Abstract
Background: Heart rate (HR) and respiratory rate (RR) can be challenging to measure accurately and reliably in neonates. The introduction of innovative, non-invasive measurement technologies suitable for resource-constrained settings is limited by the lack of appropriate clinical thresholds for accuracy comparison studies. Methods: We collected measurements of photoplethysmography-recorded HR and capnography-recorded exhaled carbon dioxide across multiple 60-second epochs (observations) in enrolled neonates admitted to the neonatal care unit at Aga Khan University Hospital in Nairobi, Kenya. Trained study nurses manually recorded HR, and the study team manually counted individual breaths from capnograms. For comparison, HR and RR also were measured using an automated signal detection algorithm. Clinical measurements were analyzed for repeatability. Results: A total of 297 epochs across 35 neonates were recorded. Manual HR showed a bias of -2.4 (-1.8%) and a spread between the 95% limits of agreement (LOA) of 40.3 (29.6%) compared to the algorithm-derived median HR. Manual RR showed a bias of -3.2 (-6.6%) and a spread between the 95% LOA of 17.9 (37.3%) compared to the algorithm-derived median RR, and a bias of -0.5 (1.1%) and a spread between the 95% LOA of 4.4 (9.1%) compared to the algorithm-derived RR count. Manual HR and RR showed repeatability of 0.6 (interquartile range (IQR) 0.5-0.7), and 0.7 (IQR 0.5-0.8), respectively. Conclusions: Appropriate clinical thresholds should be selected a priori when performing accuracy comparisons for HR and RR. Automated measurement technologies typically use median values rather than counts, which significantly impacts accuracy. A wider spread between the LOA, as much as 30%, should be considered to account for the observed physiological nuances and within- and between-neonate variability and different averaging methods. Wider adoption of thresholds by data standards organizations and technology developers and manufacturers will increase the robustness of clinical comparison studies.
Highlights
There is a high risk of mortality during the neonatal period, in resource-constrained settings[1]
The manual Heart rate (HR) demonstrated a negative bias of -2.4 (-1.8%) compared to the median pulse oximetry signal quality index (PO-SQI) HR, and a marked spread between the 95% limits of agreement (LOA) of 40.3 (29.6%)
Removing data from a single outlier neonate resulted in a smaller bias of -1.4 (-1.0%), a tighter spread between the 95% LOA of 24.7 (18.2%), and a lower root mean square deviation (RMSD) of 6.4 (4.7%) (Table 4; Figure 2)
Summary
There is a high risk of mortality during the neonatal period, in resource-constrained settings[1]. Continuous monitoring of neonatal vital signs enables early detection of physiological deterioration and potential opportunities for lifesaving interventions[2,3,4]. The development of innovative, non-invasive, multiparameter continuous physiological monitoring (MCPM) technologies for neonates offers the promise of improving clinical outcomes in this vulnerable population. A neonate’s marked physiological variability, small size, and often fragile condition can offer challenges when measuring and monitoring vital signs. A lack of neonatal clinical validation standards further undermines the development of MCPM technologies clinically validated for neonates. The introduction of innovative, non-invasive measurement technologies suitable for resource-constrained settings is limited by the lack of appropriate clinical thresholds for accuracy comparison studies. Manual HR showed a bias of -2.4 (-1.8%) and a spread between the 95% limits of agreement (LOA) of 40.3 (29.6%) compared to the algorithm-derived median HR. Conclusions: Appropriate clinical thresholds should be selected a version 2
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