“Idealized” vs. “True” learning curves: the case of laparoscopic liver resection

Abstract

The "true" learning curve for LLR is more appropriately described as alternating periods of improvement and regression until mastery is achieved. Surgeons should understand the true learning curves of procedures they perform, recognizing and mitigating the increased risk they assume by taking on more complex procedures.

Trends in indications, complications and outcomes for venous resection during pancreatoduodenectomy

“…The possible reasons for this are a case-mix effect (undertaking a more complex procedure), or overconfidence resulting in lapses in technique or judgement 26 . For other areas of hepatopancreatobiliary surgery, it has recently been shown that the learning curve for laparoscopic liver surgery, even for a single-surgeon experience, is comprised of cycles of alternating improvement and regression, partly owing to an increase in major resections over time 27 . The first 42 patients in the present cohort were included over 72 months, but the annual number of venous resections increased substantially in the latest period.…”

Is there evidence for a surgeon learning curve for endothelial keratoplasty in Australia?

“…Many studies split their cases into cohorts of arbitrary size, based on total numbers analysed, date of data collection or other external factors . In selecting our analyses, we sought to allow the data to indicate the length of learning curve, rather than simply exploring comparisons between groups of grafts based on arbitrary levels of surgeon experience.…”

“…Many studies split their cases into cohorts of arbitrary size, based on total numbers analysed, date of data collection or other external factors. 2,26,[28][29][30][31][32] In Table 4. Cox proportional hazards regression model for Descemet stripping endothelial keratoplasty (DSEKs) and Descemet stripping automated endothelial keratoplasty (DSAEKs) combined, including hazard ratio (HR), standard error (SE) and confidence interval (CI), obtained via hierarchical exclusion of variables based on level of significance until all remaining variables made a significant independent contribution to the model selecting our analyses, we sought to allow the data to indicate the length of learning curve, rather than simply exploring comparisons between groups of grafts based on arbitrary levels of surgeon experience.…”

Advances and challenges in laparoscopic surgery in the management of hepatocellular carcinoma

“…There are issues regarding the nature of the learning curve. Even though it is thought of as an “idealized” curve, gradually progressing until reaching a plateau, Villani et al[ 79 ] could not but notice several improvements and regressions regarding complications, operative time and blood loss, associated partially to the constantly increasing complexity of the procedures attempted. As a consequence, they proposed the model of the “true” learning curve for LLR, which is characterized by a pattern of “ups and downs” until surgeons become experienced, when their performance reaches peak and the beneficial outcomes are constantly seen.…”