AnesthesiologyPub Date : 2025-05-01Epub Date: 2025-04-08DOI: 10.1097/ALN.0000000000005362
Gaetano Scaramuzzo, Dan Stieper Karbing, Carlo Alberto Volta, Stephen Edward Rees, Savino Spadaro
{"title":"Ventilation/Perfusion and Pulmonary Complications: Reply.","authors":"Gaetano Scaramuzzo, Dan Stieper Karbing, Carlo Alberto Volta, Stephen Edward Rees, Savino Spadaro","doi":"10.1097/ALN.0000000000005362","DOIUrl":"https://doi.org/10.1097/ALN.0000000000005362","url":null,"abstract":"","PeriodicalId":7970,"journal":{"name":"Anesthesiology","volume":"142 5","pages":"964-965"},"PeriodicalIF":9.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AnesthesiologyPub Date : 2025-05-01Epub Date: 2025-04-08DOI: 10.1097/ALN.0000000000005417
George A Mashour
{"title":"Prefrontal Cortex and the Control of Arousal States.","authors":"George A Mashour","doi":"10.1097/ALN.0000000000005417","DOIUrl":"https://doi.org/10.1097/ALN.0000000000005417","url":null,"abstract":"","PeriodicalId":7970,"journal":{"name":"Anesthesiology","volume":"142 5","pages":"785-786"},"PeriodicalIF":9.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AnesthesiologyPub Date : 2025-05-01Epub Date: 2025-04-08DOI: 10.1097/ALN.0000000000005395
Douglas A Colquhoun, Allison M Janda, Graciela Mentz, Clark A Fisher, Robert B Schonberger, Nirav Shah, Sachin Kheterpal, Michael R Mathis
{"title":"Accounting for Healthcare Structures When Measuring Variation in Care.","authors":"Douglas A Colquhoun, Allison M Janda, Graciela Mentz, Clark A Fisher, Robert B Schonberger, Nirav Shah, Sachin Kheterpal, Michael R Mathis","doi":"10.1097/ALN.0000000000005395","DOIUrl":"10.1097/ALN.0000000000005395","url":null,"abstract":"<p><p>Health services research frequently focuses on variation in the structure, process, and outcomes of clinical care. Robust approaches for detection and attribution of variation are foundational to both quality improvement and outcomes research. Describing care in structured healthcare systems across hospitals in which clinicians work to provide care for patients as a multileveled structure allows the impact of organization on practice and outcome to be ascertained. Mixed-effect statistical models can describe both the partitioning of variation among levels of these structures and by inclusion of explanatory variables the valid estimation of the features of health systems, clinicians, or patients, with observed differences in processes or patient outcomes. In this Readers' Toolbox, the authors describe the rationale for considering healthcare structures when assessing clinical practice, outcomes, and sources of variation. They describe statistical considerations and methods for the estimation of analysis of structured data and assessment of variance.</p>","PeriodicalId":7970,"journal":{"name":"Anesthesiology","volume":"142 5","pages":"793-805"},"PeriodicalIF":9.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11981012/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AnesthesiologyPub Date : 2025-05-01Epub Date: 2025-04-08DOI: 10.1097/ALN.0000000000005457
Alexander S Doyal, Jonathan P Wanderer, Holly B Ende
{"title":"Gazing into Recovery: Processed EEG Depth of Anesthesia Algorithms for Neurologic Outcomes after Cardiac Arrest.","authors":"Alexander S Doyal, Jonathan P Wanderer, Holly B Ende","doi":"10.1097/ALN.0000000000005457","DOIUrl":"https://doi.org/10.1097/ALN.0000000000005457","url":null,"abstract":"","PeriodicalId":7970,"journal":{"name":"Anesthesiology","volume":"142 5","pages":"A18"},"PeriodicalIF":9.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AnesthesiologyPub Date : 2025-05-01Epub Date: 2025-04-08DOI: 10.1097/ALN.0000000000005420
Martin Dres, Ewan C Goligher
{"title":"Lost in Transition: New Evidence on the Risks of Underassisted Ventilation on the Diaphragm.","authors":"Martin Dres, Ewan C Goligher","doi":"10.1097/ALN.0000000000005420","DOIUrl":"https://doi.org/10.1097/ALN.0000000000005420","url":null,"abstract":"","PeriodicalId":7970,"journal":{"name":"Anesthesiology","volume":"142 5","pages":"787-789"},"PeriodicalIF":9.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AnesthesiologyPub Date : 2025-05-01Epub Date: 2024-12-19DOI: 10.1097/ALN.0000000000005336
Martina Baiardo Redaelli, Fabrizio Monaco, Nikola Bradic, Anna Mara Scandroglio, Lian Kah Ti, Alessandro Belletti, Cristina Viscido, Margherita Licheri, Fabio Guarracino, Alessandro Pruna, Antonio Pisano, Domenico Pontillo, Francesco Federici, Rosario Losiggio, Giovanni Serena, Enrico Tomasi, Simona Silvetti, Marco Ranucci, Luca Brazzi, Andrea Cortegiani, Giovanni Landoni, Pasquale Mastroroberto, Gianluca Paternoster, Mario F L Gaudino, Alberto Zangrillo, Rinaldo Bellomo
{"title":"Amino Acid Infusion for Kidney Protection in Cardiac Surgery Patients with Chronic Kidney Disease: A Secondary Analysis of the PROTECTION Trial.","authors":"Martina Baiardo Redaelli, Fabrizio Monaco, Nikola Bradic, Anna Mara Scandroglio, Lian Kah Ti, Alessandro Belletti, Cristina Viscido, Margherita Licheri, Fabio Guarracino, Alessandro Pruna, Antonio Pisano, Domenico Pontillo, Francesco Federici, Rosario Losiggio, Giovanni Serena, Enrico Tomasi, Simona Silvetti, Marco Ranucci, Luca Brazzi, Andrea Cortegiani, Giovanni Landoni, Pasquale Mastroroberto, Gianluca Paternoster, Mario F L Gaudino, Alberto Zangrillo, Rinaldo Bellomo","doi":"10.1097/ALN.0000000000005336","DOIUrl":"10.1097/ALN.0000000000005336","url":null,"abstract":"<p><strong>Background: </strong>In the PROTECTION trial (Intravenous Amino Acid Therapy for Kidney Protection in Cardiac Surgery), intravenous amino acids decreased the occurrence of acute kidney injury in cardiac surgery patients with cardiopulmonary bypass. Recruitment of renal functional reserve may be responsible for such protection. However, patients with chronic kidney disease have diminished renal functional reserve, and amino acids may be less protective in such patients. Thus, a separate investigation of such patients is warranted.</p><p><strong>Methods: </strong>For this study chronic kidney disease was defined as an estimated glomerular filtration rate of less than 60 ml · min -1 · 1.73 m -2 , and patients with estimated glomerular filtration rates greater than or equal to 60 ml · min -1 · 1.73 m -2 served as controls. The primary outcome was the occurrence of acute kidney injury. Secondary outcomes included severity of acute kidney injury, need for and duration of renal replacement therapy, and all-cause mortality.</p><p><strong>Results: </strong>Among chronic kidney disease patients (n = 812), compared with placebo, amino acids significantly decreased the rate of acute kidney injury (43.1% vs 50.3%; relative risk, 0.86; 95% CI, 0.74 to 0.99; P = 0.041; number needed to treat = 14) with a median percentage increase in estimated glomerular filtration rate from baseline to postoperative day 3 of 12.7% versus 6.5% ( P = 0.002). In estimated glomerular filtration rate-based chronic kidney disease subgroups (30 to 39, 40 to 49, and 50 to 59 ml · min -1 · 1.73 m -2 ), the amino acid effect was similar (interaction P = 0.50). Finally, amino acid infusion decreased the occurrence of severe (stage 3) acute kidney injury (2.7% vs . 5.6%; relative risk 0.48; 95% CI, 0.24 to 0.98; P = 0.038).</p><p><strong>Conclusions: </strong>Amino acid infusion protected chronic kidney disease patients undergoing cardiopulmonary bypass from developing acute kidney injury, with an absolute risk reduction of 7% and a number needed to treat of 14 in a cohort with a greater than 45% rate of acute kidney injury. Moreover, it delivered a greater than 50% relative risk reduction in severe acute kidney injury.</p>","PeriodicalId":7970,"journal":{"name":"Anesthesiology","volume":" ","pages":"818-828"},"PeriodicalIF":9.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AnesthesiologyPub Date : 2025-05-01Epub Date: 2025-01-09DOI: 10.1097/ALN.0000000000005369
Samuel B Snider, Bradley J Molyneaux, Anarghya Murthy, Quinn Rademaker, Hafeez Rajwani, Benjamin M Scirica, Jong Woo Lee, Christopher W Connor
{"title":"Developing an Electroencephalogram-based Model to Predict Awakening after Cardiac Arrest Using Partial Processing with the BIS Engine.","authors":"Samuel B Snider, Bradley J Molyneaux, Anarghya Murthy, Quinn Rademaker, Hafeez Rajwani, Benjamin M Scirica, Jong Woo Lee, Christopher W Connor","doi":"10.1097/ALN.0000000000005369","DOIUrl":"10.1097/ALN.0000000000005369","url":null,"abstract":"<p><strong>Background: </strong>Accurate prognostication in comatose survivors of cardiac arrest is a challenging and high-stakes endeavor. The authors sought to determine whether internal electroencephalogram (EEG) subparameters extracted by the BIS monitor (Medtronic, USA), a device commonly used to estimate depth of anesthesia intraoperatively, could be repurposed to predict recovery of consciousness after cardiac arrest.</p><p><strong>Methods: </strong>In this retrospective cohort study, a three-layer neural network was trained to predict recovery of consciousness to the point of command following versus not based on 48 h of continuous EEG recordings in 315 comatose patients admitted to a single U.S. academic medical center after cardiac arrest (derivation cohort, n = 181; validation cohort, n = 134). Continuous EEGs were partially processed into subparameters using virtualized emulation of the BIS Engine ( i.e. , the internal software of the BIS monitor) applied to signals from the frontotemporal leads of the standard 10-20 EEG montage. The model was trained on hourly averaged measurements of these internal subparameters. This model's performance was compared to the modified Westhall qualitative EEG scoring framework.</p><p><strong>Results: </strong>Maximum prognostic accuracy in the derivation cohort was achieved using a network trained on only four BIS subparameters (inverse burst suppression ratio, mean spectral power density, gamma power, and theta/delta power). In a held-out sample of 134 patients, the model outperformed current state-of-the-art qualitative EEG assessment techniques at predicting recovery of consciousness (area under the receiver operating characteristics curve, 0.86; accuracy, 0.87; sensitivity, 0.83; specificity, 0.88; positive predictive value, 0.71; negative predictive value, 0.94). Gamma band power has not been previously reported as a correlate of recovery potential after cardiac arrest.</p><p><strong>Conclusions: </strong>In patients comatose after cardiac arrest, four EEG features calculated internally by the BIS Engine were repurposed by a compact neural network to achieve a prognostic accuracy superior to the current clinical qualitative accepted standard, with high sensitivity for recovery. These features hold promise for assessing patients after cardiac arrest.</p>","PeriodicalId":7970,"journal":{"name":"Anesthesiology","volume":" ","pages":"806-817"},"PeriodicalIF":9.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11978491/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142942906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}