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Respiratory rate and pulse oximetry derived information as predictors of hospital admission in young children in Bangladesh: a prospective observational study
  1. Ainara Garde1,
  2. Guohai Zhou2,
  3. Shahreen Raihana3,
  4. Dustin Dunsmuir4,
  5. Walter Karlen5,
  6. Parastoo Dekhordi1,
  7. Tanvir Huda3,6,
  8. Shams El Arifeen3,
  9. Charles Larson7,
  10. Niranjan Kissoon7,
  11. Guy A Dumont1,
  12. J Mark Ansermino4
  1. 1Department of Electrical & Computer Engineering, The University of British Columbia, Vancouver, British Columbia, Canada
  2. 2Department of Statistics, The University of British Columbia, Vancouver, British Columbia, Canada
  3. 3Centre for Child and Adolescent Health, International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh
  4. 4Department of Anesthesiology, Pharmacology & Therapeutics, The University of British Columbia, Vancouver, British Columbia, Canada
  5. 5Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland
  6. 6School of Public Health, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
  7. 7Department of Pediatrics, British Columbia Children's Hospital and The University of British Columbia, Vancouver, British Columbia, Canada
  1. Correspondence to Dr Ainara Garde; ainara.garde{at}cw.bc.ca

Abstract

Objective Hypoxaemia 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.

Setting Tertiary-level hospital emergency department in Bangladesh.

Participants Children 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 outcome The need for hospitalisation based on expert physician review and follow-up.

Methods Pulse 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.

Results Children 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.

Conclusions Objective 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.

  • Paediatric infectious disease
  • Pulse oximetry
  • Heart rate variability
  • Global health
  • Mobile health

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

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