Objective: To establish reference values for fetal heart rate (FHR) indices across time, frequency and nonlinear domains throughout pregnancy in a tertiary hospital population, considering sex. The influence of the number of fetuses, birth weight,and time to delivery on FHR was evaluated. Methods: This retrospective cohort study analyzed the initial FHR tracing upon hospital admission between 24° and 41° weeks of gestation, excluding cases in labor, with medication use, or a confirmed medical indication. Reference values were established using the Generalized Additive Models for Location Scale and Shape framework. Likelihood ratio test assessed whether including clinical variables significantly improved model fit. Results: The cohort included 3219 fetuses, of which 48% were female and 91% singleton pregnancies. Median gestational age was 32⁺⁶. Birth weight was below p10 in 22% and above p90 in 9%. Median tracing duration was 42.5 min and median signal loss was 1.95%. Most indices were significantly associated with gestational age and several showed significant sex differences. Model fit significantly improved for multiple indices when including number of fetuses, birth weight, or time to delivery. Conclusions: This article presents gestational age- and sex-specific reference values for FHR in a large tertiary hospital population. The influence of gestational age was reaffirmed and significant differences related to sex, number of fetuses, birth weight, and time to delivery were identified. This enhances understanding of fetal autonomic regulation and supports a more individualized approach to predictive fetal monitoring. Further research is needed to determine the clinical utility of these reference values in practical monitoring and risk assessment.

This study aimed to establish reference values for heart rate frequency and variability indices in preterm neonates admitted to a neonatal intensive care unit of a tertiary care hospital during their first week of life. In this retrospective cohort study, the Generalized Additive Models for Location Scale and Shape framework was employed to establish reference values for heart rate indices across time-domain, frequency-domain and nonlinear-domain in neonates considering gestational age, postnatal age, sex and birth weight. Heart rate tracings of 594 neonates (45% female; median gestational age at birth 29⁰ (IQR 26⁶-30⁵); 38% birth weight <p10, 6% birth weight >p90) were analyzed. Reference values were established for 25 heart rate indices. Nearly all heart rate indices were significantly influenced by gestational age, postnatal age and sex. Baseline heart rate decreased with gestational age, increased with postnatal age and was higher in females. Heart rate standard deviation increased with gestational age and postnatal age and was lower in female. Inclusion of birth weight significantly improved model fit for all HRV indices. This study highlights the importance of considering gestational and postnatal age, sex and birth weight when interpreting neonatal heart rate frequency and variability in preterm neonates. These findings support the need for personalized approaches for neonatal monitoring and interpretation. Future research should validate these values in larger, more diverse populations, including additional clinical factors such as neonatal complications and medication administration, to determine their clinical relevance.

Objective This study aimed to explore the fetal heart rate trend in the week before birth, the transition from fetal to neonatal heart rate, and the neonatal heart rate trend in the week after birth in preterm neonates admitted to a tertiary care hospital, considering maternal and neonatal factors. Study Design A retrospective cohort study was conducted, including neonates born between 24 and 34 weeks of gestation. Baseline heart rate, average deceleration capacity, standard deviation, skewness, and sample entropy were assessed using interrupted time series and difference-in-differences analyses. Subgroup analyses were performed according to gestational age at birth, sex, birth weight, mode of delivery, Apgar score at 5minutes, umbilical cord pH, and neonatal medication. Results The fetal and neonatal heart rate of 123 patients was analyzed. After birth, step change of baseline (2.23bpm,p<0.05), average deceleration capacity (0.43bpm,p<0.001), and skewness (0.47 nu,p<0.001) increased, while sample entropy (−0.68 bits,p<0.001) and standard deviation (−1.15bpm,p<0.001) decreased. Postnatally, baseline increased in linear slope and decreased in quadratic slope (bothp<0.001). Average deceleration capacity decreased in linear slope (p<0.001). Sample entropy and standard deviation increased in linear slopes (bothp<0.001). Skewness increased in quadratic slope (p<0.05). Subgroup analyses revealed that delivery mode, medication, and birth weight modulated these trends. Conclusion This study provides unique insights into heart rate frequency and variability trends during the period around preterm birth. It highlights the dynamic physiological adaptation that occurs during the transition from intrauterine to extrauterine life in preterm infants and may help inform future research on fetal and neonatal monitoring and clinical management. Key Points Heart rate frequency and variability dynamics were assessed around preterm birth in a NICU cohort. After birth, heart rate frequency increased while variability measures decreased. Heart rate frequency and variability differed by gestational age, birth weight, medication, and delivery mode.

Background: Arterial pressure measurements are important to monitor vital function in neonates, and values are known to be dependent of gestational and postnatal age. Current reference ranges for mean arterial pressure in neonates have been derived from small samples and combined data of noninvasive and invasive measurements. We aimed to define reference values for noninvasive mean, systolic, and diastolic blood pressure during the first week of life in otherwise healthy preterm and term neonates defined by gestational and postnatal age. Methods: In this retrospective cohort study in a neonatal intensive care unit (NICU) in a Dutch tertiary paediatric hospital, we included the noninvasive blood pressures of neonates admitted between 2016 and 2018, with exclusion of those with severe comorbidities (major cardiac malformations, intracerebral haemorrhage, and tracheal intubation >6 h). We defined the median (P50) with −2 standard deviations (SD) (P0.23), −1 SD (P16), +1 SD (P84), and +2 SD (P97.7) for gestational age and postnatal age using quantile regression, percentiles provided online (http://bloodpressure-neonate.com/). Results: A total of 607 neonates, with 5885 measurements, fulfilled the inclusion criteria. The P50 values of mean noninvasive arterial blood pressure in extreme preterm infants steeply increased during the first day after birth and gradually increased within a week from 27 to 49 mm Hg at 24 h of gestational age, and from 49 to 61 mm Hg at 41 weeks of gestational age. Conclusions: These reference values for noninvasive blood pressure in neonates in the NICU for various gestational age groups provide guidance for clinical decision-making in healthy and diseased neonates during anaesthesia and sedation.

Background: The association between body composition (e.g. sarcopenia or visceral obesity) and treatment outcomes, such as survival, using single-slice computed tomography (CT)-based measurements has recently been studied in various patient groups. These studies have been conducted with different software programmes, each with their specific characteristics, of which the inter-observer, intra-observer, and inter-software correlation are unknown. Therefore, a comparative study was performed. Methods: Fifty abdominal CT scans were randomly selected from 50 different patients and independently assessed by two observers. Cross-sectional muscle area (CSMA, i.e. rectus abdominis, oblique and transverse abdominal muscles, paraspinal muscles, and the psoas muscle), visceral adipose tissue area (VAT), and subcutaneous adipose tissue area (SAT) were segmented by using standard Hounsfield unit ranges and computed for regions of interest. The inter-software, intra-observer, and inter-observer agreement for CSMA, VAT, and SAT measurements using FatSeg, OsiriX, ImageJ, and sliceOmatic were calculated using intra-class correlation coefficients (ICCs) and Bland–Altman analyses. Cohen's κ was calculated for the agreement of sarcopenia and visceral obesity assessment. The Jaccard similarity coefficient was used to compare the similarity and diversity of measurements. Results: Bland–Altman analyses and ICC indicated that the CSMA, VAT, and SAT measurements between the different software programmes were highly comparable (ICC 0.979–1.000, P < 0.001). All programmes adequately distinguished between the presence or absence of sarcopenia (κ = 0.88–0.96 for one observer and all κ = 1.00 for all comparisons of the other observer) and visceral obesity (all κ = 1.00). Furthermore, excellent intra-observer (ICC 0.999–1.000, P < 0.001) and inter-observer (ICC 0.998–0.999, P < 0.001) agreement for all software programmes were found. Accordingly, excellent Jaccard similarity coefficients were found for all comparisons (mean ≥ 0.964). Conclusions: FatSeg, OsiriX, ImageJ, and sliceOmatic showed an excellent agreement for CSMA, VAT, and SAT measurements on abdominal CT scans. Furthermore, excellent inter-observer and intra-observer agreement were achieved. Therefore, results of studies using these different software programmes can reliably be compared.