Korean Journal of Anesthesiology最新文献

{"title":"Age-dependent electroencephalogram alterations under remimazolam anesthesia.","authors":"Jayyoung Bae, Myung Il Bae, Dong Woo Han, Jaehyun Kwon, Young Song","doi":"10.4097/kja.25686","DOIUrl":"10.4097/kja.25686","url":null,"abstract":"<p><strong>Background: </strong>Remimazolam is a novel benzodiazepine anesthetic increasingly used for total intravenous anesthesia (TIVA); however, its electroencephalographic signatures-especially in elderly patients-remain poorly characterized. This study aimed to evaluate the relationship between age and intraoperative electroencephalogram (EEG) dynamics during remimazolam-based TIVA.</p><p><strong>Methods: </strong>This prospective observational study analyzed EEG recordings from 69 adult patients receiving remimazolam-based TIVA. We conducted linear regression and Pearson correlation analyses to assess the correlation between age and intraoperative EEG components, including absolute and relative power of EEG frequency bands, frontal coherence, aperiodic components, burst suppression ratio, patient state index (PSI), and spectral edge frequency.</p><p><strong>Results: </strong>Absolute alpha (r = -0.412, P < 0.001), beta (r = -0.459, P < 0.001), and gamma power (r = -0.372, P = 0.002) decreased with age. Conversely, relative delta (r = 0.297, P = 0.013) and theta power (r = 0.433, P < 0.001) increased with age, whereas relative alpha (r = -0.354, P = 0.003) and beta power (r = -0.266, P = 0.027) decreased with age. Frontal coherence of delta (r = -0.436, P < 0.001), theta (r = -0.279, P = 0.02), alpha (r = -0.269, P = 0.025), and beta (r = -0.27, P = 0.025) oscillations decreased with age.</p><p><strong>Conclusions: </strong>Older patients exhibited decreased alpha and beta powers, increased delta and theta dominance, and decreased frontal coherence under remimazolam anesthesia guided by the PSI. These findings suggest age-specific alterations in cortical dynamics that may affect EEG monitoring during remimazolam anesthesia.</p>","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":" ","pages":"318-331"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13247345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147504494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smoother emergence after craniotomy: regional airway blockade as an alternative.","authors":"Seongheon Lee","doi":"10.4097/kja.26482","DOIUrl":"10.4097/kja.26482","url":null,"abstract":"","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":"79 3","pages":"262-263"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244165/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical value of ultrasound-based skin-to-hyoid measurement in obese patients.","authors":"Yoon Ji Choi","doi":"10.4097/kja.26416","DOIUrl":"10.4097/kja.26416","url":null,"abstract":"","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":"79 3","pages":"259-261"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244162/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large language models for predicting postoperative complications: benefits, potential, and limitations of clinical use.","authors":"Young-Suk Kwon","doi":"10.4097/kja.26425","DOIUrl":"10.4097/kja.26425","url":null,"abstract":"","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":"79 3","pages":"257-258"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244166/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in intensive care units: a scoping review addressing the translational gap to clinical practice.","authors":"Francesco Zarantonello, Alessandro De Cassai, Tommaso Pettenuzzo, Nicolò Sella, Giulia Mormando, Annalisa Bolzon, Giulia Aviani Fulvio, Carlo Alberto Bertoncello, Annalisa Boscolo","doi":"10.4097/kja.251142","DOIUrl":"10.4097/kja.251142","url":null,"abstract":"<p><strong>Background: </strong>Critically ill patients generate large volumes of complex data, creating challenges for timely clinical decision making in intensive care units (ICUs). Artificial intelligence (AI) has emerged as a promising tool for supporting diagnosis, monitoring, prognostication, and workflow optimization in this setting. This scoping review aimed to map current AI applications in critical care and identify practical clinical applications.</p><p><strong>Methods: </strong>A systematic search of the MEDLINE, Scopus, and EMBASE databases was conducted for studies published between January 2015 and June 2025. Eligible studies evaluated practical AI applications in ICU settings involving patients, relatives, or healthcare professionals. Data pertaining to study design, AI techniques, clinical domains, outcomes, model characteristics, and implementation features were extracted.</p><p><strong>Results: </strong>In total, 112 studies were included. Most were retrospective observational studies (59.8%) focusing on adult populations. Machine learning was the predominant technology used (76.8%), and the main clinical applications were outcome and mortality predictions, early warning systems, and monitoring, particularly in neurological and respiratory domains. Notably, 24.1% of included studies relied on North American public databases, raising concerns about geographic data monoculture, and only 27.7% of the systems provided real-time bedside applications. Most systems remained at the experimental stage, with limited real-world implementation, heterogeneous performance reporting, and a frequent lack of external validation.</p><p><strong>Conclusions: </strong>AI applications in ICUs have expanded rapidly and show substantial promise for improving patient care and workflow efficiency. Future research should prioritize prospective multicenter validation, explainability, and implementation science to ensure the safe and effective integration of AI into critical care.</p>","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":" ","pages":"291-305"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244170/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correcting what cannot be corrected: rethinking publication bias analysis methods in clinical meta-analyses.","authors":"Hyun Kang","doi":"10.4097/kja.26020","DOIUrl":"10.4097/kja.26020","url":null,"abstract":"<p><p>Methods to assess and adjust for publication bias are often presented as tools to correct distorted evidence in meta-analyses. However, statistical adjustment cannot recover information that was selectively generated, reported, or disseminated. Clinical evidence syntheses frequently rely on small or selective sets of trials and are characterized by substantial heterogeneity, multiple outcomes and time points, and complex dissemination pathways. Publication bias analysis methods are thus prone to over-interpretation and may yield conflicting conclusions. Therefore, they should be understood as an inferential process that links detection, model-based adjustment, and interpretation under explicit and unverifiable assumptions. We review classical methods to detect publication bias, including funnel plots, tests of small-study effects, and P-value-based approaches, and demonstrate their essential role as stress tests of model adequacy rather than as definitive detectors of publication bias. We then examine widely used methods to adjust for publication bias, such as trim-and-fill, selection models, regression-based approaches relating the effect size to study precision, and the Bayesian approach, clarifying their key assumptions and typical failure modes. Using a worked example, we illustrate how applying different publication bias adjustment methods to the same evidence base can yield divergent adjusted effects, emphasizing their assumption dependence. We additionally identify common misuses, propose a framework for evaluations, and discuss emerging challenges related to preprints, umbrella reviews, and AI-assisted evidence synthesis. This review thus aims to help align the strength of clinical conclusions with the robustness or fragility of the underlying data, with direct implications for authors, reviewers, and editors.</p>","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":" ","pages":"271-290"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244164/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147513347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Age-dependent frontal EEG changes under remimazolam: reconsidering EEG monitoring interpretation.","authors":"Bon-Wook Koo","doi":"10.4097/kja.26471","DOIUrl":"10.4097/kja.26471","url":null,"abstract":"","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":"79 3","pages":"255-256"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rethinking publication bias: from mechanical correction to sensitivity-based interpretation.","authors":"Sangseok Lee","doi":"10.4097/kja.26474","DOIUrl":"10.4097/kja.26474","url":null,"abstract":"","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":" ","pages":"253-254"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244163/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147839820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy of ultrasound-measured skin-to-hyoid bone distance for predicting difficult mask ventilation in patients with obesity: a prospective observational study.","authors":"Maha Mostafa, Israa ElGeneidi, Ahmed Hasanin, Mostafa Ali, Hanan Mostafa, Nader Noshy Naguib","doi":"10.4097/kja.25118","DOIUrl":"10.4097/kja.25118","url":null,"abstract":"<p><strong>Background: </strong>The risk of difficult mask ventilation (DMV) is high in patients with obesity. Therefore, we evaluated the accuracy of ultrasound-measured skin-to-hyoid bone distance (SHD) for predicting DMV in this population.</p><p><strong>Methods: </strong>This prospective observational study included adult patients with obesity scheduled for elective surgery. Preoperative airway assessment included the modified Mallampati test, thyromental distance, sternomental distance, upper lip bite test, mouth opening, neck mobility, STOP-Bang score, and the SHD measured by a handheld ultrasound probe. The mask ventilation grade was evaluated using the 4-level Han score, and grades 3 and 4 were considered as DMV. The primary outcome was the ability of SHD to predict DMV using area under the receiver operating characteristic curve (AUC) analysis. A multivariate model including the STOP-Bang score, modified Mallampati test, upper lip bite test, and SHD was also assessed.</p><p><strong>Results: </strong>Data from 326 patients were analyzed. The DMV incidence was 22/326 (6.7%). Patients with DMV were predominantly male and had higher weight, STOP-Bang score, modified Mallampati grade, upper lip bite class, and SHD than did those with easy mask ventilation. The AUC (95% CI) of the SHD for predicting DMV was 0.88 (0.84-0.92). An SHD > 1.9 cm had a positive-predictive value of 27%, while its negative-predictive value was 99% (for SHD ≤ 1.9 cm). Multivariate analysis revealed that the SHD was an independent predictor of DMV.</p><p><strong>Conclusions: </strong>In patients with obesity, SHD measured by a handheld ultrasound probe is an independent predictor of DMV and can accurately predict DMV. An SHD ≤ 1.9 cm can exclude DMV with 99% accuracy.</p>","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":" ","pages":"353-359"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144497462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inhalational versus total intravenous anesthesia in noncardiac surgery: a comparative review of clinical outcomes.","authors":"Ah Ran Oh, Jungchan Park","doi":"10.4097/kja.25634","DOIUrl":"10.4097/kja.25634","url":null,"abstract":"<p><p>Inhalational anesthetics have long been the cornerstone of general anesthesia in noncardiac surgery owing to their reliable pharmacokinetics, ease of administration, and cardiopulmonary benefits such as bronchodilation and myocardial preconditioning. Total intravenous anesthesia (TIVA), achieved using short-acting agents such as propofol and remifentanil, and supported by target-controlled infusion systems and depth-of-anesthesia monitors, has emerged as a widely adopted alternative. TIVA is associated with improved recovery profiles, reduced incidence of postoperative nausea and vomiting, and potential neuroprotective and immunomodulatory effects. In this review, we compared the pharmacological mechanisms and clinical implications of inhalational anesthesia and TIVA, focusing on myocardial injury after noncardiac surgery and other perioperative outcomes. We summarized evidence from randomized controlled trials, large-scale observational studies, and health system-level analyses across multiple outcome domains: all-cause mortality, cardiovascular complications, pulmonary and renal outcomes, oncological prognosis, and system-level factors, such as cost-effectiveness and environmental impact. While inhalational agents demonstrated advantages in terms of cardioprotection and airway management, TIVA was found to offer potential benefits in select populations, particularly in cancer surgery and neuroanesthesia. No single technique demonstrated consistent superiority across all clinical contexts. Therefore, the selection of anesthetic technique should be personalized based on surgical risk, patient comorbidities, institutional infrastructure, and clinician expertise. Emerging trends in sustainability and precision medicine further underscore the need for individualized evidence-based strategies. By combining mechanistic insights with evidence from clinical practice, this review aimed to provide a balanced framework to guide optimal anesthetic decision-making in noncardiac surgery.</p>","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":" ","pages":"264-270"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13247346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145654598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}