Current Local Anesthetic Applications in Regional Anesthesia

Complete anesthesia is often described using terminology that pertains to the pharmacodynamic effects of the medications administered. This vocabulary often includes akinesia, analgesia, amnesia and hypnosis. Local anesthesia is more specific and represents the administration of an amide or ester local anesthetic, to affect analgesia, at or around the site of administration. Anesthesiologists employ a breadth of different clinical techniques that utilize local anesthetic medications. These techniques include topical, mucosal, endotracheal, intravenous, peripheral nerve block, epidural, and intrathecal (spinal) administration. Unique to the fields of anesthesiology and pain medicine, however, is the administration of epidural and intrathecal local anesthetic. Together, these routes are jointly referred to as neuraxial anesthesia and are often utilized to facilitate surgical intervention, labor analgesia, or pain therapy. The history of neuraxial local anesthetic administration is rich and intriguing. The anatomy of the spinal cord and surrounding structures is complex and pertinent to the pharmacologic discussion of neuraxial local anesthetic administration. The pharmacodynamic and pharmacokinetic interactions of local anesthetics, when administered via the neuraxial route, are unique and worthy of continued investigation. Much has been studied, but there is still more to be discovered. These topics will be the focus of our discussion

An Arp2/3 Nucleated F-Actin Shell Fragments Nuclear Membranes at Nuclear Envelope Breakdown in Starfish Oocytes

Animal cells disassemble and reassemble their nuclear envelopes (NEs) upon each division. Nuclear envelope breakdown (NEBD) serves as a major regulatory mechanism by which mixing of cytoplasmic and nuclear compartments drives the complete reorganization of cellular architecture, committing the cell for division. Breakdown is initiated by phosphorylation-driven partial disassembly of the nuclear pore complexes (NPCs), increasing their permeability but leaving the overall NE structure intact. Subsequently, the NE is rapidly broken into membrane fragments, defining the transition from prophase to prometaphase and resulting in complete mixing of cyto- and nucleoplasm. However, the mechanism underlying this rapid NE fragmentation remains largely unknown. Here, we show that NE fragmentation during NEBD in starfish oocytes is driven by an Arp2/3 complex-nucleated F-actin “shell” that transiently polymerizes on the inner surface of the NE. Blocking the formation of this F-actin shell prevents membrane fragmentation and delays entry of large cytoplasmic molecules into the nucleus. We observe spike-like protrusions extending from the F-actin shell that appear to “pierce” the NE during the fragmentation process. Finally, we show that NE fragmentation is essential for successful reproduction, because blocking this process in meiosis leads to formation of aneuploid eggs.MIT Faculty Start-up FundNational Science Foundation (U.S.). Graduate Research Fellowshi

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.</p

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.</p

A Federated Database for Obesity Research: An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders

Spinal Anaesthesia for Cesarean Section in a Patient with Vascular Type Ehlers-Danlos Syndrome

We report the administration of spinal anaesthesia for cesarean delivery in a parturient with vascular Ehlers-Danlos syndrome. Parturients who genetically inherit this disorder are at risk for significant morbidity and mortality. Risks during pregnancy include premature labor, uterine prolapse, and uterine rupture. Additionally, such laboring parturients are at increased risk of hemodynamic volatility, vascular stress, and severe postpartum hemorrhage. Instrumented delivery and cesarean delivery bring additional risks. Nonpregnancy-related complications include excessive bleeding, intestinal rupture, cardiac valvular dysfunction, and arterial dissection. Despite the complexity of this condition, literature focusing on specific intraoperative anaesthetic management is sparse

Experiences with Regional Anesthesia for Analgesia During Prolonged Aeromedical Evacuation

NTRODUCTION: There is much debate regarding the appropriate analgesic management of patients undergoing medical evacuation following combat trauma. Our primary objective was to review the utility of regional anesthetic techniques in patients undergoing aeromedical evacuation following surgical limb amputation as treatment for combat trauma. METHODS: This study was conducted as an observational retrospective cohort whereby acutely injured amputee patients were identified via the U.S. Transportation Command\u27s patient movement database. The Theater Medical Data Store was cross-referenced for additional patient care data including opioid consumption, duration of regional technique, pain scores, and rates of intubation. RESULTS: Eighty-four records were retrieved from the Theater Medical Data Store. All 84 patients were victims of improvised explosive device detonation requiring limb amputation and subsequent transport from Kandahar Airfield or Camp Bastion, Afghanistan, to the United States. The majority of interventions remained in place throughout the evacuation process. A significant decrease in opioid consumption in patients receiving regional anesthesia was identified at each leg of the medical evacuation process. Pain scores were sporadically reported and not statistically different. Higher rates of intubation were identified in the nonregional anesthetic group. DISCUSSION: Our analysis demonstrates the feasibility and effectiveness of applying regional anesthetic techniques for pain management to our combat wounded trauma patients throughout multiple stages of aeromedical evacuation. Benefits include the potential for less sedation and less opioid consumption while potentially foregoing the requirement for intubation during transport