Do Long-time Team-mates Lead to Better Team Performance? A Social Network Analysis of Data from Major League Baseball

Dual attending surgeon strategy learning curve in single-staged posterior spinal fusion (PSF) surgery for 415 idiopathic scoliosis (IS) cases

BACKGROUND CONTEXT

The implementation of a dual attending surgeon strategy had improved perioperative outcomes of idiopathic scoliosis (IS) patients. Nevertheless, the learning curve of a dual attending surgeon practice in single-staged posterior spinal fusion (PSF) surgery has not been established.

OBJECTIVE

To evaluate the surgical learning curve of a dual attending surgeon strategy in IS patients.

STUDY DESIGN

Retrospective study.

PATIENT SAMPLE

415 IS patients (Cobb angle <90°) who underwent PSF using a dual attending surgeon strategy OUTCOME MEASURES: Primary outcomes included operative time, total blood loss, allogenic blood transfusion requirement, length of hospital stay and perioperative complication rate.

METHODS

Regression analysis using Locally Weighted Scatterplot Smoothing (LOWESS) method was applied to create the best-fit-curve between case number versus operative time and total blood loss in identifying cut-off points for the learning curve.

RESULTS

The mean Cobb angle was 60.8±10.8°. Mean operative time was 134.4±32.1 minutes and mean total blood loss was 886.0±450.6 mL. The mean length of hospital stay was 3.0±1.6 days. The learning curves of a dual attending surgeon strategy in this study were established at the 115th case (operative time) and 196th case (total blood loss) respectively (p<.001). In comparison of cases before and after the cut-off points, mean operative time reduced significantly from 147.2±36.5 minutes to 129.5±28.9 minutes and mean total blood loss reduced significantly from 1015.1±506.6 mL to 770.4±357.3 mL (p<.001). No allogenic blood transfusion was required and there were 7 perioperative complications (n=7/415, 1.7%) recorded.

CONCLUSION

The learning curve of a dual surgeon strategy in single-staged PSF surgery based on operative time and total blood loss were established at 115th case and 196th case respectively (p<.001).

The Role of Hypernetworks as a Multilevel Methodology for Modelling and Understanding Dynamics of Team Sports Performance

Despite its importance in many academic fields, traditional scientific methodologies struggle to cope with analysis of interactions in many complex adaptive systems, including team sports. Inherent features of such systems (e.g. emergent behaviours) require a more holistic approach to measurement and analysis for understanding system properties. Complexity sciences encompass a holistic approach to research on collective adaptive systems, which integrates concepts and tools from other theories and methods (e.g. ecological dynamics and social network analysis) to explain functioning of such systems in their natural environments. Multilevel networks and hypernetworks comprise novel and potent methodological tools for assessing team dynamics at more sophisticated levels of analysis, increasing their potential to impact on competitive performance in team sports. Here, we discuss how concepts and tools derived from studies of multilevel networks and hypernetworks have the potential for revealing key properties of sports teams as complex, adaptive social systems. This type of analysis can provide valuable information on team performance, which can be used by coaches, sport scientists and performance analysts for enhancing practice and training. We examine the relevance of network sciences, as a sub-discipline of complexity sciences, for studying the dynamics of relational structures of sports teams during practice and competition. Specifically, we explore the benefits of implementing multilevel networks, in contrast to traditional network techniques, highlighting future research possibilities. We conclude by recommending methods for enhancing the applicability of hypernetworks in analysing team dynamics at multiple levels.