Respiratory rate and pulse oximetry derived information as predictors of hospital admission in young children in Bangladesh: a prospective observational study

• Published in: BMJ open Vol. 6; no. 8; p. e011094
• Main Authors: Garde, Ainara, Zhou, Guohai, Raihana, Shahreen, Dunsmuir, Dustin, Karlen, Walter, Dekhordi, Parastoo, Huda, Tanvir, Arifeen, Shams El, Larson, Charles, Kissoon, Niranjan, Dumont, Guy A, Ansermino, J Mark
• Format: Journal Article
• Language: English
• Published: England BMJ Publishing Group LTD 17.08.2016; BMJ Publishing Group
• Subjects: Arrhythmias, Cardiac - diagnosis; Bangladesh; Blood; Child, Preschool; Chronic Disease; Data collection; Disease; Early Diagnosis; Female; Global Health; Hospitalization; Hospitals; Humans; Hypoxia - diagnosis; Illnesses; Infant; Infant, Newborn; Infections; Interfaces; Low income groups; Male; Medical personnel; Medical referrals; Mobile Applications; Mortality; Oximetry; Oxygen - blood; Oxygen saturation; Photoplethysmography; Physicians; Point-of-Care Systems; Prospective Studies; Pulse oximetry; Reproducibility of Results; Respiratory Rate - physiology; Sepsis; Smartphones; Womens health; United States > US; Bangladesh; Global health; Pulse oximetry; Heart rate variability; Paediatric infectious disease; Mobile health
• ISSN: 2044-6055; 2044-6055
• DOI: 10.1136/bmjopen-2016-011094

ObjectiveHypoxaemia is a strong predictor of mortality in children. Early detection of deteriorating condition is vital to timely intervention. We hypothesise that measures of pulse oximetry dynamics may identify children requiring hospitalisation. Our aim was to develop a predictive tool using only objective data derived from pulse oximetry and observed respiratory rate to identify children at increased risk of hospital admission.SettingTertiary-level hospital emergency department in Bangladesh.ParticipantsChildren under 5 years (n=3374) presenting at the facility (October 2012–April 2013) without documented chronic diseases were recruited. 1-minute segments of pulse oximetry (photoplethysmogram (PPG), blood oxygen saturation (SpO2) and heart rate (HR)) and respiratory rate were collected with a mobile app.Primary outcomeThe need for hospitalisation based on expert physician review and follow-up.MethodsPulse rate variability (PRV) using pulse peak intervals of the PPG signal and features extracted from the SpO2 signal, all derived from pulse oximetry recordings, were studied. A univariate age-adjusted logistic regression was applied to evaluate differences between admitted and non-admitted children. A multivariate logistic regression model was developed using a stepwise selection of predictors and was internally validated using bootstrapping.ResultsChildren admitted to hospital showed significantly (p<0.01) decreased PRV and higher SpO2 variability compared to non-admitted children. The strongest predictors of hospitalisation were reduced PRV-power in the low frequency band (OR associated with a 0.01 unit increase, 0.93; 95% CI 0.89 to 0.98), greater time spent below an SpO2 of 98% and 94% (OR associated with 10 s increase, 1.4; 95% CI 1.3 to 1.4 and 1.5; 95% CI 1.4 to 1.6, respectively), high respiratory rate, high HR, low SpO2, young age and male sex. These variables provided a bootstrap-corrected AUC of the receiver operating characteristic of 0.76.ConclusionsObjective measurements, easily obtained using a mobile device in low-resource settings, can predict the need for hospitalisation. External validation will be required before clinical adoption.