Medicine
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Case Reports
Snare device retrieval of occluder embolized in patent foramen ovale closure: A case report.
Transcatheter interventional closure therapy is the main treatment method for patent foramen ovale (PFO). However, occluder abscission is a serious complication in PFO interventional therapy. Thus, timely and effective management of the occluder detachment is crucial for improving patient prognosis. ⋯ When the PFO occlusion device is detached, interventional treatment would lead to minimal trauma, fast postoperative recovery, and a definite therapeutic effect. Based on mastering the indications and standardizing the operational process, this is a safe and effective minimally invasive treatment method.
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Observational Study
Discussion on the mechanism of Tiaoqi Xiaowei decoction in the treatment of chronic atrophic gastritis based on network pharmacology and molecular docking: An observational study.
To explore the mechanism of Tiaoqi Xiaowei decoction in the treatment of chronic atrophic gastritis by network pharmacology and molecular docking. The main active components and targets of Tiaoqi Xiaowei decoction were obtained from TCMSP database. The databases of Disgenet, GeneCards, and OMIM were used to obtain chronic atrophic gastritis-related targets. ⋯ A total of 188 signaling pathways were screened out, including cancer pathway, PI3K-Akt, IL-17, and TNF signaling pathway. Molecular docking results showed that the key components of Tiaoqi Xiaowei decoction had a favorable binding affinity with key targets. Tiaoqi Xiaowei decoction acts on multiple targets such as AKT1, TP53, VEGFA, TNF, IL6, PTGS2, and synergistically treats chronic atrophic gastritis by regulating inflammatory responses and tumor-related signaling pathways.
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Evidence from observational researches have suggested that mental diseases are able to affect thyroid diseases. However, the causal relationship between mental diseases and the risk of thyroid diseases still remains unclear. Herein, we conducted a two-sample Mendelian randomization (MR) statistical analysis method to assess the causality between mental diseases and thyroid diseases. ⋯ Then we subsequently conducted a consistent robustness analysis to assess heterogeneity and horizontal pleiotropy. Our method reports causal relationships exist mental diseases and the risk of thyroid diseases. Subsequent researches are still warranted to determine how mental diseases influence the development of thyroid diseases.
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Hypertensive heart disease was difficult to cure with drugs, and most patients had poor compliance, leading to recurrent disease and poor quality of life. The intelligent management mode based on the Internet of Things avoided the excessive dependence of the elderly patients on medical institutions in the traditional medical model and enabled patients to monitor themselves. This study aimed to explore the impact on self-management ability and prognosis of elderly patients with hypertensive heart disease. ⋯ After intervention, the scores of self-management ability in diet control, self-care skills, rehabilitation exercise, and self-monitoring in observation group were higher than those in control group (P < .05). After intervention, the total incidence of chest tightness, dyspnea, arrhythmia, edema, and nausea in the observation group was 5 (6.67%), which was significantly lower than that in the control group 12 (16.00%) (P < .05). The application of intelligent management mode based on the Internet of Things could effectively improve patients' blood pressure level, improve patients' self-management ability, and significantly improve the prognosis, which was worthy of popularization and application.
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Analyses using population-based health administrative data can return erroneous results if case identification is inaccurate ("misclassification bias"). An acetabular fracture (AF) prediction model using administrative data decreased misclassification bias compared to identifying AFs using diagnostic codes. This study measured the accuracy of this AF prediction model in another hospital. ⋯ The AF prediction model was very discriminative (c-statistic 0.90, 95% CI: 0.87-0.92) and very well calibrated (integrated calibration index 0.056, 95% CI: 0.039-0.074). AF probability can be accurately determined using routinely collected health administrative data. This observation supports using the AF prediction model to minimize misclassification bias when studying AF using health administrative data.