Anaesthesia Critical Care & Pain Medicine最新文献

Background

Postoperative complications, particularly respiratory complications, are of significant clinical concern in patients undergoing elective thoracic surgery. Dexamethasone (DXM), commonly administered to prevent postoperative nausea and vomiting (PONV), has potential anti-inflammatory effects that might be beneficial in reducing these complications. We aimed to investigate whether intraoperative DXM administration could mitigate the occurrence of respiratory complications following elective thoracic surgery.

Methods

We conducted a single-center observational study, including patients who underwent elective thoracic surgery from 2012 to 2020. The primary outcome was the onset of acute respiratory failure within 7 days post-surgery. Secondary outcomes encompassed other postoperative complications, duration of hospital stay, and mortality within 30 days post-surgery. An overlap propensity score analysis was employed to estimate the treatment effect.

Results

We included 1,247 adult patients, 897 who received dexamethasone (DXM) and 350 who served as controls. Intraoperative dexamethasone administration was associated with a significant reduction in respiratory complications with an adjusted relative risk (RR) of 0.65 (95% CI: 0.43−0.97). There was also a significant decline in composite infectious criteria with an adjusted RR of 0.76 (95% CI: 0.63−0.93). Cardiac complications were also assessed as a composite criterion, and a significant reduction was observed (adjusted RR, 0.68; 95% CI, 0.51−0.9). However, there were no association with mechanical complications, mortality within 30 days (adjusted RR of 0.43, 95% CI: 0.17–1.09) or in the length of hospital stay (adjusted RR of 0.85, 95% CI: 0.71–1.02).

Conclusions

Dexamethasone administration was associated with a reduction in postoperative respiratory complications. Further prospective studies are needed to confirm these findings.

Background

Reporting and analysis of adverse events (AE) is associated with improved health system learning, quality outcomes, and patient safety. Manual text analysis is time-consuming, costly, and prone to human errors. We aimed to demonstrate the feasibility of novel machine learning and natural language processing (NLP) approaches for early predictions of adverse events and provide input to direct quality improvement and patient safety initiatives.

Methods

We used machine learning to analyze 9559 continuously reported AE by clinicians and healthcare systems to the French National Health accreditor (HAS) between January 1, 2009, and December 31, 2020 . We validated the labeling of 135,000 unique de-identified AE reports and determined the associations between different system's root causes and patient consequences. The model was validated by independent expert anesthesiologists.

Results

The machine learning (ML) and Artificial Intelligence (AI) model trained on 9559 AE datasets accurately categorized 8800 (88%) of reported AE. The three most frequent AE types were “difficult orotracheal intubation” (16.9% of AE reports), “medication error” (10.5%), and “post-induction hypotension” (6.9%). The accuracy of the AI model reached 70.9% sensitivity, 96.6% specificity for “difficult intubation”, 43.2% sensitivity, and 98.9% specificity for “medication error.”

Conclusions

This unsupervised ML method provides an accurate, automated, AI-supported search algorithm that ranks and helps to understand complex risk patterns and has greater speed, precision, and clarity when compared to manual human data extraction. Machine learning and Natural language processing (NLP) models can effectively be used to process natural language AE reports and augment expert clinician input. This model can support clinical applications and methodological standards and used to better inform and enhance decision-making for improved risk management and patient safety.

Trial Registration

The study was approved by the ethics committee of the French Society of Anesthesiology (IRB 00010254-2020-20) and the CNIL (CNIL: 118 58 95) and the study was registered with ClinicalTrials.gov (NCT: NCT05185479).

Discussions of the environmental impacts of general anesthetics have focused on greenhouse gas (GHG) emissions from inhaled agents, with those of total intravenous anesthesia (TIVA) recently coming to the forefront. Clinical experts are calling for the expansion of research toward life cycle assessment (LCA) to comprehensively study the impact of general anesthetics. We provide an overview of proposed environmental risks, including direct GHG emissions from inhaled anesthetics and non-GHG impacts and indirect GHG emissions from propofol. A practical description of LCA methodology is also provided, as well as how it applies to the study of general anesthesia. We describe available LCA studies comparing the environmental impacts of a lower carbon footprint inhaled anesthetic, sevoflurane, to TIVA/propofol and discuss their life cycle steps: manufacturing, transport, clinical use, and disposal. Significant hotspots of GHG emission were identified as the manufacturing and disposal of sevoflurane and use (attributed to the manufacture of the required syringes and syringe pumps) for propofol. However, the focus of these studies was solely on GHG emissions, excluding other environmental impacts of wasted propofol, such as water/soil toxicity. Other LCA gaps included a lack of comprehensive GHG emission estimates related to the manufacturing of TIVA plastic components, high-temperature incineration of propofol, and gas capture technologies for inhaled anesthetics. Considering that scarce LCA evidence does not allow for a definite conclusion to be drawn regarding the overall environmental impacts of sevoflurane and TIVA, we conclude that current anesthetic practice involving these agents should focus on patient needs and established best practices as more LCA research is accumulated.

Background

Adenotonsillectomy is often curative for pediatric obstructive sleep apnea, yet children remain at high risk of respiratory complications in the postoperative period. We sought to determine the incidence and risk factors for respiratory depression and airway obstruction, as well as clinically apparent respiratory events in the post-anesthesia care unit (PACU) in high-risk children after adenotonsillectomy.

Methods

In this prospective cohort study, we enrolled 60 high-risk children having adenotonsillectomy. Our primary outcome was respiratory depression and airway obstruction in the PACU measured using a noninvasive respiratory volume monitor (RVM) and defined by episodes of predicted minute ventilation less than 40% for at least 2 min. We measured clinically apparent respiratory events using continuous observation by trained study staff.

Results

The median (range) age of our sample was 4 years (1, 16) and 27 (45%) were female. Black and Hispanic race children comprised 80% (n = 48) of our cohort. Thirty-nine (65%) had at least one episode of PACU respiratory depression or airway obstruction measured using the RVM, while only 21 (35%) had clinically apparent respiratory events. Poisson regression demonstrated the following associations with an increase in episodes of respiratory depression and airway obstruction: BMI Z-score less than −1 (estimate 3.91; [95%CI 1.49–10.23]), BMI Z-score 1–2 (estimate 2.04; [1.20–3.48]), and two or more comorbidities (estimate 1.96; [1.11–3.46]).

Conclusions

Respiratory volume monitoring in the immediate postoperative period after pediatric high-risk adenotonsillectomy identifies impaired ventilation more frequently than is clinically apparent.

Background

Whether the optimization of cerebral oxygenation based on regional cerebral oxygen saturation (rSO₂) monitoring reduces the occurrence of cerebral ischemic lesions is unknown.

Methods

This multicenter, randomized, controlled trial recruited adults admitted for scheduled carotid endarterectomy. Patients were randomized between the standard of care or optimization of cerebral oxygenation based on rSO₂ monitoring using near-infrared spectroscopy. In the intervention group, in case of a decrease in rSO₂ in the intervention, the following treatments were sequentially recommended: (1) increasing oxygenotherapy, (2) reducing the tidal volume, (3) legs up-raising, (4) performing a fluid challenge and (5) initiating vasopressor support. The primary endpoint was the number of new cerebral ischemic lesions detected using magnetic resonance imaging pre- and postoperatively. Secondary endpoints included new neurological deficits and mortality on day 120 after surgery.

Results

Among the 879 patients who were randomized, 665 (75.7%) were men. There was no statistically significant difference between groups for the mean number of new cerebral ischemic lesions per patient up to 3 days after surgery: 0.35 (±1.05) in the standard group vs. 0.58 (±2.83), in the NIRS group; mean difference, 0.23 [95% CI, −0.06 to 0.52]; estimate, 0.22 [95% CI, −0.06 to 0.50]. New neurological deficits up to day 120 after hospital discharge were not different between the groups: 15 (3,39%) in the standard group vs. 42 (5,49%) in the NIRS group; absolute difference, 2,10 [95% CI, −0,62 to 4,82]. There was no significant difference between groups for the median [IQR] hospital length of stay: 4.0 [4.0–6.0] in the standard group vs. 5.0 [4.0–6.0] in the NIRS group; mean difference, −0.11 [95% CI, −0.65 to 0.44]. The mortality rate on day 120 was not different between the standard group (0.68%) vs. the NIRS group (0.92%); absolute difference = 0.24% [95% CI, −0.94 to 1.41].

Conclusions

Among patients undergoing carotid endarterectomy, optimization of cerebral oxygenation based on rSO₂ did not reduce the occurrence of cerebral ischemic lesions postoperatively compared with controlled hypertensive therapy.

Trial registration

ClinicalTrials.gov identifier: NCT01415648.

Background

To date, there is no instrument to adequately assess self-reported quality of recovery (QoR) in the post-anesthesia care unit (PACU). We previously developed the QoR-PACU, a 13-item questionnaire specifically applicable to the PACU. The feasibility, acceptance, and validity of the QoR-PACU were promising. However, measures of reliability were slightly lower than expected.

Methods

We modified the QoR-PACU and evaluated its psychometric properties in a cohort of adult patients scheduled for non-cardiac surgery with general anesthesia. The modified QoR-PACU (termed QoR-PACU₂) was administered before surgery and postoperatively in the PACU at the time of the decision to discharge.

Results

A total of 307 patients were included in the final analysis. Postoperative QoR-PACU₂ sum scores differed across categories of sex, perioperative and surgical risk, and modes of airway management. The duration of anesthesia and surgery, maximum pain intensity and analgesic requirement in the PACU, and length of PACU stay were all inversely correlated with QoR in the PACU. Cronbach’s alpha was 0.70 (95%CI: 0.66–0.75). The intra-class correlation coefficient was 0.86 (95%CI: 0.70–0.94, p < 0.001) for intra-rater reliability (n = 24) and 0.94 (95%CI 0.90 to 0.97, p < 0.001) for inter-rater reliability (n = 31). Cohen’s effect size was 0.68 and the standardized response mean was 0.57.

Conclusion

The QoR-PACU₂ assesses self-reported QoR after surgery in the PACU. Measures of feasibility, validity, and reliability were consistently high. Measures of responsiveness were moderate, which might be attributable to the heterogeneity of the study population. Future studies should include aspects of ethnicity and cross-cultural applicability.