TY - JOUR
T1 - Performance of automated point-of-care respiratory rate counting versus manual counting in children under five admitted with severe febrile illness to Kisantu Hospital, DR Congo
AU - Tack, Bieke
AU - Vita, Daniel
AU - Mbaki, Thomas Nsema
AU - Lunguya, Octavie
AU - Toelen, Jaan
AU - Jacobs, Jan
N1 - FTX; DOAJ; (CC BY 4.0)
PY - 2021
Y1 - 2021
N2 - To improve the early recognition of danger signs in children with severe febrile illness in low resource settings, WHO promotes automated respiratory rate (RR) counting, but its performance is unknown in this population. Therefore, we prospectively evaluated the field performance of automated point-of-care plethysmography-based RR counting in hospitalized children with severe febrile illness (<5 years) in DR Congo. A trained research nurse simultaneously counted the RR manually (comparative method) and automatically with the Masimo Rad G pulse oximeter. Valid paired RR measurements were obtained in 202 (83.1%) children, among whom 43.1% (87/202) had fast breathing according to WHO criteria based on manual counting. Automated counting frequently underestimated the RR (median difference of -1 breath/minute; p2.5-p97.5 limits of agreement: -34-6), particularly at higher RR. This resulted in a failure to detect fast breathing in 24.1% (21/87) of fast breathing children (positive percent agreement: 75.9%), which was not explained by clinical characteristics (p > 0.05). Children without fast breathing were mostly correctly classified (negative percent agreement: 98.3%). In conclusion, in the present setting the automated RR counter performed insufficiently to facilitate the early recognition of danger signs in children with severe febrile illness, given wide limits of agreement and a too low positive percent agreement.
AB - To improve the early recognition of danger signs in children with severe febrile illness in low resource settings, WHO promotes automated respiratory rate (RR) counting, but its performance is unknown in this population. Therefore, we prospectively evaluated the field performance of automated point-of-care plethysmography-based RR counting in hospitalized children with severe febrile illness (<5 years) in DR Congo. A trained research nurse simultaneously counted the RR manually (comparative method) and automatically with the Masimo Rad G pulse oximeter. Valid paired RR measurements were obtained in 202 (83.1%) children, among whom 43.1% (87/202) had fast breathing according to WHO criteria based on manual counting. Automated counting frequently underestimated the RR (median difference of -1 breath/minute; p2.5-p97.5 limits of agreement: -34-6), particularly at higher RR. This resulted in a failure to detect fast breathing in 24.1% (21/87) of fast breathing children (positive percent agreement: 75.9%), which was not explained by clinical characteristics (p > 0.05). Children without fast breathing were mostly correctly classified (negative percent agreement: 98.3%). In conclusion, in the present setting the automated RR counter performed insufficiently to facilitate the early recognition of danger signs in children with severe febrile illness, given wide limits of agreement and a too low positive percent agreement.
U2 - 10.3390/diagnostics11112078
DO - 10.3390/diagnostics11112078
M3 - A1: Web of Science-article
C2 - 34829427
SN - 2075-4418
VL - 11
JO - Diagnostics (Basel)
JF - Diagnostics (Basel)
IS - 11
ER -