Posts Tagged ‘Critical Care’
Derivation, External Validation and Clinical Implications of a deep learning approach for intracranial pressure estimation using non-cranial waveform measurements.
Link: https://doi.org/10.1101/2024.01.30.24301974 Authors: Gulamali, Faris; Jayaraman, Pushkala; Sawant, Ashwin S; Desman, Jacob; Fox, Benjamin; Chang, Annie; Soong, Brian Y; Arivazaghan, Naveen; Reynolds, Alexandra S; Duong, Son Q; Vaid, Akhil; Kovatch, Patricia; Freeman, Robert; Hofer, Ira S; Sakhuja, Ankit; Dangayach, Neha S; Reich, David S; Charney, Alexander W; Nadkarni, Girish N Abstract: Increased intracranial pressure (ICP)…
Read MoreRemote Monitoring and Artificial Intelligence: Outlook for 2050.
Link: https://doi.org/10.1213/ANE.0000000000006712 Authors: Feinstein, Max; Katz, Daniel; Demaria, Samuel; Hofer, Ira S Abstract: Remote monitoring and artificial intelligence will become common and intertwined in anesthesiology by 2050. In the intraoperative period, technology will lead to the development of integrated monitoring systems that will integrate multiple data streams and allow anesthesiologists to track patients more effectively.…
Read MoreA novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19.
Link: https://doi.org/S0933-3657(23)00264-6 Authors: Oh, Wonsuk; Jayaraman, Pushkala; Tandon, Pranai; Chaddha, Udit S; Kovatch, Patricia; Charney, Alexander W; Glicksberg, Benjamin S; Nadkarni, Girish N Abstract: Computational subphenotyping, a data-driven approach to understanding disease subtypes, is a prominent topic in medical research. Numerous ongoing studies are dedicated to developing advanced computational subphenotyping methods for cross-sectional data. However,…
Read MorePost-operative urinary retention is impacted by neuromuscular block reversal agent choice: A retrospective cohort study in US hospital setting.
Link: https://doi.org/S0952-8180(23)00294-5 Authors: Bash, Lori D; Turzhitsky, Vladimir; Mark, Robert J; Hofer, Ira S; Weingarten, Toby N Abstract: Perioperative neuromuscular blocking agents are pharmacologically reversed to minimize complications associated with residual neuromuscular block. Neuromuscular block reversal with anticholinesterases (e.g., neostigmine) require coadministration of an anticholinergic agent (e.g., glycopyrrolate) to mitigate muscarinic activity; however, sugammadex, devoid…
Read MoreValidation of a convolutional neural network that reliably identifies electromyographic compound motor action potentials following train-of-four stimulation: an algorithm development experimental study.
Link: https://doi.org/10.1016/j.bjao.2023.100236 Authors: Epstein, Richard H; Perez, Olivia F; Hofer, Ira S; Renew, J Ross; Brull, Sorin J; Nemes, Réka Abstract: International guidelines recommend quantitative neuromuscular monitoring when administering neuromuscular blocking agents. The train-of-four count is important for determining the depth of block and appropriate reversal agents and doses. However, identifying valid compound motor action…
Read MoreCirculating Metabolomic Associations with Neurocognitive Outcomes in Pediatric CKD.
Link: https://doi.org/10.2215/CJN.0000000000000318 Authors: Lee, Arthur M; Xu, Yunwen; Hooper, Stephen R; Abraham, Alison G; Hu, Jian; Xiao, Rui; Matheson, Matthew B; Brunson, Celina; Rhee, Eugene P; Coresh, Josef; Vasan, Ramachandran S; Schrauben, Sarah; Kimmel, Paul L; Warady, Bradley A; Furth, Susan L; Hartung, Erum A; Denburg, Michelle R; , Abstract: Children with CKD are at…
Read MoreImplications of the Use of Artificial Intelligence Predictive Models in Health Care Settings : A Simulation Study.
Link: https://doi.org/10.7326/M23-0949 Authors: Vaid, Akhil; Sawant, Ashwin; Suarez-Farinas, Mayte; Lee, Juhee; Kaul, Sanjeev; Kovatch, Patricia; Freeman, Robert; Jiang, Joy; Jayaraman, Pushkala; Fayad, Zahi; Argulian, Edgar; Lerakis, Stamatios; Charney, Alexander W; Wang, Fei; Levin, Matthew; Glicksberg, Benjamin; Narula, Jagat; Hofer, Ira; Singh, Karandeep; Nadkarni, Girish N Abstract: Substantial effort has been directed toward demonstrating uses of…
Read MoreComparing ChatGPT and GPT-4 performance in USMLE soft skill assessments.
Link: https://doi.org/10.1038/s41598-023-43436-9 Authors: Brin, Dana; Sorin, Vera; Vaid, Akhil; Soroush, Ali; Glicksberg, Benjamin S; Charney, Alexander W; Nadkarni, Girish; Klang, Eyal Abstract: The United States Medical Licensing Examination (USMLE) has been a subject of performance study for artificial intelligence (AI) models. However, their performance on questions involving USMLE soft skills remains unexplored. This study aimed…
Read MoreClinical Informatics in Critical Care Medicine.
Link: https://doi.org/10.59249/WTTU3055 Authors: Nadkarni, Girish N; Sakhuja, Ankit Abstract: Continuous monitoring and treatment of patients in intensive care units generates vast amounts of data. Critical Care Medicine clinicians incorporate this continuously evolving data to make split-second, life or death decisions for management of these patients. Despite the abundance of data, it can be challenging to…
Read MoreDigital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup.
Link: https://doi.org/10.1038/s41581-023-00744-7 Authors: Kashani, Kianoush B; Awdishu, Linda; Bagshaw, Sean M; Barreto, Erin F; Claure-Del Granado, Rolando; Evans, Barbara J; Forni, Lui G; Ghosh, Erina; Goldstein, Stuart L; Kane-Gill, Sandra L; Koola, Jejo; Koyner, Jay L; Liu, Mei; Murugan, Raghavan; Nadkarni, Girish N; Neyra, Javier A; Ninan, Jacob; Ostermann, Marlies; Pannu, Neesh; Rashidi, Parisa; Ronco,…
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