BMC Anesthesiology最新文献

Background: To protect patients during anesthesia, difficult airway management is a serious issue that needs to be carefully planned for and carried out. Machine learning prediction tools have recently become increasingly common in medicine, frequently surpassing more established techniques. This study aims to utilize machine learning techniques on predictive parameters for challenging airway management.

Methods: This study was cross-sectional. The Shahid Beheshti University of Medical Sciences in Iran's Loghman Hakim and Shahid Labbafinezhad hospitals provided 622 records in total for analysis. Using the forest of trees approach and feature importance, important features were chosen. The Synthetic Minority Oversampling Technique (SMOTE) and repeated edited nearest neighbor under-sampling were used to balance the data. Using Python and 10-fold cross-validation, seven machine learning algorithms were assessed: Logistic Regression, Support Vector Machines (SVM), Random Forest (INFORMATION-GAIN and GINI-INDEX), Decision Tree, and K-Nearest Neighbors (KNN). Metrics like F-measure, AUC, Recall, Accuracy, Specificity, and Precision were used to evaluate the performance of the model.

Results: Twenty-four important features were chosen from the original 32 features. The under-sampling strategy produced better results than SMOTE. Among the algorithms, KNN (Euclidean, Minkowski) had better performance than other algorithms. The highest values ​​for accuracy, precision, recall, F-measure, and AUC were obtained at 0.87, 0.88, 0.82, 0.85, and 0.87, respectively.

Conclusion: Algorithms for machine learning provide insightful information for anticipating challenging airway management. By making it possible to forecast airway difficulties more accurately, these techniques can potentially improve clinical practice and patient outcomes.

Artificial Intelligence (AI), especially Machine Learning (ML), has developed systems capable of performing tasks that require human intelligence. In anesthesiology and other medical fields, AI applications can improve the precision and efficiency of daily clinical practice, and can also facilitate a personalized approach to patient care, which can lead to improved outcomes and quality of care. ML has been successfully applied in various settings of daily anesthesiology practice, such as predicting acute kidney injury, optimizing anesthetic doses, and managing postoperative nausea and vomiting. The critical evaluation of ML models in healthcare is crucial to assess their validity, safety, and clinical applicability. Evaluation metrics allow an objective statistical assessment of model performance. Tools such as Shapley Values (SHAP) help interpret how individual variables contribute to model predictions. Transparency in reporting is key in maintaining trust in these technologies and to ensure their use follows ethical principles, aiming to reduce safety concerns while also benefiting patients. Understanding evaluation metrics is essential, as they provide detailed information on model performance and their ability to discriminate between individual class rates. This article offers a comprehensive framework in assessing the validity, applicability, and limitations of models, guiding responsible and effective integration of ML technologies into clinical practice. A balance between innovation, patient safety and ethical considerations must be pursued.

Background: Disorientation is an early indicator of developing postoperative delirium (POD), which is associated with increased mortality and cognitive decline. The well-established "Confusion-Assessment-Method-for-Intensive-Care-Unit" (CAM-ICU) for diagnosing POD in intubated patients cannot make use of the feature 'disorientation', as this requires verbal communication. Other tools such as the 4AT test for disorientation but are not established in ICU settings. We therefore combined test-variables of the CAM-ICU (level of consciousness, fluctuating mental status and inattention) with verbal testing for disorientation to develop and enhance diagnostic accuracy of the "Confusion Assessment Method for Intermediate Care Unit" (CAM-IMC). In the present study we describe the development and the evaluation of the diagnostic accuracy of the CAM-IMC.

Methods: We conducted a prospective cohort-study to develop and evaluate the diagnostic accuracy of the CAM-IMC and disorientation for diagnosing POD in non-intubated patients undergoing elective cardiac surgery. All patients were eligible during data collection period. Exclusion criteria were preexisting brain-organic disease, age < 50 years, preoperative intubation, and insufficient language skills. Patients were assessed for POD using the CAM-IMC as the index-test by two independent examiners over three postoperative days. Reference-testing was conducted by experienced reference-raters. The primary outcome was the diagnostic test-performance.

Results: Among 178 eligible patients, 624 paired observations were completed with 155 patients. Of these, 9% experienced POD. Sensitivity and specificity were 0.96 (CI-95%: 0.87-1.00) and 0.94 (CI-95%: 0.92-0.96), respectively. Area-Under-the-Receiver-Operating-Characteristic-Curve (AUROC; equivalent to c-statistic) for CAM-IMC with a cut-off at three points was 0.95 (CI-95%: 0.93-0.98). The interrater reliability was 0.80 (CI-95%: 0.69-0.91).

Conclusion: The CAM-IMC demonstrates excellent test performance for diagnosing POD in non-intubated patients by combining features of the CAM-ICU with 'disorientation'. Given an aging community with an increasing delirium risk, the CAM-IMC provides a highly structured assessment tool for POD. It enables early and accurate detection of delirium, which is critical for timely intervention and improved patient outcomes. The CAM-IMC appears to be a useful tool to be implemented in units for not-intubated patients and seems to be the perfect match where the CAM-ICU is already in use for monitoring POD.

Trial registration: DRKS00026980 (German registry of clinical studies).

Introduction: Endotracheal intubation can be difficult or even fail under certain patient and anaesthesiologist conditions. During the COVID-19 pandemic a country-wide lockdown policy was enforced in Thailand which stipulated that anaesthesiologists wear personal protective equipment, powered air purifying respirator, or goggles and surgical/N95 mask during the intubation procedure. Thus, an anaesthesiologist's vision is restricted and grip on the equipment less sure. Under these conditions, the incidence of difficult intubation was expected to increase.

Methods: This time-series study was based on the aggregated age- and sex-standardized monthly incidence of difficult intubation among all intubated patients whose data were recorded in the national insurance claims database and among patients recorded in the records of a university hospital from January 2018 to September 2022. Changes in incidence of difficult intubation following the implementation of a lockdown policy from 26 March 2020 during the COVID-19 pandemic were explored using negative binomial regression and interrupted linear regression time-series analysis.

Results: Data of 922,274 individuals in the national database and 95,457 individuals in the university database were retrieved. The overall incidence of difficult intubation in both settings dropped by 25% following lockdown, significantly so in the national database (p < 0.001). At the point of interruption, a significant drop in level was evident in the national data (of 1.682 per thousand per month, P = 0.003) and a non-significant drop at the university level (of 1.118 per thousand per month, P = 0.304).

Discussion: The decreased incidence of difficult intubation during the lockdown period was contrary to expectation but might be related to the deployment solely of anaesthesiologists and more experienced anaesthetic staff using videolaryngoscopes during lockdown following the recommendation for intubation during respiratory disease pandemics.

Background: Postoperative sore throat is a frequent and distressing complication caused by airway instrumentation during general anesthesia. The discomfort can lead to immediate distress, delayed recovery and reduce patient satisfaction. The objective of this study was to determine the effectiveness of preoperative ketamine gargle on the occurrence of postoperative sore throat among adult patients who underwent surgery under general anesthesia with endotracheal tube.

Method: PubMed, Cochrane Library, Google Scholar, and World Clinical Trial Registry were searched to find the eligible randomized control trials comparing the effect of preoperative ketamine gargle and placebo gargle on the occurrence of postoperative sore throat after surgery with endotracheal tube in adult patients. We utilized Review Manager Version 5.4 to perform statistical analyses. Cochrane risk of bias tool for randomized control trials was used to assess the risk of bias of included studies. We explored heterogeneity using the I² test. In addition to this, subgroup analysis, and sensitivity analysis was conducted to confirm the robustness of findings. The risk of publication bias was tested using funnel plot Pooled risk ratio along with 95% confidence interval (CI) was used to analyze the outcome.

Result: In the present systematic review and metanalysis, seventeen [17] randomized controlled trials (RCTs) with 1552 participants were included. Compared with placebo, preoperative ketamine gargle is effective to reduce postoperative sore throat (RR = 0.48; 95%CI [0.45, 0.52] in adult patients undergoing surgery under general anesthesia with endotracheal tube.

Conclusion: Preoperative ketamine gargle before induction of general anesthesia is effective to reduce the occurrence of postoperative sore throat in adult patients undergoing surgery under general anesthesia with an endotracheal tube. Further studies with large sample size, better study quality and optimal reporting could be conducted to determine the long-term efficacy and safety of ketamine gargle in different surgical populations.

Background: Vasopressors are effective in managing perioperative hypotension in high-risk parturients undergoing Caesarean section (CS). Nevertheless, the optimal vasopressor for addressing hypotension induced by neuraxial anesthesia remains a subject of investigation.

Methods: We compared hypotension episodes among high-risk parturients who received ephedrine, noradrenaline, or phenylephrine by searching four electronic databases and reviewing the relevant references. Inclusion criteria encompassed randomized controlled trials directly comparing two or more vasopressors in the context of managing hypotension in high-risk parturients undergoing neuraxial anesthesia for CS. A network meta-analysis was performed using fixed-effects and Bayesian random-effects models.

Results: We analyzed 13 trials involving 1,262 patients. While our direct and indirect comparisons revealed no reveal statistically significant differences in the number of hypotensive episodes among patients treated with different vasopressors, vasopressors were hierarchically ranked. Phenylephrine (Rank of the best choice = 0.81) exhibited the highest effectiveness in preventing hypotension, followed by ephedrine (Rank of the best choice = 0.10) and noradrenaline (Rank of the best choice = 0.09). Bradycardia occurrence was higher in patients administered phenylephrine compared to those given noradrenaline (risk ratio [RR]: 0.23; 95% confidence interval [CI]: 0.03 to 0.85) or ephedrine (RR: 0.01; 95% CI: 0.00 to 0.12). Notably, patients treated with phenylephrine or noradrenaline experienced reduced occurrences of nausea or vomiting compared to those who received ephedrine (RR: 0.37; 95% CI: 0.19 to 0.59 for phenylephrine and RR: 0.28; 95% CI: 0.10 to 0.75 for noradrenaline). Regarding fetal outcomes, no significant differences were noted between noradrenaline and phenylephrine. Overall norepinephrine in maternal outcomes may be more favorable.

Conclusions: Our findings suggest the potential advantages of phenylephrine for reducing hypotensive episodes in high-risk parturients undergoing CS. Noradrenalin may emerge as an alternative, particularly for women at high risk of caesarean delivery.

Trial registration: This systematic review was registered at PROSPERO (CRD42023397259).

Backgrounds: Anticipating difficult laryngoscopy is crucial for preoperative assessment, especially for patients with cervical spondylosis. Radiological assessment has become essential for improving airway management safety. This research introduces novel radiological indicators from lateral cervical X-ray in the extended head position proposed to enhance the accuracy of predicting difficult laryngoscopy.

Methods: A prospective cohort study included 422 patients scheduled for elective cervical spine surgery. The Cormack-Lehane grades I and II were categorized as "easy laryngoscopy group", while grades III and IV were labeled "difficult laryngoscopy group". Demographic data, conventional bedside indicators including inter-incisor gap (IIG), neck circumference (NC), thyromental distance, the upper lip bite test (ULBT), and 4 radiological indicators including Mandibular Length, Laryngeal Height, the Larynx-Mandibular Angle Test (LMAT) and Larynx-Mandibular Height Test (LMHT) were analyzed comparatively. A binary logistic regression model was developed to identify independent predictive factors. The predictive value of the indicators was evaluated with the area under the curve (AUC).

Results: A total of 402 patients were analyzed in the present study. A binary logistic regression model identified IIG, NC, ULBT, and LMAT as the independent indicators associated with difficult laryngoscopy. A novel combined predictive model equation was derived: Ɩ=-0.969 - 1.33×IIG + 0.408×ULBT + 0.201×NC - 0.042×LMAT. The AUC for this composite model was 0.776, exceeding the individual AUC of 0.677 for LMHT.

Conclusion: LMHT and the novel combined predictive model incorporating LMAT are potentially valuable predictors for difficult laryngoscopy in patients with cervical spondylosis.

Trial registration: The study was registered at the Chinese Clinical Trial Registry (ChiCTR2200058361) on April 7, 2022.

Background: The integration of smart glasses with ultrasound technology offers a novel approach to improve the efficiency of radial arterial catheterization. Few studies have investigated the effectiveness of smart glasses in enhancing procedural outcomes in a clinical setting. This study aims to assess whether smart glasses combined with ultrasound can improve the initial success rate of radial artery catheterization compared to traditional ultrasound-guided methods in adults.

Methods: This single-blinded, randomized controlled trial enrolled patients aged 18-70 with American Society of Anesthesiologists physical status I-III, who required radial artery catheterization as part of their procedure under general anesthesia. Patients were randomized 1:1 into the ultrasound group and the smart glasses group. Radial arterial catheterization was carried out by one of six anesthesiologists before general anesthesia. The primary endpoint was the first puncture success rate. Secondary endpoints included hand-eye coordination (measured by head rotations, probe repositioning and needle redirections), operator's satisfaction.

Results: A total of 222 patients were analyzed, with the smart glasses group demonstrating a higher rate of first puncture success compared to the control group (88.3% [98/111] vs. 72.1% [80/111]; P = 0.002; relative risk [RR], 1.23; 95% CI (1.07, 1.40)). Hand-eye coordination improved significantly in the smart glasses group than the control group, including: fewer number of head rotations (0 [0, 0] vs. 3 [2, 6]; P < 0.001); fewer number of ultrasound probe repositioning (0 [0, 0] vs. 0 [0, 1]; P < 0.001); fewer number of needle redirections (0 [0, 1] vs. 1 [0, 3]; P < 0.001). The proportion of positive satisfaction (81 to 100 points) in the smart glasses group was higher (89.2% [99/111] vs. 69.4% [77/111]; P <  0.001; RR, 1.29; 95% CI (1.12, 1.48)).

Conclusions: The use of smart glasses significantly improved the first puncture success rate, hand-eye coordination ability and operators' satisfaction in radial arterial catheterization.

Trial registration: The study was registered at Chictr.org.cn with the number ChiCTR2400081399 on 29/02/2024.

Background: In reconstructive surgeries, iliac crest bone graft harvesting is commonly preferred. The pain experienced after surgery at the anterior iliac crest (AIC) donor site might be more intense compared to the pain at the primary surgical area where the graft is placed. To address this issue, we defined a novel technique called the anterior iliac block (AIB), which can provide analgesia with lower volumes. In this study, the effect of this technique for AIC bone greft harvesting was evaluated.

Methods: Patients who were operated on and had AIC bone graft harvested included in this retrospective study. The study collected age, height, weight, ASA classification, and duration of surgery, information on the regional anesthesia technique, block performance, postoperative pain severity, opioid consumption, rescue analgesics used in the first postoperative 24 h.

Results: Data from 16 patients were analyzed. The popliteal sciatic block was performed in eight patients, infraclavicular brachial plexus block in four patients, supraclavicular brachial plexus block in one patient, PENG block in one patient, and proximal adductor canal block in two patients two provide analgesia for primary surgery. The median morphine consumption at postoperative 24th hour was 3.5 mg, median NRS score was 1 at postoperative 1st hour, and 0 at postoperative 6th, 12th and 24th hours.

Conclusions: The study findings indicate that the AIB provides adequate analgesia for AIC graft harvesting in the first postoperative 24-hour period. It can be used as an adjuvant to the peripheric nerve block for the primary surgical site.

Trial registration: NCT06295224.