Asystolic donor warm ischemia time is associated with development of postreperfusion syndrome in donation after circulatory death liver transplant.

BACKGROUND: Individual events during donation after circulatory death (DCD) procurement, such as hypotensive or hypoxic warm ischemia, or circulatory arrest are all a part of donor warm ischemia time (dWIT), and may have differing effects on the outcome of the liver graft. This study aimed to identify risk factors for postreperfusion syndrome (PRS), a state of severe hemodynamic derangement following graft reperfusion, and its impact on DCD liver transplantation (LT) outcomes. METHODS: This was a retrospective analysis using 106 DCD LT. Detailed information for events during procurement (withdrawal of life support; systolic blood pressure < 80 mmHg; oxygen saturation < 80%; circulatory arrest; aortic cold perfusion) and their association with the development of PRS were examined using logistic regression. RESULTS: The overall incidence of PRS was 26.4%, occurring in 28 patients. Independent risk factors for PRS were asystolic dWIT (odds ratio (OR) 3.65, 95% confidence interval (CI) 1.38-9.66) and MELD score (OR 1.06, 95% CI 1.01-1.10). Total bilirubin was significantly higher in the PRS group at postoperative day (POD) 1 (p = .02; 5.2 mg/dL vs. 3.4 mg/dL), POD 3 (p = .049; 4.5 mg/dL vs. 2.8 mg/dL), and POD 7 (p = .04; 3.1 mg/dL vs. 1.9 mg/dL). Renal replacement therapy after LT was more likely to be required in the PRS group (p = .01; 48.2% vs. 23.1%). CONCLUSION: Asystolic dWIT is a risk factor for the development of PRS in DCD LT. Our results suggest that asystolic dWIT should be considered when selecting DCD liver donors.

Unveiling the evolving landscape of stroke care costs: A time-driven analysis.

INTRODUCTION: Stroke is a common cause of mortality in the United States. However, the economic burden of stroke on the healthcare system is not well known. In this study, we aim to calculate the annual cumulative and per-patient cost of stroke. METHODS: We conducted a retrospective analysis of Nationwide Emergency Department Sample (NEDS). We calculate annual trends in cost for stroke patients from 2006 to 2019. A multivariate linear regression with patient characteristics (e.g. age, sex, Charlson Comorbidity Index) as covariates was used to identify factors for higher costs. RESULTS: In this study time-period, 2,998,237 stroke patients presented to the ED and 2,481,171 (83 %) were admitted. From 2006 to 2019, the cumulative ED cost increased by a factor of 7.0 from 0.49 ± 0.03 to 3.91 ± 0.16 billion dollars (p < 0.001). The cumulative inpatient (IP) cost increased by a factor of 2.7 from 14.42 ± 0.78 to 37.06 ± 2.26 billion dollars (p < 0.001. Per-patient ED charges increased by a factor of 3.0 from 1950 ± 64 to 7818 ± 260 dollars (p < 0.001). Per-patient IP charges increased by 89 % from 40.22 +/- 1.12 to 76.06 ± 3.18 thousand dollars (p < 0.001). CONCLUSION: Strokes place an increasing financial burden on the US healthcare system. Certain patient demographics including age, male gender, more comorbidities, and insurance type were significantly associated with increased cost of care.

Dimensions of Uncertainty: A spatiotemporal review of five COVID-19 datasets.

COVID-19 surveillance across the U.S. is essential to tracking and mitigating the pandemic, but data representing cases and deaths may be impacted by attribute, spatial, and temporal uncertainties. COVID-19 case and death data are essential to understanding the pandemic and serve as key inputs for prediction models that inform policy-decisions; consistent information across datasets is critical to ensuring coherent findings. We implement an exploratory data analytic approach to characterize, synthesize, and visualize spatial-temporal dimensions of uncertainty across commonly used datasets for case and death metrics (Johns Hopkins University, the New York Times, USAFacts, and 1Point3Acres). We scrutinize data consistency to assess where and when disagreements occur, potentially indicating underlying uncertainty. We observe differences in cumulative case and death rates to highlight discrepancies and identify spatial patterns. Data are assessed using pairwise agreement (Cohen's kappa) and agreement across all datasets (Fleiss' kappa) to summarize changes over time. Findings suggest highest agreements between CDC, JHU, and NYT datasets. We find nine discrete type-components of information uncertainty for COVID-19 datasets reflecting various complex processes. Understanding processes and indicators of uncertainty in COVID-19 data reporting is especially relevant to public health professionals and policymakers to accurately understand and communicate information about the pandemic.

Abdominal Organ Transplantation: Noteworthy Literature in 2023.

This review highlights noteworthy literature published in 2023 and pertinent to anesthesiologists and critical care physicians caring for patients undergoing abdominal organ transplantation. We feature 9 studies from 593 peer-reviewed papers on pancreatic transplantation, 3 from 194 on intestinal transplantation, and 28 from over 4513 on kidney transplantation. The liver transplantation section includes a special focus on 20 studies from 5666 clinical trial publications. We explore a broad range of topics, including donor management, perioperative recipient management, and innovative pharmacologic and mechanical interventions tested for the improvement of patient and graft outcomes and survival.

Drop the shortcuts: image augmentation improves fairness and decreases AI detection of race and other demographics from medical images.

BACKGROUND: It has been shown that AI models can learn race on medical images, leading to algorithmic bias. Our aim in this study was to enhance the fairness of medical image models by eliminating bias related to race, age, and sex. We hypothesise models may be learning demographics via shortcut learning and combat this using image augmentation. METHODS: This study included 44,953 patients who identified as Asian, Black, or White (mean age, 60.68 years ±18.21; 23,499 women) for a total of 194,359 chest X-rays (CXRs) from MIMIC-CXR database. The included CheXpert images comprised 45,095 patients (mean age 63.10 years ±18.14; 20,437 women) for a total of 134,300 CXRs were used for external validation. We also collected 1195 3D brain magnetic resonance imaging (MRI) data from the ADNI database, which included 273 participants with an average age of 76.97 years ±14.22, and 142 females. DL models were trained on either non-augmented or augmented images and assessed using disparity metrics. The features learned by the models were analysed using task transfer experiments and model visualisation techniques. FINDINGS: In the detection of radiological findings, training a model using augmented CXR images was shown to reduce disparities in error rate among racial groups (-5.45%), age groups (-13.94%), and sex (-22.22%). For AD detection, the model trained with augmented MRI images was shown 53.11% and 31.01% reduction of disparities in error rate among age and sex groups, respectively. Image augmentation led to a reduction in the model's ability to identify demographic attributes and resulted in the model trained for clinical purposes incorporating fewer demographic features. INTERPRETATION: The model trained using the augmented images was less likely to be influenced by demographic information in detecting image labels. These results demonstrate that the proposed augmentation scheme could enhance the fairness of interpretations by DL models when dealing with data from patients with different demographic backgrounds. FUNDING: National Science and Technology Council (Taiwan), National Institutes of Health.

In-hospital outcomes following surgery versus conservative therapy in elderly patients with C2 fractures: a propensity score-matched analysis.

OBJECTIVE: Second cervical vertebrae (C2) fractures are a common traumatic spinal injury in the elderly population. Surgical fusion and nonoperative bracing are two primary treatments for cervical instability, but the former is often withheld in the elderly due to concerns for poor postoperative outcomes arising from patient frailty. This study sought to evaluate the in-hospital differences in mortality, outcomes, and discharge disposition in elderly patients with C2 fractures undergoing surgical intervention compared with conservative therapy. METHODS: The National Trauma Data Bank was queried from 2017 to 2019 for all patients aged ≥ 65 years with C2 fractures undergoing either surgical stabilization or conservative therapy. Propensity score matching was performed using k-nearest neighbors with replacement based on patient demographics, comorbidities, insurance type, injury severity, and fracture type. Group differences were compared using Student t-tests and Pearson's chi-square tests with Benjamini-Hochberg multiple comparisons correction. Subgroup analyses were performed in the 65-74, 75-79, and 80+ year age subgroups. RESULTS: Six thousand forty-nine patients were identified, of whom 2156 underwent surgery and 3893 received conservative treatment. Following matching, the surgery group had significantly lower mortality rates (5.52% vs 9.6%, p < 0.001), a longer mean hospital length of stay (LOS; 12.64 vs 7.49 days p < 0.001), and slightly higher rates of several complications (< 3% difference), as well as lower rates of discharge home (14.56% vs 23.52%, p < 0.001) and to hospice (1.07% vs 2.09%, p = 0.02) and a higher rate of discharge to intermediate care (68.83% vs 48.28%, p < 0.001). Similar trends in mortality and LOS were noted in all 3 subgroups. CONCLUSIONS: In elderly patients with C2 fractures, surgical stabilization confers a small survival advantage with a slightly higher in-hospital complication rate compared to conservative therapy. The increased rate of discharge to rehabilitation may represent better long-term prognosis following surgery. The increased risk of short-term complications is present but relatively small, thus surgery should not be withheld in patients with good long-term prognosis.

Effect of Li6.4La3Zr1.4Ta0.6O12 Fillers on the Interfacial Properties between Composite PEO-LiTFSI Electrolytes with Li Metal during Cycling.

PEO-LiX solid polymer electrolyte (SPE) with the addition of Li6.4La3Zr1.4Ta0.6O12 (LLZTO) fillers is considered as a promising solid-state electrolyte for solid-state Li-ion batteries. However, the developments of the SPE have caused additional challenges, such as poor contact interface and SPE/Li interface stability during cycling, which always lead to potentially catastrophic battery failure. The main problem is that the real impact of LLZTO fillers on the interfacial properties between SPE and Li metal is still unclear. Herein, we combined the electrochemical measurement and in situ synchrotron-based X-ray absorption near-edge structure (XANES) imaging technology to study the role of LLZTO fillers in directing SPE/Li interface electrochemical performance. In situ XRF-XANES mapping during cycling showed that addition of an appropriate amount of LLZTO fillers (50 wt %) can improve the interfacial contact and stability between SPE and Li metal without reacting with the PEO and Li salts. Additionally, it also demonstrated the beneficial effect of LLZTO particles for suppressing the interface reactions between the Li metal and PEO-LiTFSI SPE and further inhibiting Li-metal dendrite growth. The Li|LiFePO4 batteries deliver long cycling for over 700 cycles with a low-capacity fade rate of 0.08% per cycle at a rate of 0.3C, revealing tremendous potential in promoting the large-scale application of future solid-state Li-ion batteries.

Acoustically targeted measurement of transgene expression in the brain.

Gene expression is a critical component of brain physiology, but monitoring this expression in the living brain represents a major challenge. Here, we introduce a new paradigm called recovery of markers through insonation (REMIS) for noninvasive measurement of gene expression in the brain with cell type, spatial, and temporal specificity. Our approach relies on engineered protein markers that are produced in neurons but exit into the brain's interstitium. When ultrasound is applied to targeted brain regions, it opens the blood-brain barrier and releases these markers into the bloodstream. Once in blood, the markers can be readily detected using biochemical techniques. REMIS can noninvasively confirm gene delivery and measure endogenous signaling in specific brain sites through a simple insonation and a subsequent blood test. REMIS is reliable and demonstrated consistent improvement in recovery of markers from the brain into the blood. Overall, this work establishes a noninvasive, spatially specific method of monitoring gene delivery and endogenous signaling in the brain.