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Background and Objectives: Prolonged bed rest after the resection of spinal intradural tumors is postulated to mitigate the development of cerebrospinal fluid leaks (CSFLs), which is one of the feared postoperative complications. Nonetheless, the empirical evidence supporting this conjecture remains limited and requires further investigation. The goal of the study was to investigate whether prolonged bed rest lowers the risk of CSFL after the resection of spinal intradural tumors. The primary outcome was the rate of CSFL in each cohort. Materials and Methods: To validate this hypothesis, we conducted a comparative effectiveness research (CER) study at two distinct academic neurosurgical centers, wherein diverse postoperative treatment protocols were employed. Specifically, one center adopted a prolonged bed rest regimen lasting for three days, while the other implemented early postoperative mobilization. For statistical analysis, case–control matching was performed. Results: Out of an overall 451 cases, we matched 101 patients from each center. We analyzed clinical records and images from each case. In the bed rest center, two patients developed a CSFL (n = 2, 1.98%) compared to four patients (n = 4, 3.96%) in the early mobilization center (p = 0.683). Accordingly, CSFL development was not associated with early mobilization (OR 2.041, 95% CI 0.365–11.403; p = 0.416). Univariate and multivariate analysis identified expansion duraplasty as an independent risk factor for CSFL (OR 60.33, 95% CI: 0.015–0.447; p < 0.001). Conclusions: In this CER, we demonstrate that early mobilization following the resection of spinal intradural tumors does not confer an increased risk of the development of CSFL. [ABSTRACT FROM AUTHOR]

Background and Objectives: Prolonged bed rest after the resection of spinal intradural tumors is postulated to mitigate the development of cerebrospinal fluid leaks (CSFLs), which is one of the feared postoperative complications. Nonetheless, the empirical evidence supporting this conjecture remains limited and requires further investigation. The goal of the study was to investigate whether prolonged bed rest lowers the risk of CSFL after the resection of spinal intradural tumors. The primary outcome was the rate of CSFL in each cohort. Materials and Methods: To validate this hypothesis, we conducted a comparative effectiveness research (CER) study at two distinct academic neurosurgical centers, wherein diverse postoperative treatment protocols were employed. Specifically, one center adopted a prolonged bed rest regimen lasting for three days, while the other implemented early postoperative mobilization. For statistical analysis, case–control matching was performed. Results: Out of an overall 451 cases, we matched 101 patients from each center. We analyzed clinical records and images from each case. In the bed rest center, two patients developed a CSFL (n = 2, 1.98%) compared to four patients (n = 4, 3.96%) in the early mobilization center (p = 0.683). Accordingly, CSFL development was not associated with early mobilization (OR 2.041, 95% CI 0.365–11.403; p = 0.416). Univariate and multivariate analysis identified expansion duraplasty as an independent risk factor for CSFL (OR 60.33, 95% CI: 0.015–0.447; p < 0.001). Conclusions: In this CER, we demonstrate that early mobilization following the resection of spinal intradural tumors does not confer an increased risk of the development of CSFL.

Well-defined risk factors for cerebrospinal fluid leakage (CSFL) after intradural spine surgery are scarce in the literature. The aim of the present study was to identify patient- and surgery-related risk factors and the incidence of CSFL. For the present retrospective cohort study, we identified consecutive patients who had undergone intradural spine surgery between 2009 and 2021 at our department. The primary endpoint was the incidence of clinically or radiologically proven CSFL. The effects of the clinical and surgical factors on the occurrence of CSFL were analyzed. A total of 375 patients (60.3% women; mean age, 54 ± 16.5 years) were included. Of the 375 patients, 30 (8%) had experienced postoperative CSFL and, thus, a significantly greater risk of wound healing disorders (odds ratio [OR], 24.9; 95% confidence interval [CI], 9.3–66.7) and surgical site infections (OR, 8.4; 95% CI, 2.6–27.7; P < 0.01 for each). No patient-related factors were associated with the development of CSFL. Previous surgery at the index level correlated significantly with the occurrence of postoperative CSFL (OR, 2.76; 95% CI, 1.1–6.8; P = 0.03) on multivariate analysis. Furthermore, patients with intradural tumors tended to have a greater risk of CSFL (OR, 2.3; 95% CI, 0.9–5.8; P = 0.07). Surgery-related factors did not influence the occurrence of CSFL. Surgery on the thoracic spine had resulted in a significantly lower postoperative CSFL rate compared with surgery on the cervical or lumbar spine (OR, −2.5; 95% CI, 1.3–4.9; P = 0.02). Our study found no modifiable risk factors for preventing CSFL after intradural spine surgery. Patients with previous surgery at the index level had a greater risk of CSFL. The occurrence of CSFL resulted in significantly more wound healing disorders and surgical site infections, necessitating further therapy. [ABSTRACT FROM AUTHOR]

Previous studies have retrospectively analyzed the likely causes of cerebrospinal fluid leakage (CSFL) during cervical spine surgery and the management of CSFL after its occurrence. In the present study, we aimed to develop and validate a nomogram for the risk of CSFL in Chinese patients who had undergone cervical decompression and internal fixation (CDIF) surgery. We performed a retrospective analysis of patients who had undergone CDIF surgery. Of the 1286 included patients, 54 were in the CSFL group and 1232 were in the normal group. The patients were randomly divided into training and validation tests. The risk assessment for CSFL included 21 characteristics. The feature selection for the CSFL model was optimized using the least absolute shrinkage and selection operator regression model in the training test. Multivariate logistic regression analysis was performed to construct the model according to the selected characteristics. The clinical usefulness of the predictive model was assessed using the C-index, calibration curve, and decision curve analysis with identification and calibration. The risk prediction nomogram included the diagnosis, revision surgery, ossification of the posterior longitudinal ligament, cervical instability, and a history of malignancy in the training test. The model demonstrated high predictive power, with a C-index of 0.914 (95% confidence interval, 0.876–0.951) and an area under the curve of 0.914. The results of the decision curve analysis demonstrated the clinical usefulness of the CSFL risk nomogram when the probability threshold for CSFL was 1%–62%. Our proposed nomogram for CSFL risk includes the diagnosis, revision surgery, ossification of the posterior longitudinal ligament, cervical instability, and a history of malignancy. The nomogram can be used to evaluate the risk of CSFL for patients undergoing CDIF surgery. [ABSTRACT FROM AUTHOR]

Multi‐source domain adaptation (MDA) aims to leverage knowledge from multiple source domains to improve the classification performance on target domains. Different degrees of distribution discrepancies between every two domains pose a huge challenge to MDA tasks. Most works focus on extracting features shared by all domains, which is critical but not enough to reduce distribution discrepancies. In this paper, we propose a method named as common‐specific feature learning (CSFL). Constituting a framework of feature learning, CSFL explores a subspace where the combination of common and specific features makes learned representations comprehensive. Based on this framework, we conduct a metric learning method for learning a discriminative feature representation. Considering redundant information caused by source domains is likely to hurt the performance, we impose an effective low‐rank constraint to remove the redundant information. Further, we adopt structure consistent constraint to preserve the local structure in each domain. CSFL has obtained about 1–5% improvement of mean accuracy, compared to the state‐of‐the‐art shallow methods. Further, compared with 90.2% and 89.4% of the best baseline deep method, CSFL achieves mean accuracy of 90.8% and 89.7% on the Office‐31 and ImageCLEF‐DA datasets respectively. The encouraging results validate the effectiveness of our method. [ABSTRACT FROM AUTHOR]