Chronic subdural hematoma classification

• Recurrence prediction in chronic subdural hematomas: a risk stratification score based on 118 consecutive patients
• The Evolution and Recurrence of Chronic Subdural Hematoma was Associated with Different Distribution of Macrophage M1/M2 Polarization
• Differences in neuroradiological impacts of hematoma volume and midline shift on clinical symptoms and recurrence rate in patients with unilateral chronic subdural hematoma
• The middle meningeal artery Patency After Coil Embolization (PACE) score: A novel descriptor of angiographic occlusion
• Research on imaging biomarkers for chronic subdural hematoma recurrence
• Immunoprofile of Radiologic Chronic Subdural Hematoma Subtypes
• Revisiting the Surgical Outcomes of Non-Acute Subdural Hematomas among Retired Military Personnel : A Single Tertiary Hospital Retrospective Analysis in the Philippines
• Distribution of the Middle Meningeal Artery Variants in Patients Undergoing Embolization for Chronic Subdural Hematoma

see also Subdural hematoma classification.

Unilateral chronic subdural hematoma.

Bilateral chronic subdural hematoma.

Posterior fossa chronic subdural hematoma.

Generally chronic subdural hematomas can be classified into four groups; hypodensity, homogeneous isodensity, layered type, and mixed density type on the basis of CT scans ¹⁾.

Chronic isodense subdural hematoma.

Chronic hyperdense subdural hematoma.

Ossified chronic subdural hematoma.

Mixed density chronic subdural hematoma.

Septated chronic subdural hematoma.

Refractory chronic subdural hematoma. see also Chronic subdural hematoma recurrence

Nontraumatic chronic subdural hematoma.

The ICD-10-CM (Clinical Modification) code for CSDH is S06.5×5. The code describes a traumatic subdural hematoma, which includes chronic subdural hematoma as well as acute subdural hematoma. The S06.5×5 code is used to identify and track CSDH cases in health information systems.

The ICD-11 also provides a specific code for CSDH (8A62). This code falls under the category of “intracranial and spinal haemorrhage” and provides a more detailed classification of the condition.

Yordanov et al. reported on the accuracy of diagnostic ICD codes for identifying patients with CSDH from retrospective electronic data and explore whether basic demographic data could improve the identification of CSDH.

Data were collected retrospectively from the hospital administrative system between 2014 and 2018 of all patients coded with either S065 or I620. Analysis of the ICD codes in identifying patients with CSDH diagnosis was calculated using the caretR package in RStudioR,.and stepwise logistic regression analysis was performed to evaluate the best predictive model for CSDH.

A total of 1861 patients were identified. Of these, 189 (10.2%) had a diagnosis of non-traumatic SDH (I620) and 1672 (89.8%) traumatic subdural haematomas (S065). Variables that identified CSDH as a diagnosis on univariate logistic regression included male sex (Odds Ratios (OR) - 1.606 (1.197-2.161), elderly age (OR) - 1.023 (1.015-1.032) per year for age (p < 0.001) and shorter length of hospital stay. Using stepwise regression against AIC the best model to predict CSDH included male sex, older age, and shorter LOS. The calculated sensitivity for identifying CSDH with the model is 88.4% with a specificity of 84.5% and PPV of 87.9%.

CSDH is a common neurosurgical pathology with increasing incidence and ongoing unmet clinical need. Yordanov et al. demonstrated that case ascertainment for research purposes can be improved with the incorporation of additional demographic data but at the expense of significant case exclusion ²⁾