Non-invasive respiratory support using bubble continuous positive airway pressure (bCPAP) is useful in treating babies with respiratory distress syndrome. Despite its proven clinical and cost-effectiveness, implementation is hampered by the inappropriate administration of bCPAP in low-resource settings. A clinical algorithm—‘TRY’ (based on Tone: good; Respiratory distress; Yes, heart rate above 100 beats/min)—has been developed to correctly identify which newborns would benefit most from bCPAP in a teaching hospital in Malawi.Objective
To evaluate the reliability, sensitivity and specificity of TRY when employed by nurses in a Malawian district hospital.Methods
Nursing staff in a Malawian district hospital baby unit were asked, over a 2-month period, to complete TRY assessments for every newly admitted baby with the following inclusion criteria: clinical evidence of respiratory distress and/or birth weight less than 1.3 kg. A visiting paediatrician, blinded to nurses’ assessments, concurrently assessed each baby, providing both a TRY assessment and a clinical decision regarding the need for CPAP administration. Inter-rater reliability was calculated comparing nursing and paediatrician TRY assessment outcomes. Sensitivity and specificity were estimated comparing nurse TRY assessments against the paediatrician’s clinical decision.Results
Two hundred and eighty-seven infants were admitted during the study period; 145 (51%) of these met the inclusion criteria, and of these 57 (39%) received joint assessments. The inter-rater reliability was high (kappa 0.822). Sensitivity and specificity were 92% and 96%, respectively.Conclusions
District hospital nurses, using the TRY-CPAP algorithm, reliably identified babies that might benefit from bCPAP and thus improved its effective implementation.