Medicine
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Randomized Controlled Trial
Clinical observation of acupuncture combined with modern rehabilitation in the treatment of limb motor dysfunction after ischemic stroke: A randomized controlled trial.
Motor dysfunction is a common sequela of ischemic stroke. This study aimed to explore the effective treatment of ischemic stroke by combining acupuncture and modern rehabilitation training. ⋯ Simultaneous treatment with Zhu's scalp acupuncture and body acupuncture combined with modern rehabilitation training can significantly improve limb motor function in patients with ischemic stroke, and its efficacy is better than that of body acupuncture alone combined with modern rehabilitation training.
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Postmenopausal osteoporosis (PMOP) is a disorder of bone metabolism caused by estrogen deficiency in women after menopause, which manifests clinically as pain, spinal deformities, and even fragility fractures, affecting the quality of life of patients and possibly shortening their life span. Traditional Chinese medicine prescription Buzhong Yiqi Decoction (BZYQD) has been widely used in clinical practice and achieved good results. But there is no high-level evidence to support this result. The aim of this study is to evaluate BZYQD's efficacy and safety in the management of PMOP. ⋯ The study provides a trustable clinical foundation for BZYQD in the treatment of PMOP.
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To assess the clinical feasibility of the geriatric nutritional risk index (GNRI) and prognostic nutritional index (PNI) as determinants of survival in patients with stage I to III non-small cell lung cancer (NSCLC). This retrospective study included patients with stage I to III NSCLC from all age groups. Hazard ratios (HRs) for overall survival (OS), cancer-specific survival (CSS), and relapse-free survival (RFS) were calculated using the Cox regression analysis. ⋯ Finally, TNM stage, PI, lymphatic invasion, and GNRI were significant determinants of RFS and constituted the RFS model (C-index, 0.783). Our study showed that GNRI, but not PNI, was a predictor of OS, CSS, and RFS in patients with stage I-III NSCLC across all age groups. Excellent discriminant power was observed for OS, CSS, and RFS models.
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There is growing evidence that coronavirus disease 2019 (COVID-19) can trigger acute episodes of mood disorders or psychotic symptoms. Reports on the treatment of COVID-19-related bipolar disorder (BD) are limited. Our study aimed to investigate the potential for new or recurrent BD due to COVID-19. We qualitatively evaluate clinical treatments (acupuncture combined with medication) and any potential pathophysiological links between infection and BD. ⋯ The conclusions of this study will help clarify the effects of acupuncture combined with drug therapy on patients with COVID-19-related BD.
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Randomized Controlled Trial
Differentiation of breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using deep transfer learning based on DenseNet201.
In order to achieve better performance, artificial intelligence is used in breast cancer diagnosis. In this study, we evaluated the efficacy of different fine-tuning strategies of deep transfer learning (DTL) based on the DenseNet201 model to differentiate malignant from benign lesions on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). We collected 4260 images of benign lesions and 4140 images of malignant lesions of the breast pertaining to pathologically confirmed cases. ⋯ The average classification Pr, Rc, f1, and AUROC of S2 in the validation set were (89.00%, 80.00%, 0.81, and 0.79, respectively) higher than those of S0 (76.00%, 67.00%, 0.69, and 0.65, respectively), S1 (60.00%, 60.00%, 0.60, 0.66, and respectively), and S3 (77.00%, 73.00%, 0.74, 0.72, respectively). The degree of coincidence between S2 and the histopathological method for differentiating between benign and malignant breast lesions was high (κ = 0.749). The S2 strategy can improve the robustness of the DenseNet201 model in relatively small breast DCE-MRI datasets, and this is a reliable method to increase the Ac of discriminating benign from malignant breast lesions on DCE-MRI.