• Clinical and Experimental Pediatrics
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• v.52 no.10
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• pp.1153-1160
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• 2009

Purpose:To evaluate the risk factors for mortality and prognostic factors in pediatric hemato-oncology patients admitted to the pediatric intensive care unit (PICU). Methods:We retrospectively reviewed the medical records of pediatric hemato-oncology patients admitted at the PICU of the Asan Medical Center between September 2005 and July 2008. Patients admitted at the PICU for perioperative or terminal care were excluded. Results:Total 88 patients were analyzed. Overall ICU mortality rate was 34.1%. Mean age at PICU admission was $7.0{\pm}5.7$ years and mean duration of PICU stay was $18.1{\pm}22.2$ days. Hematologic diseases contributed to 77.3% of all the primary diagnoses, and the primary cause of admission was respiratory failure (39.8%). The factors related to increased mortality were C-reactive protein level (P<0.01), ventilation or dialysis requirement (P<0.01), and hematopoietic stem cell transplantation (P<0.05). In all, 3 scoring systems were investigated [Number of Organ System Failures (OSF number), the Pediatric Risk of Mortality III (PRISM III) score, and the Sequential Organ Failure Assessment (SOFA) score]; higher score correlated with worse outcome (P<0.01). The Oncological Pediatric Risk of Mortality (O-PRISM) scores of the 21 patients who had received hematopoietic stem cell transplantation were higher among the non-survivors, but not statistically significant (P=0.203). Conclusion:The PRISM III and SOFA scores obtained within 24 hours of PICU admission were found to be useful as early mortality predictors. The highest OSF number during the PICU stay was closely related to poor outcome.

• The Journal of the Petrological Society of Korea
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• v.22 no.2
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• pp.83-115
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• 2013

Erroneous fission-track (FT) ages caused by an inappropriate calibration in the initial stage of FT dating were redefined by re-experiments and zeta calibration using duplicate samples. Revised FT zircon ages newly define the formation ages of Yucheon Group rhyolitic-dacitic tuffs as Late Cretaceous to Early Paleocene ($78{\pm}4$ Ma to $65{\pm}2$ Ma) and Gokgangdong rhyolitic tuff as Early Eocene ($52.1{\pm}2.3$ Ma). In case of the Early Miocene volcanics, FT zircon ages from a dacitic tuff of the upper Hyodongri Volcanics ($21.6{\pm}1.4$ Ma) and a dacitic lava of the uppermost Beomgokri Volcanics ($21.3{\pm}2.0$ Ma) define chronostratigraphies of the upper Beomgokri Group, respectively in the southern Eoil Basin and in the Waeup Basin. A FT zircon age ($19.8{\pm}1.6$ Ma) from the Geumori dacitic tuff defines the time of later dacitic eruption in the Janggi Basin. Based on FT zircon ages for dacitic rocks and previous age data (mostly K-Ar whole-rock, partly Ar-Ar) for basaltic-andesitic rocks, reference ages are recommended as guides for stratigraphic correlations of the Miocene volcanics and basements in SE Korea. The times of accumulation of basin-fill sediments are also deduced from ages of related volcanics. Recommended reference ages are well matched to the whole stratigraphic sequences despite complicated basin structures and a relative short time-span. The Beomgokri Group evidently predates the Janggi Group in the Eoil-Waeup basins, while it is placed at an overlapped time-level along with the earlier Janggi Group in the Janggi Basin. Therefore, the two groups cannot be uniformly defined in a sequential order. The Janggi Group of the Janggi Basin can be evidently subdivided by ca. 20 Ma-basis into two parts, i.e., the earlier (23-20 Ma) andesitic-dacitic and later (20-18 Ma) basaltic strata.

• Journal of The Korean Society of Emergency Medicine
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• v.29 no.5
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• pp.465-473
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• 2018

Objective: We evaluated the clinical characteristics and prognoses of patients with septic shock who transferred to the emergency department (ED) in a tertiary referral center. Methods: This study was performed using a prospective, multi-center registry of septic shock, with the participation of 11 tertiary referral centers in the Korean Shock Society between October 2015 and February 2017. We classified the patients as a transferred group who transferred from other hospitals after meeting the inclusion criteria upon ED arrival and a non-transferred group who presented directly to the ED. Primary outcome was hospital mortality. We conducted multiple logistic regression analysis to assess variables related to in-hospital mortality. Results: A total of 2,098 patients were included, and we assigned 717 patients to the transferred group and 1,381 patients to the non-transferred group. The initial Sequential Organ Failure Assessment score was higher in the transferred group than the non-transferred group (6; interquartile range [IQR], 4-9 vs. 6; IQR, 4-8; P<0.001). Mechanical ventilator (29% vs. 21%, P<0.001) and renal replacement therapy (12% vs. 9%, P=0.034) within 24 hours after ED arrival were more frequently applied in the transferred group than the non-transferred group. Overall hospital mortality was 22% and there was no significant difference between transferred and non-transferred groups (23% vs. 22%, P=0.820). Multivariable analysis showed an odds ratio for in-hospital mortality of 1.00 (95% confidence interval, 0.78-1.28; P=0.999) for the transferred group compared with the non-transferred group. Conclusion: The transferred group showed higher severity and needed more organ support procedures than the non-transferred group. However, inter-hospital transfer did not affect in-hospital mortality.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.