Related Experiment Video
Updated: Jan 24, 2026

Accessing the Subdural Space of the Rodent Spinal Cord for Treatment Delivery
Published on: August 8, 2025
Surgical Treatment of Chronic Subdural Hematoma: Predicting Recurrence and Cure
Sami Ridwan1, Anna-Margarete Bohrer1, Alexander Grote1
1Department of Neurosurgery, Bethel Clinic, Bielefeld, Germany.
Background:
Chronic subdural hematoma (CSDH) is a common neurosurgical condition, especially among elderly patients. Here we have analyzed our institutional experience with surgical management of CSDH. We aimed at identifying predictors of hematoma recurrence and cure, and the respective time course.
Methods:
Pertinent data were collected from all 208 patients (136 males; median age, 78 years) treated for unilateral CSDH in our department from 2014 to 2016 after exclusion of cases with CSDH following previous head surgery or missing postoperative imaging. Pre- and postoperative neuroimaging studies were subjected to computer-assisted volumetric analyses. CSDH composition and anatomy were assessed using a modified Nakaguchi classification.
Results:
A total of 67.8% of the patients presented with neurologic deficits, and 51.4% were at least on 1 anticoagulant agent. Burr hole trephinations were performed in 94.7%. The median residual hematoma volume was 35.0 mL (44.1 mL including air). Surgical recurrences were seen in 17.8%. The median time to repeat surgery was 17 days, and 91.9% of recurrences occurred within 60 days. Recurrence rates varied between 36.4% (separated or trabecular subtypes and postoperative CSDH volume ≥35.0 mL) and 3.7% (all other subtypes and postoperative CSDH volume <35.0 mL). A neuroimaging proven cure could be documented in an estimated 90% of cases at 145 days after first surgery.
Conclusions:
Postoperative CSDH volume and the Nakaguchi classification subtypes proved the most powerful predictors of recurrence, cure, and the time to recurrence and cure. Although our results demonstrate the important impact of CSDH volume, composition, and anatomy, they also show that other so far unknown factors play a significant role as well.
More Related Videos
16:30Application of Light-cured Dental Adhesive Resin for Mounting Electrodes or Microdialysis Probes in Chronic Experiments
Published on: July 30, 2007
06:15Tumor Treating Field Therapy in Combination with Bevacizumab for the Treatment of Recurrent Glioblastoma
Published on: October 27, 2014
Related Concept Videos
Curing of Concrete
Curing Methods
Accelerated Curing of Concrete
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
End Point Prediction: Gran Plot
For potentiometric titration, the Gran plot is created by plotting...