Yoon, Ji Hyung;Park, Sejun;Park, Sungchan;Moon, Kyung Hyun;Cheon, Sang Hyeon;Kwon, Taekmin
Investigative and Clinical Urology
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v.59
no.6
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pp.376-382
/
2018
Purpose: The authors performed this study to investigate the risk factors for predicting stent failure and to evaluate its impact on prognosis. Materials and Methods: Between January 2002 and March 2017, we retrospectively reviewed 117 consecutive patients who underwent retrograde ureteral stenting and exchanging at least once every 3 months for malignant ureteral obstruction. The patients were classified according to their pre-stenting chronic kidney disease (CKD) stage. The factors affecting stent failure were analyzed using a logistic regression model. Overall survival (OS) was estimated, and the prognostic significance of each variable was estimated using Cox proportional-hazards regression modeling. Results: Before stenting, 91 patients were CKD stages 1-3 and 26 patients were CKD stages 4-5. These two groups differed significantly only in pre-stenting estimated glomerular filtration rate (eGFR), bilateral obstruction, and pre-stenting pyuria. Among the 117 patients, stent failure occurred in 30 patients (25.6%), and there were no differences between the groups. Pre-stenting pyuria and post-stenting complications were significant predictors of stent failure. There were 79 deaths in total, including 56 in the CKD stages 1-3 group and 23 in the CKD stages 4-5 group. In the multivariate analysis predicting patient OS, pre-stenting eGFR and post-stenting disease progression were significant factors. Conclusions: Internal ureteral stenting was effective for maintaining renal function in malignant ureteral obstruction. However, it did not restore renal function, which is related to the prognosis of the patients. Therefore, to improve patients' renal function and prognosis, patients who require stenting must be quickly recognized and treated.
Objective: The impact of beta blockers (BBs) on survival outcomes in ovarian cancer was investigated. Methods: By using Korean National Health Insurance Service Data, Cox proportional hazards regression was performed to analyze hazard ratios (HRs) with 95% confidence intervals (CIs) adjusting for confounding factors. Results: Among 866 eligible patients, 206 (23.8%) were BB users and 660 (76.2%) were non-users. Among the 206 BB users, 151 (73.3%) were non-selective beta blocker (NSBB) users and 105 (51.0%) were selective beta blocker (SBB) users. BB use in patients aged ${\geq}60$ years, longer duration use (${\geq}1$ year), in patients with Charlson Comorbidity Index (CCI) ${\geq}3$, and in cardiovascular disease including hypertension was associated with better survival outcome. These findings were observed in both NSBB and SBB. When duration of medication was analyzed based on number of days, NSBB (${\geq}180$ days) was associated with improved overall survival (OS) with a relatively shorter period of use compared to SBB (${\geq}720$ days). In multivariate Cox proportional hazards model, longer duration of BB medication (${\geq}1$ year) was an independent favorable prognostic factor for both OS and disease-specific survival in ovarian cancer patients. Conclusion: In our nationwide population-based cohort study, BB use was associated with better survival outcomes in ovarian cancer in cases of long term duration of use, in older patients, and in cardiovascular and/or other underlying disease (CCI ${\geq}3$).
Purpose: Previous studies have demonstrated the usefulness of the controlling nutritional status (CONUT) score in nutritional assessment and survival prediction of patients with various malignancies. However, its value in advanced gastric cancer (GC) treated with neoadjuvant chemotherapy and curative gastrectomy remains unclear. Materials and Methods: The CONUT score at different time points (pretreatment, preoperative, and postoperative) of 272 patients with advanced GC were retrospectively calculated from August 2004 to October 2015. The χ2 test or Mann-Whitney U test was used to estimate the relationships between the CONUT score and clinical characteristics as well as short-term outcomes, while the Cox proportional hazard model was used to estimate long-term outcomes. Survival curves were estimated by using the Kaplan-Meier method and log-rank test. Results: The proportion of moderate or severe malnutrition among all patients was not significantly changed from pretreatment (13.5%) to pre-operation (11.7%) but increased dramatically postoperatively (47.5%). The pretreatment CONUT-high score (≥4) was significantly associated with older age (P=0.010), deeper tumor invasion (P=0.025), and lower pathological complete response rate (CONUT-high vs. CONUT-low: 1.2% vs. 6.6%, P=0.107). Pretreatment CONUT-high score patients had worse progression-free survival (P=0.032) and overall survival (OS) (P=0.026). Adjusted for pathologic node status, the pretreatment CONUT-high score was strongly associated with worse OS in pathologic node-positive patients (P=0.039). Conclusions: The pretreatment CONUT score might be a straightforward index for immune-nutritional status assessment, while being a reliable prognostic indicator in patients with advanced GC receiving neoadjuvant chemotherapy and curative gastrectomy. Moreover, lower pretreatment CONUT scores might indicate better chemotherapy responses.
Journal of Korean Society of Industrial and Systems Engineering
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v.44
no.4
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pp.1-11
/
2021
Recently, the importance of preventive maintenance has been emerging since failures in a complex system are automatically detected due to the development of artificial intelligence techniques and sensor technology. Therefore, prognostic and health management (PHM) is being actively studied, and prediction of the remaining useful life (RUL) of the system is being one of the most important tasks. A lot of researches has been conducted to predict the RUL. Deep learning models have been developed to improve prediction performance, but studies on identifying the importance of features are not carried out. It is very meaningful to extract and interpret features that affect failures while improving the predictive accuracy of RUL is important. In this paper, a total of six popular deep learning models were employed to predict the RUL, and identified important variables for each model through SHAP (Shapley Additive explanations) that one of the explainable artificial intelligence (XAI). Moreover, the fluctuations and trends of prediction performance according to the number of variables were identified. This paper can suggest the possibility of explainability of various deep learning models, and the application of XAI can be demonstrated. Also, through this proposed method, it is expected that the possibility of utilizing SHAP as a feature selection method.
Purpose: The scoring system for traumatic liver injury (SSTLI) was developed in 2015 to predict mortality in patients with polytraumatic liver injury. This study aimed to validate the SSTLI as a prognostic factor in patients with polytrauma and liver injury through a generalized estimating equation analysis. Methods: The medical records of 521 patients with traumatic liver injury from January 2015 to December 2019 were reviewed. The primary outcome variable was in-hospital mortality. All the risk factors were analyzed using multivariate logistic regression analysis. The SSTLI has five clinical measures (age, Injury Severity Score, serum total bilirubin level, prothrombin time, and creatinine level) chosen based on their predictive power. Each measure is scored as 0-1 (age and Injury Severity Score) or 0-3 (serum total bilirubin level, prothrombin time, and creatinine level). The SSTLI score corresponds to the total points for each item (0-11 points). Results: The areas under the curve of the SSTLI to predict mortality on post-traumatic days 0, 1, 3, and 5 were 0.736, 0.783, 0.830, and 0.824, respectively. A very good to excellent positive correlation was observed between the probability of mortality and the SSTLI score (γ=0.997, P<0.001). A value of 5 points was used as the threshold to distinguish low-risk (<5) from high-risk (≥5) patients. Multivariate analysis using the generalized estimating equation in the logistic regression model indicated that the SSTLI score was an independent predictor of mortality (odds ratio, 1.027; 95% confidence interval, 1.018-1.036; P<0.001). Conclusions: The SSTLI was verified to predict mortality in patients with polytrauma and liver injury. A score of ≥5 on the SSTLI indicated a high-risk of post-traumatic mortality.
Dhruv S. Shankar;Edward S. Mojica;Christopher A. Colasanti;Anna M. Blaeser;Paola F. Ortega;Guillem Gonzalez-Lomas;Laith M. Jazrawi
Clinics in Shoulder and Elbow
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v.26
no.1
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pp.32-40
/
2023
Background: The purpose of this study was to identify predictors of the time from initial presentation to total shoulder arthroplasty (TSA) in patients with primary glenohumeral osteoarthritis (OA) and rotator cuff (RTC) arthropathy who were conservatively managed with corticosteroid injections. Methods: We conducted a retrospective cohort study of patients who underwent TSA from 2010 to 2021. Kaplan-Meier survival analysis was used to estimate median time to TSA for primary OA and RTC arthropathy patients. The Cox proportional hazards model was used to identify significant predictors of time to TSA and to calculate hazard ratios (HRs) with 95% confidence intervals (CIs). Statistical significance was set at P<0.05. Results: The cohort included 160 patients with primary OA and 92 with RTC arthropathy. In the primary OA group, median time to TSA was 15 months. Significant predictors of shorter time to TSA were older age at presentation (HR, 1.02; 95% CI, 1.00-1.04; P=0.03) and presence of moderate or severe acromioclavicular joint arthritis (HR, 1.45; 95% CI, 1.05-2.01; P=0.03). In the RTC arthropathy group, median time to TSA was 14 months, and increased number of corticosteroid injections was associated with longer time to TSA (HR, 0.87; 95% CI, 0.80-0.95; P=0.003). Conclusions: There are distinct prognostic factors for progression to TSA between primary OA patients and RTC arthropathy patients managed with corticosteroid injections. Multiple corticosteroid injections are associated with delayed time to TSA in RTC arthropathy patients.
We tested how adjuvants effect in a cancer vaccine model using an epitope derived from an autoactivation loop of membrane-type protease serine protease 14 (PRSS14; loop metavaccine) in mouse mammary tumor virus (MMTV)-polyoma middle tumor-antigen (PyMT) system and in 2 other orthotopic mouse systems. Earlier, we reported that loop metavaccine effectively prevented progression and metastasis regardless of adjuvant types and TH types of hosts in tail-vein injection systems. However, the loop metavaccine with Freund's complete adjuvant (CFA) reduced cancer progression and metastasis while that with alum, to our surprise, were adversely affected in 3 tumor bearing mouse models. The amounts of loop peptide specific antibodies inversely correlated with tumor burden and metastasis, meanwhile both TH1 and TH2 isotypes were present regardless of host type and adjuvant. Tumor infiltrating myeloid cells such as eosinophil, monocyte, and neutrophil were asymmetrically distributed among 2 adjuvant groups with loop metavaccine. Systemic expression profiling using the lymph nodes of the differentially immunized MMTV-PyMT mouse revealed that adjuvant types, as well as loop metavaccine can change the immune signatures. Specifically, loop metavaccine itself induces TH2 and TH17 responses but reduces TH1 and Treg responses regardless of adjuvant type, whereas CFA but not alum increased follicular TH response. Among the myeloid signatures, eosinophil was most distinct between CFA and alum. Survival analysis of breast cancer patients showed that eosinophil chemokines can be useful prognostic factors in PRSS14 positive patients. Based on these observations, we concluded that multiple immune parameters are to be considered when applying a vaccine strategy to cancer patients.
International Journal of Computer Science & Network Security
/
v.23
no.12
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pp.167-174
/
2023
Electronic educational environments in the conditions of quarantine restrictions of COVID-19 have become a common phenomenon for the organization of distance educational activities. Under the conditions of Russian aggression, Ukrainian proof of their use is unique. The purpose of the article is to analyze the role of electronic educational environments in the process of training applicants for higher education in Ukraine in the realities of a large-scale war. General scientific methods (analysis, synthesis, deduction, and induction) and special pedagogical prognostic methods, modeling, and SWOT analysis methods were used. In the results, the general properties of the Internet educational platforms common in Ukraine, the peculiarities of using the Moodle and Prometheus platforms, and an approximate model of the electronic learning environment were discussed. The reasons for the popularity of Moodle among Ukrainian universities are analyzed, but vulnerable elements related to security are emphasized. It was also determined that the high cost of Prometheus software and less functionality made this learning environment less relevant. The conclusions state that the military actions drew the attention of universities in Ukraine to the formation of their own educational platforms. This is especially relevant for technical and military institutions of higher education.
Dong Jin Im;Jin Hur;Kyunghwa Han;Young Joo Suh;Yoo Jin Hong;Hye-Jeong Lee;Young Jin Kim;Byoung Wook Choi
Korean Journal of Radiology
/
v.21
no.9
/
pp.1095-1103
/
2020
Objective: The present study aimed to investigate whether quantitative dual-energy computed tomography (DECT) parameters offer an incremental risk stratification benefit over the CT ventricular diameter ratio in patients with acute pulmonary embolism (PE) by using propensity score analysis. Materials and Methods: This study was conducted on 480 patients with acute PE who underwent CT pulmonary angiography (CTPA) or DECT pulmonary angiography (DE CT-PA). This propensity-matched study population included 240 patients with acute PE each in the CTPA and DECT groups. Altogether, 260 (54.1%) patients were men, and the mean age was 64.9 years (64.9 ± 13.5 years). The primary endpoint was all-cause death within 30 days. The Cox proportional hazards regression model was used to identify associations between CT parameters and outcomes and to identify potential predictors. Concordance (C) statistics were used to compare the prognoses between the two groups. Results: In both CTPA and DECT groups, right to left ventricle diameter ratio ≥ 1 was associated with an increased risk of all-cause death within 30 days (hazard ratio: 3.707, p < 0.001 and 5.573, p < 0.001, respectively). However, C-statistics showed no statistically significant difference between the CTPA and DECT groups for predicting death within 30 days (C-statistics: 0.759 vs. 0.819, p = 0.117). Conclusion: Quantitative measurement of lung perfusion defect volume by DECT had no added benefit over CT ventricular diameter ratio for predicting all-cause death within 30 days.
Levels of platelets and other hematological values were monitored in 21 Saimiri and 12 Aotus monkeys over a period of three weeks post·infection with monkey·adapted Indochina CDC-1 strain of Plasmedium falciparum. In both Snlinoiri sciureus boliviensis and Aetus nancymai karyotype-1 monkeys the severest thrombocytopenia was observed at 14 days post-infection coinciding with peak parasitemia, neutropenia, Iynlphocytosis, and anemia associated with severe hemoglobinemia and elevated fibrinogen degeneration products(FDP's), MCH and MCV profiles in Aotus monkeys decreased with ascending parasitemia. In contrast, these parameters in Saimiri were characterized by a significant compensatory increase correlating with parasitemia. In general, thrombocytopenia was one of the earliest clinical manifestations of the infection with the platelets returning to normal levels shortly after peak parasitenlia at 14 days. Platelet kinetics had a strong correlation with hematologic and parasitologic values in the Aotus nlodel. No consistent associations were observed between platelet kinetics and other parameters in the Saimiri model. These data indicate that the Aotus model for malaria is more predictable than the Saimiri. Further, platelet turnover rates and recovery provide a useful prognostic parameter during malaria infection. The results are discussed in relation to the value of the two species of monkeys as models for the pathogenesis of human malaria.
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