Neuromonitoring with near-infrared spectroscopy (NIRS) in aneurysmal subarachnoid haemorrhage: a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Aneurysmal subarachnoid haemorrhage (aSAH) is a devastating disease associated with high mortality and morbidity. The main threat to patients is delayed cerebral ischaemia (DCI). Near-infrared spectroscopy (NIRS) is a recent technology allowing continuous, non-invasive cerebral oximetry that could permit timely detection of impending DCI and appropriate intervention to improve outcomes. However, the ability of regional oxygen saturation to detect DCI, its association to the outcome, or benefits of any interventions based on NIRS data, are lacking. Our aims are to evaluate NIRS technology both as a therapeutic tool to improve outcomes in aSAH patients and as a diagnostic tool for DCI. METHODS AND ANALYSIS: MEDLINE, EMBASE, Web of Science, the Cochrane Central Register of Controlled Trials and the Cochrane Database of Systematic Reviews will be searched from their inception and without language restriction. Our search strategy will cover the themes of subarachnoid haemorrhage and cerebral oximetry, without limitations regarding studied outcomes. We will identify all observational and interventional human studies of adult patients hospitalised after aSAH that were monitored using NIRS. Functional outcome measures, including the modified Rankin Scale, the Glasgow Outcome Scale and the Barthel Index, will constitute the primary outcome. The Cochrane Risk of Bias tool will be used for randomised controlled trials, the ROBINS-I tool to assess non-randomised studies of interventions and the Newcastle-Ottawa Scale for cohort or case-control studies. The Quality Assessment of Diagnostic Accuracy Studies-2 will be applied to studies evaluating NIRS diagnostic accuracy for DCI. We will evaluate the quality of the evidence of the effect based on the Grading of Recommendations Assessment, Development and Evaluation methodology. ETHICS AND DISSEMINATION: Dissemination will proceed through submission for journal publication, trial registry completion and abstract presentation. Ethics approval is not required. PROSPERO REGISTRATION NUMBER: CRD42020077522.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".