Training in Neurology: Diagnostic Accuracy Among Neurology Residents

Abstract

ObjectiveTo describe cases presented by junior neurology residents, and to evaluate resident diagnostic patterns to help address individual and systemic educational needs.MethodsFor 6 academic years, details of all morning report cases assessed and presented by junior neurology residents were logged, including the resident's independent initial diagnostic impression. Cases were later revisited at subsequent morning reports to “close the loop” on a final diagnosis. We conducted retrospective review to quantify case demographics and to determine resident diagnostic accuracy based on pre-specified localization pathways.ResultsDemographic analysis included 1,472 cases; of these, 1,301 qualified for accuracy analysis due to diagnostic uncertainty at time of morning report. Non-neurologic etiologies represented 26.0% of cases. Central nervous system etiologies were the majority (86.0%) of neurologic cases. The most frequent diagnoses were ischemic stroke and seizure. Overall resident diagnostic accuracy was 64.0%. Accuracy was similar between central and peripheral etiologies. Of 1,301 cases, 15.3% were overcalled as neurologic, while neurologic disease was rarely mistaken as non-neurologic (5.1%). Most diagnostic errors (49.1%) occurred when determining if a case was neurologic. Where in the localization pathway errors occurred varied between etiologies.ConclusionOverall diagnostic accuracy for neurology junior residents in our cohort was similar to prior work conducted in smaller samples. Analysis of errors, particularly at the critical “neurologic or non-neurologic” decision-point, warrants further investigation. “Close the loop” methodology is simple to employ and can guide educational and quality initiatives to improve neurology resident clinical acumen.

Identifying falls remotely in people with multiple sclerosis

“…Prior studies have generally cited higher EDSS as a fall risk factor for people with MS, [ 14 , 44 ]; however, recent literature reveals risk of falls even in people recently diagnosed with MS and low disability levels [ 45 ]. While most falls in our dataset occurred in patients with moderate to severe MS-related disability (EDSS ≥ 4), 12% of Fallers had EDSS < 4 (indicating a milder degree of walking impairment).…”