Early Predictors of Global Functional Outcome after Traumatic Spinal Cord Injury: A Systematic Review
Bibliographic record
Abstract
Accurately predicting functional recovery is an asset for all clinicians and decision makers involved in the care of patients with acute traumatic spinal cord injury (TSCI). Unfortunately, there is a lack of information on the relative importance of significant predictors of global functional outcome. There is also a need for identifying functional predictors that can be timely optimized by the medical and rehabilitation teams throughout the hospitalizations phases. The main objective of this work was to systematically review and rate early factors that are consistently and independently associated with global functional outcome in individuals with TSCI. A literature search using MEDLINE, EMBASE, and Cochrane databases from January 1, 1970 to April 1, 2017 was performed. Two authors independently reviewed the titles and abstracts yielded by this literature search and subsequently selected studies to be included based on predetermined eligibility criteria. Disagreements were resolved by a consensus-based discussion, and if not, by an external reviewer. Data were extracted by three independent reviewers using a standardized table. The quality of evidence of the individual studies was assessed based on the Oxford Center for Evidence-Based Medicine modified by Wright and colleagues (2000) as well as the National Institutes of Health (2014). Fifteen articles identifying early clinical predictors of functional outcome using multiple regression analyses were included in this systematic review. Based on the compiled data, this review proposes a rating of early factors associated to global functional outcome according to their importance and their potential to be modified by the medical/rehabilitation team throughout the early phases of hospitalization. It also proposes a new conceptual framework that illustrates the impact of specific categories of factors and their interaction with each other. Ultimately, this review aims to guide clinicians and researchers in improving the continuum of care throughout early phases post-SCI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".