Αρχειοθήκη ιστολογίου

Τρίτη 3 Νοεμβρίου 2020

Behavioral Medicine Methods in Treatment of Somatic Conditions

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Background. The aim of this article is to present a short review of noninvasive, nonpharmacological treatment methods used in somatic illnesses that fall under the umbrella of approach called behavioral medicine. Methods. The narrative review method was applied in the study. Science paper databases, including PubMed, had been used to retrieve papers on therapeutic methods used in clinical setting that meet the broad criteria of behavioral medicine definition as stated in the Charter of International Behavioral Medicine Society Results. Main groups of methods, disorders in which they are being employed and their effectiveness, have been identified. Conclusions. Behavioral medicine is grouping treatment methods and interventions that hold large potential for clinical setting. Two groups of methods can be dis tinguished by the scrutiny and level of evidence gathered in their effectiveness assessment; for biofeedback, guided imagery, and hypnosis techniques, comprehensive evidence reports in the framework of U.S. Evidence Synthesis Program exist. Meditation techniques, disclosure therapies, and relaxation methods are less well assessed. Broader employment of behavioral medicine therapies in clinical setting is possible after addressing two major problems in the field, which are deficiencies in quality evidence of effectiveness for many of the methods and their insufficiencies in underlying therapeutic mechanism knowledge.
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An Epithelial-Mesenchymal Transition (EMT) Preoperative Nomogram for Prediction of Lymph Node Metastasis in Bladder Cancer (BLCA)

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Lymph node (LN) metastasis is a lethal independent risk factor for patients with bladder cancer (BLCA). Accurate evaluation of LN metastasis is of vital importance for disease staging, treatment selection, and prognosis prediction. Several histopathologic parameters are available to predict LN metastasis postoperatively. To date, medical imaging techniques have made a great contribution to preoperatively diagnosis of LN metastasis, but it also exhibits substantial false positives. Therefore, a reliable and robust method to preoperatively predict LN metastasis is urgently needed. Here, we selected 19 candidate genes related to epithelial-mesenchymal transition (EMT) across the LN metastasis samples, which was previously reported to be responsible for the subtype transition and correlation with malignancy and prog nosis of BLCA, to establish an EMT-LN signature through LASSO logistic regression analysis. The EMT-LN signature could significantly predict LN metastasis with high accuracy in the TCGA-BLCA cohort, as well as several independent cohorts. As integrating with C3orf70 mutation, we developed an individualized prediction nomogram based on the EMT-LN signature. The nomogram exhibited good discrimination on LN metastasis status, with AUC of 71.7% and 75.9% in training and testing datasets of the TCGA-BLCA cohort. Moreover, the EMT-LN nomogram displayed good calibration with in the Hosmer-Lemeshow goodness of fit test. Decision curve analysis (DCA) revealed that the EMT-LN nomogram was of high potential for clinical utility. In summary, we established an EMT-LN nomogram integrating an EMT-LN signature and C3orf70 mutation status, which acted as an easy-to-use tool to facilitate preoperative prediction of LN metastasis in BLCA individuals.
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Diagnosis of Leiomyosarcoma after Uterine Artery Embolization for Multiple Leiomyomas

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Uterine sarcoma is significantly rarer than leiomyoma and has poor prognosis. Moreover, the diagnosis of leiomyosarcoma is difficult because its symptoms, including pelvic pain, uterine mass, and/or uterine bleeding, are very similar to those of leiomyoma. There are a few cases of leiomyosarcoma wherein leiomyoma was treated with uterine artery embolization (UAE); these reports revealed that the symptoms of hypermenorrhea or/and pelvic pain persisted even after UAE. Symptoms persisting even after UAE treatment for leiomyomas, especially multiple leiomyomas, should be investigated to rule out leiomyosarcoma. Therefore, long-term follow-up is needed. Here, we describe a case of a 39-year-old woman diagnosed with leiomyosarcoma 3 years after undergoing UAE for multiple leiomyomas.
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An Integrating Immune-Related Signature to Improve Prognosis of Hepatocellular Carcinoma

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Growing evidence suggests that the superiority of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) could act as biomarkers for cancer prognosis. However, the prognostic marker for hepatocellular carcinoma with high accuracy and sensitivity is still lacking. In this research, a retrospective, cohort-based study of genome-wide RNA-seq data of patients with hepatocellular carcinoma was carried out, and two protein-coding genes (GTPBP4, TREM-1) and one lncRNA (LINC00426) were sorted out to construct an integrative signature to predict the prognosis of patients. The results show that both the AUC and the C-index of this model perform well in TCGA validation dataset, cross-platform GEO validation dataset, and different subsets divided by gender, stage, and grade. The expression pattern and functional ana lysis show that all three genes contained in the model are associated with immune infiltration, cell proliferation, invasion, and metastasis, providing further confirmation of this model. In summary, the proposed model can effectively distinguish the high- and low-risk groups of hepatocellular carcinoma patients and is expected to shed light on the treatment of hepatocellular carcinoma and greatly improve the patients' prognosis.
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PD-L1 Immunohistochemistry Comparability and Their Correlation with Clinical Characteristics in NSCLC

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Background. PD-L1 expression is an important predictive factor of response to therapy with immune checkpoint inhibitors (ICIs). This study was designed to retrospectively analyze the concordance of PD-L1 measurements using three different assays (Dako22C3, Dako28-8, and SP142) in NSCLC patients and to find possible predictors of high PD-L1 expression. Materials and Methods. Data of 144 patients with histologically confirmed NSCLC and available PD-L1 measurements treated at the Taoyuan General Hospital from 2018 to 2019 were retrospectively reviewed in the study. Patients' characteristics, including age, sex, clinical stage (T, N, and M) of NSCLC (AJCC, 8th edition), and EGFR/ALK alterations, were analyzed for association with PD-L1 expression. Results. Measurements of PD-L1 expression levels with Dako22C3 a nd Dako28-8 were comparable while SP142 showed lower levels of PD-L1 expression. The overall agreement between Dako22C3 and Dako28-8 was 82.2% and 91.6% for both 1% and 50% TPS cut-offs, respectively. The above findings were confirmed by Cohen's kappa. In addition, we found that PD-L1 expression was significantly associated with advanced N stage but not with T and M stages. Conclusion. Dako22C3 and Dako28-8 showed comparable results in assessing PD-L1 levels. Future prospective studies are needed to validate these findings. N stage may be a good predictor for PD-L1 expression.
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Hemangiopericytoma: Incidence, Treatment, and Prognosis Analysis Based on SEER Database

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Background. Hemangiopericytomas are rare tumors derived from pericytes surrounding the blood vessels. The clinicopathological characteristics and prognosis of hemangiopericytoma patients remain mostly unknown. In this retrospective cohort study, we assessed the clinicopathological characteristics of hemangiopericytoma patients, as well as the clinical usefulness of different treatment modalities. Material and Methods. We collected the clinicopathological data (between 1975 and 2016) of hemangiopericytoma and hemangioendothelioma patients from the Surveillance, Epidemiology, and End Results (SEER) database. Incidence, treatment, and patient prognosis were assessed. Results. Data from 1474 patients were analyzed in our study cohort (hemangiopericytoma: ; hemangioendothelioma: ). The incidence of hemangioperi cytoma in 2016 was 0.060 per 100,000 individuals. The overall survival (OS) and cancer-specific survival (CSS) did not differ between patients with hemangioendothelioma and those with hemangiopericytoma (,). The tumor grade had no effect on the OS of hemangiopericytoma patients. Multivariate analysis revealed the clinical usefulness of surgery in hemangiopericytoma patients (, 95% confidence interval: 0.05-0.41, ). In contrast, radiotherapy did not improve OS () or CSS (), and chemotherapy worsened patient survival (). Additionally, the combination of surgery and radiotherapy had a similar effect with surgery alone on hemangiopericytoma patient survival (OS: ; CSS: ). Surgery plus chemotherapy provided a worse clinical benefit than surgery alone ().Conclusions. Our findings suggested that hemangiopericytoma had a similar prognosis with hemangioendothelioma. Surgery was the only effective treatment that provided survival benefits in hemangiopericytoma patients, while the clinical use fulness of adjuvant chemotherapy or radiotherapy was limited.
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Application of Artificial Intelligence Techniques for the Estimation of Basal Insulin in Patients with Type I Diabetes

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Artificial intelligence techniques have been positioned in the resolution of problems in various areas of healthcare. Clinical decision support systems developed from this technology have optimized the healthcare of patients with chronic diseases through mobile applications. In this study, several models based on this methodology have been developed to calculate the basal insulin dose in patients with type I diabetes using subcutaneous insulin infusion pumps. Methods. A pilot experimental study was performed with data from 56 patients with type 1 diabetes who used insulin infusion pumps and underwent continuous glucose monitoring. Several models based on artificial intelligence techniques were developed to analyze glycemic patterns based on continuous glucose monitoring and clinical variables in order to esti mate the basal insulin dose. We used neural networks (NNs), Bayesian networks (BNs), support vector machines (SVMs), and random forests (RF). We then evaluated the agreement between predicted and actual values using several statistical error measurements: mean absolute error (MAE), mean square error (MSE), root-mean-square error (RMSE), Pearson's correlation coefficient (R), and determination coefficient (R2). Results. Twenty-four different models were obtained, one for each hour of the day, with each chosen technique. Correlation coefficients obtained with RF, SVMs, NNs, and BNs were 0.9999, 0.9921, 0.0303, and 0.7754, respectively. The error increased between 06:00 and 07:00 and between 13:00 and 17:00. Conclusions. The performance of the RF technique was excellent and got very close to the actual values. Intelligence techniques could be used to predict basal insulin dose. However, it is necessary to explore the validity of the results and select the target population. Models th at allow for more accurate levels of prediction should be further explored.
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Prognostic Values of the Gray-to-White Matter Ratio on Brain Computed Tomography Images for Neurological Outcomes after Cardiac Arrest: A Meta-Analysis

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Background and Purpose. The gray-to-white matter ratio (GWR) on brain computed tomography (CT) is associated with neurological outcomes after cardiac arrest (CA); however, the prognostic value of GWR in CA patients has yet to be confirmed. Therefore, we conducted a meta-analysis of related studies to investigate the prognostic value of GWR on brain CT for neurological outcomes after CA. Materials and Methods. The PubMed, ScienceDirect, Web of Science, and China National Knowledge Infrastructure databases were searched for all relevant articles published before March 31, 2020, without any language restrictions. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with a random-effects model using Stata 14.0 software. Result. A total of 24 eligible studies with 2812 CA patients wer e recruited in the meta-analysis. The pooled result showed that decreased GWR was correlated with poor neurological outcomes after CA (, 95% CI: 6.29–20.21, and ) with moderate heterogeneity (,). The pooled sensitivity and specificity were 0.58 (95% CI: 0.47–0.68) and 0.95 (95% CI: 0.87–0.98), respectively. The area under the curve (AUC) of GWR was 0.84 (95% CI: 0.80–0.87). Compared with GWR (cerebrum) and GWR (average), GWR using the basal ganglion level of brain CT had the highest AUC of 0.87 (0.84–0.90). Subgroup analysis indicated that heterogeneity may be derived from the time of CT measurement, preset specificity, targeted temperature management, or proportion of cardiac etiology. Sensitivity analysis indicated that the result was stable, and Deeks' plot showed no possible publication bias ().Conclusion. Current research suggests that GWR, especially using the basal ganglion level of brain CT, is a useful parameter for determining neurological outcomes after CA.
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Development of Hepatitis Disease Detection System by Exploiting Sparsity in Linear Support Vector Machine to Improve Strength of AdaBoost Ensemble Model

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Hepatitis disease is a deadliest disease. The management and diagnosis of hepatitis disease is expensive and requires high level of human expertise which poses challenges for the health care system in underdeveloped and developing countries. Hence, development of automated methods for accurate prediction of hepatitis disease is inevitable. In this paper, we develop a diagnostic system which hybridizes a linear support vector machine (SVM) model with adaptive boosting (AdaBoost) model. We exploit sparsity in linear SVM that is caused by regularization. The sparse -regularized SVM is capable of eliminating redundant or irrelevant features from feature space. After filtering features through the sparse linear SVM, the output of the SVM is applied to the AdaBoost ensemble model which is used for classificatio n purposes. Two types of numerical experiments are performed on the clinical features of hepatitis disease collected from UCI machine learning repository. In the first experiment, only conventional AdaBoost model is used, while in the second experiment, a feature vector is applied to the sparse linear SVM before its application to the AdaBoost model. Simulation results demonstrate that the strength of a conventional AdaBoost model is enhanced by 6.39% by the proposed method, and its time complexity is also reduced. In addition, the proposed method shows better performance than many previously developed methods for hepatitis disease prediction.
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Physical Therapy for Gait, Balance, and Cognition in Individuals with Cognitive Impairment: A Retrospective Analysis

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Objectives. The purpose of this study was to determine if a pragmatic physical therapy (PT) program was associated with improved cognition, gait, and balance in individuals with cognitive impairment. This study investigated these associations for individuals with Alzheimer disease (AD), vascular dementia (VaD), dementia with Lewy bodies (DLB), and mild cognitive impairment (MCI) in order to better characterize outcomes to PT for each diagnostic group. Methods. Data before and after one month of physical therapy were extracted from patient records (67 with AD, 34 with VaD, 35 with DLB, and 37 with MCI). The mean number of PT sessions over a month was 3.4 (±1.8). Outcomes covered the domains of gait, balance, and cognition with multiple outcomes used to measure different constructs within the balance and ga it domains. Results. All groups showed improvements in balance and at least one gait outcome measure. Those with MCI improved in every measure of gait and balance performance. Lastly, cognition as measured by Montreal Cognitive Assessment improved in individuals in the AD, VaD, and MCI groups. Conclusion. While this retrospective analysis is not appropriate for causal inference, results of one month of physical therapy were associated with decreases in gait, balance, and cognitive impairment in individuals with AD, VaD, DLB
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Intrinsic Brain Abnormalities in Patients with Hepatitis C Virus Infection with Cognitive Impairment: A Preliminary Resting-State fMRI Study

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Purpose. Patients with a hepatitis C virus (HCV) infection frequently exhibit various neuropsychiatric complications such as cognitive decline. This study is aimed at investigating alterations in regional and network-level neural function in patients with HCV infection and examining the association between these alterations and patients' cognition dysfunction. Methods. The study included 17 patients with HCV infection and 17 healthy controls. These individuals had undergone resting-state functional magnetic resonance imaging as well as cognitive assessment using a battery of tests that were collectively called the "psychometric hepatic encephalopathy score (PHES)" examination. Analyses of amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) were conducted to asses s, respectively, regional neural function and functional integration. Results. HCV-infected patients performed significantly worse in cognitive tests. In the HCV group, ALFF decreased in Region 1 (left medial frontal gyrus and bilateral anterior cingulate gyrus) and Region 2 (right middle and superior frontal gyrus). The HCV group showed lower FC between Region 1 and right middle frontal gyrus, whereas they presented an increase in FC between Region 2 and the left supramarginal gyrus/superior temporal gyrus and right supramarginal gyrus. No significant correlation was observed between ALFF/FC measurements and PHES result. Conclusion. This preliminary study presents additional evidence that HCV infection affects brain function, including local intrinsic neural activity and global functional integration.
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The Psychosocial Burden of HCV Infection and the Impact of Antiviral Therapy on the Quality of Life in Liver and Kidney Transplant Recipients: A Pilot Study

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Background. Therapy with direct-acting antivirals (DAA) for HCV is safe and effective in the liver (LT) and kidney transplant (KT) recipients; however, data on the quality of life (QoL) of patients are scanty. This pilot study is aimed at prospectively evaluating the QoL in LT and KT recipients before and after DAA treatment. Methods. We prospectively enrolled 17 LT and 11 KT recipients with HCV infection starting a sofosbuvir-based antiviral therapy for 12 weeks. All participants before (T0), 12 (T12), and 24 (T24) weeks after the end of the therapy completed the Short Form Health Survey (SF-36) questionnaire, the Zung Self-rating Depression Scale, and State-Trait Anxiety Inventory (STAI—Y1–Y2). Results. At T0, LT and KT patients were similar for gender, age, BMI, smoking habits, marital status, mean liv er stiffness values at Fibroscan, and HCV genotype distribution (). There were no significant differences between the 2 groups in STAI-Y1, STAI-Y2, Zung, and SF-36 scores (). At T12, all the participants showed a sustained virological response (SVR). All items of the SF-36 questionnaire improved from the pretreatment to posttreatment period within the LT group, and the 4 domains role-physical, bodily pain, social function, role-emotional, and mental health reached statistical significance ( in all cases). On the contrary, in KT patients, there was no significant improvement in SF-36 mean scores compared to at baseline at T12 and T24. Conclusions. This pilot study suggested that DAA therapy is associated with a significant improvement of the QoL only in LT recipients. Probably, KT recipients did not consider HCV a "central player" in the course of their disease, and HCV eradication did not significantly impact on their QoL.
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