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The phenomena of residual curarisation and recurarisation after the use of long-acting non-depolarising neuromuscular blocking drugs such as tubocurarine and pancuronium were well recognised 60 years ago. But the incidence seemed to decline with the introduction of atracurium and vecuronium. However, recently there have been an increasing number of reports of residual and recurrent neuromuscular block. Some of these reports are a result of inappropriate doses of rocuronium, sugammadex or both, together with inadequate neuromuscular monitoring. We urge clinicians to review their practice to ensure the highest standards of clinical care when using neuromuscular blocking drugs and reversal agents. This includes the use of quantitative neuromuscular monitoring whenever neuromuscular blocking drugs are administered.
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Bloqueio Neuromuscular , Bloqueadores Neuromusculares , Fármacos Neuromusculares não Despolarizantes , Humanos , Fármacos Neuromusculares não Despolarizantes/efeitos adversos , Androstanóis/efeitos adversos , Rocurônio , Brometo de VecurônioRESUMO
BACKGROUND: Guideline adherence in the medical field leaves room for improvement. Digitalised decision support helps improve compliance. However, the complex nature of the guidelines makes implementation in clinical practice difficult. METHODS: This single-centre prospective study included 204 adult ASA physical status 3-4 patients undergoing elective noncardiac surgery at a German university hospital. Agreement of clearance for surgery between a guideline expert and a digital guideline support tool was investigated. The decision made by the on-duty anaesthetists (standard approach) was assessed for agreement with the expert in a cross-over design. The main outcome was the level of agreement between digital guideline support and the expert. RESULTS: The digital guideline support approach cleared 18.1% of the patients for surgery, the standard approach cleared 74.0%, and the expert approach cleared 47.5%. Agreement of the expert decision with digital guideline support (66.7%) and the standard approach (67.6%) was fair (Cohen's kappa 0.37 [interquartile range 0.26-0.48] vs 0.31 [0.21-0.42], P=0.6). Taking the expert decision as a benchmark, correct clearance using digital guideline support was 50.5%, and correct clearance using the standard approach was 44.6%. Digital guideline support incorrectly asked for additional examinations in 31.4% of the patients, whereas the standard approach did not consider conditions that would have justified additional examinations before surgery in 29.4%. CONCLUSIONS: Strict guideline adherence for clearance for surgery through digitalised decision support inadequately considered patients, clinical context. Vague formulations, weak recommendations, and low-quality evidence complicate guideline translation into explicit rules. CLINICAL TRIAL REGISTRATION: NCT04058769.
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Fidelidade a Diretrizes , Cuidados Pré-Operatórios , Humanos , Estudos Prospectivos , Pessoa de Meia-Idade , Masculino , Feminino , Idoso , Cuidados Pré-Operatórios/métodos , Cuidados Pré-Operatórios/normas , Adulto , Software , Procedimentos Cirúrgicos Eletivos/normas , Sistemas de Apoio a Decisões Clínicas , Estudos Cross-Over , Guias de Prática Clínica como Assunto , Técnicas de Apoio para a Decisão , AlemanhaRESUMO
BACKGROUND: Concept drift and covariate shift lead to a degradation of machine learning (ML) models. The objective of our study was to characterize sudden data drift as caused by the COVID pandemic. Furthermore, we investigated the suitability of certain methods in model training to prevent model degradation caused by data drift. METHODS: We trained different ML models with the H2O AutoML method on a dataset comprising 102,666 cases of surgical patients collected in the years 2014-2019 to predict postoperative mortality using preoperatively available data. Models applied were Generalized Linear Model with regularization, Default Random Forest, Gradient Boosting Machine, eXtreme Gradient Boosting, Deep Learning and Stacked Ensembles comprising all base models. Further, we modified the original models by applying three different methods when training on the original pre-pandemic dataset: (Rahmani K, et al, Int J Med Inform 173:104930, 2023) we weighted older data weaker, (Morger A, et al, Sci Rep 12:7244, 2022) used only the most recent data for model training and (Dilmegani C, 2023) performed a z-transformation of the numerical input parameters. Afterwards, we tested model performance on a pre-pandemic and an in-pandemic data set not used in the training process, and analysed common features. RESULTS: The models produced showed excellent areas under receiver-operating characteristic and acceptable precision-recall curves when tested on a dataset from January-March 2020, but significant degradation when tested on a dataset collected in the first wave of the COVID pandemic from April-May 2020. When comparing the probability distributions of the input parameters, significant differences between pre-pandemic and in-pandemic data were found. The endpoint of our models, in-hospital mortality after surgery, did not differ significantly between pre- and in-pandemic data and was about 1% in each case. However, the models varied considerably in the composition of their input parameters. None of our applied modifications prevented a loss of performance, although very different models emerged from it, using a large variety of parameters. CONCLUSIONS: Our results show that none of our tested easy-to-implement measures in model training can prevent deterioration in the case of sudden external events. Therefore, we conclude that, in the presence of concept drift and covariate shift, close monitoring and critical review of model predictions are necessary.
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COVID-19 , Pandemias , Humanos , COVID-19/epidemiologia , Algoritmos , Mortalidade Hospitalar , Aprendizado de MáquinaRESUMO
Background: The prevalence of neurodegenerative diseases is increasing as is life expectancy with Alzheimer's disease accounting for two-thirds of dementia cases globally. Whether general anesthesia and surgery worsen cognitive decline is still a matter of debate and most likely depending on the interplay of various influencing factors. In order to account for this complexity, Alzheimer's disease animal models have been developed. The Tg2576 model of Alzheimer's disease is a well-established mouse model exhibiting amyloidopathy and age-dependent sex-specific differences in Alzheimer's disease symptomology. Yet, data on anesthesia in this mouse model is scarce and a systematic comparison of vital parameters during anesthesia with wild-type animals is missing. In order to investigate the safety of general anesthesia and changes in vital parameters during general anesthesia in Tg2576 mice, we did a secondary analysis of vital parameters collected during general anesthesia in aged Tg2576 mice. Methods: After governmental approval (General Administration of the Free State of Bavaria, file number: 55.2-1-54-2532-149-11) 60 mice at 10-12 months of age were exposed to isoflurane (1.6 Vol%) for 120 min, data of 58 mice was analyzed. During general anesthesia, heart rate, respiratory rate, temperature, isoflurane concentration and fraction of inspired oxygen were monitored and collected. Data were analyzed using univariate and multivariate linear mixed regression models. Results: During general anesthesia, heart rate decreased in a sex-specific manner. Respiratory rate decreased and body temperature increased dependent on genotype. However, the changes were limited and all vital parameters stayed within physiological limits. Conclusion: Isoflurane anesthesia in the Tg2576 mouse model is safe and does not seem to influence experimental results by interacting with vital parameters. The present study provides information on appropriate anesthesia in order to advance research on anesthesia and AD and could contribute to improving laboratory animal welfare.
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BACKGROUND: Surveys suggest a low level of implementation of clinical guidelines, although they are intended to improve the quality of treatment and patient safety. Which guideline recommendations are not followed and why has yet to be analysed. In this study, we investigate the proportion of European and national guidelines followed in the area of pre-operative anaesthetic evaluation prior to non-cardiac surgery. METHODS: We conducted this monocentric retrospective observational study at a German university hospital with the help of software that logically links guidelines in such a way that individualised recommendations can be derived from a patient's data. We included routine logs of 2003 patients who visited our pre-anaesthesia outpatient clinic between June 2018 and June 2020 and compared the actual conducted pre-operative examinations with the recommendations issued by the software. We descriptively analysed the data for examinations not performed that would have been recommended by the guidelines and examinations that were performed even though they were not covered by a guideline recommendation. The guidelines examined in this study are the 2018 ESAIC guidelines for pre-operative evaluation of adults undergoing elective non-cardiac surgery, the 2014 ESC/ESA guidelines on non-cardiac surgery and the German recommendations on pre-operative evaluation on non-cardiothoracic surgery from the year 2017. RESULTS: Performed ECG (78.1%) and cardiac stress imaging tests (86.1%) indicated the highest guideline adherence. Greater adherence rates were associated with a higher ASA score (ASA I: 23.7%, ASA II: 41.1%, ASA III: 51.8%, ASA IV: 65.8%, P < 0.001), lower BMI and age > 65 years. Adherence rates in high-risk surgery (60.5%) were greater than in intermediate (46.5%) or low-risk (44.6%) surgery (P < 0.001). 67.2% of technical and laboratory tests performed preoperatively were not covered by a guideline recommendation. CONCLUSIONS: Guideline adherence in pre-operative evaluation leaves room for improvement. Many performed pre-operative examinations, especially laboratory tests, are not recommended by the guidelines and may cause unnecessary costs. The reasons for guidelines not being followed may be the complexity of guidelines and organisational issues. A software-based decision support tool may be helpful. TRIAL REGISTRATION: ClinicalTrials.gov ID NCT04843202.
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A scientific panel was created consisting of 23 interdisciplinary and interprofessional experts in intensive care medicine, physiotherapy, nursing care, surgery, rehabilitative medicine, and pneumology delegated from scientific societies together with a patient representative and a delegate from the Association of the Scientific Medical Societies who advised methodological implementation. The guideline was created according to the German Association of the Scientific Medical Societies (AWMF), based on The Appraisal of Guidelines for Research and Evaluation (AGREE) II. The topics of (early) mobilisation, neuromuscular electrical stimulation, assist devices for mobilisation, and positioning, including prone positioning, were identified as areas to be addressed and assigned to specialist expert groups, taking conflicts of interest into account. The panel formulated PICO questions (addressing the population, intervention, comparison or control group as well as the resulting outcomes), conducted a systematic literature review with abstract screening and full-text analysis and created summary tables. This was followed by grading the evidence according to the Oxford Centre for Evidence-Based Medicine 2011 Levels of Evidence and a risk of bias assessment. The recommendations were finalized according to GRADE and voted using an online Delphi process followed by a final hybrid consensus conference. The German long version of the guideline was approved by the professional associations. For this English version an update of the systematic review was conducted until April 2024 and recommendation adapted based on new evidence in systematic reviews and randomized controlled trials. In total, 46 recommendations were developed and research gaps addressed.