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Jeff Ehresman, Zach Pennington, Aditya V. Karhade, Sakibul Huq, Ravi Medikonda, Andrew Schilling, James Feghali, Andrew Hersh, A. Karim Ahmed, Ethan Cottrill, Daniel Lubelski, Erick M. Westbroek, Joseph H. Schwab and Daniel M. Sciubba

OBJECTIVE

Incidental durotomy is a common complication of elective lumbar spine surgery seen in up to 11% of cases. Prior studies have suggested patient age and body habitus along with a history of prior surgery as being associated with an increased risk of dural tear. To date, no calculator has been developed for quantifying risk. Here, the authors’ aim was to identify independent predictors of incidental durotomy, present a novel predictive calculator, and externally validate a novel method to identify incidental durotomies using natural language processing (NLP).

METHODS

The authors retrospectively reviewed all patients who underwent elective lumbar spine procedures at a tertiary academic hospital for degenerative pathologies between July 2016 and November 2018. Data were collected regarding surgical details, patient demographic information, and patient medical comorbidities. The primary outcome was incidental durotomy, which was identified both through manual extraction and the NLP algorithm. Multivariable logistic regression was used to identify independent predictors of incidental durotomy. Bootstrapping was then employed to estimate optimism in the model, which was corrected for; this model was converted to a calculator and deployed online.

RESULTS

Of the 1279 elective lumbar surgery patients included in this study, incidental durotomy occurred in 108 (8.4%). Risk factors for incidental durotomy on multivariable logistic regression were increased surgical duration, older age, revision versus index surgery, and case starts after 4 pm. This model had an area under curve (AUC) of 0.73 in predicting incidental durotomies. The previously established NLP method was used to identify cases of incidental durotomy, of which it demonstrated excellent discrimination (AUC 0.97).

CONCLUSIONS

Using multivariable analysis, the authors found that increased surgical duration, older patient age, cases started after 4 pm, and a history of prior spine surgery are all independent positive predictors of incidental durotomy in patients undergoing elective lumbar surgery. Additionally, the authors put forth the first version of a clinical calculator for durotomy risk that could be used prospectively by spine surgeons when counseling patients about their surgical risk. Lastly, the authors presented an external validation of an NLP algorithm used to identify incidental durotomies through the review of free-text operative notes. The authors believe that these tools can aid clinicians and researchers in their efforts to prevent this costly complication in spine surgery.

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Sonia Ajmera, Ryan P. Lee, Andrew Schultz, David S. Hersh, Jacob Lepard, Raymond Xu, Hassan Saad, Olutomi Akinduro, Melissa Justo, Brittany D. Fraser, Mustafa Motiwala, Pooja Dave, Brian Jimenez, David A. Wallace, Olufemi Osikoya, Sebastian Norrdahl, Jennings H. Dooley, Nickalus R. Khan, Brandy N. Vaughn, Cormac O. Maher and Paul Klimo Jr.

OBJECTIVE

The objective of this study was to analyze the publication output of postgraduate pediatric neurosurgery fellows for a 10-year period as well as identify 25 individual highly productive pediatric neurosurgeons. The correlation between academic productivity and the site of fellowship training was studied.

METHODS

Programs certified by the Accreditation Council for Pediatric Neurosurgery Fellowships that had 5 or more graduating fellows from 2006 to 2015 were included for analysis. Fellows were queried using Scopus for publications during those 10 years with citation data through 2017. Pearson correlation coefficients were calculated, comparing program rankings of faculty against fellows using the revised Hirsch index (r-index; primary) and Hirsch index (h-index; secondary). A list of 25 highly accomplished individual academicians and their fellowship training locations was compiled.

RESULTS

Sixteen programs qualified with 152 fellows from 2006 to 2015; 136 of these surgeons published a total of 2009 articles with 23,735 citations. Most publications were pediatric-specific (66.7%) clinical articles (93.1%), with middle authorship (55%). Co-investigators were more likely from residency than fellowship. There was a clustering of the top 7 programs each having total publications of around 120 or greater, publications per fellow greater than 12, more than 1200 citations, and adjusted ir10 (revised 10-year institutional h-index) and ih10 (10-year institutional h-index) values of approximately 2 or higher. Correlating faculty and fellowship program rankings yielded correlation coefficients ranging from 0.53 to 0.80. Fifteen individuals (60%) in the top 25 (by r5 index) list completed their fellowship at 1 of these 7 institutions.

CONCLUSIONS

Approximately 90% of fellowship-trained pediatric neurosurgeons have 1 or more publications, but the spectrum of output is broad. There is a strong correlation between where surgeons complete their fellowships and postgraduate publications.