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Predictive Modeling of Length of Hospital Stay Following Adult Spinal Deformity Correction: Analysis of 653 Patients with an Accuracy of 75% within 2 Days.

dc.contributor.author Shaffrey, Christopher
dc.contributor.author Safaee, Michael M
dc.contributor.author Scheer, Justin K
dc.contributor.author Ailon, Tamir
dc.contributor.author Smith, Justin S
dc.contributor.author Hart, Robert A
dc.contributor.author Burton, Douglas C
dc.contributor.author Bess, Shay
dc.contributor.author Neuman, Brian J
dc.contributor.author Passias, Peter G
dc.contributor.author Miller, Emily
dc.contributor.author Schwab, Frank
dc.contributor.author Lafage, Virginie
dc.contributor.author Klineberg, Eric O
dc.contributor.author Ames, Christopher P
dc.date.accessioned 2018-10-05T16:39:20Z
dc.date.available 2018-10-05T16:39:20Z
dc.date.issued 2018-07
dc.identifier S1878-8750(18)30780-0
dc.identifier.issn 1878-8750
dc.identifier.issn 1878-8769
dc.identifier.uri https://hdl.handle.net/10161/17582
dc.description.abstract Length of stay (LOS) after surgery for adult spinal deformity (ASD) is a critical period that allows for optimal recovery. Predictive models that estimate LOS allow for stratification of high-risk patients.A prospectively acquired multicenter database of patients with ASD was used. Patients with staged surgery or LOS >30 days were excluded. Univariable predictor importance ≥0.90, redundancy, and collinearity testing were used to identify variables for model building. A generalized linear model was constructed using a training dataset developed from a bootstrap sample; patients not randomly selected for the bootstrap sample were selected to the training dataset. LOS predictions were compared with actual LOS to calculate an accuracy percentage.Inclusion criteria were met by 653 patients. The mean LOS was 7.9 ± 4.1 days (median 7 days; range, 1-28 days). Following bootstrapping, 893 patients were modeled (653 in the training model and 240 in the testing model). Linear correlations for the training and testing datasets were 0.632 and 0.507, respectively. The prediction accuracy within 2 days of actual LOS was 75.4%.Our model successfully predicted LOS after ASD surgery with an accuracy of 75% within 2 days. Factors relating to actual LOS, such as rehabilitation bed availability and social support resources, are not captured in large prospective datasets. Predictive analytics will play an increasing role in the future of ASD surgery, and future models will seek to improve the accuracy of these tools.
dc.language eng
dc.relation.ispartof World neurosurgery
dc.relation.isversionof 10.1016/j.wneu.2018.04.064
dc.subject International Spine Study Group
dc.subject Spinal Cord
dc.subject Humans
dc.subject Length of Stay
dc.subject Neurosurgical Procedures
dc.subject Retrospective Studies
dc.subject Prospective Studies
dc.subject Predictive Value of Tests
dc.subject Adolescent
dc.subject Adult
dc.subject Aged
dc.subject Aged, 80 and over
dc.subject Middle Aged
dc.subject Female
dc.subject Male
dc.subject Young Adult
dc.title Predictive Modeling of Length of Hospital Stay Following Adult Spinal Deformity Correction: Analysis of 653 Patients with an Accuracy of 75% within 2 Days.
dc.type Journal article
dc.date.updated 2018-10-05T16:39:19Z
pubs.begin-page e422
pubs.end-page e427
pubs.organisational-group School of Medicine
pubs.organisational-group Duke
pubs.organisational-group Orthopaedics
pubs.organisational-group Clinical Science Departments
pubs.publication-status Published
pubs.volume 115


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