Identification of factors associated with morbidity and postoperative length of stay in surgically managed chronic subdural haematoma using electronic health records: a retrospective cohort study

Abstract

IntroductionChronic subdural haematoma (cSDH) tends to occur in older patients, often with significant comorbidity. The incidence and effect of medical complications as well as the impact of intraoperative management strategies are now attracting increasing interest.ObjectivesWe used electronic health record data to study the profile of in-hospital morbidity and examine associations between various intraoperative events and postoperative stay.Design, setting and participantsSingle-centre, retrospective cohort of 530 cases of cSDH (2014–2019) surgically evacuated under general anaesthesia at a neurosciences centre in Cambridge, UK.Methods and outcome definitionComplications were defined using a modified Electronic Postoperative Morbidity Score. Association between complications and intraoperative care (time with mean arterial pressure <80 mm Hg, time outside of end-tidal carbon dioxide (ETCO2) range of 3–5 kPa, maintenance anaesthetic, operative time and opioid dose) on postoperative stay was assessed using Cox regression.Results53 (10%) patients suffered myocardial injury, while 24 (4.5%) suffered acute renal injury. On postoperative day 3 (D3), 280 (58% of remaining) inpatients suffered at least 1 complication. D7 rate was comparable (57%). Operative time was the only intraoperative event associated with postoperative stay (HR for discharge: 0.97 (95% CI: 0.95 to 0.99)). On multivariable analysis, postoperative complications (0.61 (0.55 to 0.68)), anticoagulation (0.45 (0.37 to 0.54)) and cognitive impairment (0.71 (0.58 to 0.87)) were associated with time to discharge.ConclusionsThere is a high postoperative morbidity burden in this cohort, which was associated with postoperative stay. We found no evidence of an association between intraoperative events and postoperative stay.

Incidence of chronic subdural haematoma: a single-centre exploration of the effects of an ageing population with a review of the literature

“…The significance of these findings on neurosurgical services is clearly apparent. Patients with cSDH exhibit a significant degree of inpatient morbidity [24] that negatively impacts on length of stay. Any increase in this workload will further stress a system that already struggles to cope with the complexities of workload, capacity, referral and repatriation [8].…”

Can compliment and complaint data inform the care of individuals with chronic subdural haematoma (cSDH)?

“…In order to evaluate the role of PALS data against traditional performance indicators, clinical care metrics, included those previously identified in this series of patients 11 and for cSDH in general by others 12 13 were taken from hospital care records. This included age, gender, independence before admission, American Society of Anesthesiologists score, admission date, referral source (local vs referred), operation date, discharge date, whether they required a reoperation, anticoagulation status and occurrence of an in-hospital complication.…”

“…Patients with cSDH pose an increasing challenge for neurosurgical care, as the condition typically occurs in elderly comorbid populations and, with well-documented changes in population demographics, 10 these numbers may rise. 11 Consequently, methods to monitor and optimise care delivery would be valuable. 12 13 This can be a particular challenge for a service involving multiple healthcare providers or centres.…”

Exploratory Analysis of Preoperative and Postoperative Risk Stratification Tools to Identify Acute Kidney and Myocardial Injury in Patients Undergoing Surgery for Chronic Subdural Haematoma

“…Such tools inform intraoperative and postoperative care as part of the National Emergency Laparotomy Audit (NELA) . Patients with chronic subdural haematomas (cSDH) are often elderly with significant comorbidity 2 . Despite this, there is a paucity of literature pertaining to risk stratification models in this cohort 3 .…”

“…Physiological state was encapsulated on each admission day using the electronic postoperative morbidity score (ePOMS) 5 (details in supplemental digital content). Full details of variable generation are published elsewhere 2 . Missing data was handled by multiple imputation 6 .…”