The Use of Validated Clinical Outcome Measures in Spinal Surgery: An Analysis of Recent Annual Meeting Abstracts
Bibliographic record
Abstract
Introduction Recently, the field of outcome assessment for patients undergoing spinal surgery has become the focus of investigation. Health-related quality of life outcome measures are fundamental to our understanding of the impact of surgical intervention on patients. Major spine academic groups have placed increasing emphasis on the use of HRQOL outcome measures, and this is no more obvious that in the requirements for abstract submissions to annual scientific meetings. The purpose of our study was to analyze the use of clinical outcome measures in abstracts accepted to the North American Spine Society (NASS) and Canadian Spine Society (CSS) annual meetings from 2010 to 2013 inclusively. We investigated the disease populations studied, the HRQOL outcome measures used, determined whether those measures had been validated in the specific patient population, and finally, whether the outcome measures used could be linked to the current WHO International Classification of Functioning, Disability, and Health (ICF). Material and Methods Accepted abstracts to NASS and CSS annual meetings from 2010 to 2013 were read. The frequency of abstracts containing clinical outcome measures and the frequency of validated versus non-validated outcome measures were analyzed. A systematic literature search was then performed using the Cochrane Library Database, PubMed, and the NASS evidence-based clinical guidelines. The concepts contained in the items of the 10 most commonly used outcome measures were selected and linked to the most specific ICF categories. Each concept of the outcome measure was linked to the ICF in a step-wise fashion. Results A total of 1,663 abstracts were read from the CSS and NASS from 2010 to 2013 inclusively. Of the abstracts accepted to CSS and NASS, 71 and 53% contained validated outcome measures, respectively. The 10 most commonly used outcome measures were the ODI, VAS, NDI, Eq. 5D, mJOA, AIS, and RMDQ. A total of 40 spinal conditions/surgical approaches were described among the 10 most commonly used health-related outcome measures. The NASS evidence-based clinical guidelines provided validity recommendations for spondylolisthesis, radiculopathy, and spinal stenosis. The Cochrane Library Database published systematic reviews for disc arthroplasty, degenerative disc disease, vertebral fractures, spinal fusion, disc replacement, back pain, cervical spondylotic myelopathy, and thoracolumbar burst fractures. All validity analyses for the remaining conditions/surgical approaches were found through PubMed and Google Scholar. All of the concepts for each outcome measure were linkable to the ICF. Conclusion According to this study, all of the 10 most commonly used outcome measures in abstracts accepted to CSS and NASS from 2010 to 2013 inclusive were validated in the field of spinal surgery. There is, however, still a need for one universal database to determine which outcome measures would be most useful for a given spinal condition or surgical approach. All of the 10 most commonly used outcome measures were linked to the WHO ICF. This provides evidence that over the past 4 years, researchers and clinicians in spinal surgery have identified the importance of utilizing validated HRQOL outcome measures as their health predictors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.068 | 0.308 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.060 | 0.055 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".