Update in Pediatric Neurocritical Care: What a Neurologist Caring for Critically Ill Children Needs to Know.

Currently nearly one-quarter of admissions to pediatric intensive care units (PICUs) worldwide are for neurocritical care diagnoses that are associated with significant morbidity and mortality. Pediatric neurocritical care is a rapidly evolving field with unique challenges due to not only age-related responses to primary neurologic insults and their treatments but also the rarity of pediatric neurocritical care conditions at any given institution. The structure of pediatric neurocritical care services therefore is most commonly a collaborative model where critical care medicine physicians coordinate care and are supported by a multidisciplinary team of pediatric subspecialists, including neurologists. While pediatric neurocritical care lies at the intersection between critical care and the neurosciences, this narrative review focuses on the most common clinical scenarios encountered by pediatric neurologists as consultants in the PICU and synthesizes the recent evidence, best practices, and ongoing research in these cases. We provide an in-depth review of (1) the evaluation and management of abnormal movements (seizures/status epilepticus and status dystonicus); (2) acute weakness and paralysis (focusing on pediatric stroke and select pediatric neuroimmune conditions); (3) neuromonitoring modalities using a pathophysiology-driven approach; (4) neuroprotective strategies for which there is evidence (e.g., pediatric severe traumatic brain injury, post-cardiac arrest care, and ischemic stroke and hemorrhagic stroke); and (5) best practices for neuroprognostication in pediatric traumatic brain injury, cardiac arrest, and disorders of consciousness, with highlights of the 2023 updates on Brain Death/Death by Neurological Criteria. Our review of the current state of pediatric neurocritical care from the viewpoint of what a pediatric neurologist in the PICU needs to know is intended to improve knowledge for providers at the bedside with the goal of better patient care and outcomes.

Automated Calculator for the Pediatric Sequential Organ Failure Assessment Score: Development and External Validation in a Single-Center 7-Year Cohort, 2015-2021.

OBJECTIVES: The pediatric Sequential Organ Failure Assessment (pSOFA) score summarizes severity of organ dysfunction and can be used to predict in-hospital mortality. Manual calculation of the pSOFA score is time-consuming and prone to human error. An automated method that is open-source, flexible, and scalable for calculating the pSOFA score directly from electronic health record data is desirable. DESIGN: Single-center, retrospective cohort study. SETTING: Quaternary 40-bed PICU. PATIENTS: All patients admitted to the PICU between 2015 and 2021 with ICU stay of at least 24 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used 77 records to evaluate the automated score. The automated algorithm had an overall accuracy of 97%. The algorithm calculated the respiratory component of two cases incorrectly. An expert human annotator had an initial accuracy of 75% at the patient level and 95% at the component level. An untrained human annotator with general clinical research experience had an overall accuracy of 16% and component-wise accuracy of 67%. Weighted kappa for agreement between the automated method and the expert annotator's initial score was 0.92 (95% CI, 0.88-0.95), and between the untrained human annotator and the automated score was 0.50 (95% CI, 0.36-0.61). Data from 9146 patients (in-hospital mortality 3.6%) were included to validate externally the discriminability of the automated pSOFA score. The admission-day pSOFA score had an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.77-0.82). CONCLUSIONS: The developed automated algorithm calculates pSOFA score with high accuracy and is more accurate than a trained expert rater and nontrained data abstracter. pSOFA's performance for predicting in-hospital mortality was lower in our cohort than it was for the originally derived score.

Comparing the Quality of Domain-Specific Versus General Language Models for Artificial Intelligence-Generated Differential Diagnoses in PICU Patients.

OBJECTIVES: Generative language models (LMs) are being evaluated in a variety of tasks in healthcare, but pediatric critical care studies are scant. Our objective was to evaluate the utility of generative LMs in the pediatric critical care setting and to determine whether domain-adapted LMs can outperform much larger general-domain LMs in generating a differential diagnosis from the admission notes of PICU patients. DESIGN: Single-center retrospective cohort study. SETTING: Quaternary 40-bed PICU. PATIENTS: Notes from all patients admitted to the PICU between January 2012 and April 2023 were used for model development. One hundred thirty randomly selected admission notes were used for evaluation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Five experts in critical care used a 5-point Likert scale to independently evaluate the overall quality of differential diagnoses: 1) written by the clinician in the original notes, 2) generated by two general LMs (BioGPT-Large and LLaMa-65B), and 3) generated by two fine-tuned models (fine-tuned BioGPT-Large and fine-tuned LLaMa-7B). Differences among differential diagnoses were compared using mixed methods regression models. We used 1,916,538 notes from 32,454 unique patients for model development and validation. The mean quality scores of the differential diagnoses generated by the clinicians and fine-tuned LLaMa-7B, the best-performing LM, were 3.43 and 2.88, respectively (absolute difference 0.54 units [95% CI, 0.37-0.72], p < 0.001). Fine-tuned LLaMa-7B performed better than LLaMa-65B (absolute difference 0.23 unit [95% CI, 0.06-0.41], p = 0.009) and BioGPT-Large (absolute difference 0.86 unit [95% CI, 0.69-1.0], p < 0.001). The differential diagnosis generated by clinicians and fine-tuned LLaMa-7B were ranked as the highest quality in 144 (55%) and 74 cases (29%), respectively. CONCLUSIONS: A smaller LM fine-tuned using notes of PICU patients outperformed much larger models trained on general-domain data. Currently, LMs remain inferior but may serve as an adjunct to human clinicians in real-world tasks using real-world data.

Pharmacokinetic Modeling of Optimized Midazolam and Pentobarbital Dosing Used in Treatment Protocols of Refractory Status Epilepticus.

OBJECTIVES: To model bolus dosing, infusion rate, and weaning rate on theoretical serum concentration of midazolam and pentobarbital used in the treatment of refractory status epilepticus (RSE). DESIGN: One- and two-compartment in silico pharmacokinetic models of midazolam and pentobarbital. SETTING: Not applicable. SUBJECTS: Not applicable. INTERVENTIONS: We compared the model variables used in midazolam and pentobarbital protocols for standard RSE. MEASUREMENTS AND MAIN RESULTS: Standard RSE treatment protocols result in steady-state serum concentrations that are 6.2-9.0-fold higher for the one-compartment model and 2.3-4.7-fold higher for the two-compartment model. In the model, not including bolus doses delays the achievement of serum steady-state concentration by 0.5 and 2.7 hours for midazolam and pentobarbital, respectively. Abrupt discontinuation of these medications reduces modeled medication exposure by 1.1 and 6.4 hours, respectively. CONCLUSIONS: Our in silico pharmacokinetic modeling of standard midazolam and pentobarbital dosing protocols for RSE suggests potential variables to optimize in future clinical studies.

Optic Nerve Sheath Viscoelastic Properties: Re-Examination of Biomechanical Behavior and Clinical Implications.

BACKGROUND: Meta-analyses show a variable relationship between optic nerve sheath diameter (ONSD) and the presence of raised intracranial pressure (ICP). Because optic nerve sheath (ONS) tissue can be deformed, it is possible that ONSD reflects not only the current ICP but also prior deforming biomechanical exposures. In this post hoc analysis of two published data sets, we characterize ONS Young's modulus (E, mechanical stress per unit of strain) and calculate threshold pressure for plastic deformation. METHODS: The authors of two previously published articles contributed primary data for these unique post hoc analyses. Human cadaveric ex vivo measurements of ONSD (n = 10) and luminal distending pressure (range 5 to 65 mm Hg) were used to calculate E and the threshold pressure for plastic deformation. Clinical in vivo measurements of ONSD and ICP during endotracheal tube suction from patients with traumatic brain injury (n = 15) were used to validate the ex vivo cadaveric findings. RESULTS: Ex vivo ONS estimate of E was 140 ± 1.3 mm Hg (mean ± standard error), with evidence of plastic deformation occurring with distending pressure at 45 mm Hg. Similar E (71 ± 10 mm Hg) was estimated in vivo with an average ICP of 34 ± 2 mm Hg. CONCLUSIONS: Ex vivo, ONS plastic deformation occurs at levels of pressure commonly seen in patients with raised ICP, leading to distortion of the ICP-ONSD relationship. This evidence of plastic deformation may illustrate why meta-analyses fail to identify a single threshold in ONSD associated with the presence of raised ICP. Future studies characterizing time-dependent viscous characteristics of the ONS will help determine the time course of ONS tissue biomechanical behavior.

Radiation dose enhancement of gadolinium-based AGuIX nanoparticles on HeLa cells.

Radiation dose enhancement of high-Z nanoparticles is an active area of research in cancer therapeutics. When kV and MV energy photon beams interact with high-Z nanoparticles in a tumor, the release of secondary electrons can injure tumor cells, leading to a higher treatment efficacy than radiation alone. We present a study that characterizes the radiation dose enhancing effects of gadolinium-based AGuIX nanoparticles on HeLa cells. Our in vitro clonogenic survival assays showed an average dose enhancement of 1.54× for 220 kVp radiation and 1.15× for 6 MV radiation. The sensitivity enhancement ratio at 4 Gy (SER4Gy) was 1.54 for 220 kVp and 1.28 for 6 MV, indicating that these nanoparticles may be useful for clinical radiation therapy. FROM THE CLINICAL EDITOR: This study characterized the radiation dose enhancing effects of gadolinium-based AGuIX nanoparticles on HeLa cells, showing clear effects at 220 kV as well as 6 MV, suggesting that after additional studies, these nanoparticles may be beneficial in human radiation therapy.

Heart Rate Change as a Potential Digital Biomarker of Brain Death in Critically Ill Children With Acute Catastrophic Brain Injury.

Bedside measurement of heart rate (HR) change (HRC) may provide an objective physiologic marker for when brain death (BD) may have occurred, and BD testing is indicated in children. OBJECTIVES: To determine whether HRC, calculated using numeric HR measurements sampled every 5 seconds, can identify patients with BD among patients with catastrophic brain injury (CBI). DESIGN SETTING AND PARTICIPANTS: Single-center, retrospective study (2008-2020) of critically ill children with acute CBI. Patients with CBI had a neurocritical care consultation, were admitted to an ICU, had acute neurologic injury on presentation or during hospitalization based on clinical and/or imaging findings, and died or survived with Glasgow Coma Scale (GCS) less than 13 at hospital discharge. Patients meeting BD criteria (BD group) were compared with those with cardiopulmonary death (CD group) or those who survived to discharge. MAIN OUTCOMES AND MEASURES: HRC was calculated as the interquartile range of HR divided by median HR using 5-minute windows with 50% overlap for up to 5 days before death or end of recording. HRC was compared among the BD, CD, and survivor groups. RESULTS: Of 96 patients with CBI (69% male, median age 4 years), 28 died (8 BD, 20 CD) and 20 survived (median GCS 9 at discharge). Within 24 hours before death, HRC was lower in BD compared with CD patients or survivors (0.01 vs 0.03 vs 0.04, p = 0.001). In BD patients, HRC decreased at least 1 day before death. HRC discriminated BD from CD patients and survivors with 90% sensitivity, 70% specificity, 44% positive predictive value, 96% negative predictive value (area under the receiver operating characteristic curve 0.88, 95% CI, 0.80-0.93). CONCLUSIONS AND RELEVANCE: HRC is a novel digital biomarker that, with further validation, may be useful as a classifier for BD in the overall course of patients with CBI.

A Survey of Neuromonitoring Practices in North American Pediatric Intensive Care Units.

BACKGROUND: Neuromonitoring is the use of continuous measures of brain physiology to detect clinically important events in real-time. Neuromonitoring devices can be invasive or non-invasive and are typically used on patients with acute brain injury or at high risk for brain injury. The goal of this study was to characterize neuromonitoring infrastructure and practices in North American pediatric intensive care units (PICUs). METHODS: An electronic, web-based survey was distributed to 70 North American institutions participating in the Pediatric Neurocritical Care Research Group. Questions related to the clinical use of neuromonitoring devices, integrative multimodality neuromonitoring capabilities, and neuromonitoring infrastructure were included. Survey results were presented using descriptive statistics. RESULTS: The survey was completed by faculty at 74% (52 of 70) of institutions. All 52 institutions measure intracranial pressure and have electroencephalography capability, whereas 87% (45 of 52) use near-infrared spectroscopy and 40% (21/52) use transcranial Doppler. Individual patient monitoring decisions were driven by institutional protocols and collaboration between critical care, neurology, and neurosurgery attendings. Reported device utilization varied by brain injury etiology. Only 15% (eight of 52) of institutions utilized a multimodality neuromonitoring platform to integrate and synchronize data from multiple devices. A database of neuromonitoring patients was maintained at 35% (18 of 52) of institutions. Funding for neuromonitoring programs was variable with contributions from hospitals (19%, 10 of 52), private donations (12%, six of 52), and research funds (12%, six of 52), although 73% (40 of 52) have no dedicated funds. CONCLUSIONS: Neuromonitoring indications, devices, and infrastructure vary by institution in North American pediatric critical care units. Noninvasive modalities were utilized more liberally, although not uniformly, than invasive monitoring. Further studies are needed to standardize the acquisition, interpretation, and reporting of clinical neuromonitoring data, and to determine whether neuromonitoring systems impact neurological outcomes.

PEGylated liposomal Gemcitabine: insights into a potential breast cancer therapeutic.

PURPOSE: Nanoencapsulation of chemotherapeutics is an established method to target breast tumors and has been shown to enhance the efficacy of therapy in various animal models. During the past two decades, the nucleoside analog Gemcitabine has been under investigation to treat both recalcitrant and localized breast cancer, often in combination with other chemotherapeutics. In this study, we investigated the chemotherapeutic efficacy of a novel Gemcitabine-encapsulated liposome previously formulated by our group, GemPo, on both sensitive (4T1) and recalcitrant (MDA-MB-231) breast cancer cell lines. METHODS: Gemcitabine free drug and liposomal Gemcitabine were compared both in vitro and in vivo using breast cancer models. RESULTS: We demonstrated that GemPo differently hindered the growth, survival and migration of breast cancer cells, according to their drug sensitivities. Specifically, whereas GemPo was a more potent cytotoxic and apoptotic agent in sensitive breast cancer cells, it more potently inhibited cell migration in the resistant cell line. However, GemPo still acted as a more potent inhibitor of migration, in comparison with free Gemcitabine, irrespective of cell sensitivity. Administration of GemPo in a 4T1-bearing mouse model inhibited tumor growth while increasing mice survival, as compared with free Gemcitabine and a vehicle control. Interestingly, the inclusion of a mitotic inhibitor, Paclitaxel, synergized only with free Gemcitabine in this model, yet was as effective as GemPo alone. However, inclusion of Paclitaxel with GemPo significantly improved mouse survival. CONCLUSIONS: Our study is the first to demonstrate the pleiotropic effects of Gemcitabine and Gemcitabine-loaded nanoparticles in breast cancer, and opens the door for a novel treatment for breast cancer patients.