Academic journal article Bulletin of the World Health Organization

An Evaluation of Clinical Indicators for Severe Paediatric Illness

Academic journal article Bulletin of the World Health Organization

An Evaluation of Clinical Indicators for Severe Paediatric Illness

Article excerpt

Introduction

The reduction of child mortality rates in developing countries, which are about 5-15 times higher than those in developed countries (1-3), is one of the greatest public health challenges faced by developing countries. In many countries attempts to achieve this goal are hampered by difficulties in access to health services that provide correct standard case management, or ignorance among families of the signs of severe disease in children or of the most appropriate place to go for treatment (3). At the international level, therefore, several organizations have sought to improve the quality of paediatric health care in developing countries by encouraging the use of standardized approaches to diagnosis and treatment. For some diseases, these recommendations have been simplified and promoted as algorithms.(a,b) These algorithms, which were designed to be used by clinical workers at first-level health facilities, encourage a standard approach to clinical diagnosis based on the duration and severity of the patient's symptoms and on the detection of simple signs by physical examination.

Algorithms for management of single disease entities such as diarrhoea or acute respiratory infections have been successfully instituted in many countries (4).(c,d) However, children often suffer from multiple disease processes simultaneously, and the use of disease-specific algorithms may inadvertently make health care workers focus attention on only one disease (5,6). To overcome this problem WHO has recently developed a composite algorithm, known as the Sick Child Charts, to integrate previous algorithms aimed at the main causes of preventable paediatric morbidity and mortality in the developing world (7). These causes include acute respiratory infection, malaria, measles, diarrhoeal disease, malnutrition, and otitis media, which are estimated to cause 70% of deaths among children in the developing world.

This algorithm is organized so that severely ill children can be rapidly identified and managed. Children with any one of 13 clinical signs of severe illness are to be given initial therapy and referred for more intensive health care. These signs were taken from disease-specific algorithms and were combined by WHO with the aid of expert clinical opinion.(e) The signs are presumed to identify children at high risk of death or serious disability and include the inability to drink, abnormal mental status (defined as being abnormally sleepy or difficult to rouse), convulsions (from the carer's history), evidence of malnutrition (wasting, oedema), respiratory distress (chest wall retraction, stridor), severe dehydration (abnormal skin turgor, repeated vomiting), meningitis (stiff neck), mastoiditis (tender swelling behind the ear), severe anaemia (pallor of the conjunctivae), and corneal ulceration or clouding.

The usefulness of this system to identify children with severe illness has not been assessed. As part of an evaluation of a preliminary version of the Sick Child Assess and Classify Chart, we examined the clinical utility of these 13 signs. We recorded the prevalence of the signs among children seen in outpatient clinics, assessed their current role in determining hospital admission, and determined the risk of in-hospital mortality associated with each sign.

Methods

Study site. The outpatient evaluation was conducted from August to December 1993 in four clinics in Siaya District, western Kenya, and in the paediatric outpatient department of Siaya District Hospital, which is the referral hospital for the district. The inpatient study was conducted from mid-June to mid-November 1993 in the inpatient ward of Siaya District Hospital. This inpatient service admits children from both its own outpatient department and other facilities in the district.

Study population and sUrvey methods. The investigators selected prospective health workers with a minimum of secondary school education to be trained to identify the 13 signs of severity. …

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