Evaluating the Learning Curve for Subarachnoid Spinal Anesthesia Among Anesthesiology Fellows Using CUSUM Analysis. How Much is Enough?

Background: Subarachnoid spinal anesthesia is a critical yet technically challenging procedure in anesthesiology. Despite its importance, limited data are available on the number of attempts required for trainees to achieve competency and proficiency. Cumulative sum (CUSUM) analysis provides a systematic approach to evaluating learning curves and establishing benchmarks for procedural success. Methods: This study included 39 first-year anesthesiology fellows at the University of Brescia from January 2021 to January 2023. Residents recorded 1,624 spinal anesthesia procedures using an online data collection system. CUSUM analysis was used to evaluate performance trends and determine competency thresholds, defined as “competent” (failure rate ≤ 15%) and “proficient” (failure rate ≤ 10%). Multilevel logistic regression identified factors influencing procedural outcomes. Results: Data from nine fellows maintaining consecutive records were analyzed. Competency was achieved within 16–153 procedures (median: 39), while proficiency required a mean of 67 procedures. Linear learning trajectories were observed in most residents, although variability existed, with some requiring additional training to stabilize performance. Key factors influencing failure included BMI > 40 (OR = 4.53), poorly palpable interspinous spaces (OR = 2.19–9.43), and sitting position (OR = 0.42). Experience reduced failure rates by 2.63% per additional procedure (p < 0.001). Discussion: CUSUM analysis effectively tracked learning curves and identified individual progress. Competency benchmarks supported structured training programs, while patient and procedural variables highlighted the need for diverse clinical exposure. Variability among trainees underscored the importance of tailored feedback and support. Conclusions: Competency in subarachnoid spinal anesthesia is typically achieved after a median of 39 procedures, with proficiency requiring further practice. CUSUM analysis offers a robust framework for optimizing anesthesiology training, enhancing procedural success, and ensuring patient safety.