Cerebrospinal fluid biomarkers of neuroinflammation and postoperative neurocognitive disorders in patients undergoing orthopaedic surgery: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Postoperative neurocognitive disorders (PNDs) are characterised by gradual cognitive decline or change occurring after anaesthesia and surgery, and they are common in patients undergoing orthopaedic surgery. The onset of PNDs has been associated with dementia or other types of neurocognitive disorders in later life. Moreover, cerebrospinal fluid (CSF) biomarkers of neuroinflammation, including amyloid beta-40 peptide, amyloid beta-42 peptide, total tau protein, phosphorylated tau protein and neurofilament light chain, have been reported to be crucial in several high-quality clinical studies on PNDs. However, the role of these biomarkers in the onset of PNDs remains controversial. Therefore, this study aims to determine the association between CSF biomarkers of neuroinflammation and the onset of PNDs in patients undergoing orthopaedic surgery, which will provide novel insights for investigating PNDs and other types of dementia. METHODS AND ANALYSIS: This systematic review and meta-analysis will be conducted in accordance with the Preferred Reporting Items for Systematic Reviewd and Meta-Analyses 2020 statement. Moreover, we will search MEDLINE (via OVID), EMBASE and the Cochrane Library without any language and date restrictions. Observational studies will be included. Two reviewers will independently perform the entire procedure, and disagreements will be settled by discussion between them and consultation with a third reviewer. Standardised electronic forms will be generated to extract data. The risk of bias in the individual studies will be evaluated using the Newcastle-Ottawa scale. All statistical analyses will be performed using the RevMan software or the Stata software. ETHICS AND DISSEMINATION: This study will include peer-reviewed published articles; thus, no ethical issues will be involved. Further, the final manuscript will be published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42022380180.
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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 | 0.048 | 0.064 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.024 | 0.028 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.046 | 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".