It has been hypothesized that providing deep neuromuscular block (a posttetanic count of 1 or more, but a train-of-four [TOF] count of zero) when compared with moderate block (TOF counts of 1-3) for laparoscopic surgery would allow for the use of lower inflation pressures while optimizing surgical space and enhancing patient safety. We conducted a literature search on 6 different medical databases using 3 search strategies in each database in an attempt to find data substantiating this proposition. In addition, we studied the reference lists of the articles retrieved in the search and of other relevant articles known to the authors. There is some evidence that maintaining low inflation pressures during intra-abdominal laparoscopic surgery may reduce postoperative pain. Unfortunately most of the studies that come to these conclusions give few if any details as to the anesthetic protocol or the management of neuromuscular block. Performing laparoscopic surgery under low versus standard pressure pneumoperitoneum is associated with no difference in outcome with respect to surgical morbidity, conversion to open cholecystectomy, hemodynamic effects, length of hospital stay, or patient satisfaction. There is a limit to what deep neuromuscular block can achieve. Attempts to perform laparoscopic cholecystectomy at an inflation pressure of 8 mm Hg are associated with a 40% failure rate even at posttetanic counts of 1 or less. Well-designed studies that ask the question "is deep block superior to moderate block vis-à-vis surgical operating conditions" are essentially nonexistent. Without exception, all the peer-reviewed studies we uncovered which state that they investigated this issue have such serious flaws in their protocols that the authors' conclusions are suspect. However, there is evidence that abdominal compliance was not increased by a significant amount when deep block was established when compared with moderate neuromuscular block. Maintenance of deep block for the duration of the pneumoperitoneum presents a problem for clinicians who do not have access to sugammadex. Reversal of block with neostigmine at a time when no response to TOF stimulation can be elicited is slow and incomplete and increases the potential for postoperative residual neuromuscular block. The obligatory addition of sugammadex to any anesthetic protocol based on the continuous maintenance of deep block is not without associated caveats. First, monitoring of neuromuscular function is still essential and second, antagonism of deep block necessitates doses of sugammadex of ≥4.0 mg/kg. Thus, maintenance of deep block has substantial economic repercussions. There are little objective data to support the proposition that deep neuromuscular block (when compared with less intense block; TOF counts of 1-3) contributes to better patient outcome or improves surgical operating conditions.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1213/ANE.0000000000000471 | DOI Listing |
Environ Monit Assess
January 2025
Civil Engineering, SRM Institute of Science and Technology, Kattankulathur, 603203, India.
Papermaking wastewater consists of a sizable amount of industrial wastewater; hence, real-time access to precise and trustworthy effluent indices is crucial. Because wastewater treatment processes are complicated, nonlinear, and time-varying, it is essential to adequately monitor critical quality indices, especially chemical oxygen demand (COD). Traditional models for predicting COD often struggle with sensitivity to parameter tuning and lack interpretability, underscoring the need for improvement in industrial wastewater treatment.
View Article and Find Full Text PDFJ Biotechnol
January 2025
Department of Chemical Engineering, University of Massachusetts Lowell, Lowell, MA 01854. Electronic address:
Recombinant adeno-associated viruses (rAAVs) comprise a promising viral vector for therapeutic gene delivery to treat disease. However, the current manufacturing capability of rAAVs must be improved to meet commercial demand. Previously published omics studies indicate that rAAV production through transient transfection triggers antiviral responses and endoplasmic reticulum stress responses in the host cell.
View Article and Find Full Text PDFAlzheimers Dement (N Y)
January 2025
Indiana Alzheimer Disease Research Center and Center for Neuroimaging, Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis Indiana USA.
Introduction: The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.
View Article and Find Full Text PDFJ Gastric Cancer
January 2025
Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Endoscopic submucosal dissection is performed in cases of early gastric cancer, where the risk of lymph node metastasis (LNM) is expected to be negligible, and 12%-21% of these patients are deemed to have undergone non-curative resections based on pathological criteria. In such cases, decisions regarding additional treatments must be made to maximize curability, depending on the anticipated LNM risk. Well-established risk factors for LNM include lymphatic invasion, vascular invasion, deep submucosal invasion, positive vertical margins, and larger tumor size.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, Vietnam.
The field of medical image segmentation powered by deep learning has recently received substantial attention, with a significant focus on developing novel architectures and designing effective loss functions. Traditional loss functions, such as Dice loss and Cross-Entropy loss, predominantly rely on global metrics to compare predictions with labels. However, these global measures often struggle to address challenges such as occlusion and nonuni-form intensity.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!