Background The number of elderly patients with early renal cell carcinoma (RCC) is on the rise. However, there is still a lack of accurate prediction models for the prognosis of early RCC in elderly patients. It is necessary to establish a new nomogram to predict the prognosis of elderly patients with early RCC. Methods The data of patients aged above 65 years old with TNM stage I and II RCC were downloaded from the SEER database between 2010 and 2018. The patients from 2010 to 2017 were randomly assigned to the training cohort (n = 7233) and validation cohort (n = 3024). Patient data in 2018(n = 1360) was used for external validation. We used univariable and multivariable Cox regression model to evaluate independent prognostic factors and constructed a nomogram to predict the 1-, 3-, and 5-year overall survival (OS) rates of patients with early-stage RCC. Multiple parameters were used to validate the nomogram, including the consistency index (C-index), the calibration plots, the area under the receiver operator characteristics (ROC) curve, and the decision curve analysis (DCA). Results The study included a total of 11,617 elderly patients with early RCC. univariable and multivariable Cox regression analysis based on predictive variables such as age, sex, histologic type, Fuhrman grade, T stage, surgery type, tumors number, tumor size, and marriage were included to establish a nomogram. The C-index of the training cohort and validation cohort were 0.748 (95% CI: 0.760–0.736) and 0.744 (95% CI: 0.762–0.726), respectively. In the external validation cohort, C-index was 0.893 (95% CI: 0.928–0.858). The calibration plots basically coincides with the diagonal, indicating that the observed OS was almost equal to the predicted OS. It was shown in DCA that the nomogram has more important clinical significance than the traditional TNM stage. Conclusion A novel nomogram was developed to assess the prognosis of an elderly patient with early RCC and to predict prognosis and formulate treatment and follow-up strategies.

Background: Pulmonary arterial hypertension (PAH) patients with pregnancy have high maternal mortality. This study aimed to provide clinical evidence with multidisciplinary team (MDT) management and to evaluate the clinical outcomes in PAH patients during the perinatal period.Methods: We conducted a retrospective evaluation of PAH patients pregnant at the First Affiliated Hospital of Chongqing Medical University between May 2015 and May 2021.Results: Twenty-two patients (24 pregnancies) were included in this study and received MDT management, and 21 pregnancies chose to continue pregnancy with cesarean section. Nine (37.5%) were first-time pregnancies at 27.78 ± 6.16 years old, and 15 (62.5%) were multiple pregnancies at 30.73 ± 3.71 years old. The average gestational week at hospitalization and delivery were 29.38 ± 8.63 weeks and 32.37 ± 7.20 weeks, individually. Twenty-one (87.5%) pregnancies received single or combined pulmonary vasodilators. The maternal survival rate of PAH patients reached 91.7%. Fifteen (62.5%) pregnancies were complicated with severe adverse events. Patients with complicated adverse events showed lower percutaneous oxygen saturation (SpO2), lower albumin, lower fibrinogen, higher pulmonary artery systolic pressure (PASP), higher blood pressure, longer activated partial thromboplastin time, and longer coagulation time. Fourteen (66.7%) pregnancies with cesarean sections were prematurely delivered and 85.7% newborns who survived after the operation remained alive.Conclusion: The survival rate of parturients with PAH was improved in relation to MDT and pulmonary vasodilator therapy during the perinatal period compared with previous studies. SpO2, albumin, PASP, blood pressure, and coagulation function should be monitored carefully in PAH patients during pregnancy.

Background: Hypopharyngeal squamous cell carcinomas (HPSCC) is one of the causes of death in elderly patients, an accurate prediction of survival can effectively improve the prognosis of patients. However, there is no accurate assessment of the survival prognosis of elderly patients with HPSCC. The purpose of this study is to establish a nomogram to predict the cancer-specific survival (CSS) of elderly patients with HPSCC.Methods: The clinicopathological data of all patients from 2004 to 2018 were downloaded from the SEER database. These patients were randomly divided into a training set (70%) and a validation set (30%). The univariate and multivariate Cox regression analysis confirmed independent risk factors for the prognosis of elderly patients with HPSCC. A new nomogram was constructed to predict 1-, 3-, and 5-year CSS in elderly patients with HPSCC. Then used the consistency index (C-index), the calibration curve, and the area under the receiver operating curve (AUC) to evaluate the accuracy and discrimination of the prediction model. Decision curve analysis (DCA) was used to assess the clinical value of the model.Results: A total of 3,172 patients were included in the study, and they were randomly divided into a training set (N = 2,219) and a validation set (N = 953). Univariate and multivariate analysis suggested that age, T stage, N stage, M stage, tumor size, surgery, radiotherapy, chemotherapy, and marriage were independent risk factors for patient prognosis. These nine variables are included in the nomogram to predict the CSS of patients. The C-index for the training set and validation was 0.713 (95% CI, 0.697–0.729) and 0.703 (95% CI, 0.678–0.729), respectively. The AUC results of the training and validation set indicate that this nomogram has good accuracy. The calibration curve indicates that the observed and predicted values are highly consistent. DCA indicated that the nomogram has a better clinical application value than the traditional TNM staging system.Conclusion: This study identified risk factors for survival in elderly patients with HPSCC. We found that age, T stage, N stage, M stage, tumor size, surgery, radiotherapy, chemotherapy, and marriage are independent prognostic factors. A new nomogram for predicting the CSS of elderly HPSCC patients was established. This model has good clinical application value and can help patients and doctors make clinical decisions.

ObjectivesThe aim of this study was to investigate the association between diabetes status and the risk of breast cancer among adult Americans, exploring the impact of BMI, age, and race on this relationship.MethodsA cross-sectional analysis of 8,249 individuals from the National Health and Nutrition Examination Survey (NHANES) was conducted. Diabetes was categorized as type 2 diabetes and prediabetes, with both conditions diagnosed according to the ADA 2014 guidelines. The association between diabetes status and breast cancer risk was explored using multiple logistic regression analysis.ResultsPatients with diabetes had higher odds of breast cancer (OR: 1.51; 95% CI 1.00 to 2.28), Using the two-piecewise linear regression model, it was observed that there is a threshold effect in the risk of breast cancer occurrence at the age of 52 years. Specifically, the risk of breast cancer is relatively low before the age of 52 but increases significantly after this age.ConclusionsThis study identified a significant association between diabetes status and breast cancer risk among adult Americans. We also found a threshold effect in breast cancer occurrence at the age of 52. Age was significantly associated with breast cancer risk in both Non-Hispanic White and Non-Hispanic Black individuals. These findings underscore the importance of diabetes management, maintaining a healthy BMI, and age-related risk considerations in reducing breast cancer risk.

Tetracycline is a broad-spectrum class of antibiotics. The use of excessive doses of tetracycline antibiotics can result in their residues in food, posing varying degrees of risk to human health. Therefore, the establishment of a rapid and sensitive field detection method for tetracycline residues is of great practical importance to improve the safety of food-derived animal foods. Electrochemical analysis techniques are widely used in the field of pollutant detection because of the simple detection principle, easy operation of the instrument, and low cost of analysis. In this review, we summarize the electrochemical detection of tetracycline antibiotics by bibliometrics. Unlike the previously published reviews, this article reviews and analyzes the development of this topic. The contributions of different countries and different institutions were analyzed. Keyword analysis was used to explain the development of different research directions. The results of the analysis revealed that developments and innovations in materials science can enhance the performance of electrochemical detection of tetracycline antibiotics. Among them, gold nanoparticles and carbon nanotubes are the most used nanomaterials. Aptamer sensing strategies are the most favored methodologies in electrochemical detection of tetracycline antibiotics.