# Central & peripheral body temperature in VLBW preterm infants during the neonatal period: Relationship to neonatal infection and necrotizing enterocolitis

> **NIH NIH R01** · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · 2020 · $537,050

## Abstract

Central & peripheral body temperature in VLBW preterm infants during the neonatal period:
 Relationship to neonatal infection and necrotizing enterocolitis
 Objective: We will measure continuous abdominal temperatures (AT) and foot temperatures (FT) in
440 preterm infants from five neonatal units over 28 days to predict occurrence of infection. Abnormal values of
the central-peripheral temperature difference (CpTD), greater than 2º and less than 0, are a sign of autonomic
instability occurring during infection. We will model the temporal relationship between abnormal CpTD values
and the diagnosis of infection to find the best predictive model to use continuous temperature monitoring as a
non-invasive, inexpensive predictive monitoring tool for infection. For comparison, we will measure continuous
heart rate characteristics (HRC) from a HeRO monitor which predicts infection in preterm infants using heart
rate variability. Predictive models of CpTD and HRC will be compared and combined to find the optimal
predictive monitoring tool for infection in our sample. We will examine covariates of infants' demographic
factors, maternal obstetrical histories, and infants' clinical context for interaction effects between our predictors
of CpTD and HRC for infection. Methods: Infants will be enrolled from five NICUs in North and South Carolina.
Research nurses or site PIs will obtain parental consent for infants to be enrolled up to 6 hours of age, if they
are less than 32 weeks gestational age and less than 1500 grams at birth. Study personnel will attach a
thermistor to the sole of the foot and to the abdomen for each study infant. Thermistors will be attached to a
data logger which will measure temperature every minute for the first 28 days of life. A HeRO monitor will be
attached to each infant's standard cardiopulmonary monitor and a USB drive in the HeRO monitor will collect
hourly HRC scores for 28 days. Maternal obstetrical history, infant demographics and infant clinical context
variables will be entered into a RedCap data base to be analyzed with physiological data. Data management
and analyses will be conducted at University of South Carolina, College of Nursing. Data Analysis: Our
interest for this study is the CpTD (AT-FT=CpTD). We will investigate that measure as two derived variables
HTD (number/percentage of minutes with CpTd>2) and NTD (number/percentage of minutes with CpTD<0)
which are continuous variables. Predictive models will be built utilizing HTD and NTD information defined over
various lengths of preceding time (24 to 72 hours) to ultimately yield the optimal predictive model for diagnosis
of infection based on CpTD. Our predictive model will be compared to the HRC model utilizing a Monte Carlo
cross-validation approach in which we use 70% of the data for training and 30% for validation. Finally, we will
combine the HRC predictive covariates to the CpTD covariates to investigate whether the combined model
offers further improvements ...

## Key facts

- **NIH application ID:** 9955379
- **Project number:** 5R01NR017872-03
- **Recipient organization:** UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
- **Principal Investigator:** Robin Britt Dail
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $537,050
- **Award type:** 5
- **Project period:** 2018-09-26 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9955379

## Citation

> US National Institutes of Health, RePORTER application 9955379, Central & peripheral body temperature in VLBW preterm infants during the neonatal period: Relationship to neonatal infection and necrotizing enterocolitis (5R01NR017872-03). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/9955379. Licensed CC0.

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