Learning Curves in Pediatric Minimally Invasive Surgery: A Systematic Review of the Literature and a Framework for Reporting
Alexander Macdonald, Munther J. Haddad, Simon A. Clarke
- 发表年份
- 2016
- 引用次数
- 27
摘要
AIMS: There exists a learning curve (LC) with the adoption of any minimally invasive surgical (MIS) technique with implications for training, implementation, and evaluation. A standardized approach to describing and analyzing LCs in pediatric MIS is lacking. We sought to determine how pediatric MIS LCs are quantified and present a framework for reporting. METHODS: Systematic search of MEDLINE and EMBASE 1985-October 2015 for articles describing MIS in the pediatric population and presenting formal analysis of the LC. Articles screened by two independent reviewers. RESULTS: Twenty-nine articles (n = 17 general abdominal/thoracic, n = 12 urological) from an 18-year period (1997-2015) were included representing 3345 procedures (n = 3116 laparoscopic, n = 10 thoracoscopic, n = 219 robotic). Seven (24%) were prospective, three multicenter. Twenty-two (76%) presented data pertaining to >1 operating surgeon. Operative time was the most commonly employed surrogate of proficiency (n = 26 [90%] studies). Twenty (69%) described >1 LC outcome measure. Sixteen additional measures were described, including conversion (n = 12 studies); blood loss (n = 4 studies); complications (n = 10 studies); and postoperative outcomes (n = 14 studies). Three studies assessed impact of LC on trainees and one considered economic impact. LCs were presented in tabular form (n = 14 studies) and graphically (n = 19). Eleven (38%) studies undertook statistical appraisal utilizing comparative statistics (n = 8 studies) and regression analysis (n = 4 studies). CONCLUSIONS: Multiple outcome measures of proficiency are employed in reporting pediatric MIS experience and analysis of LCs is inconsistent. A standardized multioutcome approach to reporting should be encouraged. In addition, attempts should be made to quantify the impact on trainee involvement. We present an idealized framework for reporting.
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