Risk Factors and Predictive Nomogram for Survival in Elderly Patients with Brain Glioma.

OBJECTIVE: To determine the factors that contribute to the survival of elderly individuals diagnosed with brain glioma and develop a prognostic nomogram. METHODS: Data from elderly individuals (age ≥65 years) histologically diagnosed with brain glioma were sourced from the Surveillance, Epidemiology, and End Results (SEER) database. The dataset was randomly divided into a training cohort and an internal validation cohort at a 6:4 ratio. Additionally, data obtained from Tangdu Hospital constituted an external validation cohort for the study. The identification of independent prognostic factors was achieved through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, enabling the construction of a nomogram. Model performance was evaluated using C-index, ROC curves, calibration plot and decision curve analysis (DCA). RESULTS: A cohort of 20 483 elderly glioma patients was selected from the SEER database. Five prognostic factors (age, marital status, histological type, stage, and treatment) were found to significantly impact overall survival (OS) and cancer-specific survival (CSS), with tumor location emerging as a sixth variable independently linked to CSS. Subsequently, nomogram models were developed to predict the probabilities of survival at 6, 12, and 24 months. The assessment findings from the validation queue indicate a that the model exhibited strong performance. CONCLUSION: Our nomograms serve as valuable prognostic tools for assessing the survival probability of elderly glioma patients. They can potentially assist in risk stratification and clinical decision-making.

Nomogram for Predicting Central Nervous System Infection Following Traumatic Brain Injury in the Elderly.

OBJECTIVE: This study aims to identify risk factors for central nervous system (CNS) infection in elderly patients hospitalized with traumatic brain injury (TBI) and to develop a reliable predictive tool for assessing the likelihood of CNS infection in this population. METHOD: We conducted a retrospective study on 742 elderly TBI patients treated at Tangdu Hospital, China. Clinical data was randomly split into training and validation sets (7:3 ratio). By conducting univariate and multivariate logistic regression analysis in the training set, we identified a list of variables to develop a nomogram for predicting the risk of CNS infection. We evaluated the performance of the predictive model in both cohorts respectively, using receiver operating characteristics curves, calibration curves, and decision curve analysis. RESULTS: Results of the logistic analysis in the training set indicated that surgical intervention (P = 0.007), red blood cell count (P = 0.019), C-reactive protein concentration (P < 0.001), and cerebrospinal fluid leakage (P < 0.001) significantly predicted the occurrence of CNS infection in elderly TBI patients. The model constructed based on these variables had high predictive capability (area under the curve-training = 0.832; area under the curve-validation = 0.824) as well as clinical utility. CONCLUSIONS: A nomogram constructed based on several key predictors reasonably predicts the risk of CNS infection in elderly TBI patients upon hospital admission. The model of the nanogram may contribute to timely interventions and improve health outcomes among affected individuals.

Classification of Central Nervous System Tumors Histologically Diagnosed in a Single Center of China 2003-2019.

OBJECTIVE: The classification of central nervous system (CNS) tumors has changed greatly. The Central Brain Tumor Registry of the United States (CBTRUS) and other institutions have analyzed the incidence rate and characteristics of primary CNS tumors. However, there are limited studies analyzing the incidence rate and characteristics of CNS tumors in China. To better understand CNS tumors in China, we summarized all primary CNS tumors diagnosed pathologically in a single center from 2003 to 2019. METHODS: All patients with primary CNS tumors who underwent neurosurgery at our hospital from January 2003 to December 2019 were included in this study. The data were collected from the hospital information system, including diagnosis time, age, gender, anatomic sites, and pathologic results. RESULTS: A total of 17,226 cases of primary CNS tumors were retrospectively analyzed in this study. Among all cases, the major tumor types included meningiomas, tumors of neuroepithelial tissue, and pituitary adenomas. Most tumors of neuroepithelial tissue were glioblastoma and astrocytoma. Most tumors of neuroepithelial tissue were located in the frontal lobe. However, grade 4 tumors of neuroepithelial tissue were more common in the temporal lobe. The median age of all patients was 46 years. The incidence of CNS tumors was higher in women than in men. CONCLUSIONS: Based on this data set, we analyzed various parameters of CNS tumors and found that grade 4 tumors of neuroepithelial tissue were more common in the temporal lobe, which were rarely reported in previous articles.

Hydration Characteristics and Early Strength Evolution of Classified Fine Tailings Cemented Backfill.

To explore the hydration characteristics and early strength evolution of classified fine tailings cemented backfill (CFTCB), a nuclear magnetic resonance (NMR) analysis and a volume resistivity test were performed on classified fine tailings filling slurry (CFTFS). The early hydration products of CFTCB were studied by scanning electron microscopy (SEM) and X-ray diffraction (XRD) phase analysis. Uniaxial compressive strength (UCS) test was carried out, and the microscopic characteristics and strength rules of the hydration reaction of CFTCB were analyzed. Based on the experiment, we found the law of water content change and porosity evolution. The early hydration reaction can be divided into the dissolution, setting, and hardening stages. The volume resistivity test results show that the volume resistance of filling slurry increases slowly at first then decreases, and finally increases rapidly. The variation trend of volume resistivity is related to the degree of hydration reaction. When combined with the hydration characteristics of backfill materials, the hydration reaction rate determines the growth rate of early strength of backfill, and the formation of hydration products is the reason for the early strength increase in backfill. The research conclusion has an important theoretical guiding value and engineering significance in mine filling production organization and filling ratio parameter optimization.