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Persistent Identifier
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doi:10.18130/V3/7UAPHU |
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Publication Date
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2021-04-07 |
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Title
| Data Associated with the Publication: Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms |
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Author
| Zimmet, Amanda MUniversity of Virginia, Department of MedicineORCID0000-0003-1457-3072
Sullivan, Brynne AUniversity of Virginia, Department of PediatricsORCID0000-0001-9580-4121
Fairchild, Karen DUniversity of Virginia, Department of PediatricsORCID0000-0002-1081-8741
Moorman, J RandallUniversity of Virginia, Department of MedicineORCID0000-0002-5772-1648
Isler, Joseph RColumbia University, Department of PediatricsORCID0000-0001-5814-3838
Wallman-Stokes, Aaron WColumbia University, Department of PediatricsORCID0000-0002-5945-490X
Sahni, RakeshColumbia University, Department of Pediatrics
Vesoulis, Zachary AWashington University St. Louis, Department of PediatricsORCID0000-0001-8290-0069
Ratcliffe, Sarah JUniversity of Virginia, Department of Public Health ScienceORCID0000-0002-6644-8284
Lake, Douglas EUniversity of Virginia, Department of MedicineORCID0000-0001-6259-4850 |
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Point of Contact
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Use email button above to contact.
Lake, Douglas E (Department of Medicine) |
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Dataset Description
| This repository contains the dataset and code for the manuscript: Zimmet AM, Sullivan BA, Fairchild KD, Moorman JR, Isler JR, Wallman-Stokes AW, Sahni R, Vesoulis ZA, Ratcliffe SJ, & Lake DE. Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms. Pediatric Research 2021. https://doi.org/10.1038/s41390-021-01428-3. EXPLANATION OF DATA FILES AND CODE To understand all of the included data files and to tell you which key files do what, review the ReadMe_VitalSignMetrics_20200226.txt file. HOW TO USE THE CODE After reviewing ReadMe_VitalSignMetrics_20200226.txt file, follow the entire code progression from raw data (the raw data itself could not be published), to summary data (included in this repository), through figure generation, via the script Pipeline.m. ABSTRACT Background: Continuous heart rate (HR) and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 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 1,168 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/minute over the first two weeks and mean SpO2 remaining stable around 94% over time. The number of bradycardia events was higher at one site, and the duration of desaturations was longer at another site. Conclusion: Mean HR and SpO2 were generally similar among VLBW infants at three NICUs from birth through six weeks of age, but bradycardia and desaturation events differed in the first two weeks after birth. This highlights the importance of developing predictive analytics tools at multiple sites. |
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Subject
| Medicine, Health and Life Sciences |
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Keyword
| neonate
neonatology
newborn
prematurity
preterm infants
continuous monitoring
predictive analytics
algorithm |
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Related Publication
| Zimmet AM, Sullivan BA, Fairchild KD, Moorman JR, Isler JR, Wallman-Stokes AW, Sahni R, Vesoulis ZA, Ratcliffe SJ, & Lake DE. Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms. Pediatric Research 2021. https://doi.org/10.1038/s41390-021-01428-3. doi: https://doi.org/10.1038/s41390-021-01428-3 |
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Language
| English |
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Producer
| University of Virginia (UVA)
Columbia University (CU)
Washington University St. Louis (WUSTL) |
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Data Creation Date
| 2012-01-01 |
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Production Location
| University of Virginia, Columbia University, Washington University St. Louis |
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Funding Information
| HHS | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): R01 HD072071
HHS | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): K23 HD097254-01
HHS | NIH | National Institute of Neurological Disorders and Stroke (NINDS): K23 NS111086 |
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Depositor
| Zimmet, Amanda |
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Deposit Date
| 2021-02-08 |
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Time Period
| Start Date: 2012; End Date: 2018 |
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Date of Collection
| Start Date: 2012; End Date: 2018 |
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Software
| MATLAB, Version: 2019a |