Differences between real-world and score-based decision-making in the microsurgical management of patients with unruptured intracranial aneurysms.

BACKGROUND: Management of unruptured intracranial aneurysms (UIAs) is complex, balancing the risk of rupture and risk of treatment. Therefore, prediction scores have been developed to support clinicians in the management of UIAs. We analyzed the discrepancies between interdisciplinary cerebrovascular board decision-making factors and the results of the prediction scores in our cohort of patients who received microsurgical treatment of UIAs. METHODS: Clinical, radiological, and demographical data of 221 patients presenting with 276 microsurgically treated aneurysms were collected, from January 2013 to June 2020. UIATS, PHASES, and ELAPSS were calculated for each treated aneurysm, resulting in subgroups favoring treatment or conservative management for each score. Cerebrovascular board decision-factors were collected and analyzed. RESULTS: UIATS, PHASES, and ELAPSS recommended conservative management in 87 (31.5%) respectively in 110 (39.9%) and in 81 (29.3%) aneurysms. The cerebrovascular board decision-factors leading to treatment in these aneurysms (recommended to manage conservatively in the three scores) were: high life expectancy/young age (50.0%), angioanatomical factors (25.0%), multiplicity of aneurysms (16.7%). Analysis of cerebrovascular board decision-making factors in the "conservative management" subgroup of the UIATS showed that angioanatomical factors (P=0.001) led more frequently to surgery. PHASES and ELAPSS subgroups "conservative management" were more frequently treated due to clinical risk factors (P=0.002). CONCLUSIONS: Our analysis showed more aneurysms were treated based on "real-world" decision-making than recommended by the scores. This is because these scores are models trying to reproduce reality, which is yet not fully understood. Aneurysms, which were recommended to manage conservatively, were treated mainly because of angioanatomy, high life expectancy, clinical risk factors, and patient's treatment wish. The UIATS is suboptimal regarding assessment of angioanatomy, the PHASES regarding clinical risk factors, complexity, and high life expectancy, and the ELAPSS regarding clinical risk factors and multiplicity of aneurysms. These findings support the need to optimize prediction models of UIAs.

Development of machine learning-based preoperative predictive analytics for unruptured intracranial aneurysm surgery: a pilot study.

BACKGROUND: The decision to treat unruptured intracranial aneurysms (UIAs) or not is complex and requires balancing of risk factors and scores. Machine learning (ML) algorithms have previously been effective at generating highly accurate and comprehensive individualized preoperative predictive analytics in transsphenoidal pituitary and open tumor surgery. In this pilot study, we evaluate whether ML-based prediction of clinical endpoints is feasible for microsurgical management of UIAs. METHODS: Based on data from a prospective registry, we developed and internally validated ML models to predict neurological outcome at discharge, as well as presence of new neurological deficits and any complication at discharge. Favorable neurological outcome was defined as modified Rankin scale (mRS) 0 to 2. According to the Clavien-Dindo grading (CDG), every adverse event during the post-operative course (surgery and not surgery related) is recorded as a complication. Input variables included age; gender; aneurysm complexity, diameter, location, number, and prior treatment; prior subarachnoid hemorrhage (SAH); presence of anticoagulation, antiplatelet therapy, and hypertension; microsurgical technique and approach; and various unruptured aneurysm scoring systems (PHASES, ELAPSS, UIATS). RESULTS: We included 156 patients (26.3% male; mean [SD] age, 51.7 [11.0] years) with UIAs: 37 (24%) of them were treated for multiple aneurysm and 39 (25%) were treated for a complex aneurysm. Poor neurological outcome (mRS ≥ 3) was seen in 12 patients (7.7%) at discharge. New neurological deficits were seen in 10 (6.4%), and any kind of complication occurred in 20 (12.8%) patients. In the internal validation cohort, area under the curve (AUC) and accuracy values of 0.63-0.77 and 0.78-0.91 were observed, respectively. CONCLUSIONS: Application of ML enables prediction of early clinical endpoints after microsurgery for UIAs. Our pilot study lays the groundwork for development of an externally validated multicenter clinical prediction model.

Cardiac Arrest During Spine Surgery in the Prone Position: Case Report and Review of the Literature.

OBJECTIVE: Intraoperative cardiac arrest (CA) is usually attributable to pre-existing disease or intraoperative complications. In rare cases, intraoperative stress can demask certain genetic diseases, such as catecholaminergic polymorphic ventricular tachycardia (CPVT). It is essential that neurosurgeons be aware of the etiologies, risk factors, and initial management of CA during surgery with the patient in the prone position. METHODS: We present a case of CA directly after spinal fusion for lumbar spondylolisthesis and review the literature on cardiac arrests during spinal neurosurgery in the prone position. We focus on etiologies of CA in patients with structurally normal hearts. RESULTS: After resuscitation, a 53-years-old female patient achieved return of spontaneous circulation after 17 minutes, without any neurologic deficits and with substantial improvement of functional disability and pain scores. Extensive imaging, stress testing, and genetic screening ruled out common etiologies of CA. In this patient with a structurally normal heart, CPVT was established as the most likely cause. We identified 18 additional cases of CA associated with spinal neurosurgery in the prone position. Most cases occurred during deformity or fusion procedures. Commonly reported etiologies of CA were air embolism, hypovolemia, and dural traction leading to vasovagal response. In patients with structurally normal hearts, inherited arrhythmia syndromes including CPVT, Brugada syndrome, and long QT syndrome should be included in the differential diagnosis and specifically included in testing. CONCLUSIONS: Although intraoperative CA is rare during spine surgery, neurosurgeons should be aware of the etiologies and the specific difficulties in the management associated with the prone position.