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The objective of this study is to develop a model for predicting the time of early symptomatic (delayed or nonhealing wound) restenosis after infrapopliteal angioplasty in patients with critical limb ischemia (CLI). This is a single-center retrospective cohort study evaluating 60 de novo infrapopliteal lesions of 38 limbs in 35 patients with CLI, who underwent successful endovascular treatment (EVT) from October 2016 to December 2018 and follow-up angiography within 3 months from the procedure. Outcome measures were binary restenosis at follow-up angiography and clinical outcome at 3 months. Patient/limb/lesion characteristics were compared between the restenosis and non-restenosis groups. Angiographic restenosis predictors were assessed to develop a model for predicting the time of restenosis using multinomial logistic regression. The restenosis rate at follow-up angiography (median time, 41 days [IQR 27-58 days]) was 38% (23/60). After adjustment for covariables, longer period between EVT and follow-up angiography and lower C-reactive protein (CRP) were the predictors of angiographic restenosis. We developed a model for predicting the time of early symptomatic restenosis with a probability of 70%: "Days = 200 - 2.1 age - 13 CTO + 3.3 CRP" (R = 0.81, RMSE = 0.27), e.g., 80 years old, CTO (+), CRP 4.4 mg/dl: 32.2 days. The predictive model including age, CTO, and CRP might allow estimation of the period for the angiographic restenosis development.
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http://dx.doi.org/10.1007/s12928-020-00691-1 | DOI Listing |
Clin Orthop Relat Res
September 2025
Leni & Peter W. May Department of Orthopaedic Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Background: Peripheral nerve injury commonly results in pain and long-term disability for patients. Recovery after in-continuity stretch or crush injury remains inherently unpredictable. However, surgical intervention yields the most favorable outcomes when performed shortly after injury.
View Article and Find Full Text PDFJAMA Dermatol
September 2025
Department of Population Health, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.
Importance: Increasingly, strategies to systematically detect melanomas invoke targeted approaches, whereby those at highest risk are prioritized for skin screening. Many tools exist to predict future melanoma risk, but most have limited accuracy and are potentially biased.
Objectives: To develop an improved melanoma risk prediction tool for invasive melanoma.
Curr Med Sci
September 2025
Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Objective: To develop a novel prognostic scoring system for severe cytokine release syndrome (CRS) in patients with B-cell acute lymphoblastic leukemia (B-ALL) treated with anti-CD19 chimeric antigen receptor (CAR)-T-cell therapy, aiming to optimize risk mitigation strategies and improve clinical management.
Methods: This single-center retrospective cohort study included 125 B-ALL patients who received anti-CD19 CAR-T-cell therapy from January 2017 to October 2023. These cases were selected from a cohort of over 500 treated patients on the basis of the availability of comprehensive baseline data, documented CRS grading, and at least 3 months of follow-up.
Mol Divers
September 2025
Department of Biotechnology, National Institute of Technology Raipur, Raipur, Chhattisgarh, 492001, India.
Traditional drug discovery methods like high-throughput screening and molecular docking are slow and costly. This study introduces a machine learning framework to predict bioactivity (pIC₅₀) and identify key molecular properties and structural features for targeting Trypanothione reductase (TR), Protein kinase C theta (PKC-θ), and Cannabinoid receptor 1 (CB1) using data from the ChEMBL database. Molecular fingerprints, generated via PaDEL-Descriptor and RDKit, encoded structural features as binary vectors.
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