• Title/Summary/Keyword: logistic curve

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Pre-Coronavirus Disease 2019 Pediatric Acute Appendicitis: Risk Factors Model and Diagnosis Modality in a Developing Low-Income Country

  • Salim, Jonathan;Agustina, Flora;Maker, Julian Johozua Roberth
    • Pediatric Gastroenterology, Hepatology & Nutrition
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    • v.25 no.1
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    • pp.30-40
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    • 2022
  • Purpose: Pediatric acute appendicitis has a stable incidence rate in Western countries with an annual change of -0.36%. However, a sharp increase was observed in the Asian region. The Indonesian Health Department reveals appendicitis as the fourth most infectious disease, with more than 64,000 patients annually. Hence, there is an urgent need to identify and evaluate the risk factors and diagnostic modalities for accurate diagnosis and early treatment. This study also clarifies the usage of pediatric appendicitis score (PAS) for children <5 years of age. Methods: The current study employed a cross-sectional design with purposive sampling through demographic and PAS questionnaires with ultrasound sonography (USG) results. The analysis was performed using the chi-square and Mann-Whitney tests and logistic regression. Results: This study included 21 qualified patients with an average age of 6.76±4.679 years, weighing 21.72±10.437 kg, and who had been hospitalized for 4.24±1.513 days in Siloam Teaching Hospital. Compared to the surgical gold standard, PAS and USG have moderate sensitivity and specificity. Bodyweight and stay duration were significant for appendicitis (p<0.05); however, all were confounders in the multivariate regression analysis. Incidentally, a risk prediction model was generated with an area under the curve of 72.73%, sensitivity of 100.0%, specificity of 54.5%, and a cut-off value of 151. Conclusion: PAS outperforms USG in the sensitivity of diagnosing appendicitis, whereas USG outperforms PAS in terms of specificity. This study demonstrates the use of PAS in children under 5 years old. Meanwhile, no risk factors were significant in multivariate pediatric acute appendicitis risk factors.

Plasma Neutrophil Gelatinase-associated Lipocalin and Leukocyte Differential Count in Children with Febrile Urinary Tract Infection

  • Son, Min Hwa;Yim, Hyung Eun;Yoo, Kee Hwan
    • Childhood Kidney Diseases
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    • v.25 no.2
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    • pp.84-91
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    • 2021
  • Purpose: We aimed to study the association of plasma neutrophil gelatinase-associated lipocalin (pNGAL) and leukocyte differential count in children with febrile urinary tract infection (UTI). Methods: Medical records of 154 children aged 1 month to 13 years with febrile UTI who were hospitalized were retrospectively reviewed. Associations between pNGAL levels and blood leukocyte differential count at admission and after 48 hours of treatment were investigated in children with or without acute pyelonephritis (APN). Results: The APN group (n=82) showed higher pNGAL levels, neutrophil count, monocyte count, and neutrophil-to-lymphocyte ratio (NLR), compared to the non-APN group (n=72) (all P<0.05). After adjustment for age and sex, pNGAL showed positive correlations with neutrophil count and NLR in both groups (all P<0.05). Additionally, it was correlated with the monocyte-to-lymphocyte ratio (MLR) only in the APN group (P<0.05). Before and after treatment, pNGAL was positively correlated with neutrophil count, NLR, and MLR in patients with APN while it was related with neutrophil count and NLR in those without APN (all P<0.05). Areas under the receiver operating curve of pNGAL, neutrophil count, NLR, and MLR for predicting APN were 0.804, 0.760, 0.730, and 0.636, respectively (all P<0.05). Only pNGAL was independently associated with the presence of APN in a multivariable logistic regression analysis (P<0.05). Conclusion: In children with febrile UTIs, pNGAL might be associated with leukocyte differential count and the presence of APN.

Barthel's Index: A Better Predictor for COVID-19 Mortality Than Comorbidities

  • da Costa, Joao Cordeiro;Manso, Maria Conceicao;Gregorio Susana;Leite, Marcia;Pinto, Joao Moreira
    • Tuberculosis and Respiratory Diseases
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    • v.85 no.4
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    • pp.349-357
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    • 2022
  • Background: The most consistently identified mortality determinants for the new coronavirus 2019 (COVID-19) infection are aging, male sex, cardiovascular/respiratory diseases, and cancer. They were determined from heterogeneous cohorts that included patients with different disease severity and previous conditions. The main goal of this study was to determine if activities of daily living (ADL) dependence measured by Barthel's index could be a predictor for COVID-19 mortality. Methods: A prospective cohort study was performed with a consecutive sample of 340 COVID-19 patients representing patients from all over the northern region of Portugal from October 2020 to March 2021. Mortality risk factors were determined after controlling for demographics, ADL dependence, admission time, comorbidities, clinical manifestations, and delay-time for diagnosis. Central tendency measures were used to analyze continuous variables and absolute numbers (proportions) for categorical variables. For univariable analysis, we used t test, chi-square test, or Fisher exact test as appropriate (α=0.05). Multivariable analysis was performed using logistic regression. IBM SPSS version 27 statistical software was used for data analysis. Results: The cohort included 340 patients (55.3% females) with a mean age of 80.6±11.0 years. The mortality rate was 19.7%. Univariate analysis revealed that aging, ADL dependence, pneumonia, and dementia were associated with mortality and that dyslipidemia and obesity were associated with survival. In multivariable analysis, dyslipidemia (odds ratio [OR], 0.35; 95% confidence interval [CI], 0.17-0.71) was independently associated with survival. Age ≥86 years (pooled OR, 2.239; 95% CI, 1.100-4.559), pneumonia (pooled OR, 3.00; 95% CI, 1.362-6.606), and ADL dependence (pooled OR, 6.296; 95% CI, 1.795-22.088) were significantly related to mortality (receiver operating characteristic area under the curve, 82.1%; p<0.001). Conclusion: ADL dependence, aging, and pneumonia are three main predictors for COVID-19 mortality in an elderly population.

Real-time prediction for multi-wave COVID-19 outbreaks

  • Zuhairohab, Faihatuz;Rosadi, Dedi
    • Communications for Statistical Applications and Methods
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    • v.29 no.5
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    • pp.499-512
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    • 2022
  • Intervention measures have been implemented worldwide to reduce the spread of the COVID-19 outbreak. The COVID-19 outbreak has occured in several waves of infection, so this paper is divided into three groups, namely those countries who have passed the pandemic period, those countries who are still experiencing a single-wave pandemic, and those countries who are experiencing a multi-wave pandemic. The purpose of this study is to develop a multi-wave Richards model with several changepoint detection methods so as to obtain more accurate prediction results, especially for the multi-wave case. We investigated epidemiological trends in different countries from January 2020 to October 2021 to determine the temporal changes during the epidemic with respect to the intervention strategy used. In this article, we adjust the daily cumulative epidemiological data for COVID-19 using the logistic growth model and the multi-wave Richards curve development model. The changepoint detection methods used include the interpolation method, the Pruned Exact Linear Time (PELT) method, and the Binary Segmentation (BS) method. The results of the analysis using 9 countries show that the Richards model development can be used to analyze multi-wave data using changepoint detection so that the initial data used for prediction on the last wave can be determined precisely. The changepoint used is the coincident changepoint generated by the PELT and BS methods. The interpolation method is only used to find out how many pandemic waves have occurred in given a country. Several waves have been identified and can better describe the data. Our results can find the peak of the pandemic and when it will end in each country, both for a single-wave pandemic and a multi-wave pandemic.

The Neutrophil-to-Lymphocyte Ratio as a Predictor of Postoperative Outcomes in Patients Undergoing Coronary Artery Bypass Grafting

  • Hyun Ah Lim;Joon Kyu Kang;Hwan Wook Kim;Hyun Son;Ju Yong Lim
    • Journal of Chest Surgery
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    • v.56 no.2
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    • pp.99-107
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    • 2023
  • Background: The neutrophil-to-lymphocyte ratio (NLR) has been suggested as a novel predictive marker of cardiovascular disease. However, its prognostic role in patients under-going coronary artery bypass grafting (CABG) is unclear. This study aimed to determine the association between the preoperative NLR and early mortality in patients undergoing CABG. Methods: Cardiac surgery was performed in 2,504 patients at Seoul St. Mary's Hospital from January 2010 to December 2021. This study retrospectively reviewed 920 patients who underwent isolated CABG, excluding those for whom the preoperative NLR was unavailable. The primary endpoints were the 30- and 90-day mortality after isolated CABG. Risk factor analysis was performed using logistic regression analysis. Based on the optimal cut-off value of preoperative NLR on the receiver operating characteristic curve, high and low NLR groups were compared. Results: The 30- and 90-day mortality rates were 3.8% (n=35) and 7.0% (n=64), respectively. In the multivariable analysis, preoperative NLR was significantly associated with 30-day mortality (odds ratio [OR], 1.28; 95% confidence interval [CI], 1.17-1.39; p<0.001) and 90-day mortality (OR, 1.17; 95% CI, 1.07-1.28; p<0.001). The optimal cut-off value of the preoperative NLR was 3.4. Compared to the low NLR group (<3.4), the high NLR group (≥3.4) showed higher 30- and 90-day mortality rates (1.4% vs. 12.1%, p<0.001; 2.8% vs. 21.3%, p<0.001, respectively). Conclusion: Preoperative NLR was strongly associated with early mortality after isolated CABG, especially in patients with a high preoperative NLR (≥3.4). Further studies with larger cohorts are necessary to validate these results.

Association between Optic Nerve Sheath Diameter/Eyeball Transverse Diameter Ratio and Neurological Outcomes in Patients with Aneurysmal Subarachnoid Hemorrhage

  • Jinsung Kim;Hyungoo Shin;Heekyung Lee
    • Journal of Korean Neurosurgical Society
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    • v.66 no.6
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    • pp.664-671
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    • 2023
  • Objective : The optic nerve sheath diameter (ONSD)/eyeball transverse diameter (ETD) ratio is a more reliable marker of intracranial pressure than the ONSD alone. We aimed to investigate the predictive value of the ONSD/ETD ratio (OER) for neurological outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH). Methods : Adult patients with aSAH who visited the emergency department of a tertiary hospital connected to a South Korean university between January 2015 and December 2021 were included. Data on patient characteristics and brain computed tomography scan findings, including the ONSD and ETD, were collected using a predefined protocol. According to the neurological outcome at hospital discharge, the patients were divided into the unfavorable neurological outcome (UNO; cerebral performance category [CPC] score 3-5) and the favorable neurological outcome (FNO; CPC score 1-2) groups. The primary outcome was the association between the OER and neurological outcomes in patients with aSAH. Results : A total of 171 patients were included in the study, of whom 118 patients (69%) had UNO. Neither the ONSD (p=0.075) nor ETD (p=0.403) showed significant differences between the two groups. However, the OER was significantly higher in the UNO group in the univariate analysis (p=0.045). The area under the receiver operating characteristic curve of the OER for predicting UNO was 0.603 (p=0.031). There was no independent relationship between the OER and UNO in the multivariate logistic regression analysis (adjusted odds ratio, 0.010; p=0.576). Conclusion : The OER was significantly higher in patients with UNO than in those with FNO, and the OER was more reliable than the ONSD alone. However, the OER had limited utility in predicting UNO in patients with aSAH.

Mesh Selectivity of Beam Trawl for Shrimps (새우조망의 망목선택성)

  • Oh, Taek-Yun;Cho, Young-Bok;Park, Gwang-Jei;Jeong, Sun-Beom;Kim, Min-Seok;Kim, Hyeong-Seok;Lee, Ju-Hee
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.40 no.1
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    • pp.86-94
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    • 2004
  • This study was conducted to mesh selectivity of Beam trawl for shrimps fishing experiment in the coastal waters around Geomundo, South sea of Korea, during from Oct. to Nov. 2002. The selectivity parameters of big head shrimp (Solenocera melantho) have been studied on the covered con-end method. with mesh of 8, 38, 51 and 61 mm. Selection curves and selection parameters were calculated by using a logistic function S=1/(1+exp-(aCL+b)). The mesh selection master curves were estimated by S=1/(1+exp$^{({\alpha}(CL/M)+{\beta}}$), and the optimum mesh size were calculated with (L/M)50 of master curve. Optimum mesh size and selectivity master curves for the southern rough shrimp (Yrachysalambria curvirostris) and smoothshell shrimp (Parapenaeopsis tenella) optimum mesh size and selectivity master curves were estimated by big head shrimp master curves. The results obtained are summarized as follows : Selection parameters '${\alpha}$' and '${\beta}$' of the master curve for big head shrimp were 8.84 and -5.89, and The selection factor of the master curve (L/M)$_{50}$ was 0.67. The optimum mesh size of minimum length for sexual maturity for big head shrimp was 30.7 mm. Estimated (L/M)$_{50}$ for southern rough shrimp and smoothshell shrimp by using the master curve of big head shrimp was 0.73 and the optimum mesh sizes were 25.5 mm for southern rough shrimp and 16.9 mm for smoothshell shrimp, respectively.

A theoretical approach and its application for a dynamic method of estimating and analyzing science and technology levels : case application to ten core technologies for the next generation growth engine (동태적 기술수준 측정 방법에 대한 이론적 접근 : 차세대성장동력 기술의 사례분석)

  • Bark, Pyeng-Mu
    • Journal of Korea Technology Innovation Society
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    • v.10 no.4
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    • pp.654-686
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    • 2007
  • To estimate and analyze an interested science and technology level in any case requires three basic informations: (1) relative positions of our technology level, (2) other relevant technology level of the world best country holding the state of the art technology, and (3) its theoretical or practical maximum level within a certain period of time. Further, additional information from analyzing its respective rate of technology changes is necessary. It seems that most previous empirical or case studies on technology level have not considered third and fourth informations seriously, and thus critically have missed important findings from a dynamic point of view on the matter. A dynamic approach considering types of development processes and paths as well as current position needs an application of a concept of technology development stages and respective growth curves. This paper proposes a new method of approach and application by implementing relatively simple types of the growth curve(S-curve) such as logistic and Comports curves and applying estimation results of these curves to ten core technologies of the growth engines for the next future generation in Korea. The study implies that Korean science and technology level in general clearly gets higher as it approaches to a recent time of period, but relative technology gap from the world best in terms of catching-up period does not get better or narrower in case of at least part of the concerned technologies such as bio new drugs and human organs, and intelligence robots. The possibility does exist that some of our concerned technologies shooting for the next future generation may not come to the world highest level in the near future. The purpose of this study is to propose possibilities of catching-up, if any, by estimating its relevant type of growth pattern by way of measuring and analyzing technology level and by analyzing the technology development process through a position analysis. At this stage this study tries to introduce a new theoretical approach of estimating technology level and its application to existing case study results(data) from Korea Institute of Science and Technology Planning and Evaluation(KISTEP) and Korea Institute of Industrial Technology Evaluation and Planing(ITEP), for years of 2004 and 2006 respectively. The study has some limitations in terms of accuracy of measuring(estimating) a relevant growth curve to a particular technology, feasibility of applying estimated results, accessing and analyzing panel experts opinions. Hence, it is recommended that further study would follow soon enough to verify practical applicability and possible expansion of the study results.

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The Comparison of Basic Science Research Capacity of OECD Countries

  • Lim, Yang-Taek;Song, Choong-Han
    • Journal of Technology Innovation
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    • v.11 no.1
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    • pp.147-176
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    • 2003
  • This Paper Presents a new measurement technique to derive the level of BSRC (Basic Science and Research Capacity) index by use of the factor analysis which is extended with the assumption of the standard normal probability distribution of the selected explanatory variables. The new measurement method is used to forecast the gap of Korea's BSRC level compared with those of major OECD countries in terms of time lag and to make their international comparison during the time period of 1981∼1999, based on the assumption that the BSRC progress function of each country takes the form of the logistic curve. The US BSRC index is estimated to be 0.9878 in 1981, 0.9996 in 1990 and 0.99991 in 1999, taking the 1st place. The US BSRC level has been consistently the top among the 16 selected variables, followed by Japan, Germany, France and the United Kingdom, in order. Korea's BSRC is estimated to be 0.2293 in 1981, taking the lowest place among the 16 OECD countries. However, Korea's BSRC indices are estimated to have been increased to 0.3216 (in 1990) and 0.44652 (in 1999) respectively, taking 10th place. Meanwhile, Korea's BSRC level in 1999 (0.44652) is estimated to reach those of the US and Japan in 2233 and 2101, respectively. This means that Korea falls 234 years behind USA and 102 years behind Japan, respectively. Korea is also estimated to lag 34 years behind Germany, 16 years behind France and the UK, 15 years behind Sweden, 11 years behind Canada, 7 years behind Finland, and 5 years behind the Netherlands. For the period of 1981∼1999, the BSRC development speed of the US is estimated to be 0.29700. Its rank is the top among the selected OECD countries, followed by Japan (0.12800), Korea (0.04443), and Germany (0.04029). the US BSRC development speed (0.2970) is estimated to be 2.3 times higher than that of Japan (0.1280), and 6.7 times higher than that of Korea. German BSRC development speed (0.04029) is estimated to be fastest in Europe, but it is 7.4 times slower than that of the US. The estimated BSRC development speeds of Belgium, Finland, Italy, Denmark and the UK stand between 0.01 and 0.02, which are very slow. Particularly, the BSRC development speed of Spain is estimated to be minus 0.0065, staying at the almost same level of BSRC over time (1981 ∼ 1999). Since Korea shows BSRC development speed much slower than those of the US and Japan but relative]y faster than those of other countries, the gaps in BSRC level between Korea and the other countries may get considerably narrower or even Korea will surpass possibly several countries in BSRC level, as time goes by. Korea's BSRC level had taken 10th place till 1993. However, it is estimated to be 6th place in 2010 by catching up the UK, Sweden, Finland and Holland, and 4th place in 2020 by catching up France and Canada. The empirical results are consistent with OECD (2001a)'s computation that Korea had the highest R&D expenditures growth during 1991∼1999 among all OECD countries ; and the value-added of ICT industries in total business sectors value added is 12% in Korea, but only 8% in Japan. And OECD (2001b) observed that Korea, together with the US, Sweden, and Finland, are already the four most knowledge-based countries. Hence, the rank of the knowledge-based country was measured by investment in knowledge which is defined as public and private spending on higher education, expenditures on R&D and investment in software.

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A Study on Clinical Variables Contributing to Differentiation of Delirium and Non-Delirium Patients in the ICU (중환자실 섬망 환자와 비섬망 환자 구분에 기여하는 임상 지표에 관한 연구)

  • Ko, Chanyoung;Kim, Jae-Jin;Cho, Dongrae;Oh, Jooyoung;Park, Jin Young
    • Korean Journal of Psychosomatic Medicine
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    • v.27 no.2
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    • pp.101-110
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    • 2019
  • Objectives : It is not clear which clinical variables are most closely associated with delirium in the Intensive Care Unit (ICU). By comparing clinical data of ICU delirium and non-delirium patients, we sought to identify variables that most effectively differentiate delirium from non-delirium. Methods : Medical records of 6,386 ICU patients were reviewed. Random Subset Feature Selection and Principal Component Analysis were utilized to select a set of clinical variables with the highest discriminatory capacity. Statistical analyses were employed to determine the separation capacity of two models-one using just the selected few clinical variables and the other using all clinical variables associated with delirium. Results : There was a significant difference between delirium and non-delirium individuals across 32 clinical variables. Richmond Agitation Sedation Scale (RASS), urinary catheterization, vascular catheterization, Hamilton Anxiety Rating Scale (HAM-A), Blood urea nitrogen, and Acute Physiology and Chronic Health Examination II most effectively differentiated delirium from non-delirium. Multivariable logistic regression analysis showed that, with the exception of vascular catheterization, these clinical variables were independent risk factors associated with delirium. Separation capacity of the logistic regression model using just 6 clinical variables was measured with Receiver Operating Characteristic curve, with Area Under the Curve (AUC) of 0.818. Same analyses were performed using all 32 clinical variables;the AUC was 0.881, denoting a very high separation capacity. Conclusions : The six aforementioned variables most effectively separate delirium from non-delirium. This highlights the importance of close monitoring of patients who received invasive medical procedures and were rated with very low RASS and HAM-A scores.