Arterial flow patterns in healthy transitioning near-term neonates

Stritzke, Amélie; Murthy, Prashanth; Kaur, Sukhjeet; Kuret, Verena; Liang, Zhiying; Howell, Sarah; Tyberg, John V.

doi:10.1136/bmjpo-2018-000333

Cited by 6 publications

(11 citation statements)

References 33 publications

(40 reference statements)

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Section: Discussionsupporting

confidence: 91%

“…In correspondence with other studies, the arterial CBF velocities increased from day one to day two of life ( 25 ). We were not able to detect the physiological drop in arterial RI and PI that occurs shortly after birth ( 25 ). This is probably due to the timing of the US recordings, as most of the neonates (77%) were older than 24 h at inclusion ( 25 ).…”

Section: Discussionsupporting

confidence: 91%

“…The mean arterial CBF velocities, RI, and PI were lower than what has been found in other studies ( 25 – 28 ). The NeoDoppler system lacks a grayscale 2D-imaging to optimize the angle of insonation, which could have underestimated the velocity measurements.…”

Section: Discussioncontrasting

confidence: 79%

“…We were not able to detect the physiological drop in arterial RI and PI that occurs shortly after birth ( 25 ). This is probably due to the timing of the US recordings, as most of the neonates (77%) were older than 24 h at inclusion ( 25 ). As has previously been found, behavioral state influenced arterial PI, but not arterial Vmean and PSV ( 7 ).…”

Section: Discussionmentioning

confidence: 77%

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Low frequency cerebral arterial and venous flow oscillations in healthy neonates measured by NeoDoppler

et al. 2022

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BackgroundA cerebroprotective effect of low frequency oscillations (LFO) in cerebral blood flow (CBF) has been suggested in adults, but its significance in neonates is not known. This observational study evaluates normal arterial and venous cerebral blood flow in healthy neonates using NeoDoppler, a novel Doppler ultrasound system which can measure cerebral hemodynamics continuously.MethodUltrasound Doppler data was collected for 2 h on the first and second day of life in 36 healthy term born neonates. LFO (0.04–0.15 Hz) were extracted from the velocity curve by a bandpass filter. An angle independent LFO index was calculated as the coefficient of variation of the filtered curve. Separate analyses were done for arterial and venous signals, and results were related to postnatal age and behavioral state (asleep or awake).ResultsThe paper describes normal physiologic variations of arterial and venous cerebral hemodynamics. Mean (SD) arterial and venous LFO indices (%) were 6.52 (2.55) and 3.91 (2.54) on day one, and 5.60 (1.86) and 3.32 (2.03) on day two. After adjusting for possible confounding factors, the arterial LFO index was estimated to decrease by 0.92 percent points per postnatal day (p < 0.001). The venous LFO index did not change significantly with postnatal age (p = 0.539). Arterial and venous LFO were not notably influenced by behavioral state.ConclusionThe results indicate that arterial LFO decrease during the first 2 days of life in healthy neonates. This decrease most likely represents normal physiological changes related to the transitional period. A similar decrease for venous LFO was not found.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

Section: Discussioncontrasting

confidence: 79%

Section: Discussionmentioning

confidence: 77%

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Low frequency cerebral arterial and venous flow oscillations in healthy neonates measured by NeoDoppler

et al. 2022

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“…Renal artery Doppler is clinicians’ most common non-invasive method to quantitatively assess renal vascularity and perfusion [ 23 , 24 ]. Renal perfusion is responsible for glomerular filtration, and although the renal artery resistance index (RRI) is not currently part of KDIGO guidelines, it is often used as a measure of renal perfusion and a nonspecific prognostic marker for various disorders that affect the kidney [ 25 ].…”

Section: Resultsmentioning

confidence: 99%

An Exploratory Review on the Potential of Artificial Intelligence for Early Detection of Acute Kidney Injury in Preterm Neonates

Kandasamy,

Baker

2023

Diagnostics

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A preterm birth is a live birth that occurs before 37 completed weeks of pregnancy. Approximately 15 million babies are born preterm annually worldwide, indicating a global preterm birth rate of about 11%. Up to 50% of premature neonates in the gestational age (GA) group of <29 weeks’ gestation will develop acute kidney injury (AKI) in the neonatal period; this is associated with high mortality and morbidity. There are currently no proven treatments for established AKI, and no effective predictive tool exists. We propose that the development of advanced artificial intelligence algorithms with neural networks can assist clinicians in accurately predicting AKI. Clinicians can use pathology investigations in combination with the non-invasive monitoring of renal tissue oxygenation (rSO2) and renal fractional tissue oxygenation extraction (rFTOE) using near-infrared spectroscopy (NIRS) and the renal resistive index (RRI) to develop an effective prediction algorithm. This algorithm would potentially create a therapeutic window during which the treating clinicians can identify modifiable risk factors and implement the necessary steps to prevent the onset and reduce the duration of AKI.

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