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Finding an adequate dose of the drug by revealing the dose–response relationship is very crucial and a challenging problem in the clinical development. The main concerns in dose‐finding study are to identify a minimum effective dose (MED) in anesthesia studies and maximum tolerated dose (MTD) in oncology clinical trials. For the estimation of MED and MTD, we propose two modifications of Firth's logistic regression using reparametrization, called reparametrized Firth's logistic regression (rFLR) and ridge‐penalized reparametrized Firth's logistic regression (RrFLR). The proposed methods are designed by directly reducing the small‐sample bias of the maximum likelihood estimate for the parameter of interest. In addition, we develop a method on how to construct confidence intervals for rFLR and RrFLR using profile penalized likelihood. In the up‐and‐down biased‐coin design, numerical studies confirm the superior performance of the proposed methods in terms of the mean squared error, bias, and coverage accuracy of confidence intervals. [ABSTRACT FROM AUTHOR]

This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF) and ensemble smoother (ES) as representative frameworks, discusses their pros and cons, and investigates recent progress to overcome their drawbacks. The typical weaknesses of ensemble-based methods are non-Gaussian parameters, improper prior ensembles and finite population size. Three categorized approaches, to mitigate these limitations, are reviewed with recent accomplishments; improvement of Kalman gains, add-on of transformation functions, and independent evaluation of observed data. The data assimilation in heterogeneous reservoirs, applying the improved ensemble methods, is discussed on predicting unknown dynamic data in reservoir characterization. [ABSTRACT FROM AUTHOR]

Abstracts Reservoir characterization is one of the most important works for decision makings in petroleum industry. Ensemble Kalman filter (EnKF) has been researched for history matching, but it requires lots of simulation time. Although ensemble smoother (ES) is much faster than EnKF, it is hard to apply for complex models such as channelized reservoirs due to overshooting and filter divergence problems. The concept of clustered covariance has been proposed only for 2D reservoirs using ES to keep simulation time low and improve history matching results. In this research, a distance-based method and ES with clustered covariance (ESC) are applied to 3D channel fields for the first time. At first, the distance-based method, which consists of Hausdorff distance, multidimensional scaling, and K-means clustering, is successfully applied to 3D fields. Ensemble members in the same group show similar facies distributions and connectivity. Secondly, ESC is compared to a standard EnKF and ES. Updated models from the two methods cannot preserve bimodal distribution and future productions of them show biased predictions. Due to vertical heterogeneity and bimodal distribution of reservoir permeability, it is hard to assimilate reliably for EnKF and ES methods alone in 3D channelized reservoirs. However, ESC manages overshooting problem in ES and preserves bimodal distribution with reliable uncertainty ranges in reservoir performances. It requires about 4% of history matching time of EnKF for the cases tested. Furthermore, only 10 reservoir models selected from the distance-based clustering can replace 200 total ensembles for uncertainty quantification. Therefore, ESC can be applicable to 3D channelized reservoirs with geological uncertainties. [ABSTRACT FROM AUTHOR]

Susceptible–exposed–infectious–recovered (SEIR) models were applied to assess the effectiveness of non-pharmaceutical interventions (NPIs) and to study the dynamic behavior of the COVID-19 pandemic. Recently, SEIR models have evolved to address the change of human mobility by some NPIs for predicting the new confirmed cases. However, the models have serious limitations when applied to Seoul. Seoul has two representative quarantine policies, i.e. social distancing and the ban on gatherings. Effects of the two policies need to be reflected in different functional forms in the model because changes in human mobility do not fully reflect the ban on gatherings. Thus we propose a modified SEIR model to assess the effectiveness of social distancing, ban on gatherings and vaccination strategies. The application of the modified SEIR model was illustrated by comparing the model output with real data. • Seoul has two quarantine policies such as social distancing and ban on gatherings. • Ban on gatherings aims to mitigate the risk of mass infection in various facilities. • We propose a modified SEIR model to assess the effectiveness of the two policies. • Effects of the two policies need to be reflected in different functional forms. [ABSTRACT FROM AUTHOR]

Multi-color flow cytometry is the standard approach for immunophenotyping clinical samples. With the recent advances in cancer immunotherapy, myeloid-derived suppressor cells (MDSC), immature myeloid-lineage cells in cancer patient blood and the tumor microenvironment, are highlighted as an important immune cell population that correlates with prognosis and therapeutic efficacy. In contrast to their clear functions and existence, immunophenotyping of MDSC is not consistent among investigators due to surface antigens overlapping with many normal hematopoietic lineage cell populations. We performed a clinical study and analyzed more than 1000 breast cancer patients blood samples to quantitate MDSC during breast cancer progression. In this methodology manuscript, we described detailed procedures for study design, sample logistics and handling, staining and flow cytometric analysis. This protocol used a 7-color fluorochrome-conjugated antibody panel to analyze polymorphonuclear (PMN)- and monocytic (M)-MDSC subsets simultaneously. The interim analysis results of this study showed that both PMN and M-MDSC populations are increased in patients with bone metastasis compared with patients with visceral organ metastasis. In conclusion, this work provides a versatile, comprehensive, and practical protocol to measure MDSC in patient blood samples. [ABSTRACT FROM AUTHOR]

Introduction: Owing to the coronavirus disease 19 pandemic, the demand for telemedicine has increased. However, the awareness of and experience with telemedicine among the Korean population have not been investigated. Therefore, we examined Korean outpatients' experience with and awareness of telemedicine. Methods: From December 2020 to March 2021, we conducted a survey exploring the awareness of and experience with telemedicine of outpatients who were consecutively enrolled by family physicians from four hospitals. The participants completed questionnaires on sociodemographic characteristics and knowledge, experience, satisfaction, preference, and future considerations concerning telemedicine. We evaluated factors associated with satisfaction with telemedicine experiences using multivariate logistic regression analysis. Results: Among the 563 study participants, 364 participants had experience with telemedicine. More than 95% of the telemedicine visits were performed by telephone consultation, and the most common disease type for telemedicine visits was chronic diseases (67.5%). Overall, 82.4% of the participants were satisfied with telemedicine. More than 90% of the participants were satisfied with telemedicine in terms of saving time and money relative to hospital visits, no risk of infection, and convenience. According to the multivariate logistic regression analysis, adults aged ≥65 years (odds ratio [OR] 3.53, 95% confidence interval [CI] 1.44–8.68), residents of a metropolitan city (OR 6.8, 95% CI 1.41–32.55), and those with knowledge of telemedicine (OR 2.96, 95% CI 1.21–7.26) were more likely to be satisfied with their telemedicine experience, compared with their counterparts. For chronic diseases, participants with telemedicine experience were significantly more likely to prefer telemedicine for revisits, compared with those with no telemedicine experience. Nonetheless, most respondents recognized that telemedicine requires improvement. Conclusions: Most Korean outpatients showed high satisfaction with telemedicine. Telemedicine may be considered in various medical situations in the future. Therefore, building a practical system for telemedicine and changes in the medical environment are required. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has been suggested to improve the performance of prediction models. Nevertheless, research on predicting the risk in patients with acute myocardial infarction (AMI) has been limited and showed inconsistency in the performance of ML models versus traditional models (TMs). This study developed ML-based models (logistic regression with regularization, random forest, support vector machine, and extreme gradient boosting) and compared their performance in predicting the short- and long-term mortality of patients with AMI with those of TMs with comparable predictors. The endpoints were the in-hospital mortality of 14,183 participants and the three- and 12-month mortality in patients who survived at discharge. The performance of the ML models in predicting the mortality of patients with an ST-segment elevation myocardial infarction (STEMI) was comparable to the TMs. In contrast, the areas under the curves (AUC) of the ML models for non-STEMI (NSTEMI) in predicting the in-hospital, 3-month, and 12-month mortality were 0.889, 0.849, and 0.860, respectively, which were superior to the TMs, which had corresponding AUCs of 0.873, 0.795, and 0.808. Overall, the performance of the predictive model could be improved, particularly for long-term mortality in NSTEMI, from the ML algorithm rather than using more clinical predictors. [ABSTRACT FROM AUTHOR]

Background: The survival rate of breast cancer survivors (BCSs) is > 90%. Particular issues are upper arm dysfunction caused by surgery and treatments. Physical activity has been recommended to improve shoulder function and quality of life (QoL) in BCSs. However, rehabilitation programs tend not to be continuous.Purpose: To explore the effectiveness of therapeutic inflatable ball self-exercise for improving shoulder function and QoL in breast cancer survivors (BCSs) following breast cancer surgery.Patients and Methods: Seventy-two BCSs were allocated to two groups, conventional self-exercise (CSE; n = 34; age, 48.9 ± 7.2 years) and therapeutic inflatable ball self-exercise (IBE; n = 38; age, 47.7 ± 8.9 years); 22 in the CSE and 23 in the IBE group completed the interventions. Both groups performed intervention for 12 weeks, three times per week and 15 min a day at least. Measurement was performed three times for shoulder range of motion (ROM), handgrip strength, Shoulder Pain and Disability Index (SPADI), and Functional Assessment of Cancer Therapy-Breast (FACT-B).Result: Flexion and extension of shoulder ROM showed significant differences between the two groups at 12 weeks. Flexion and extension of shoulder ROM showed significant differences for t1-t2 (p = 0.02) and t0-t1 (p = 0.04). Abduction showed a significant difference for t0-t1 (p = 0.03), t1-t2 (p = 0.02), and t0-t2 (p = 0.01). CSE (7 points) and IBE (20 points) satisfied the MDC in FACT-B total score. The MDC of the SPADI total score was 13 points in the CSE group and 9 points in the IBE group.Conclusion: IBE would be more appropriate to start the rehabilitation for BCSs and CSE would be effective after the pain has improved. [ABSTRACT FROM AUTHOR]