• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2012.04a
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• pp.190-193
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• 2012

The tools that classify the severity of patients based on the prediction of mortality include APACHE, SAPS, and MPM. Theses tools rely crucially on the evaluation of patients' general clinical status on the first date of their admission to ICU. Nursing activities are one of the most crucial factors influencing on the quality of treatment that patients receive and one of the contributing factors for their prognosis and safety. The purpose of this study was to identify the goodness-of-fit of CPSCS of critical patient severity classification system(CPSCS) and Glasgow coma scale(GCS) and the clinical usefulness of its death rate prediction. Data were collected from the medical records of 187 neurological patients who were admitted to the ICU of C University Hospital. The data were analyzed through $x^2$ test, t-test, Mann-Whitney, Kruskal-Wallis, goodness-of-fit test, and ROC curve. In accordance with patients' general and clinical characteristics, patient mortality turned out to be statistically different depending on ICU stay, endotracheal intubation, central venous catheter, and severity by CPSCS. Homer-Lemeshow goodness-of-fit tests were CPSCS and GCS and the results of the discrimination test using the ROC curve were $CPSCS_0$,.734, $GCS_0$,.583, $CPSCS_{24}$,.734, $GCS_{24}$,.612, $CPSCS_{48}$,.591, $GCS_{48}$,.646, $CPSCS_{72}$,.622, and $GCS_{72}$,.623. Logistic regression analysis showed that each point on the CPSCS score signifies1.034 higher likelihood of dying. Applied to neurologically ill patients, early CPSCS scores can be regarded as a useful tool.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.3
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• pp.267-275
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• 2012

In this study, crack growth in a center-cracked plate is predicted under mode I variable amplitude loading, and the result is validated by experiment. Huang's model is employed to describe crack growth with acceleration and retardation due to the variable loading effect. Experiment is conducted with Al6016-T6 plate, in which the load is applied, and crack length is measured periodically. Particle Filter algorithm, which is based on the Bayesian approach, is used to estimate model parameters from the experimental data, and predict the crack growth of the future in the probabilistic way. The prediction is validated by the run-to-failure results, from which it is observed that the method predicts well the unique behavior of crack retardation and the more data are used, the closer prediction we get to the actual run-to-failure data.

• Korean Journal of Radiology
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• v.24 no.7
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• pp.626-639
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• 2023

Objective: To investigate the association of clinical, pathologic, and magnetic resonance imaging (MRI) variables with progressive disease (PD) during neoadjuvant chemotherapy (NAC) and distant metastasis-free survival (DMFS) in patients with triple-negative breast cancer (TNBC). Materials and Methods: This single-center retrospective study included 252 women with TNBC who underwent NAC between 2010 and 2019. Clinical, pathologic, and treatment data were collected. Two radiologists analyzed the pre-NAC MRI. After random allocation to the development and validation sets in a 2:1 ratio, we developed models to predict PD and DMFS using logistic regression and Cox proportional hazard regression, respectively, and validated them. Results: Among the 252 patients (age, 48.3 ± 10.7 years; 168 in the development set; 84 in the validation set), PD was occurred in 17 patients and 9 patients in the development and validation sets, respectively. In the clinical-pathologic-MRI model, the metaplastic histology (odds ratio [OR], 8.0; P = 0.032), Ki-67 index (OR, 1.02; P = 0.044), and subcutaneous edema (OR, 30.6; P = 0.004) were independently associated with PD in the development set. The clinical-pathologic-MRI model showed a higher area under the receiver-operating characteristic curve (AUC) than the clinical-pathologic model (AUC: 0.69 vs. 0.54; P = 0.017) for predicting PD in the validation set. Distant metastases occurred in 49 patients and 18 patients in the development and validation sets, respectively. Residual disease in both the breast and lymph nodes (hazard ratio [HR], 6.0; P = 0.005) and the presence of lymphovascular invasion (HR, 3.3; P < 0.001) were independently associated with DMFS. The model consisting of these pathologic variables showed a Harrell's C-index of 0.86 in the validation set. Conclusion: The clinical-pathologic-MRI model, which considered subcutaneous edema observed using MRI, performed better than the clinical-pathologic model for predicting PD. However, MRI did not independently contribute to the prediction of DMFS.

• Journal of Korean Biological Nursing Science
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• v.16 no.4
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• pp.259-266
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• 2014

Purpose: The purpose of this study was to analyze risk factors in predicting medical patients transferred to Intensive Care Unit (ICU) on the general ward. Methods: We reviewed retrospectively clinical data of 120 medical patients on the general ward and a Modified Early Warning Score (MEWS) between ICU group and general ward group. Data were analyzed with multivariate logistic regression and the area under the receiver operating characteristic curves using SPSS/WIN 18.0 program. Results: Fifty-two ICU patients and 68 general ward patients were included. In multivariate logistic regression, the MEWSs (Odds Ratio [OR], 1.91; 95% confidence interval [CI], 1.32-2.76), sequential organ failure assessment score (OR, 1.28; 95% CI, 1.10-1.72), $PaO_2/FiO_2$ ratio (OR, 0.98; 95% CI, 0.98-0.99), and saturation (OR, 0.93; 95% CI, 0.88-0.99) were predictive of ICU transfer. The sensitivity and the specificity of the MEWSs used with a cut-off value of six were 80.8% and 70.6% respectively for ICU transfer. Conclusion: These findings suggest that early prediction and treatment of patients with high risk of ICU transfer may improve the prognosis of patients.

• Journal of Hospice and Palliative Care
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• v.2 no.2
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• pp.138-143
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• 1999

Accurately estimating survival times in terminal cancer patients is very difficult for palliative care clinicians. But a reasonably accurate estimate of survival would permit the medical team to : Plan the ideal therapeutic strategy between overtreatment and too early discontinuation of specific therapy. Answer any questions asked by the patient or family. Organize adequate assistance for the patient concerned. Decide on the eligibility of the patient for clinical trials and whether to begin a treatment, the effects of which will not be immediate. This case was a 79 year-old male patient with colon cancer. He complained of dry mouth, anorexia, weight loss and showed KPS $40{\sim}50$ on admission day. 40 days later he died. To improve patient/family quality of life, it is necessary to improve the ability to estimate accurately a patient's length of survival.

• BMB Reports
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• v.43 no.10
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• pp.643-648
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• 2010

Sir William Osler (1849-1919) recognized that "variability is the law of life, and as no two faces are the same, so no two bodies are alike, and no two individuals react alike and behave alike under the abnormal conditions we know as disease". Accordingly, the traditional methods of medicine are not always best for all patients. Over the last decade, the study of genomes and their derivatives (RNA, protein and metabolite) has rapidly advanced to the point that genomic research now serves as the basis for many medical decisions and public health initiatives. Genomic tools such as sequence variation, transcription and, more recently, personal genome sequencing enable the precise prediction and treatment of disease. At present, DNA-based risk assessment for common complex diseases, application of molecular signatures for cancer diagnosis and prognosis, genome-guided therapy, and dose selection of therapeutic drugs are the important issues in personalized medicine. In order to make personalized medicine effective, these genomic techniques must be standardized and integrated into health systems and clinical workflow. In addition, full application of personalized or genomic medicine requires dramatic changes in regulatory and reimbursement policies as well as legislative protection related to privacy. This review aims to provide a general overview of these topics in the field of personalized medicine.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.17 no.1
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• pp.57-60
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• 2014

Acute acalculous cholecystitis (AAC) is an inflammation of the gallbladder in the absence of demonstrated stones. AAC is frequently associated with severe systemic inflammation. However, the exact etiology and pathogenesis of AAC still remain unclear. Acute infection with Epstein Barr virus (EBV) in childhood is usually aymptomatic, whereas it often presents as typical infectious mononucleosis symptoms such as fever, cervical lymphadenopathy, and hepatosplenomegaly. AAC may occur during the course of acute EBV infection, which is rarely encountered in the pediatric population. AAC complicating the course of a primary EBV infection is usually associated with a favorable outcome. Most of the patients recover without any surgical treatment. Therefore, the detection of EBV in AAC would be important for prediction of better prognosis. We describe the case of a 10-year-old child who presented with AAC during the course of primary EBV infection, the first in Korea, and review the relevant literature.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10401-10405
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• 2015

Background: Molecular prognostic markers have been under investigation for the last decade and no validated marker to date has been proven to be used in daily clinical practice for urinary bladder cancers. The aim of the present study is to evaluate the significance of HYAL-1 expression in prediction of recurrence and progression in pT1 urothelial carcinomas. Materials and Methods: Eighty-nine urothelial carcinoma cases staged as T1 according to 2004 WHO classification were studied. Representative sections from every case were stained immunohistochemically for HYAL-1 and scored between 0 and +3, according to staining density, and graded as low and high for the scores 0-1 and 2-3, respectively. Results: Of the 89 pT1 bladder cancer patients, HYAL-1 expression was high in 92.1% (82 patients; 72 patients +3 and 10 patients +2) and low in 7.9% (only 7 patients; 6 patients +1 and 1 patient 0) of the cases. Of the 89 patients, 38 (42.7%) had recurrence and 22 (24.7%) showed progression. HYAL-1 staining did not show significant characteristics for tumor grade, accompanying CIS, multiplicity, tumor size, age and sex. HYAL-1 expression did not have any prognostic value in estimating recurrence or progression. Conclusions: HYAL-1 expression was found to be high, but did not have any prognostic importance in T1 bladder urothelial carcinomas.

• Journal of Gastric Cancer
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• v.13 no.3
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• pp.129-135
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• 2013

Gastric cancer is the second leading cause of cancer-related deaths worldwide. In advanced and metastatic gastric cancer, the conventional chemotherapy with limited efficacy shows an overall survival period of about 10 months. Patient specific and effective treatments known as personalized cancer therapy is of significant importance. Advances in high-throughput technologies such as microarray and next generation sequencing for genes, protein expression profiles and oncogenic signaling pathways have reinforced the discovery of treatment targets and personalized treatments. However, there are numerous challenges from cancer target discoveries to practical clinical benefits. Although there is a flood of biomarkers and target agents, only a minority of patients are tested and treated accordingly. Numerous molecular target agents have been under investigation for gastric cancer. Currently, targets for gastric cancer include the epidermal growth factor receptor family, mesenchymal-epithelial transition factor axis, and the phosphatidylinositol 3-kinase-AKT-mammalian target of rapamycin pathways. Deeper insights of molecular characteristics for gastric cancer has enabled the molecular classification of gastric cancer, the diagnosis of gastric cancer, the prediction of prognosis, the recognition of gastric cancer driver genes, and the discovery of potential therapeutic targets. Not only have we deeper insights for the molecular diversity of gastric cancer, but we have also prospected both affirmative potentials and hurdles to molecular diagnostics. New paradigm of transdisciplinary team science, which is composed of innovative explorations and clinical investigations of oncologists, geneticists, pathologists, biologists, and bio-informaticians, is mandatory to recognize personalized target therapy.

• BMB Reports
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• v.48 no.8
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• pp.427-428
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• 2015

Despite high interests on microenvironmental regulation of leukemic cells, little is known for bone marrow (BM) niche in leukemia patients. Our recent study on BMs of acute myeloid leukemia (AML) patients showed that the mesenchymal stromal cells (MSCs) are altered during leukemic conditions in a clinical course-dependent manner. Leukemic blasts caused reprogramming of transcriptomes in MSCs and remodeling of niche cross-talk, selectively suppressing normal primitive hematopoietic cells while supporting leukemogenesis and chemo-resistance. Notably, differences in BM stromal remodeling were correlated to heterogeneity in subsequent clinical courses of AML, i.e., low numbers of mesenchymal progenitors at initial diagnosis were correlated to complete remission for 5-8 years, and high contents of mesenchymal progenitor or MSCs correlated to early or late relapse, respectively. Thus, stromal remodeling by leukemic cell is an intrinsic part of leukemogenesis that can contribute to the clonal dominance of leukemic cells over normal hematopoietic cells, and can serve as a biomarker for prediction of prognosis. [BMB Reports 2015; 48(8): 427-428]