Publications by authors named "Peter Hu"

Virtual reality (VR) is a promising intervention for both experimentally induced and clinical pain, but the factors contributing to the efficacy of VR remain relatively unclear, partially because selecting adequate controls in existing VR studies is challenging. Here, we identified and isolated several factors potentially influencing the hypoalgesic effect of VR. In this within-subjects, counterbalanced controlled study, healthy participants received painful heat stimulation under 5 conditions: VR Ocean (immersive ocean environment), Sham VR Ocean (nonimmersive ocean environment), VR Neutral (immersive neutral environment), Imagination (self-imagined ocean environment), and No-intervention.

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Purpose Of Review: This review investigates the use of machine learning (ML) in prognosticating outcomes for traumatic brain injury (TBI). It underscores the benefits of ML models in processing and integrating complex, multimodal data-including clinical, imaging, and physiological inputs-to identify intricate non-linear relationships that traditional methods might overlook.

Recent Findings: ML algorithms of clinical features, neuroimaging, and metrics from the autonomic nervous system enhance the early detection of clinical deterioration and improve outcome prediction.

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Purpose: To evaluate prevalence and incidence rates of pigmentary maculopathy and retinopathy (PM/PR), and visual acuity (VA) changes in patients exposed to pentosan polysulfate sodium (PPS) and in patients with interstitial cystitis (IC) not exposed to PPS.

Methods: This is a retrospective cohort study (January 2015-March 2021) which included adult de-identified patients from the American Academy of Ophthalmology IRIS® Registry (Intelligent Research in Sight) and Komodo Health database. Three patient cohorts were identified: two PPS-exposed patient cohorts, and Non-PPS-exposed IC patient cohort.

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Introduction: Access to quality-assured medicines remains unequal between high-income and low-income countries. To bridge this gap, product development and supply in low- and middle-income countries (LMICs) should follow World Health Organization (WHO)'s policies and recommendations whilst aligning with international standards.

Areas Covered: We reviewed two cases on oxytocin access for postpartum hemorrhage (PPH), a condition that disproportionately affects mothers in low-income countries.

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Background: Paroxysmal sympathetic hyperactivity (PSH) occurs with high prevalence among critically ill patients with traumatic brain injury (TBI) and is associated with worse outcomes. The PSH-Assessment Measure (PSH-AM) consists of a Clinical Features Scale and a diagnosis likelihood tool (DLT) intended to quantify the severity of sympathetically mediated symptoms and the likelihood that they are due to PSH, respectively, on a daily basis. Here, we aim to identify and explore the value of dynamic trends in the evolution of sympathetic hyperactivity following acute TBI using elements of the PSH-AM.

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  • * A successful case is presented involving the use of right internal jugular vein access for the PASCAL mitral valve repair system.
  • * This approach offers a safer alternative for patients who cannot undergo traditional surgical procedures due to their high-risk status.
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  • The study focuses on assessing how well continuous vital signs (VS) can predict the severity of traumatic injuries and the need for lifesaving interventions (LSIs) compared to traditional invasive methods like lactate measurements.
  • Researchers analyzed data from 300 patients treated in a prehospital helicopter setting, using continuous VS along with laboratory tests to see which method was better at predicting outcomes such as ICU admission and discharge times.
  • The findings indicated that continuous VS models outperformed single initial VS readings for predicting LSIs and ICU stay length and showed performance comparable to lactate tests for predicting 24-hour discharge, highlighting their potential in emergency medical decision-making.
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  • A study in Ucayali, Peru examined two methods for detecting soil-transmitted helminth infections in children: the old method called Kato-Katz (KK1.0) and a new method using artificial intelligence called KK2.0.
  • The researchers analyzed stool samples from 510 kids aged 5-14 and found that KK2.0 could detect more cases of Ascaris lumbricoides compared to KK1.0, especially at the 30-minute mark.
  • The results showed that while both methods had similar detection rates for other types of infections, KK2.0 was better at finding low levels of A. lumbricoides infection in the kids.
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  • Acute traumatic coagulopathy (ATC) occurs shortly after injury and is associated with higher risks of massive transfusion and mortality in trauma patients.
  • A machine learning-based Coagulation Risk Index (CRI) was developed to predict ATC using continuous vital signs recorded during the first 15 minutes after a patient’s admission to a trauma center.
  • The CRI showed high accuracy in predicting ATC, achieving true positive rates of over 90% for different levels of international normalized ratio (INR), indicating its effectiveness for early identification of coagulopathy in bleeding trauma patients.
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Background: Paroxysmal Sympathetic Hyperactivity (PSH) occurs with high prevalence among critically ill Traumatic Brain Injury (TBI) patients and is associated with worse outcomes. The PSH-Assessment Measure (PSH-AM) consists of a Clinical Features Scale (CFS) and a Diagnosis Likelihood Tool (DLT), intended to quantify the severity of sympathetically-mediated symptoms and likelihood that they are due to PSH, respectively, on a daily basis. Here, we aim to identify and explore the value of dynamic trends in the evolution of sympathetic hyperactivity following acute TBI using elements of the PSH-AM.

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This perspective, marking the 30th anniversary of the Tissue Engineering journal, discusses the exciting trends in the global commercialization of tissue engineering technology. Within a historical context, we present an evolution of challenges and a discussion of the last 5 years of global commercial successes and emerging market trends, highlighting the continued expansion of the field in the northeastern United States. This leads to an overview of the last 5 years' progress in clinical trials for tissue-engineered therapeutics, including an analysis of trends in success and failure.

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Agricultural aircraft operations are associated with unique challenges. In particular, these include maintaining awareness of obstacles associated with flight at very low altitudes. Wire strikes are a common cause of accidents in these operations.

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Determination of prognosis in the triage process after traumatic brain injury (TBI) is difficult to achieve. Current severity measures like the Trauma and injury severity score (TRISS) and revised trauma score (RTS) rely on additional information from the Glasgow Coma Scale (GCS) and the Injury Severity Score (ISS) which may be inaccurate or delayed, limiting their usefulness in the rapid triage setting. We hypothesized that machine learning based estimations of GCS and ISS obtained through modeling of continuous vital sign features could be used to rapidly derive an automated RTS and TRISS.

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Background: Clinicians working in intensive care units (ICUs) are immersed in a cacophony of alarms and a relentless onslaught of data. Within this frenetic environment, clinicians make high-stakes decisions using many data sources and are often oversaturated with information of varying quality. Traditional bedside monitors only depict static vital signs data, and these data are not easily viewable remotely.

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Multifocal ganglioneuromas are characterized by the presence of multiple benign neuroepithelial tumor nodules and are less common than solitary tumors. A small percentage of ganglioneuromas present with a fatty appearance. Only a few cases of multifocal ganglioneuromas have been reported, due to both their rarity and minimal symptomatic presentation; therefore, generalizations about risk factors and predictive markers are very difficult.

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Background: Paroxysmal sympathetic hyperactivity (PSH) occurs in a subset of patients with traumatic brain injury (TBI) and is associated with worse outcomes. Sepsis is also associated with worse outcomes after TBI and shares several physiologic features with PSH, potentially creating diagnostic confusion and suboptimal management of each. This is the first study to directly investigate the interaction between PSH and infection using robust diagnostic criteria.

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Background: The implementation of multimodality monitoring in the clinical management of patients with disorders of consciousness (DoC) results in physiological measurements that can be collected in a continuous and regular fashion or even at waveform resolution. Such data are considered part of the "Big Data" available in intensive care units and are potentially suitable for health care-focused artificial intelligence research. Despite the richness in content of the physiological measurements, and the clinical implications shown by derived metrics based on those measurements, they have been largely neglected from previous attempts in harmonizing data collection and standardizing reporting of results as part of common data elements (CDEs) efforts.

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Severe traumatic injury leads to marked systemic inflammation and multiorgan injury. Endogenous drivers such as extracellular nucleic acid may play a role in mediating innate immune response and the downstream pathogenesis. Here, we explored the role of plasma extracellular RNA (exRNA) and its sensing mechanism in inflammation and organ injury in a murine model of polytrauma.

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Introduction: The randomized phase III KEYNOTE-522 trial demonstrated that addition of pembrolizumab to neoadjuvant chemotherapy provided a significant improvement in event-free survival and a favorable trend in overall survival for high-risk early-stage triple-negative breast cancer (eTNBC). This analysis evaluated the cost-effectiveness of pembrolizumab in combination with chemotherapy as neoadjuvant treatment and continued as a single-agent adjuvant treatment after surgery vs. neoadjuvant chemotherapy for patients with high-risk eTNBC in the USA.

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Secondary neurologic decline (ND) after traumatic brain injury (TBI) is independently associated with outcome, but robust predictors of ND are lacking. In this retrospective analysis of consecutive isolated TBI admissions to the R. Adams Cowley Shock Trauma Center between November 2015 and June 2018, we aimed to develop a triage decision support tool to quantify risk for early ND.

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Cortical neural dynamics mediate information processing for the cerebral cortex, which is implicated in fundamental biological processes such as vision and olfaction, in addition to neurological and psychiatric diseases. Spontaneous pain is a key feature of human neuropathic pain. Whether spontaneous pain pushes the cortical network into an aberrant state and, if so, whether it can be brought back to a "normal" operating range to ameliorate pain are unknown.

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Objective: In the KEYNOTE-355 (KN355) trial, pembrolizumab in combination with chemotherapy demonstrated superior efficacy and manageable safety compared with chemotherapy alone in patients with previously untreated locally recurrent inoperable and metastatic triple-negative breast cancer (mTNBC) with PD-L1 positive (Combined Positive Score [CPS]≥ 10) tumours. This study aimed to evaluate the clinical benefits and risks of pembrolizumab measured by quality-adjusted survival in the trial population.

Methods: The study used data from the final analysis of KN355.

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This study evaluated the cost-effectiveness of pembrolizumab/chemotherapy combinations for previously untreated metastatic triple-negative breast cancer patients in the USA with PD-L1 combined positive score ≥10. A partitioned-survival model was developed to project health outcomes and direct medical costs over a 20-year time horizon. Efficacy and safety data were from randomized clinical trials.

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