OBJECTIVE: We established a reliable nomogram model to predict the recurrence of chronic subdural hematoma (CSDH) after burr hole surgery. METHODS: We retrospectively analyzed 514 patients who were treated in our hospital between January 2010 and November 2017 and included 231 patients in this study. We used univariate and binary logistic regression analysis to identify the significantly related predictors for recurrence. Subsequently, we established the nomogram model using these predictors and validated it. RESULTS: The total rate of recurrence after initial surgery for CSDH was 14.29% (33/231) during the following 3 months. We found that preoperative hematoma volume (greater than 121 mL), postoperative residual cavity volume (greater than 72 mL), computed tomography scan imaging type (hyper- and mixed-density type), and age (older than 65 years of age) were significantly related to recurrence. We used 50% recurrence rate as the classification cutoff, with the corresponding points of 252 to validate the nomogram model. The accuracy of predicting the recurrence of CSDH calculated by the binary logistic regression model was 91.7%. The sensitivity and specificity of the nomogram were 87.88% and 84.85%, respectively. CONCLUSIONS: This nomogram model had a high precision to predict the recurrence of CSDH. It needs more external and prospective validation in the future. We expect this model could be used in different neurosurgical problems as well.
OBJECTIVE: We established a reliable nomogram model to predict the recurrence of chronic subdural hematoma (CSDH) after burr hole surgery. METHODS: We retrospectively analyzed 514 patients who were treated in our hospital between January 2010 and November 2017 and included 231 patients in this study. We used univariate and binary logistic regression analysis to identify the significantly related predictors for recurrence. Subsequently, we established the nomogram model using these predictors and validated it. RESULTS: The total rate of recurrence after initial surgery for CSDH was 14.29% (33/231) during the following 3 months. We found that preoperative hematoma volume (greater than 121 mL), postoperative residual cavity volume (greater than 72 mL), computed tomography scan imaging type (hyper- and mixed-density type), and age (older than 65 years of age) were significantly related to recurrence. We used 50% recurrence rate as the classification cutoff, with the corresponding points of 252 to validate the nomogram model. The accuracy of predicting the recurrence of CSDH calculated by the binary logistic regression model was 91.7%. The sensitivity and specificity of the nomogram were 87.88% and 84.85%, respectively. CONCLUSIONS: This nomogram model had a high precision to predict the recurrence of CSDH. It needs more external and prospective validation in the future. We expect this model could be used in different neurosurgical problems as well.
Authors: Dana C Holl; Ana Mikolic; Jurre Blaauw; Roger Lodewijkx; Merijn Foppen; Korné Jellema; Niels A van der Gaag; Heleen M den Hertog; Bram Jacobs; Joukje van der Naalt; Dagmar Verbaan; K H Kho; C M F Dirven; Ruben Dammers; Hester F Lingsma; David van Klaveren Journal: Acta Neurochir (Wien) Date: 2022-05-03 Impact factor: 2.816
Authors: Ishita P Miah; Yeliz Tank; Frits R Rosendaal; Wilco C Peul; Ruben Dammers; Hester F Lingsma; Heleen M den Hertog; Korné Jellema; Niels A van der Gaag Journal: Neuroradiology Date: 2020-10-22 Impact factor: 2.804