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1.
Hassen Lena M. Albarrak Rana A. Albahlal Reem A. Alsaqabi Dimah K. Hassen Ikhlass M. Daghestani Maha H. Alqurtas Eman M. Alkhalaf Abdulaziz T. Bedaiwi Mohammed K. Omair Mohammed A. Almaghlouth Ibrahim A. 《Quality of life research》2022,31(11):3229-3239
Quality of Life Research - The COVID-19 pandemic might add to the stressors experienced by people living with rheumatic diseases. This study aimed to examine rheumatic patients’ functional... 相似文献
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Journal of Behavioral Medicine - Evidence supports the use of graphic warnings to educate the public about the health harms of smoking and suggests warnings eliciting negative emotional responses... 相似文献
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Feng Song Li Ruipiao Wang Zhiying 《Odontology / the Society of the Nippon Dental University》2022,110(3):508-522
Odontology - To investigate the characterization and function of a novel porous osteogenic material (PLLA / DDM) containing polylactic acid and demineralized dentin matrix. The surface morphology... 相似文献
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Brittney H. Cotta Margaret F. Meagher Aaron Bradshaw Stephen T. Ryan Gerant Rivera-Sanfeliz 《Expert review of anticancer therapy》2019,19(4):301-308
Introduction: Percutaneous renal mass biopsy has evolved over the last decade with improvements on previous pitfalls including low tissue yield, high non-diagnostic rates, and complications. As understanding of tumor biology and natural history of renal cortical neoplasms has improved, percutaneous renal mass biopsy is poised to have an expanding role in an area characterized by individualized management and refined risk stratification.
Areas covered: This review summarizes the evolution of renal mass biopsy to its current state with respect to outcomes, indications, and clinical guidelines.
Expert opinion: With improved understanding of differential biological potential of renal cortical neoplasms combined with technical improvements in diagnostic yield and accuracy, utilization of renal mass biopsy is becoming an important adjunct to patient care in a broad range of clinical scenarios, including active surveillance, thermal ablation, and use of primary systemic therapy in localized and advanced settings. 相似文献
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Wang-Shu Zhu Si-Ya Shi Ze-Hong Yang Chao Song Jun Shen 《World journal of gastroenterology : WJG》2020,26(11):1208-1220
BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy. 相似文献
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Stepanova E. S. Makarenkova L. M. Chistyakov V. V. Rybakov Yu. L. Gukasov V. M. Fedotcheva T. A. Parshin V. A. Votyakov V. A. Shimanovskii N. L. 《Pharmaceutical Chemistry Journal》2019,52(12):1016-1020
Pharmaceutical Chemistry Journal - An HPLC-MS method for simultaneous quantitative determination of a novel gestagenic pharmaceutical and two of its metabolites in rat and rabbit blood sera was... 相似文献