Impact of different surgical and non-surgical interventions on health-related quality of life after thoracolumbar burst fractures without neurological deficit: protocol for a comprehensive systematic review with network meta-analysis
Bibliographic record
Abstract
INTRODUCTION: There is no international consensus on how to treat thoracolumbar burst fractures (TLBFs) without neurological deficits. The planned systematic review with network meta-analyses (NMA) aims to compare the effects on treatment outcomes, focusing on midterm health-related quality of life (HRQoL). METHODS AND ANALYSIS: We will conduct a comprehensive and systematic literature search, identifying studies comparing two or more treatment modalities. We will search MEDLINE, EMBASE, Google Scholar, Scopus and Web of Science from January 2000 until July 2023 for publications. We will include (randomised and non-randomised) controlled clinical trials assessing surgical and non-surgical treatment methods for adults with TLBF. Screening of references, data extraction and risk of bias (RoB) assessment will be done independently by two reviewers. We will extract relevant studies, participants and intervention characteristics. The RoB will be assessed using the revised Cochrane RoB V.2.0 tool for randomised trials and the Newcastle-Ottawa Scale for controlled trials. The OR for dichotomous data and standardised mean differences for continuous data will be presented with their respective 95% CIs. We will conduct a random-effects NMA to assess the treatments and determine the superiority of the therapeutic approaches. Our primary outcomes will be midterm (6 months to 2 years after injury) overall HRQoL and pain. Secondary outcomes will include radiological or clinical findings. We will present network graphs, forest plots and relative rankings on plotted rankograms corresponding to the treatment rank probabilities. The ranking results will be represented by the area under the cumulative ranking curve. Analyses will be performed in Stata V.16.1 and R. The quality of the evidence will be evaluated according to the Grading of Recommendations, Assessment, Development and Evaluations framework. ETHICS AND DISSEMINATION: Ethical approval is not required. The research will be published in a peer-reviewed journal.
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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 | 0.078 | 0.109 |
| Meta-epidemiology (narrow) | 0.009 | 0.005 |
| Meta-epidemiology (broad) | 0.030 | 0.043 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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".