Hospital-level variation in hospitalization costs for spinal fusion in the United States.

BACKGROUND: With a growing emphasis on value of care, understanding factors associated with rising healthcare costs is increasingly important. In this national study, we evaluated the degree of center-level variation in the cost of spinal fusion. METHODS: All adults undergoing elective spinal fusion were identified in the 2016 to 2020 National Inpatient Sample. Multilevel mixed-effect models were used to rank hospitals based on risk-adjusted costs. The interclass coefficient (ICC) was utilized to tabulate the amount of variation attributable to hospital-level characteristics. The association of high cost-hospital (HCH) status with in-hospital mortality, perioperative complications, and overall resource utilization was analyzed. Predictors of increased costs were secondarily explored. RESULTS: An estimated 1,541,740 patients underwent spinal fusion, and HCH performed an average of 9.5% of annual cases. HCH were more likely to be small (36.8 vs 30.5%, p<0.001), rural (10.1 vs 8.8%, p<0.001), and located in the Western geographic region (49.9 vs 16.7%, p<0.001). The ICC demonstrated 32% of variation in cost was attributable to the hospital, independent of patient-level characteristics. Patients who received a spinal fusion at a HCH faced similar odds of mortality (0.74 [0.48-1.15], p = 0.18) and perioperative complications (1.04 [0.93-1.16], p = 0.52), but increased odds of non-home discharge (1.30 [1.17-1.45], p<0.001) and prolonged length of stay (ß 0.34 [0.26-0.42] days, p = 0.18). Patient factors such as gender, race, and income quartile significantly impacted costs. CONCLUSION: The present analysis identified 32% of the observed variation to be attributable to hospital-level characteristics. HCH status was not associated with increased mortality or perioperative complications.

In Vivo Intravascular Pacing Using a Wireless Microscale Stimulator.

Millions of patients worldwide are implanted with permanent pacemakers for the treatment of cardiac arrhythmias and conduction disorders. The increased use of these devices has established a growing clinical need to mitigate associated complications. Pacemaker leads, in particular, present the primary risks in most implants. While wireless power transfer holds great promise in eliminating implantable device leads, anatomical constraints limit efficient wireless transmission over the necessary operational range. We thereby developed a transmitter-centered control system for wireless power transfer with sufficient power for continuous cardiac pacing. Device safety was validated using a computational model of the system within an MRI-based anatomical model. The pacer was then fabricated to meet the acute constraints of the anterior cardiac vein (ACV) to enable intravascular deployment while maintaining power efficiency. Our computational model revealed the wireless system to operate at > 50 times below the tissue energy absorption safety criteria. We further demonstrated the capacity for ex vivo pacing of pig hearts at 60 beats per minute (BPM) and in vivo pacing at 120 BPM following pacer deployment in the ACV. This work thus established the capacity for wireless intravascular pacing with the potential to eliminate complications associated with current lead-based deep tissue implants.

Three-dimensional Imaging Coupled with Topological Quantification Uncovers Retinal Vascular Plexuses Undergoing Obliteration.

Introduction: Murine models provide microvascular insights into the 3-D network disarray seen in retinopathy and cardiovascular diseases. Light-sheet fluorescence microscopy (LSFM) has emerged to capture retinal vasculature in 3-D, allowing for assessment of the progression of retinopathy and the potential to screen new therapeutic targets in mice. We hereby coupled LSFM, also known as selective plane illumination microscopy, with topological quantification, to characterize the retinal vascular plexuses undergoing preferential obliteration. Method and Result: In postnatal mice, we revealed the 3-D retinal microvascular network in which the vertical sprouts bridge the primary (inner) and secondary (outer) plexuses, whereas, in an oxygen-induced retinopathy (OIR) mouse model, we demonstrated preferential obliteration of the secondary plexus and bridging vessels with a relatively unscathed primary plexus. Using clustering coefficients and Euler numbers, we computed the local versus global vascular connectivity. While local connectivity was preserved (p > 0.05, n = 5 vs. normoxia), the global vascular connectivity in hyperoxia-exposed retinas was significantly reduced (p < 0.05, n = 5 vs. normoxia). Applying principal component analysis (PCA) for auto-segmentation of the vertical sprouts, we corroborated the obliteration of the vertical sprouts bridging the secondary plexuses, as evidenced by impaired vascular branching and connectivity, and reduction in vessel volumes and lengths (p < 0.05, n = 5 vs. normoxia). Conclusion: Coupling 3-D LSFM with topological quantification uncovered the retinal vasculature undergoing hyperoxia-induced obliteration from the secondary (outer) plexus to the vertical sprouts. The use of clustering coefficients, Euler's number, and PCA provided new network insights into OIR-associated vascular obliteration, with translational significance for investigating therapeutic interventions to prevent visual impairment.

Saak Transform-Based Machine Learning for Light-Sheet Imaging of Cardiac Trabeculation.

OBJECTIVE: Recent advances in light-sheet fluorescence microscopy (LSFM) enable 3-dimensional (3-D) imaging of cardiac architecture and mechanics in toto. However, segmentation of the cardiac trabecular network to quantify cardiac injury remains a challenge. METHODS: We hereby employed "subspace approximation with augmented kernels (Saak) transform" for accurate and efficient quantification of the light-sheet image stacks following chemotherapy-treatment. We established a machine learning framework with augmented kernels based on the Karhunen-Loeve Transform (KLT) to preserve linearity and reversibility of rectification. RESULTS: The Saak transform-based machine learning enhances computational efficiency and obviates iterative optimization of cost function needed for neural networks, minimizing the number of training datasets for segmentation in our scenario. The integration of forward and inverse Saak transforms can also serve as a light-weight module to filter adversarial perturbations and reconstruct estimated images, salvaging robustness of existing classification methods. The accuracy and robustness of the Saak transform are evident following the tests of dice similarity coefficients and various adversary perturbation algorithms, respectively. The addition of edge detection further allows for quantifying the surface area to volume ratio (SVR) of the myocardium in response to chemotherapy-induced cardiac remodeling. CONCLUSION: The combination of Saak transform, random forest, and edge detection augments segmentation efficiency by 20-fold as compared to manual processing. SIGNIFICANCE: This new methodology establishes a robust framework for post light-sheet imaging processing, and creating a data-driven machine learning for automated quantification of cardiac ultra-structure.

Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Reverse Total Shoulder Arthroplasty.

Background: Reverse total shoulder arthroplasty (rTSA) offers tremendous promise for the treatment of complex pathologies beyond the scope of anatomic total shoulder arthroplasty but is associated with a higher rate of major postoperative complications. We aimed to design and validate a machine learning (ML) model to predict major postoperative complications or readmission following rTSA. Methods: We retrospectively reviewed California's Office of Statewide Health Planning and Development database for patients who underwent rTSA between 2015 and 2017. We implemented logistic regression (LR), extreme gradient boosting (XGBoost), gradient boosting machines, adaptive boosting, and random forest classifiers in Python and trained these models using 64 binary, continuous, and discrete variables to predict the occurrence of at least one major postoperative complication or readmission following primary rTSA. Models were validated using the standard metrics of area under the receiver operating characteristic (AUROC) curve, area under the precision-recall curve (AUPRC), and Brier scores. The key factors for the top-performing model were determined. Results: Of 2799 rTSAs performed during the study period, 152 patients (5%) had at least 1 major postoperative complication or 30-day readmission. XGBoost had the highest AUROC and AUPRC of 0.681 and 0.129, respectively. The key predictive features in this model were patients with a history of implant complications, protein-calorie malnutrition, and a higher number of comorbidities. Conclusion: Our study reports an ML model for the prediction of major complications or 30-day readmission following rTSA. XGBoost outperformed traditional LR models and also identified key predictive features of complications and readmission.

A Multi-Dimensional Analysis of a Novel Approach for Wireless Stimulation.

The elimination of integrated batteries in biomedical implants holds great promise for improving health outcomes in patients with implantable devices. However, despite extensive research in wireless power transfer, achieving efficient power transfer and effective operational range have remained a hindering challenge within anatomical constraints. OBJECTIVE: We hereby demonstrate an intravascular wireless and batteryless microscale stimulator, designed for (1) low power dissipation via intermittent transmission and (2) reduced fixation mechanical burden via deployment to the anterior cardiac vein (ACV, ∼3.8 mm in diameter). METHODS: We introduced a unique coil design circumferentially confined to a 3 mm diameter hollow-cylinder that was driven by a novel transmitter-based control architecture with improved power efficiency. RESULTS: We examined wireless capacity using heterogenous bovine tissue, demonstrating >5 V stimulation threshold with up to 20 mm transmitter-receiver displacement and 20° of misalignment. Feasibility for human use was validated using Finite Element Method (FEM) simulation of the cardiac cycle, guided by pacer phantom-integrated Magnetic Resonance Images (MRI). CONCLUSION: This system design thus enabled sufficient wireless power transfer in the face of extensive stimulator miniaturization. SIGNIFICANCE: Our successful feasibility studies demonstrated the capacity for minimally invasive deployment and low-risk fixation.

Wireless Pacing Using an Asynchronous Three-Tiered Inductive Power Transfer System.

Despite numerous advancements in pacemaker technology for the treatment of cardiac arrhythmias and conduction disorders, lead-related complications associated with these devices continue to compromise patient safety and survival. In this work, we present a system architecture that has the capacity to deliver power to a wireless, batteryless intravascular pacer. This was made possible through a three-tiered, dual-sub-system, four-coil design, which operates on two different frequencies through intermittent remote-controlled inductive power transfer. System efficiency was enhanced using coil design optimization, and validated using numerical simulations and experimental analysis. Our pacemaker design was concepted to achieve inductive power transfer over a 55 mm range to a microscale pacer with a 3 mm diameter. Thus, the proposed system design enabled long-range wireless power transfer to a small implanted pacer with the capacity for intravascular deployment to the anterior cardiac vein. This proposed stent-like fixation mechanism can bypass the multitude of complications associated with pacemaker wires while wireless power can eliminate the need for repeated procedures for battery replacement.

Mesenchymal Stem Cell-Derived Extracellular Vesicles Decrease Lung Injury in Mice.

Human mesenchymal stem cell (MSC) extracellular vesicles (EV) can reduce the severity of bacterial pneumonia, but little is known about the mechanisms underlying their antimicrobial activity. In the current study, we found that bacterial clearance induced by MSC EV in Escherichia coli pneumonia in C57BL/6 mice was associated with high levels of leukotriene (LT) B4 in the injured alveolus. More importantly, the antimicrobial effect of MSC EV was abrogated by cotreatment with a LTB4 BLT1 antagonist. To determine the role of MSC EV on LT metabolism, we measured the effect of MSC EV on a known ATP-binding cassette transporter, multidrug resistance-associated protein 1 (MRP1), and found that MSC EV suppressed MRP1 mRNA, protein, and pump function in LPS-stimulated Raw264.7 cells in vitro. The synthesis of LTB4 and LTC4 from LTA4 are competitive, and MRP1 is the efflux pump for LTC4 Inhibition of MRP1 will increase LTB4 production. In addition, administration of a nonspecific MRP1 inhibitor (MK-571) reduced LTC4 and subsequently increased LTB4 levels in C57BL/6 mice with acute lung injury, increasing overall antimicrobial activity. We previously found that the biological effects of MSC EV were through the transfer of its content, such as mRNA, microRNA, and proteins, to target cells. In the current study, miR-145 knockdown abolished the effect of MSC EV on the inhibition of MRP1 in vitro and the antimicrobial effect in vivo. In summary, MSC EV suppressed MRP1 activity through transfer of miR-145, thereby resulting in enhanced LTB4 production and antimicrobial activity through LTB4/BLT1 signaling.

Mesenchymal stem cell derived secretome and extracellular vesicles for acute lung injury and other inflammatory lung diseases.

INTRODUCTION: Acute respiratory distress syndrome is a major cause of respiratory failure in critically ill patients. Despite extensive research into its pathophysiology, mortality remains high. No effective pharmacotherapy exists. Based largely on numerous preclinical studies, administration of mesenchymal stem or stromal cell (MSC) as a therapeutic for acute lung injury holds great promise, and clinical trials are currently underway. However, concern for the use of stem cells, specifically the risk of iatrogenic tumor formation, remains unresolved. Accumulating evidence now suggest that novel cell-free therapies including MSC-derived conditioned medium and extracellular vesicles released from MSCs might constitute compelling alternatives. AREAS COVERED: The current review summarizes the preclinical studies testing MSC conditioned medium and/or MSC extracellular vesicles as treatment for acute lung injury and other inflammatory lung diseases. EXPERT OPINION: While certain logistical obstacles limit the clinical applications of MSC conditioned medium such as the volume required for treatment, the therapeutic application of MSC extracellular vesicles remains promising, primarily due to ability of extracellular vesicles to maintain the functional phenotype of the parent cell. However, utilization of MSC extracellular vesicles will require large-scale production and standardization concerning identification, characterization and quantification.