Non-invasive pulse arrival time is associated with cardiac index in pediatric heart transplant patients with normal ejection fraction.

OBJECTIVE: Cardiac Index (CI) is a key physiologic parameter to ensure end organ perfusion in the pediatric intensive care unit (PICU). Determination of CI requires invasive cardiac measurements and is not routinely done at the PICU bedside. To date, there is no gold standard non-invasive means to determine CI. This study aims to use a novel non-invasive methodology, based on routine continuous physiologic data, called Pulse Arrival Time (PAT) as a surrogate for CI in patients with normal Ejection Fraction. Approach: Electrocardiogram (ECG) and photoplethysmogram (PPG) signals were collected from beside monitors at a sampling frequency of 250 samples per second. Continuous PAT, derived from the ECG and PPG waveforms was averaged per patient. Pearson's correlation coefficient was calculated between PAT and CI, PAT and heart rate (HR), and PAT and ejection fraction (EF). Main Results: Twenty patients underwent right heart cardiac catheterization. The mean age of patients was 11.7±5.4 years old, ranging from 11 months old to 19 years old, the median age was 13.4 years old. HR in this cohort was 93.8±17.0 beats per minute. The average EF was 54.4±9.6%. The average CI was 3.51±0.72 L/min/m2, with ranging from 2.6 to 4.77 L/min/m2. The average PAT was 0.31±0.12 seconds. Pearson correlation analysis showed a positive correlation between PAT and CI (0.57, p < 0.01). Pearson correlation between HR and CI, and correlation between EF and CI was 0.22 (p = 0.35) and 0.03 (p = 0.23) respectively. The correlation between PAT, when indexed by HR (i.e. PAT × HR), and CI minimally improved to 0.58 (p < 0.01). Significance: This pilot study demonstrates that PAT may serve as a valuable surrogate marker for CI at the bedside, as a non-invasive and continuous modality in the PICU. The use of PAT in clinical practice remains to be thoroughly investigated. .

Perioperative Neuromonitoring in Children with Congenital Heart Disease.

Although neonates and children with congenital heart disease are primarily hospitalized for cardiac and pulmonary diseases, they are also at an increased risk for neurologic injury due to both empiric differences that can exist in their nervous systems and acquired injury from cardiopulmonary pathology and interventions. Although early efforts in care focused on survival after reparative cardiac surgery, as surgical and anesthetic techniques have evolved and survival rates accordingly improved, the focus has now shifted to maximizing outcomes among survivors. Children and neonates with congenital heart disease experience seizures and poor neurodevelopmental outcomes at a higher rate than age-matched counterparts. The aim of neuromonitoring is to help clinicians identify patients at highest risk for these outcomes to implement strategies to mitigate these risks and to also help with neuroprognostication after an injury has occurred. The mainstays of neuromonitoring are (1) electroencephalographic monitoring to evaluate brain activity for abnormal patterns or changes and to identify seizures, (2) neuroimaging to reveal structural changes and evidence of physical injury in and around the brain, and (3) near-infrared spectroscopy to monitor brain tissue oxygenation and detect changes in perfusion. This review will detail the aforementioned techniques and their use in the care of pediatric patients with congenital heart disease.

Automatic identification of intracranial pressure waveform during external ventricular drainage clamping: segmentation via wavelet analysis.

Objective. The objective of this study is to develop and validate a method for automatically identifying segments of intracranial pressure (ICP) waveform data from external ventricular drainage (EVD) recordings during intermittent drainage and closure.Methods. The proposed method uses time-frequency analysis through wavelets to distinguish periods of ICP waveform in EVD data. By comparing the frequency compositions of the ICP signals (when the EVD system is clamped) and the artifacts (when the system is open), the algorithm can detect short, uninterrupted segments of ICP waveform from the longer periods of non-measurement data. The method involves applying a wavelet transform, calculating the absolute power in a specific range, using Otsu thresholding to automatically identify a threshold, and performing a morphological operation to remove small segments. Two investigators manually graded the same randomly selected one-hour segments of the resulting processed data. Performance metrics were calculated as a percentage.Results. The study analyzed data from 229 patients who had EVD placed following subarachnoid hemorrhage between June 2006 and December 2012. Of these, 155 (67.7%) were female and 62 (27%) developed delayed cerebral ischemia. A total of 45 150 h of data were segmented. 2044 one-hour segments were randomly selected and evaluated by two investigators (MM and DN). Of those, the evaluators agreed on the classification of 1556 one-hour segments. The algorithm was able to correctly identify 86% (1338 h) of ICP waveform data. 8.2% (128 h) of the time the algorithm either partially or fully failed to segment the ICP waveform. 5.4% (84 h) of data, artifacts were mistakenly identified as ICP waveforms (false positives).Conclusion. The proposed algorithm automates the identification of valid ICP waveform segments of waveform in EVD data and thus enables the inclusion in real-time data analysis for decision support. It also standardizes and makes research data management more efficient.

A Deep Learning Framework for Deriving Noninvasive Intracranial Pressure Waveforms from Transcranial Doppler.

Increased intracranial pressure (ICP) causes disability and mortality in the neurointensive care population. Current methods for monitoring ICP are invasive. We designed a deep learning framework using a domain adversarial neural network to estimate noninvasive ICP, from blood pressure, electrocardiogram, and cerebral blood flow velocity. Our model had a mean of median absolute error of 3.88 ± 3.26 mmHg for the domain adversarial neural network, and 3.94 ± 1.71 mmHg for the domain adversarial transformers. Compared with nonlinear approaches, such as support vector regression, this was 26.7% and 25.7% lower. Our proposed framework provides more accurate noninvasive ICP estimates than currently available. ANN NEUROL 2023;94:196-202.

Phagosomal TLR signaling upon Borrelia burgdorferi infection.

Internalization and degradation of live Bb within phagosomal compartments of monocytes, macrophages and dendritic cells (DCs), allows for the release of lipoproteins, nucleic acids and other microbial products, triggering a broad and robust inflammatory response. Toll-like receptors (TLRs) are key players in the recognition of spirochetal ligands from whole viable organisms (i.e., vita-PAMPs). Herein we will review the role of endosomal TLRs in the response to the Lyme disease spirochete.

Human TLR8 is activated upon recognition of Borrelia burgdorferi RNA in the phagosome of human monocytes.

Phagocytosed Borrelia burgdorferi (Bb), the Lyme disease spirochete, induces a robust and complex innate immune response in human monocytes, in which TLR8 cooperates with TLR2 in the induction of NF-κB-mediated cytokine production, whereas TLR8 is solely responsible for transcription of IFN-ß through IRF7. We now establish the role of Bb RNA in TLR8-mediated induction of IFN-ß. First, using TLR2-transfected HEK.293 cells, which were unable to phagocytose intact Bb, we observed TLR2 activation by lipoprotein-rich borrelial lysates and TLR2 synthetic ligands but not in response to live spirochetes. Purified Bb RNA, but not borrelial DNA, triggered TLR8 activation. Neither of these 2 ligands induced activation of TLR7. Using purified human monocytes we then show that phagocytosed live Bb, as well as equivalent amounts of borrelial RNA delivered into the phagosome by polyethylenimine (PEI), induces transcription of IFN-ß and secretion of TNF-α. The cytokine response to purified Bb RNA was markedly impaired in human monocytes naturally deficient in IRAK-4 and in cells with knockdown TLR8 expression by small interfering RNA. Using confocal microscopy we provide evidence that TLR8 colocalizes with internalized Bb RNA in both early (EEA1) and late endosomes (LAMP1). Live bacterial RNA staining indicates that spirochetal RNA does not transfer from the phagosome into the cytosol. Using fluorescent dextran particles we show that phagosomal integrity in Bb-infected monocytes is not affected. We demonstrate, for the first time, that Bb RNA is a TLR8 ligand in human monocytes and that transcription of IFN-ß in response to the spirochete is induced from within the phagosomal vacuole through the TLR8-MyD88 pathway.

TLR8: the forgotten relative revindicated.

The endosomal Toll-like receptors (TLRs) TLR3, TLR7, TLR8 and TLR9 are important in sensing foreign nucleic acids encountered by phagocytes. Because TLR8 was initially thought to be non-functional in mice, less is known about TLR8 than the genetically and functionally related TLR7. Originally associated with the recognition of single-stranded RNA of viral origin, there is now evidence that human TLR8 is also able to sense bacterial RNA released within phagosomal vacuoles, inducing the production of both nuclear factor (NF)-κB-dependent cytokines and type I interferons (IFNs), such as IFN-ß. The functions of TLR8 extend beyond the recognition of foreign pathogens and include cross-talk with other endosomal TLRs, a process that may also have a role in the generation of autoimmunity.