Investigation into the clinical performance of rectus sheath block in reducing postoperative pain following surgical intervention: A systematic review and meta-analysis of randomised controlled trials.

Background and Aims: Rectus sheath block (RSB) is an effective postoperative pain control technique in abdominal surgical procedures. This systematic review evaluated the efficacy and outcome data of patients undergoing RSB compared to the standard of care in both laparoscopic and open surgical procedures. Methods: This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO ID: CRD42022372596). The search was restricted to randomised controlled trials (RCTs) comparing RSB effectiveness on postoperative pain to any standard general anaesthesia technique (control). We systematically explored PubMed, Medline, Central, Scopus and Web of Science for RCTs from inception to September 2023. The primary outcome was the evaluation of pain scores at rest 0-2, 10-12 and 12-24 h postoperatively. The secondary outcome was the analysis of postoperative intravenous (IV) morphine equivalent consumption at 24-h. A risk-of-bias tool for randomised trials (ROB 2.0, Cochrane, Copenhagen, Denmark) assessment and Grades of Recommendation, Assessment, Development and Evaluation (GRADE, Cochrane, Copenhagen, Denmark) analysis was conducted to evaluate the quality of the RCTs. Results: Twenty RCTs involving 708 participants who received RSB intervention and 713 who received alternative analgesic care were included. RSB pain scores were significantly lower than control at 0-2 h (P < 0.001) and 10-12 h (P < 0.001) postoperatively. No significant effect was observed at 24 h (P = 0.11). RSB performance compared to control in 24-h IV morphine equivalency in milligrams was significantly lower (P < 0.001). Conclusion: RSB implementation was associated with reduced postoperative pain scores and decreased opioid consumption in IV morphine equivalency up to 24 h following surgical intervention.

Robotic Anesthesia: A Vision for 2050.

The last 2 decades have brought important developments in anesthetic technology, including robotic anesthesia. Anesthesiologists titrate the administration of pharmacological agents to the patients' physiology and the needs of surgery, using a variety of sophisticated equipment (we use the term "pilots of the human biosphere"). In anesthesia, increased safety seems coupled with increased technology and innovation. This article gives an overview of the technological developments over the past decades, both in terms of pharmacological and mechanical robots, which have laid the groundwork for robotic anesthesia: target-controlled drug infusion systems, closed-loop administration of anesthesia and sedation, mechanical robots for intubation, and the latest development in the world of communication with the arrival of artificial intelligence (AI)-derived chatbots are presented.

Beyond the Echo: The Evolution and Revolution of Ultrasound in Anesthesia.

This article explores the evolving role of ultrasound technology in anesthesia. Ultrasound emerged decades ago, offering clinicians noninvasive, economical, radiation-free, and real-time imaging capabilities. It might seem that such an old technology with apparent limitations might have had its day, but this review discusses both the current applications of ultrasound (in nerve blocks, vascular access, and airway management) and then, more speculatively, shows how integration of advanced ultrasound modalities such as contrast-enhanced imaging with virtual reality (VR), or nanotechnology can alter perioperative patient care. This article will also explore the potential of robotics and artificial intelligence (AI) in augmenting ultrasound-guided anesthetic procedures and their implications for medical practice and education.

The ITAG Spinal Simulator (ISS): A New Simulator for Difficult Lumbar Punctures.

Lumbar punctures present a specific challenge in various medical specialties; appropriate simulators need to take into account the specific technical difficulties related to a realistic patient population, but currently fail to address the variety of anatomical differences seen in practice. We interviewed several leaders in the field of anesthesiology with extensive experience in lumbar puncture procedures, subsequently developing a more realistic training simulator. This novel simulator was built using silicone-based materials and advanced 3D-printing techniques, specifically tailored to be capable of mimicking a variety of patient populations without having to dispose of essential components after each use. Two Anesthesiologists with at least 20 years of experience were asked to perform several spinal tap procedures. Following testing, experts rated the simulator based on its procedural realism, usefulness in improving skill set, and overall simulation efficacy.The gathered validation outcomes based on the questionnaire evaluations completed by experts show excellent preliminary results, with an overall mean score of 4.8 out of 5 (96%). These preliminary results highlight the potential for the simulator's application as a tool to improve medical simulation education and future patient outcomes.

Utilizing Deep Learning to Identify an Ultrasound-guided Nerve Block Target Zone.

Ultrasound guided nerve blocks are increasingly being used in perioperative care as a means of safely delivering analgesia. Unfortunately, identifying nerves in ultrasound images presents a challenging task for novice anesthesiologists. Drawing from online resources, here we attempted to address this issue by developing a deep learning algorithm capable of automatically identifying the transversus abdominis plane region in ultrasound images. Training of our dataset was done using the U-Net architecture and artificial augmentation was done to optimize our training dataset. The Dice score coefficient was used to evaluate our model, with further evaluation against a test set composed of manually drawn labels from a pool of (n=10) expert anesthesiologists.Across all labelers the model achieved a global Dice score of 73.31% over the entire test set. These preliminary results highlight the potential effectiveness of this model as a future ultrasound decision support system in the field of anesthesia.

Ultrasound Calculation of Fat Volume for Liposuction: A Clinical Software Validation.

BACKGROUND: Fat manipulation procedures such as liposuction contain a degree of subjectivity primarily guided by the surgeon's visual or tactile perception of the underlying fat. Currently, there is no cost-effective, direct method to objectively measure fat depth and volume in real time. OBJECTIVES: Utilizing innovative ultrasound-based software, the authors aimed to validate fat tissue volume and distribution measurements in the preoperative setting. METHODS: Eighteen participants were recruited to evaluate the accuracy of the new software. Recruited participants underwent ultrasound scans within the preoperative markings of the study area before surgery. Ultrasound-estimated fat profiles were generated with the in-house software and compared directly with the intraoperative aspirated fat recorded after gravity separation. RESULTS: Participants' mean age and BMI were 47.6 (11.3) years and 25.6 (2.3) kg/m2, respectively. Evaluation of trial data showed promising results following the use of a Bland Altman agreement analysis. For the 18 patients and 44 volumes estimated, 43 of 44 measurements fell within a confidence interval of 95% when compared with the clinical lipoaspirate (dry) volumes collected postsurgery. The bias was estimated at 9.15 mL with a standard deviation of 17.08 mL and 95% confidence interval between -24.34 mL and 42.63 mL. CONCLUSIONS: Preoperative fat assessment measurements agreed significantly with intraoperative lipoaspirate volumes. The pilot study demonstrates, for the first time, a novel companion tool with the prospect of supporting surgeons in surgical planning, measuring, and executing the transfer of adipose tissues.

Clinical Performance of Decision Support Systems in Anesthesia, Intensive Care, and Emergency Medicine: A Systematic Review and Meta-Analysis.

BACKGROUND: Medical technology is expanding at an alarming rate, with its integration into health care often reflected by the constant evolution of best practices. This rapid expansion of available treatment modalities, when coupled with progressively increasing amounts of consequential data for health care professionals to manage, creates an environment where complex and timely decision-making without the aid of technology is inconceivable. Decision support systems (DSSs) were, therefore, developed as a means of supporting the clinical duties of health care professionals through immediate point-of-care referencing. The integration of DSS can be especially useful in critical care medicine, where the combination of complex pathologies, the multitude of parameters, and the general state of patients require swift informed decision-making. The systematic review and meta-analysis were performed to evaluate DSS outcomes compared to the standard of care (SOC) in critical care medicine. METHODS: This systematic review and subsequent meta-analysis were performed after the EQUATOR networks Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA). We systematically explored PubMed, Ovid, Central, and Scopus for randomized controlled trials (RCTs) from January 2000 to December 2021. The primary outcome of this study was to evaluate whether DSS is more effective than SOC practice in critical care medicine within the following disciplines: anesthesia, emergency department (ED), and intensive care unit (ICU). A random-effects model was used to estimate the effect of DSS performance, with 95% confidence intervals (CIs) in both continuous and dichotomous results. Outcome-based, department-specific, and study-design subgroup analyses were performed. RESULTS: A total of 34 RCTs were included for analysis. In total, 68,102 participants received DSS intervention, while 111,515 received SOC. Analysis of the continuous (standardized mean difference [SMD], -0.66; 95% CI [-1.01 to -0.30]; P < .01) and binary outcomes (odds ratio [OR], 0.64; 95% CI, [0.44-0.91]; P < .01) was statistically significant and suggests that health interventions are marginally improved with DSS integration in comparison to SOC in critical care medicine. Subgroup analysis in anesthesia (SMD, -0.89; 95% CI, [-1.71 to -0.07]; P < .01) and ICU (SMD, -0.63; 95% CI [-1.14 to -0.12]; P < .01) were deemed statistically supportive of DSS in improving outcome, with evidence being indeterminate in the field of emergency medicine (SMD, -0.24; 95% CI, [-0.71 to 0.23]; P < .01). CONCLUSIONS: DSSs were associated with a beneficial impact in critical care medicine on a continuous and binary scale; however, the ED subgroup was found to be inconclusive. Additional RCTs are required to determine the effectiveness of DSS in critical care medicine.

Description of a Novel Web-Based Liposuction System to Estimate Fat Volume and Distribution.

BACKGROUND: Preoperative planning for liposuction is vital to ensure safe practice and patient satisfaction. However, current standards of fat assessment before surgery are guided by subjective methods such as visual inspection, skin-pinch tests, and waist circumference measurements. OBJECTIVES: This study aimed to develop an inexpensive software-based tool that utilizes ultrasound (US) imaging and an online platform to accurately simulate regional subcutaneous adipose tissue (SAT) distribution and safe volume estimation for liposuction procedures. METHODS: The authors present a web-based platform with integrated 2-dimensional (2D) and 3-dimensional (3D) simulations of SAT to support liposuction planning and execution. SAT-Map was constructed using multiple sub-applications linked with the python framework programming language (Wilmington, DE). RESULTS: The SAT-Map interface provides an intuitive and fluid means of generating patient-specific models and volumetric data. To further accommodate this, an operational manual was prepared to achieve consistent visualization and examination of estimated SAT content. The system currently supports static 2D heatmap simulation and 3D interactive virtual modelling of the SAT distribution. Supplementary clinical studies are needed to evaluate SAT-Map's clinical performance and practicality. CONCLUSIONS: SAT-Map revolutionizes the concept of preoperative planning for liposuction by developing the first combined web-based software that objectively simulates fat distribution and measures safe liposuction volume. Our software approach presents a cost-efficient, accessible, and user-friendly system offering multiple advantages over current SAT assessment modalities. The immediacy of clinically accurate 3D virtual simulation provides objective support to surgeons towards improving patient conversation, outcomes, and satisfaction in liposuction procedures.

Fluctuating NMDA Receptor Subunit Levels in Perirhinal Cortex Relate to Their Dynamic Roles in Object Memory Destabilization and Reconsolidation.

Reminder cues can destabilize consolidated memories, rendering them modifiable before they return to a stable state through the process of reconsolidation. Older and stronger memories resist this process and require the presentation of reminders along with salient novel information in order to destabilize. Previously, we demonstrated in rats that novelty-induced object memory destabilization requires acetylcholine (ACh) activity at M1 muscarinic receptors. Other research predominantly has focused on glutamate, which modulates fear memory destabilization and reconsolidation through GluN2B- and GluN2A-containing NMDARs, respectively. In the current study, we demonstrate the same dissociable roles of GluN2B- and N2A-containing NMDARs in perirhinal cortex (PRh) for object memory destabilization and reconsolidation when boundary conditions are absent. However, neither GluN2 receptor subtype was required for novelty-induced destabilization of remote, resistant memories. Furthermore, GluN2B and GluN2A subunit proteins were upregulated selectively in PRh 24 h after learning, but returned to baseline by 48 h, suggesting that NMDARs, unlike muscarinic receptors, have only a temporary role in object memory destabilization. Indeed, activation of M1 receptors in PRh at the time of reactivation effectively destabilized remote memories despite inhibition of GluN2B-containing NMDARs. These findings suggest that cholinergic activity at M1 receptors overrides boundary conditions to destabilize resistant memories when other established mechanisms are insufficient.