Browsing by Author "Kim, Sunghan"

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    Delirium Detection using GAMMA Wave and Machine Learning: A Pilot Study
    (Wiley, 2022) Mulkey, Malissa; Albanese, Thomas; Kim, Sunghan; Huang, Huyanting; Yang, Baijain; School of Nursing
    Delirium occurs in as many as 80% of critically ill older adults and is associated with increased long-term cognitive impairment, institutionalization, and mortality. Less than half of delirium cases are identified using currently available subjective assessment tools. Electroencephalogram (EEG) has been identified as a reliable objective measure but has not been feasible. This study was a prospective pilot proof-of-concept study, to examine the use of machine learning methods evaluating the use of gamma band to predict delirium from EEG data derived from a limited lead rapid response handheld device. Data from 13 critically ill participants aged 50 or older requiring mechanical ventilation for more than 12 h were enrolled. Across the three models, accuracy of predicting delirium was 70 or greater. Stepwise discriminant analysis provided the best overall method. While additional research is needed to determine the best cut points and efficacy, use of a handheld limited lead rapid response EEG device capable of monitoring all five cerebral lobes of the brain for predicting delirium hold promise.
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    A large West Antarctic Ice Sheet explains early Neogene sea-level amplitude
    (Nature, 2021) Marschalek, J. W.; Zurli, L.; Talarico, F.; van de Flierdt, T.; Vermeesch, P.; Carter, A.; Beny, F.; Bout-Roumazeilles, V.; Sangiorgi, F.; Hemming, S. R.; Pérez, L. F.; Colleoni, F.; Prebble, J. G.; van Peer, T. E.; Perotti, M.; Shevenell, A. E.; Browne, I.; Kulhanek, D. K.; Levy, R.; Harwood, D.; Sullivan, N. B.; Meyers, S. R.; Griffith, E. M.; Hillenbrand, C.-D.; Gasson, E.; Siegert, M. J.; Keisling, B.; Licht, K. J.; Kuhn, G.; Dodd, J. P.; Boshuis, C.; De Santis, L.; McKay, R. M.; IODP Expedition 374; Ash, Jeanine; Beny, François; Browne, Imogen M.; Cortese, Giuseppe; De Santis, Laura; Dodd, Justin P.; Esper, Oliver M.; Gales, Jenny A.; Harwood, David M.; Ishino, Saki; Keisling, Benjamin A.; Kim, Sookwan; Kim, Sunghan; Kulhanek, Denise K.; Laberg, Jan Sverre; Leckie, R. Mark; McKay, Robert M.; Müller, Juliane; Patterson, Molly O.; Romans, Brian W.; Romero, Oscar E.; Sangiorgi, Francesca; Seki, Osamu; Shevenell, Amelia E.; Singh, Shiv M.; Cordeiro de Sousa, Isabela M.; Sugisaki, Saiko T.; van de Flierdt, Tina; van Peer, Tim E.; Xiao, Whenshen; Xiong, Zhifang; Earth Sciences, School of Science
    Early to Middle Miocene sea-level oscillations of approximately 40-60 m estimated from far-field records1-3 are interpreted to reflect the loss of virtually all East Antarctic ice during peak warmth2. This contrasts with ice-sheet model experiments suggesting most terrestrial ice in East Antarctica was retained even during the warmest intervals of the Middle Miocene4,5. Data and model outputs can be reconciled if a large West Antarctic Ice Sheet (WAIS) existed and expanded across most of the outer continental shelf during the Early Miocene, accounting for maximum ice-sheet volumes. Here we provide the earliest geological evidence proving large WAIS expansions occurred during the Early Miocene (~17.72-17.40 Ma). Geochemical and petrographic data show glacimarine sediments recovered at International Ocean Discovery Program (IODP) Site U1521 in the central Ross Sea derive from West Antarctica, requiring the presence of a WAIS covering most of the Ross Sea continental shelf. Seismic, lithological and palynological data reveal the intermittent proximity of grounded ice to Site U1521. The erosion rate calculated from this sediment package greatly exceeds the long-term mean, implying rapid erosion of West Antarctica. This interval therefore captures a key step in the genesis of a marine-based WAIS and a tipping point in Antarctic ice-sheet evolution.
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    Rapid Hand-held Continuous EEG has the Potential to Detect Delirium in Older Adults
    (Wolters Kluwer, 2022) Mulkey, Malissa A.; Gantt, Laura T.; Hardin, Sonya R.; Munro, Cindy L.; Everhart, D. Erik; Kim, Sunghan; Schoeman, Alexander M.; Roberson, Donna W.; McAuliffe, Maura; Olson, DaiWai M.; School of Nursing
    Background: Delirium-related biochemical derangements lead to electrical changes that can be detected in electroencephalographic (EEG) patterns followed by behavioral signs and symptoms. Studies using limited lead EEG show a large difference between patients with and without delirium while discriminating delirium from other causes. Handheld rapid EEG devices may be capable of detecting delirium before symptom onset, thus providing an objective physiological method to detect delirium when it is most amenable to interventions. Objective: The aim of this study was to explore the potential for rapid EEG to detect waveform pattern changes consistent with delirium status. Methods: This prospective exploratory pilot study used a correlational design and mixed models to explore the relationships between handheld portable EEG data and delirium status. Results: While being under powered minimized opportunities to detect statistical differences in EEG-derived ratios using spectral density analysis, sleep-to-wake ratios tended to be higher in patients with delirium. Conclusions: Limited lead EEG may be useful in predicting adverse outcomes and risk for delirium in older critically ill patients. Although this population is at the highest risk for mortality, delirium is not easily identified by current clinical assessments. Therefore, further investigation of limited lead EEG for delirium detection is warranted.