Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective:To investigate the clinical characteristics and possible mechanisms of remote intracranial hematoma (RIH) in patients with intracranial aneurysm after interventional embolization.Methods:Six patients with RIH from a series of 58 consecutive patients with intracranial aneurysm, admitted to and performed interventional embolization in our hospital from January 2016 and December 2018, were chosen in our study. Their clinical data were analyzed retrospectively and compared with those without RIH at the same period.Results:In these 6 patients, 4 had history of hypertension, 5 had aneurysm located in the internal carotid artery, 5 were treated with stents combined with postoperative routine anticoagulation treatment. The remote intracranial hematoma occurred within 7 d of interventional embolization, and the hematoma was located in the cerebral hemisphere on the same side of the aneurysm; 4 patients underwent intracranial hematoma puncture catheter drainage; 1 patient was treated conservatively, and one was treated by craniotomy. After treatment, 1 patient recovered (modified Rankin scale [mRS] score of 1), 1 patient had poor prognosis (mRS scores of 5) and discharged automatically, and the rest 4 patients (mRS scores of 3-5) left some degrees of neurological dysfunction. As compared with 52 patients without RIH, 6 patients with RIH had significantly higher percentages of patients used stents and postoperatively used anticoagulation, and higher percentages of patients with poor clinical outcomes at discharge ( P<0.05). Conclusion:Stent-assisted coil embolization in patients with internal carotid artery aneurysm combined with hypertension should be highly vigilant about the possibility of RIH.

After a description of the demand for medical information in grass-root PLA health units, the experiences of Medical Library of Chinese PLA in providing medical information service for grass-root PLA health units were summarized, and suggestions were proposed for medical library and information institutions to provide information service for them.

Research of co-authorship network can reveal the scientific research collaboration network and can thus help us to have an understanding of it. Graphic database and Neo4J were described in detail due to the limitations of relationship database in processing the data of co-authorship network. Graphic database Neo4J-based research and practice of co-authorship network were analyzed with the Institutional Knowledge System of AMMS that we were involved in its construction as an example, and the advantages of Neo4J-based co-authorship network were summarized.

Lymphatic system has important functions such as immune defense and maintaining the stability of internal environment.Traditional anatomy of the central nervous system thought that there are no lymphatic vessels lined with endothelial cells in the central nervous system or lymph circulation.But the latest research shows that there is lymph circulation in the brain,and the meningeal lymphatic vessels are found.To further elucidate the structure and function of the lymph circulation in the central nervous system,we review the latest research progress of composition,drainage and physiological functions of the central nervous system and how it plays a role in the immune related diseases of the central nervous system.