• Title/Summary/Keyword: Regression Curve

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Incidence of Obesity-related Diabetes Mellitus in Adults with Prediabetes: Use of Data from a Prospective Cohort Study (당뇨전단계 성인의 비만이 당뇨병 발생 위험에 미치는 영향: 전향적 코호트 자료의 활용)

  • Han, Nara;Cho, HyangSoon;Ju, Jeong Suk;Lee, Kyoung Mee
    • Journal of East-West Nursing Research
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    • v.29 no.2
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    • pp.106-116
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    • 2023
  • Purpose: The purpose of this study was to identify the impact of obesity on the incidence of diabetes mellitus in adults with pre-diabetes. Methods: This study employed a longitudinal study design and utilized secondary data drawn from the Korean Genome and Epidemiology Study. This study used data from a sample of 3,693 adults with prediabetes who were followed every two years from 2001 to 2018. Statistical data analysis for frequency, number of cases per 1,000 person-years, log-rank test, Kaplan-Meier curve, and Cox's proportional hazards regression analysis was performed using IBM SPSS statistics version 26. Results: During the observation period, there were 1,309 (35.4%) patients with diabetes, and the total number of person-years was 35,342. The incidence of diabetes was higher in the obese group compared to the normal weight group (body mass index [BMI]: hazard ratio=1.57, 95% confidence interval [CI]=1.40~1.77, waist: hazard ratio=1.55, 95% CI=1.38~1.76, waist to hip ratio [WHR]: hazard ratio=1.53, 95% CI=1.24~1.89, body fat [BF] (%): hazard ratio=1.42, 95% CI=1.27~1.61). Conclusion: An increase in BMI, waist circumference, and WHR, which are indicators of obesity, can exacerbate the risk factors for diabetes. Thus, a decrease in BMI, waist circumference, and WHR is necessary to prevent pre-diabetes. In particular, health care professionals should provide individualized weight management program interventions, including adult obesity programs and obesity counseling in partnership with local health departments, to reduce BMI and waist circumference in people at high risk for diabetes.

Noncontrast Computed Tomography-Based Radiomics Analysis in Discriminating Early Hematoma Expansion after Spontaneous Intracerebral Hemorrhage

  • Zuhua Song;Dajing Guo;Zhuoyue Tang;Huan Liu;Xin Li;Sha Luo;Xueying Yao;Wenlong Song;Junjie Song;Zhiming Zhou
    • Korean Journal of Radiology
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    • v.22 no.3
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    • pp.415-424
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    • 2021
  • Objective: To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH). Materials and Methods: We retrospectively reviewed 261 patients with sICH who underwent initial NCCT within 6 hours of ictus and follow-up CT within 24 hours after initial NCCT, between April 2011 and March 2019. The clinical characteristics, imaging signs and radiomics features extracted from the initial NCCT images were used to construct models to discriminate early HE. A clinical-radiologic model was constructed using a multivariate logistic regression (LR) analysis. Radiomics models, a radiomics-radiologic model, and a combined model were constructed in the training cohort (n = 182) and independently verified in the validation cohort (n = 79). Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate the discriminative power. Results: The AUC of the clinical-radiologic model for discriminating early HE was 0.766. The AUCs of the radiomics model for discriminating early HE built using the LR algorithm in the training and validation cohorts were 0.926 and 0.850, respectively. The AUCs of the radiomics-radiologic model in the training and validation cohorts were 0.946 and 0.867, respectively. The AUCs of the combined model in the training and validation cohorts were 0.960 and 0.867, respectively. Conclusion: NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE.

CT-Based Fagotti Scoring System for Non-Invasive Prediction of Cytoreduction Surgery Outcome in Patients with Advanced Ovarian Cancer

  • Na Young Kim;Dae Chul Jung;Jung Yun Lee;Kyung Hwa Han;Young Taik Oh
    • Korean Journal of Radiology
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    • v.22 no.9
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    • pp.1481-1489
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    • 2021
  • Objective: To construct a CT-based Fagotti scoring system by analyzing the correlations between laparoscopic findings and CT features in patients with advanced ovarian cancer. Materials and Methods: This retrospective cohort study included patients diagnosed with stage III/IV ovarian cancer who underwent diagnostic laparoscopy and debulking surgery between January 2010 and June 2018. Two radiologists independently reviewed preoperative CT scans and assessed ten CT features known as predictors of suboptimal cytoreduction. Correlation analysis between ten CT features and seven laparoscopic parameters based on the Fagotti scoring system was performed using Spearman's correlation. Variable selection and model construction were performed by logistic regression with the least absolute shrinkage and selection operator method using a predictive index value (PIV) ≥ 8 as an indicator of suboptimal cytoreduction. The final CT-based scoring system was internally validated using 5-fold cross-validation. Results: A total of 157 patients (median age, 56 years; range, 27-79 years) were evaluated. Among 120 (76.4%) patients with a PIV ≥ 8, 105 patients received neoadjuvant chemotherapy followed by interval debulking surgery, and the optimal cytoreduction rate was 90.5% (95 of 105). Among 37 (23.6%) patients with PIV < 8, 29 patients underwent primary debulking surgery, and the optimal cytoreduction rate was 93.1% (27 of 29). CT features showing significant correlations with PIV ≥ 8 were mesenteric involvement, gastro-transverse mesocolon-splenic space involvement, diaphragmatic involvement, and para-aortic lymphadenopathy. The area under the receiver operating curve of the final model for prediction of PIV ≥ 8 was 0.72 (95% confidence interval: 0.62-0.82). Conclusion: Central tumor burden and upper abdominal spread features on preoperative CT were identified as distinct predictive factors for high PIV on diagnostic laparoscopy. The CT-based PIV prediction model might be useful for patient stratification before cytoreduction surgery for advanced ovarian cancer.

The Impact of Right Atrial Size to Predict Success of Direct Current Cardioversion in Patients With Persistent Atrial Fibrillation

  • Christoph Doring;Utz Richter;Stefan Ulbrich;Carsten Wunderlich;Micaela Ebert;Sergio Richter;Axel Linke;Krunoslav Michael Sveric
    • Korean Circulation Journal
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    • v.53 no.5
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    • pp.331-343
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    • 2023
  • Background and Objectives: The prognostic implication of right atrial (RA) and left atrial (LA) size for an immediate success of direct current cardioversion (DCCV) in atrial fibrillation (AF) remains unclear. This study aimed to compare RA and LA size for the prediction of DCCV success. Methods: Between 2012 and 2018, 734 consecutive outpatients were screened for our prospective registry. Each eligible patient received a medical history, blood analysis, and transthoracic echocardiography with a focus on indexed RA (iRA) area and LA volume (iLAV) prior to DCCV with up to three biphasic shocks (200-300-360 J) or additional administration of amiodarone or flecainide to restore sinus rhythm. Results: We enrolled 589 patients, and DCCV was in 89% (n=523) successful. Mean age was 68 ± 10 years, and 40% (n=234) had New York heart association class >II. A prevalence of the male sex (64%, n=376) and of persistent AF (86%, n=505) was observed. Although DCCV success was associated with female sex (odds ratio [OR], 1.88; 95% confidence interval [CI], 1.06-3.65), with absence of coronary heart disease and normal left ventricular function (OR, 2.24; 95% CI, 1.26-4.25), with short AF duration (OR, 1.93; 95% CI, 1.05-4.04) in univariable regression, only iRA area remained a stable and independent predictor of DCCV success (OR, 0.27; 95% CI, 0.12-0.69; area under the curve 0.71), but not iLAV size (OR, 1.16; 95% CI, 1.05-1.56) in multivariable analysis. Conclusions: iRA area is superior to iLAV for the prediction of immediate DCCV success in AF.

Contrast-Enhanced CT and Ultrasonography Features of Intracholecystic Papillary Neoplasm with or without associated Invasive Carcinoma

  • Jae Hyun Kim;Jung Hoon Kim;Hyo-Jin Kang;Jae Seok Bae
    • Korean Journal of Radiology
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    • v.24 no.1
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    • pp.39-50
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    • 2023
  • Objective: To assess the contrast-enhanced CT and ultrasonography (US) findings of intracholecystic papillary neoplasm (ICPN) and determine the imaging features predicting ICPN associated with invasive carcinoma (ICPN-IC). Materials and Methods: In this retrospective study, we enrolled 119 consecutive patients, including 60 male and 59 female, with a mean age ± standard deviation of 63.3 ± 12.1 years, who had pathologically confirmed ICPN (low-grade dysplasia [DP] = 34, high-grade DP = 35, IC = 50) and underwent preoperative CT or US. Two radiologists independently assessed the CT and US findings, focusing on wall and polypoid lesion characteristics. The likelihood of ICPN-IC was graded on a 5-point scale. Univariable and multivariable logistic regression analyses were performed to identify significant predictors of ICPN-IC separately for wall and polypoid lesion findings. The performances of CT and US in distinguishing ICPN-IC from ICPN with DP (ICPN-DP) was evaluated using the area under the receiver operating characteristic curve (AUC). Results: For wall characteristics, the maximum wall thickness (adjusted odds ratio [aOR] = 1.4; 95% confidence interval [CI]: 1.1-1.9) and mucosal discontinuity (aOR = 5.6; 95% CI: 1.3-23.4) on CT were independently associated with ICPN-IC. Among 119 ICPNs, 110 (92.4%) showed polypoid lesions. Regarding polypoid lesion findings, multiplicity (aOR = 4.0; 95% CI: 1.6-10.4), lesion base wall thickening (aOR = 6.0; 95% CI: 2.3-15.8) on CT, and polyp size (aOR = 1.1; 95% CI: 1.0-1.2) on US were independently associated with ICPN-IC. CT showed a higher diagnostic performance than US in predicting ICPN-IC (AUC = 0.793 vs. 0.676; p = 0.002). Conclusion: ICPN showed polypoid lesions and/or wall thickening on CT or US. A thick wall, multiplicity, presence of wall thickening in the polypoid lesion base, and large polyp size are imaging findings independently associated with invasive cancer and may be useful for differentiating ICPN-IC from ICPN-DP.

Prediction of Venous Trans-Stenotic Pressure Gradient Using Shape Features Derived From Magnetic Resonance Venography in Idiopathic Intracranial Hypertension Patients

  • Chao Ma;Haoyu Zhu;Shikai Liang;Yuzhou Chang;Dapeng Mo;Chuhan Jiang;Yupeng Zhang
    • Korean Journal of Radiology
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    • v.25 no.1
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    • pp.74-85
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    • 2024
  • Objective: Idiopathic intracranial hypertension (IIH) is a condition of unknown etiology associated with venous sinus stenosis. This study aimed to develop a magnetic resonance venography (MRV)-based radiomics model for predicting a high trans-stenotic pressure gradient (TPG) in IIH patients diagnosed with venous sinus stenosis. Materials and Methods: This retrospective study included 105 IIH patients (median age [interquartile range], 35 years [27-42 years]; female:male, 82:23) who underwent MRV and catheter venography complemented by venous manometry. Contrast enhanced-MRV was conducted under 1.5 Tesla system, and the images were reconstructed using a standard algorithm. Shape features were derived from MRV images via the PyRadiomics package and selected by utilizing the least absolute shrinkage and selection operator (LASSO) method. A radiomics score for predicting high TPG (≥ 8 mmHg) in IIH patients was formulated using multivariable logistic regression; its discrimination performance was assessed using the area under the receiver operating characteristic curve (AUROC). A nomogram was constructed by incorporating the radiomics scores and clinical features. Results: Data from 105 patients were randomly divided into two distinct datasets for model training (n = 73; 50 and 23 with and without high TPG, respectively) and testing (n = 32; 22 and 10 with and without high TPG, respectively). Three informative shape features were identified in the training datasets: least axis length, sphericity, and maximum three-dimensional diameter. The radiomics score for predicting high TPG in IIH patients demonstrated an AUROC of 0.906 (95% confidence interval, 0.836-0.976) in the training dataset and 0.877 (95% confidence interval, 0.755-0.999) in the test dataset. The nomogram showed good calibration. Conclusion: Our study presents the feasibility of a novel model for predicting high TPG in IIH patients using radiomics analysis of noninvasive MRV-based shape features. This information may aid clinicians in identifying patients who may benefit from stenting.

Nomogram Models for Distinguishing Intraductal Carcinoma of the Prostate From Prostatic Acinar Adenocarcinoma Based on Multiparametric Magnetic Resonance Imaging

  • Ling Yang;Xue-Ming Li;Meng-Ni Zhang;Jin Yao;Bin Song
    • Korean Journal of Radiology
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    • v.24 no.7
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    • pp.668-680
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    • 2023
  • Objective: To compare multiparametric magnetic resonance imaging (MRI) features of intraductal carcinoma of the prostate (IDC-P) with those of prostatic acinar adenocarcinoma (PAC) and develop prediction models to distinguish IDC-P from PAC and IDC-P with a high proportion (IDC ≥ 10%, hpIDC-P) from IDC-P with a low proportion (IDC < 10%, lpIDC-P) and PAC. Materials and Methods: One hundred and six patients with hpIDC-P, 105 with lpIDC-P and 168 with PAC, who underwent pretreatment multiparametric MRI between January 2015 and December 2020 were included in this study. Imaging parameters, including invasiveness and metastasis, were evaluated and compared between the PAC and IDC-P groups as well as between the hpIDC-P and lpIDC-P subgroups. Nomograms for distinguishing IDC-P from PAC, and hpIDC-P from lpIDC-P and PAC, were made using multivariable logistic regression analysis. The discrimination performance of the models was assessed using the receiver operating characteristic area under the curve (ROC-AUC) in the sample, where the models were derived from without an independent validation sample. Results: The tumor diameter was larger and invasive and metastatic features were more common in the IDC-P than in the PAC group (P < 0.001). The distribution of extraprostatic extension (EPE) and pelvic lymphadenopathy was even greater, and the apparent diffusion coefficient (ADC) ratio was lower in the hpIDC-P than in the lpIDC-P group (P < 0.05). The ROC-AUCs of the stepwise models based solely on imaging features for distinguishing IDC-P from PAC and hpIDC-P from lpIDC-P and PAC were 0.797 (95% confidence interval, 0.750-0.843) and 0.777 (0.727-0.827), respectively. Conclusion: IDC-P was more likely to be larger, more invasive, and more metastatic, with obviously restricted diffusion. EPE, pelvic lymphadenopathy, and a lower ADC ratio were more likely to occur in hpIDC-P, and were also the most useful variables in both nomograms for predicting IDC-P and hpIDC-P.

Predicting serum acetaminophen concentrations in acute poisoning for safe termination of N-acetylcysteine in a resource-limited environment (약물농도를 알 수 없는 환경에서 acetaminophen 급성 중독환자의 안전한 N-acetylcysteine 치료 종료를 위한 혈중약물 검출 예측)

  • Dahae Kim;Kyungman Cha;Byung Hak So
    • Journal of The Korean Society of Clinical Toxicology
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    • v.21 no.2
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    • pp.128-134
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    • 2023
  • Purpose: The Prescott nomogram has been utilized to forecast hepatotoxicity from acute acetaminophen poisoning. In developing countries, emergency medical centers lack the resources to report acetaminophen concentrations; thus, the commencement and cessation of treatment are based on the reported dose. This study investigated risk factors that can predict acetaminophen detection after 15 hours for safe treatment termination. Methods: Data were collected from an urban emergency medical center from 2010 to 2020. The study included patients ≥14 years of age with acute acetaminophen poisoning within 15 hours. The correlation between risk factors and detection of acetaminophen 15 hours after ingestion was evaluated using logistic regression, and the area under the curve (AUC) was calculated. Results: In total, 181 patients were included in the primary analysis; the median dose was 150.9 mg/kg and 35 patients (19.3%) had acetaminophen detected 15 hours after ingestion. The dose per weight and the time to visit were significant predictors for acetaminophen detection after 15 hours (odds ratio, 1.020 and 1.030, respectively). The AUCs were 0.628 for a 135 mg/kg cut-off value and 0.658 for a cut-off 450 minutes, and that of the combined model was 0.714 (sensitivity: 45.7%, specificity: 91.8%). Conclusion: Where acetaminophen concentrations are not reported during treatment following the UK guidelines, it is safe to start N-acetylcysteine immediately for patients who are ≥14 years old, visit within 15 hours after acute poisoning, and report having ingested ≥135 mg/kg. Additional N-acetylcysteine doses should be considered for patients visiting after 8 hours.

GeoAI-Based Forest Fire Susceptibility Assessment with Integration of Forest and Soil Digital Map Data

  • Kounghoon Nam;Jong-Tae Kim;Chang-Ju Lee;Gyo-Cheol Jeong
    • The Journal of Engineering Geology
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    • v.34 no.1
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    • pp.107-115
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    • 2024
  • This study assesses forest fire susceptibility in Gangwon-do, South Korea, which hosts the largest forested area in the nation and constitutes ~21% of the country's forested land. With 81% of its terrain forested, Gangwon-do is particularly susceptible to wildfires, as evidenced by the fact that seven out of the ten most extensive wildfires in Korea have occurred in this region, with significant ecological and economic implications. Here, we analyze 480 historical wildfire occurrences in Gangwon-do between 2003 and 2019 using 17 predictor variables of wildfire occurrence. We utilized three machine learning algorithms—random forest, logistic regression, and support vector machine—to construct wildfire susceptibility prediction models and identify the best-performing model for Gangwon-do. Forest and soil map data were integrated as important indicators of wildfire susceptibility and enhanced the precision of the three models in identifying areas at high risk of wildfires. Of the three models examined, the random forest model showed the best predictive performance, with an area-under-the-curve value of 0.936. The findings of this study, especially the maps generated by the models, are expected to offer important guidance to local governments in formulating effective management and conservation strategies. These strategies aim to ensure the sustainable preservation of forest resources and to enhance the well-being of communities situated in areas adjacent to forests. Furthermore, the outcomes of this study are anticipated to contribute to the safeguarding of forest resources and biodiversity and to the development of comprehensive plans for forest resource protection, biodiversity conservation, and environmental management.

Simultaneous resection of synchronous colorectal liver metastasis: Feasibility and development of a prediction model

  • Mufaddal Kazi;Shraddha Patkar;Prerak Patel;Aditya Kunte;Ashwin Desouza;Avanish Saklani;Mahesh Goel
    • Annals of Hepato-Biliary-Pancreatic Surgery
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    • v.27 no.1
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    • pp.40-48
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    • 2023
  • Backgrounds/Aims: Timing of resection for synchronous colorectal liver metastasis (CRLM) has been debated for decades. The aim of the present study was to assess the feasibility of simultaneous resection of CRLM in terms of major complications and develop a prediction model for safe resections. Methods: A retrospective single-center study of synchronous, resectable CRLM, operated between 2013 and 2021 was conducted. Upper limit of 95% confidence interval (CI) of major complications (≥ grade IIIA) was set at 40% as the safety threshold. Logistic regression was used to determine predictors of morbidity. Prediction model was internally validated by bootstrap estimates, Harrell's C-index, and correlation of predicted and observed estimates. Results: Ninety-two patients were operated. Of them, 41.3% had rectal cancers. Major hepatectomy (≥ 4 segments) was performed for 25 patients (27.2%). Major complications occurred in 20 patients (21.7%, 95% CI: 13.8%-31.5%). Predictors of complications were the presence of comorbidities and major hepatectomy (area under the ROC curve: 0.692). Unacceptable level of morbidity (≥ 40%) was encountered in patients with comorbidities who underwent major hepatectomy. Conclusions: Simultaneous bowel and CRLM resection appear to be safe. However, caution should be exercised when combining major liver resections with bowel resection in patients with comorbid conditions.