The Reality of Accomplishing Surgery Within 24 hours for Complete Cervical Spinal Cord Injury: Clinical Practices and Safety.

  title={The Reality of Accomplishing Surgery Within 24 hours for Complete Cervical Spinal Cord Injury: Clinical Practices and Safety.},
  author={Michael Balas and Peter Pr{\"o}mmel and Laura Nguyen and Andrew S. Jack and Gerald Lebovic and Jetan H. Badhiwala and Leodante da Costa and Avery B. Nathens and Michael G. Fehlings and Jefferson R. Wilson and Christopher D. Witiw},
  journal={Journal of neurotrauma},
Substantial clinical data supports an association between superior neurological outcomes and early (within 24 hours) surgical decompression for those with traumatic cervical spinal cord injury (SCI). Despite this, much discussion persists around feasibility and safety of this time threshold, particularly for those with a complete cervical SCI. This study aims to assess clinical practices and the safety profile of early surgery across a large sample of North American trauma centers. Data was… 
1 Citations



Process benchmarking appraisal of surgical decompression of spinal cord following traumatic cervical spinal cord injury: opportunities to reduce delays in surgical management.

The benchmarking analysis suggests that health-related factors are key determinants of the timing from SCI to spinal cord decompression.

Race and socioeconomic disparity in treatment and outcome of traumatic cervical spinal cord injury with fracture: Nationwide Inpatient Sample database, 1998–2009

African-American race and low socioeconomic status (LSES) were significant predictors of lower odds to undergo surgery and unfavorable discharge disposition, respectively; potentially explained by a higher odds of increased New Injury Severity Score classification at presentation.

Comparing paired vs non-paired statistical methods of analyses when making inferences about absolute risk reductions in propensity-score matched samples

  • P. Austin
  • Psychology
    Statistics in medicine
  • 2011
Differences between the empirical and advertised performance of methods for independent samples were greater when the treatment-selection process was stronger compared with when treatment- selection process was weaker.

Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies

  • P. Austin
  • Economics
    Pharmaceutical statistics
  • 2011
An extensive series of Monte Carlo simulations were conducted to determine the optimal caliper width for estimating differences in means (for continuous outcomes) and risk differences (for binary outcomes).

A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena

Moves of variation in logistic regression should be promoted in social epidemiological and public health research as efficient means of quantifying the importance of the context of residence for understanding disparities in health and health related behaviour.

An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

  • P. Austin
  • Economics
    Multivariate behavioral research
  • 2011
The propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects, and different causal average treatment effects and their relationship with propensity score analyses are described.

Marginal Structural Models and Causal Inference in Epidemiology

In observational studies with exposures or treatments that vary over time, standard approaches for adjustment of confounding are biased when there exist time-dependent confounders that are also

Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies

Entropy balancing, a data preprocessing method to achieve covariate balance in observational studies with binary treatments, obviates the need for continual balance checking and iterative searching over propensity score models that may stochastically balance the covariate moments.