Special announcement—procedural sedation: a position paper of the Canadian Anesthesiologists’ Society

Dobson, Gregory

doi:10.1007/s12630-018-1231-y

Can J Anesth/J Can Anesth

2018

DOI: 10.1007/s12630-018-1231-y

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Special announcement—procedural sedation: a position paper of the Canadian Anesthesiologists’ Society

Gregory Dobson¹

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“…release of the 2019 revised edition, we are excited to have a comprehensively updated version of Appendix 6, which represents the CAS position paper on procedural sedation. Regular readers of the Journal will have noted that the position paper was published, 2 along with an accompanying editorial, 3 in the December 2018 print issue to help achieve a wider circulation and dissemination of the document. For this reason, the CAS felt it deserving of publication on its own, in addition to making it available as electronic supplementary material, which is the usual process for all Guidelines appendices.…”

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Special announcement: Guidelines to the Practice of Anesthesia—Revised Edition 2019

Dobson¹

2018

Can J Anesth/J Can Anesth

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This issue of the Journal features the 2019 revised edition of the Guidelines to the Practice of Anesthesia 1 as developed and annually updated by the Canadian Anesthesiologists' Society (CAS) Committee on Standards, and approved by the CAS Board of Directors. The CAS has endorsed Guidelines since their initial development in 1974 (and publication in 1977), and the Journal has published yearly updates since 2009. They are widely recognized as a valuable clinical resource for anesthesia practitioners both nationally and internationally. Indeed, they are frequently downloaded as free web content and regularly cited in other peer-reviewed articles.The Committee on Standards welcomes questions, comments, and constructive criticism on this Guidelines document. Any queries and their related responses to them are available on the CAS website. Indeed, this present editorial commentary should be considered an invitation to any anesthesiologist, allied health professional, or healthcare administrator to report their questions or comments to the Committee on Standards (standards@cas).In view of the comprehensive and lengthy nature of the Guidelines document, this editorial serves to draw readers' attention to some of the specific topics updated in this new version. It also provides commentary about other issues undergoing further consideration for publication in future versions of the Guidelines.Appendices to the Guidelines, position papers, and other guideline documents are regularly reviewed by the committee and updated as required. To coincide with the

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Special announcement: Guidelines to the Practice of Anesthesia—Revised Edition 2019

Dobson¹

2018

Can J Anesth/J Can Anesth

Self Cite

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Automating sedation state assessments using natural language processing

Conway,

Li,

Rad

et al. 2024

J of Nursing Scholarship

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IntroductionCommon goals for procedural sedation are to control pain and ensure the patient is not moving to an extent that is impeding safe progress or completion of the procedure. Clinicians perform regular assessments of the adequacy of procedural sedation in accordance with these goals to inform their decision‐making around sedation titration and also for documentation of the care provided. Natural language processing could be applied to real‐time transcriptions of audio recordings made during procedures in order to classify sedation states that involve movement and pain, which could then be integrated into clinical documentation systems. The aim of this study was to determine whether natural language processing algorithms will work with sufficient accuracy to detect sedation states during procedural sedation.DesignA prospective observational study was conducted.MethodsAudio recordings from consenting participants undergoing elective procedures performed in the interventional radiology suite at a large academic hospital were transcribed using an automated speech recognition model. Sentences of transcribed text were used to train and evaluate several different NLP pipelines for a text classification task. The NLP pipelines we evaluated included a simple Bag‐of‐Words (BOW) model, an ensemble architecture combining a linear BOW model and a “token‐to‐vector” (Tok2Vec) component, and a transformer‐based architecture using the RoBERTa pre‐trained model.ResultsA total of 15,936 sentences from transcriptions of 82 procedures was included in the analysis. The RoBERTa model achieved the highest performance among the three models with an area under the ROC curve (AUC‐ROC) of 0.97, an F1 score of 0.87, a precision of 0.86, and a recall of 0.89. The Ensemble model showed a similarly high AUC‐ROC of 0.96, but lower F1 score of 0.79, precision of 0.83, and recall of 0.77. The BOW approach achieved an AUC‐ROC of 0.97 and the F1 score was 0.7, precision was 0.83 and recall was 0.66.ConclusionThe transformer‐based architecture using the RoBERTa pre‐trained model achieved the best classification performance. Further research is required to confirm the that this natural language processing pipeline can accurately perform text classifications with real‐time audio data to allow for automated sedation state assessments.Clinical RelevanceAutomating sedation state assessments using natural language processing pipelines would allow for more timely documentation of the care received by sedated patients, and, at the same time, decrease documentation burden for clinicians. Downstream applications can also be generated from the classifications, including for example real‐time visualizations of sedation state, which may facilitate improved communication of the adequacy of the sedation between clinicians, who may be performing supervision remotely. Also, accumulation of sedation state assessments from multiple procedures may reveal insights into the efficacy of particular sedative medications or identify procedures where the current approach for sedation and analgesia is not optimal (i.e. a significant amount of time spent in “pain” or “movement” sedation states).

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Special announcement—procedural sedation: a position paper of the Canadian Anesthesiologists’ Society

Cited by 2 publications

References 4 publications

Special announcement: Guidelines to the Practice of Anesthesia—Revised Edition 2019

Special announcement: Guidelines to the Practice of Anesthesia—Revised Edition 2019

Automating sedation state assessments using natural language processing

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