) had none of the 13 signs. Pallor and chest wall retraction were most highly associated with hospital admission (odds ratio [OR], 8.6 and 5.3, respectively). Among the 1139 inpatients, 666 (58%) presented with at least 1 sign and 75 (7%) died, 67 (89%) of whom had at least 1 clinical sign at admission. Overall, the mortality risk associated with having at least 1 sign was 6.5 times higher than that for children with none of the signs. The signs most associated with mortality were abnormal mental status (OR, 59.6), poor skin turgor (OR, 5.6), pallor (OR, 4.3), repeated vomiting (OR, 3.6), chest wall retraction (OR, 2.7), and edema (OR, 2.4). Although studies in other settings are required to validate the WHO logarithm, this schema appears to be a feasible means for identifying high-risk children in developing countries.