Medicine
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In this study, risk factors for coronary slow flow (CSF) patients were examined, and a clinical prediction model was created. This study involved 573 patients who underwent coronary angiography at our hospital because of chest pain from January 2020 to April 2022. They were divided into CSF group (249 cases) and noncoronary slow flow (NCF) group (324 cases) according to the coronary blood flow results. ⋯ The areas under the curve for the training and external validation sets were respectively 0.730 (95% CI: 0.681-0.779) and 0.770 (95%CI: 0.699-0.841). Nomogram calibration curves indicated intense calibration, and the results of the Hosmer-Lemeshow goodness-of-fit test indicated that χ² = 1.118, P = .572. The nomogram combining various risk factors can be used for individualized predictions of CSF patients and then facilitate prompt and specific treatment.
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This study aimed to develop and validate a prognostic model for elderly patients with differentiated thyroid carcinoma (DTC) based on various demographic and clinical parameters in order to accurately predict patient outcomes. Patients who were diagnosed with DTC and were over 55 years old between 2010 and 2019 were identified from the Surveillance, Epidemiology, and End Results database. The patients were then randomly divided into a training set and a validation set in a 7:3 ratio, and patients from our center were included as an external validation group. ⋯ Using these predictors, nomograms were constructed to estimate the probability of overall survival and cancer specific survival. The nomograms demonstrated a high level of predictive accuracy, as evidenced by the concordance index, and the calibration plots indicated that the predicted outcomes were consistent with the actual outcomes. Furthermore, the decision curve analysis demonstrated that the nomograms provided substantial clinical net benefit, indicating their utility in clinical practice.
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Poor prognosis in patients with distant metastasis of gastric signet ring cell carcinoma (GSRC), and there are few studies on the development and validation of the diagnosis and prognosis of distant metastasis of GSRC. The Surveillance, Epidemiology, and End Results database was used to identify patients with GSRC from 2004 to 2019. Univariate and multivariate logistic regression analysis were used to identify independent risk factors for distant metastasis of GSRC, while univariate and multivariate Cox proportional hazard regression analysis were used to determine independent prognostic factors for patients with distant metastasis of GSRC. ⋯ The receiver operating characteristic curve, calibration curve, decision curve analysis curve, and Kaplan-Meier survival curve of the training set and validation set confirmed that the 2 nomograms could accurately predict the occurrence and prognosis of distant metastasis in GSRC. Two nomograms can serve as effective prediction tools for predicting distant metastasis in GSRC patients and the prognosis of patients with distant metastasis. They have a certain clinical reference value.
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Observational Study
Increased serum leptin levels are associated with metabolic syndrome and semen parameters in patients with infertility.
This study aims to ascertain the associations between serum leptin levels and metabolic syndrome and semen parameters in patients with infertility. A total of 200 patients who were diagnosed as primary infertility in our hospital were enrolled in this study, and they were divided into MetS group and non-MetS group. About 30 healthy men were enrolled as the control group. ⋯ Moreover, sperm concentration was correlated with FSH (R = -0.268, P < .001) and inhibin B (R = 0.401, P < .001), and normal morphology was correlated with HDL (R = 0.233, P < .001) and TG (R = -0.182, P < .01). In primary infertile patients, sperm normal morphology were found to be depressed and related to MetS. Leptin was increased in patients diagnosed with MetS and associated with semen parameters.
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In response to global health challenges, implementing innovative educational strategies is crucial for preparing public health professionals with the required skills. This study employed CiteSpace and VOSviewer to visually analyze 3 decades of research on virtual simulation technology in public health education and training. The visual knowledge map created aimed to uncover the research trends, key areas of interest, and emerging frontiers in this domain. ⋯ This study presents the inaugural comprehensive analysis of global trends, hotspots, frontiers, and advancements in the implementation of virtual simulation technology in public health education and training, utilizing CiteSpace and VOSviewer software. The research findings reveal a significant surge in publications since 2019, with a particular emphasis on disaster medicine, telehealth, and virtual reality, indicating the versatility and promise of virtual simulation in the changing educational environments. These findings emphasize the significance of virtual simulation as a dynamic and progressive tool in public health education, proposing a promising direction for future research and practical applications.