Perioperative statistical risk stratification is widespread. Such tools inform intraoperative and postoperative care as part of the National Emergency Laparotomy Audit (NELA)1.

Patients with chronic subdural haematomas (cSDH) are often elderly with significant comorbidity2. Despite this, there is a paucity of literature pertaining to risk stratification models in this cohort3. At our centre, as part of a multidisciplinary improvement initiative (the ‘Improving Care in Elderly Neurosurgery Initiative’ (ICENI)4) (Project ID:PRN7705) we demonstrated a significant association between postoperative complications and length of stay2. As a further analysis within this cohort of operated cSDH, we explore the potential of using retrospective electronic health record (EHR) data to generate prognostic statistical models for the identification of two end-organ complications (myocardial injury –troponin above the upper limit of normal and acute kidney injury (AKI) –a rise in serum creatinine of ≥ 1.5 times baseline). Outcomes were chosen based on data availability and veracity as well as clinical relevance. The integrated nature of our EHR permitted incorporation of variables reflecting intraoperative management. This enabled an exploratory analysis of models that, analogous to NELA, could be used preoperatively and updated postoperatively.