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An evaluation of clinical indicators for severe paediatric illness
L A Paxton1, S C Redd, R W Steketee
1Rakai Project, Entebbe, Uganda.
Insights
The Sick Child Charts algorithm helps identify severely ill children in developing countries. Key signs like abnormal mental status significantly increase the risk of death, highlighting the need for health worker training.
Area of Science:
- Global Health
- Pediatrics
- Public Health
Background:
- The World Health Organization (WHO) developed the Sick Child Charts algorithm to combat high pediatric morbidity and mortality in developing nations.
- The algorithm targets major childhood killers: acute respiratory infection, malaria, measles, diarrheal disease, and malnutrition.
Purpose of the Study:
- To evaluate the effectiveness of 13 key signs of severe illness in identifying children needing intensive care.
- To assess the utility of these signs in current clinical practice and within the Sick Child Chart algorithm in rural Kenya.
Main Methods:
- A study was conducted in a rural district of western Kenya to evaluate the diagnostic signs.
- Data collected on children in outpatient clinics and hospitalized patients, analyzing the association between specific signs and outcomes like hospital admission and death.
Main Results:
- 27% of outpatient clinic attendees presented with at least one danger sign; pallor and chest wall retraction were strong predictors of hospital admission.
- Abnormal mental status was the sign most strongly associated with death (OR=59.6), with overall mortality risk 6.5 times higher for children with any sign.
- Despite the signs' utility, 54% of hospitalized children lacked them, and 21% of those sent home had at least one sign, indicating limitations.
Conclusions:
- The identified signs are valuable for identifying a subset of severely ill children at high risk of mortality.
- Continued training and supervision of healthcare workers in identifying danger signs are crucial for reducing childhood mortality.
- Further validation of these signs in diverse settings is recommended to refine the Sick Child Chart algorithm.
Abstract:
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.