Anesthesiology and Perioperative Science最新文献

Purpose

Submaximal exercise tests (SET) are an easier to conduct and less physically demanding alternative to cardiopulmonary exercise testing for assessment of pre-operative fitness. Assessment of heart rate recovery (HRR) following SETs offers an easily obtained marker of vagal reactivation and sympathetic withdrawal and therefore provides an indication of an individual’s fitness. This study sought to assess the reproducibility of HRR across different workloads and modalities of SET.

Methods

Thirty-four healthy volunteers were recruited to undergo two SETs at 40% and 60% of their predicted maximal workload. A second group of thirty-one healthy volunteers were recruited to undergo three SETs of differing modalities; Cycle ergometry, Step and Shuttle Walk tests. HRR was quantified using the conventional indices HRR1 and HRR2 (calculated as heart rate (HR) on exercise cessation minus HR at 1 and 2 min of rest) and a novel area under the HRR vs. time curve (HRR_AUC) method. Reproducibility of results was assessed using intra-class correlation coefficient (ICC) and limits of agreements.

Results

The results showed that HRR1 and HRR2 were poorly reproducible across differing workloads and exercise modalities (ICC < 0.45 for all comparisons) whereas HRR_AUC proved to be at least moderately reproducible (ICC > 0.52 for all comparisons).

Conclusions

These results suggest that HRR_AUC may be a superior way of quantifying HRR following SETs, adding objectivity to SET results. Quantifying HRR_AUC could prove to have useful clinical applications for pre-operative risk assessment, assessing fitness to undergo treatment and monitoring disease progression.

Mechanical ventilation is an important life-saving therapy for general anesthesia and critically ill patients, but ventilation itself may be accompanied with lung injury. Ventilator-induced lung injury (VILI) exacerbates pre-existing lung disease, leading to poor clinical outcomes. Especially for patients undergoing cardiothoracic surgery and receiving one-lung ventilation (OLV), optimizing the parameters of OLV is closely related to their prognosis. It is not clear what is the best strategy to minimize VILI through adjusting ventilation parameters, including tidal volume, positive end expiratory pressure and driving pressure, etc. Different parameters, in combination, are responsible for VILI. Protective ventilation strategies, aiming to reduce postoperative pulmonary complications, have been discussed in many clinical studies and different opinions have been raised. This review addresses the pathogenesis of VILI and focus on the OLV management and better protective OLV strategies during thoracic surgery.

Pain in the postoperative period is a common patient experience that can subsequently lead to other postoperative complications if not managed appropriately. While opioids are a common pharmacologic tool for managing pain, there are risks associated with liberal opioid use. Multimodal analgesic strategies, however, can adequately manage postoperative pain and minimize the risks associated with opioids. In this review, common pharmacological treatments for multimodal analgesia will be reviewed for efficacy, risks, and benefits, including gabapentinoids, opioids, alpha-2 agonists, ketamine, Non-steroidal anti-inflammatory drugs (NSAIDs) and corticosteroids. While this may not be a comprehensive list of medication options, it represents some of the most commonly used pharmacologic techniques for managing pain in the perioperative period. In addition, newer regional anesthetic techniques will be discussed to review their efficacy, risks, and benefits as well. The goal of this review is to summarize the various options for a multimodal analgesic protocol that we encourage providers to utilize when managing postoperative pain to facilitate conservative opioid usage and improve patient outcomes overall.

Graphical Abstract

Computer-aided drug design (CADD) has emerged as a highly effective and indispensable tool for streamlining the drug discovery process, leading to significant reductions in cost and time. The integration of CADD with machine learning (ML) and deep learning (DL) technologies further enhances its potential and promises novel advancements in the field. In this article, we provide a review of the computational methods employed in the development of novel anesthetics, outlining their respective advantages and limitations. These techniques have demonstrated their utility across various stages of drug discovery, encompassing the exploration of target-ligand interactions, identification and validation of new binding sites, de novo drug design, evaluation and optimization of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties in lead compounds, as well as prediction of adverse effects. Through an in-depth exploration of computational approaches and their applications, this article aims to help relevant researchers develop safer and more effective anesthetic drugs.

Purpose

The current study was designed to investigate the analgesic effect of esketamine on patients underwent thoracoscopic surgery and the underlying mechanism.

Methods

In this randomized, double blind, placebo-controlled study, 60 patients scheduled to undergo thoracoscopic lobectomy or segmentectomy were randomized to two groups to receive esketamine (group ESK) or saline (group SAL), respectively. 0.25 mg·kg⁻¹ esketamine was given in group ESK for induction of anesthesia, and 0.12 mg·kg⁻¹·h⁻¹ esketamine for intraoperative maintenance. Group SAL received an equal volume of saline. The primary outcomes were the visual analogue scale (VAS) pain scores at rest and deep cough state which evaluated at departure from post-anesthesia care unit (PACU) (T1), 6 h, 24 h and 48 h after surgery (T2–T4). The secondary outcomes included the levels of white blood cell (WBC) count, absolute neutrophil count (ANC), interleukin-6 (IL-6), procalcitonin (PCT), anxiety/depression scores at T3, oxygen saturation (SpO2), and adverse reactions.

Results

Esketamine significantly decreased both rest and cough VAS pain scores at T1, and rest pain scores at T1, T2 and T4. Patients in ESK group had significantly lower WBC and ANC levels than SAL group, while the alteration of IL-6 and PCT levels between groups showed no significance. The anxiety scores of patients in both groups were significantly decreased after surgery. However, the depression scores of patients in ESK group did not decrease after surgery when compared with the preoperation. The postoperative SpO2 and the incidence of adverse reaction including postoperative nausea, vomiting, dizziness and dissociative symptom showed no significant difference between two groups (p > 0.05).

Conclusion

Esketamine can alleviate the acute postoperative pain of patients undergoing thoracoscopic surgery without increasing adverse reactions, and the underlying mechanism may be associated with the reduction of postoperative inflammation.

Trial registration

Registered at Chinese Clinical Trial Registry on February 7, 2022 (ChiCTR 2200056524).

Graphical Abstract

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Most people infected with the virus experience mild to moderate respiratory illness. However, some might become seriously ill and may develop acute respiratory distress syndrome (ARDS), thus requiring non-invasive or invasive mechanical ventilation. Furthermore, COVID-19 disease can involve also other organs and systems, causing several extra-pulmonary manifestations and, thus, negatively influencing the patient’s outcome. Imaging studies play a pivotal role in the monitoring of severely ill patients, especially those admitted to the intensive care unit (ICU), who can develop several potentially life-threatening complications, both from the infection itself and the mechanical supporting system. This widespread utility of imaging modalities calls for a deeper understanding of potential radiologic findings in this disease and the need for multidisciplinary collaboration between radiologists and anesthesiologists to provide actionable guidance to appropriate interventions under such conditions.