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Background The goal of this study was to create a comprehensive, integer‐weighted predictive scale of adverse events after carotid endarterectomy (CEA), which may augment risk stratification and patient counseling. Methods and Results The targeted carotid files from the prospective NSQIP (National Surgical Quality Improvement Program) registry (2011–2013) comprised the derivation population. Multivariable logistic regression evaluated predictors of a 30‐day adverse event (stroke, myocardial infarction, or death), the effect estimates of which were used to build a weighted predictive scale that was validated using the 2014 to 2015 NSQIP registry release. A total of 10 766 and 8002 patients were included in the derivation and the validation populations, in whom 4.0% and 3.7% developed an adverse event, respectively. The NSQIP registry CEA scale included 14 variables; the highest points were allocated for insulin‐dependent diabetes mellitus, high‐risk cardiac physiological characteristics, admission source other than home, an emergent operation, American Society of Anesthesiologists’ classification IV to V, modified Rankin Scale score ≥2, and presentation with a stroke. NSQIP registry CEA score was predictive of an adverse event (concordance=0.67), stroke or death (concordance=0.69), mortality (concordance=0.76), an extended hospitalization (concordance=0.73), and a nonroutine discharge (concordance=0.83) in the validation population, as well as among symptomatic and asymptomatic subgroups (P8 and 17 had 30‐day stroke or death rates >3% and 6%, the recommended thresholds for asymptomatic and symptomatic patients, respectively. Conclusions The NSQIP registry CEA scale predicts adverse outcomes after CEA and can risk stratify patients with both symptomatic and asymptomatic carotid stenosis using different thresholds for each population.

Abstract Background Although International Classification of Disease, Ninth Revision, Clinical Modification (ICD9-CM) coding is the basis of administrative claims data, no study has validated an ICD9-CM algorithm to identify patients undergoing decompressive craniectomy for space-occupying supratentorial infarction. Methods Patients who underwent decompressive craniectomy for stroke at our institution were retrospectively identified and their associated ICD9-CM codes were extracted from billing data. An ICD9-CM algorithm was generated and its accuracy compared against physician review. Results A total of 10,925 neurosurgical operations were performed from December 2008 to March 2015, of which 46 (0.4%) were decompressive craniectomy for space-occupying stroke. The ICD9-CM procedure code for craniectomy (01.25) was only encoded in 67.4% of patients, while craniotomy (01.24) was used in 19.6% and lobectomy (01.39, 01.53, 01.59) in 13.1%. The ICD-9-CM algorithm included patients with a diagnosis codes for cerebral infarction (433.11, 434.01, 434.11, and 434.91) and a procedure code for craniotomy, craniectomy, or lobectomy. Patients were excluded with an ICD9-CM diagnosis code for brain tumor, intracranial abscess, subarachnoid hemorrhage, vertebrobasilar infarction, intracranial aneurysm, Moyamoya disease, intracranial venous sinus thrombosis, vertebral artery dissection, congenital cerebrovascular anomaly, head trauma or an ICD9-CM procedure code for laminectomy. This algorithm had a sensitivity of 97.8%, specificity of 99.9%, positive predictive value of 88.2%, and negative predictive value of 99.9%. The majority of false-positive results were patients who underwent evacuation of a primary intracerebral hematoma. Conclusion An ICD-9-CM algorithm based on diagnosis and procedure codes can effectively identify patients undergoing decompressive craniectomy for supratentorial stroke.

Background During the COVID-19 pandemic, decreased volumes of stroke admissions and mechanical thrombectomy were reported. The study’s objective was to examine whether subarachnoid haemorrhage (SAH) hospitalisations and ruptured aneurysm coiling interventions demonstrated similar declines.Methods We conducted a cross-sectional, retrospective, observational study across 6 continents, 37 countries and 140 comprehensive stroke centres. Patients with the diagnosis of SAH, aneurysmal SAH, ruptured aneurysm coiling interventions and COVID-19 were identified by prospective aneurysm databases or by International Classification of Diseases, 10th Revision, codes. The 3-month cumulative volume, monthly volumes for SAH hospitalisations and ruptured aneurysm coiling procedures were compared for the period before (1 year and immediately before) and during the pandemic, defined as 1 March–31 May 2020. The prior 1-year control period (1 March–31 May 2019) was obtained to account for seasonal variation.Findings There was a significant decline in SAH hospitalisations, with 2044 admissions in the 3 months immediately before and 1585 admissions during the pandemic, representing a relative decline of 22.5% (95% CI −24.3% to −20.7%, p