Evaluation of Sibel's Advanced Neonatal Epidermal (ANNE) wireless continuous physiological monitor in Nairobi, Kenya.

Autor: Coleman J; Evaluation of Technologies for Neonates in Africa (ETNA), Nairobi, Kenya., Ginsburg AS; University of Washington, Seattle, Washington, United States of America., Macharia W; Department of Pediatrics, Aga Khan University, Nairobi, Kenya., Ochieng R; Department of Pediatrics, Aga Khan University, Nairobi, Kenya., Chomba D; Department of Pediatrics, Aga Khan University, Nairobi, Kenya., Zhou G; Center for Clinical Investigation, Brigham and Women's Hospital, Boston, Massachusetts, United States of America., Dunsmuir D; Anesthesiology, Pharmacology & Therapeutics, The University of British Columbia, Vancouver, British Columbia, Canada., Xu S; Querrey Simpson Institute for Bioelectronics, Department of Biomedical Engineering, McCormick School of Engineering, Department of Dermatology & Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Evanston, Illinois, United States of America., Ansermino JM; Anesthesiology, Pharmacology & Therapeutics, The University of British Columbia, Vancouver, British Columbia, Canada.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2022 Jun 30; Vol. 17 (6), pp. e0267026. Date of Electronic Publication: 2022 Jun 30 (Print Publication: 2022).
DOI: 10.1371/journal.pone.0267026
Abstrakt: Background: Neonatal multiparameter continuous physiological monitoring (MCPM) technologies assist with early detection of preventable and treatable causes of neonatal mortality. Evaluating accuracy of novel MCPM technologies is critical for their appropriate use and adoption.
Methods: We prospectively compared the accuracy of Sibel's Advanced Neonatal Epidermal (ANNE) technology with Masimo's Rad-97 pulse CO-oximeter with capnography and Spengler's Tempo Easy reference technologies during four evaluation rounds. We compared accuracy of heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2), and skin temperature using Bland-Altman plots and root-mean-square deviation analyses (RMSD). Sibel's ANNE algorithms were optimized between each round. We created Clarke error grids with zones of 20% to aid with clinical interpretation of HR and RR results.
Results: Between November 2019 and August 2020 we collected 320 hours of data from 84 neonates. In the final round, Sibel's ANNE technology demonstrated a normalized bias of 0% for HR and 3.1% for RR, and a non-normalized bias of -0.3% for SpO2 and 0.2°C for temperature. The normalized spread between 95% upper and lower limits-of-agreement (LOA) was 4.7% for HR and 29.3% for RR. RMSD for SpO2 was 1.9% and 1.5°C for temperature. Agreement between Sibel's ANNE technology and the reference technologies met the a priori-defined thresholds for 95% spread of LOA and RMSD. Clarke error grids showed that all HR and RR observations were within a 20% difference.
Conclusion: Our findings suggest acceptable agreement between Sibel's ANNE and reference technologies. Clinical effectiveness, feasibility, usability, acceptability, and cost-effectiveness investigations are necessary for large-scale implementation.
Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Shuai Xu is Founder and Chief Executive Officer at Sibel Health; all other authors declare no competing interests. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Databáze: MEDLINE
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