Robotic partial nephrectomy – Evaluation of the impact of case mix on the procedural learning curve

Roman, A.; Ahmed, Kamran; Challacombe, Benjamin

doi:10.1016/j.ijsu.2016.03.001

Cited by 9 publications

(4 citation statements)

References 11 publications

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“…The learning curve for RAPN is a matter of debate because there is no consensus about the definition of ‘learning curve’, which is often affected by previous experience. Using various parameters, several studies have suggested that learning curve length ranges from 5 to 150 cases ; however, in a recent study, Roman et al analysed the impact of case mix on the RAPN learning curve and showed that the learning curve of RAPN should be ongoing and hence there should not be a defined endpoint, nor could it be adequately modelled. Interestingly, when they used the common definitions, they showed that cases required to overcome the learning curve might range from 20 to 65; therefore, we chose the threshold of 60 cases in order to limit the impact of the learning curve of the expert surgeon on the results.…”

Section: Discussionmentioning

confidence: 99%

Does training of fellows affect peri‐operative outcomes of robot‐assisted partial nephrectomy?

et al. 2017

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Section: Discussionmentioning

confidence: 99%

Does training of fellows affect peri‐operative outcomes of robot‐assisted partial nephrectomy?

et al. 2017

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“…The learning curve of robotic assisted partial nephrectomy (RAPN) is steep. For surgeons already experienced with laparoscopic partial nephrectomy, the true learning curve has been proposed to be up to 65 cases, depending on the definition of proficiency ( 1 ). Adherent perinephric fat (APF), colloquially known as “sticky fat” can frustrate surgeons and complicate RAPN.…”

Section: Introductionmentioning

confidence: 99%

Prospective evaluation of the effect of adherent perinephric fat on outcomes of robotic assisted partial nephrectomy following elimination of the learning curve

et al. 2019

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Purpose: To prospectively evaluate the association of adherent perinephric fat (APF) on perioperative outcomes of robotic-assisted partial nephrectomy (RAPN) following elimination of the surgical learning curve. Materials and Methods: 305 consecutive RAPNs performed by a single experienced surgeon were analyzed. The first 100 RAPNs were considered the learning curve and therefore excluded. APF was defined as the necessity of subcapsular renal dissection to mobilize the tumor from surrounding perinephric fat. Perioperative outcomes were evaluated including operative time, warm ischemia time (WIT), postoperative complications, length of stay, margins, ischemia, and complications score (MIC), estimated blood loss (EBL), and change in pre-operative to postoperative day 1 (POD 1) laboratory values. After correction for multiple comparisons, P values ≤0.0045 were considered statistically significant but associations with P values ≤0.05 were also mentioned in the study results. Results: Fifty-eight (28.3%) patients had APF. Patients with APF had longer operative times compared to those without APF (median, 213 vs. 192 minutes, P <0.001). There was some evidence of higher increase in change in creatinine from preoperative to POD 1 among those with APF compared to those without APF, although this was not statistically significant (median, 0.2 vs. 0.1mg/dL, P=0.03). There were no other statistically significant associations between presence of APF and perioperative outcomes. Conclusions: APF is associated with increased operative time but no change in other perioperative outcomes. Surgeon experience does not affect perioperative outcomes associated with APF.

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“…The conventional view of the surgical learning curve having just one ascent and one plateau phase was challenged in this review by reports of a multiphasic learning curve arising from the tendency of surgeons to take on increasingly complex cases as their confidence improved with experience 94 , 108 . The case mix effect is well-documented in the literature as a key factor in shaping the learning curve 3 , 123 , particularly in the post-plateau phase 124 .…”

Section: Discussionmentioning

confidence: 99%

The learning curves of major laparoscopic and robotic procedures in urology: A systematic review

Chahal

Aydın

Amin

et al. 2023

International Journal of Surgery

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Background: Urology has been at the forefront of adopting laparoscopic and robot-assisted techniques to improve patient outcomes. This systematic review aimed to examine the literature relating to the learning curves of major urological robotic and laparoscopic procedures. Methods: In accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic literature search strategy was employed across PubMed, EMBASE, and the Cochrane Library from inception to December 2021, alongside a search of the grey literature. Two independent reviewers completed the article screening and data extraction stages using the Newcastle–Ottawa Scale as a quality assessment tool. The review was reported in accordance with AMSTAR (A MeaSurement Tool to Assess systematic Reviews) guidelines. Results: Of 3702 records identified, 97 eligible studies were included for narrative synthesis. Learning curves are mapped using an array of measurements including operative time (OT), estimated blood loss, complication rates as well as procedure-specific outcomes, with OT being the most commonly used metric by eligible studies. The learning curve for OT was identified as 10–250 cases for robot-assisted laparoscopic prostatectomy and 40–250 for laparoscopic radical prostatectomy. The robot-assisted partial nephrectomy learning curve for warm ischaemia time is 4–150 cases. No high-quality studies evaluating the learning curve for laparoscopic radical cystectomy and for robotic and laparoscopic retroperitoneal lymph node dissection were identified. Conclusion: There was considerable variation in the definitions of outcome measures and performance thresholds, with poor reporting of potential confounders. Future studies should use multiple surgeons and large sample sizes of cases to identify the currently undefined learning curves for robotic and laparoscopic urological procedures.

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Robotic partial nephrectomy – Evaluation of the impact of case mix on the procedural learning curve

Cited by 9 publications

References 11 publications

Does training of fellows affect peri‐operative outcomes of robot‐assisted partial nephrectomy?

Does training of fellows affect peri‐operative outcomes of robot‐assisted partial nephrectomy?

Prospective evaluation of the effect of adherent perinephric fat on outcomes of robotic assisted partial nephrectomy following elimination of the learning curve

The learning curves of major laparoscopic and robotic procedures in urology: A systematic review

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