Abstract
Background
Continuous heart rate (HR) and oxygenation (SpO2) metrics can be useful for predicting adverse events in very low birth weight (VLBW) infants. To optimize the utility of these tools, inter-site variability must be taken into account.
Methods
For VLBW infants at three neonatal intensive care units (NICUs), we analyzed the mean, standard deviation, skewness, kurtosis, and cross-correlation of electrocardiogram HR, pulse oximeter pulse rate, and SpO2. The number and durations of bradycardia and desaturation events were also measured. Twenty-two metrics were calculated hourly, and mean daily values were compared between sites.
Results
We analyzed data from 1168 VLBW infants from birth through day 42 (35,238 infant-days). HR and SpO2 metrics were similar at the three NICUs, with mean HR rising by ~10 beats/min over the first 2 weeks and mean SpO2 remaining stable ~94% over time. The number of bradycardia events was higher at one site, and the duration of desaturations was longer at another site.
Conclusions
Mean HR and SpO2 were generally similar among VLBW infants at three NICUs from birth through 6 weeks of age, but bradycardia and desaturation events differed in the first 2 weeks after birth. This highlights the importance of developing predictive analytics tools at multiple sites.
Impact
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HR and SpO2 analytics can be useful for predicting adverse events in VLBW infants in the NICU, but inter-site differences must be taken into account in developing predictive algorithms.
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Although mean HR and SpO2 patterns were similar in VLBW infants at three NICUs, inter-site differences in the number of bradycardia events and duration of desaturation events were found.
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Inter-site differences in bradycardia and desaturation events among VLBW infants should be considered in the development of predictive algorithms.
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Data and Code
Summary data and code are available on UVA Dataverse at https://doi.org/10.18130/V3/7UAPHU.
Change history
14 July 2021
A Correction to this paper has been published: https://doi.org/10.1038/s41390-021-01621-4
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Acknowledgements
This work was supported by HHS|NIH|Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) R01 HD072071 and K23 HD097254-01. HHS|NIH|National Institute of Neurological Disorders and Stroke (NINDS) K23 NS111086.
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All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data, and drafting the article or revising it critically for important intellectual content. All authors gave final approval of the version to be published.
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J.R.M. and D.E.L. have equity shares in Medical Predictive Science Corporation, Charlottesville, VA. J.R.M. is an officer and owns equity in Advanced Medical Predictive Devices, Diagnostics, and Displays. S.J.R. has received consulting fees from Airway Therapeutics. The other authors declare no competing interests.
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The original online version of this article was revised: In the Discussion section paragraph four, first sentence was changed and a Data and Code section was added.
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Zimmet, A.M., Sullivan, B.A., Fairchild, K.D. et al. Vital sign metrics of VLBW infants in three NICUs: implications for predictive algorithms. Pediatr Res 90, 125–130 (2021). https://doi.org/10.1038/s41390-021-01428-3
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DOI: https://doi.org/10.1038/s41390-021-01428-3
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