Neuromonitoring with near-infrared spectroscopy (NIRS) in aneurysmal subarachnoid hemorrhage: A systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: Near-infrared spectroscopy (NIRS) is a non-invasive, real-time and continuous cerebral oximetry monitoring with potential applications in the management of aneurysmal subarachnoid hemorrhage (aSAH) and in the detection of delayed cerebral ischemia (DCI). The aim of this study was to evaluate the association between NIRS and outcome in aSAH and its diagnostic accuracy for DCI. METHODS: Systematic review and meta-analysis of studies involving adult aSAH patients monitored with NIRS during index hospitalization. Primary outcome was the functional outcome at 90 days or more. Secondary outcomes included any functional outcome, mortality and diagnostic accuracy for DCI. Random effects meta-analyses were performed, and for diagnostic accuracy, forest plots and random effects meta-analyses were used to determine pooled sensitivity, specificity, diagnostic odds ratios and to generate a receiver operating characteristic (ROC) curve. RESULTS: Of the 28,296 citations identified, 35 satisfied inclusion criteria. Three studies (202 patients) were included for meta-analysis of the primary outcome. Cerebral desaturation events or loss of autoregulation as detected with NIRS were associated with higher risks of unfavourable outcome at 90 days (RR 4.29 95% CI [2.10;8.79]). Significant associations were also observed with mortality (RR 4.24, 95% CI [2.43;7.41]). Diagnostic accuracy analysis demonstrated moderate sensitivity (0.85), specificity (0.65), and diagnostic odds ratio (10.42), with a receiver operating characteristic (ROC) curve area of 0.68. The certainty of evidence was moderate for the association between NIRS and patient outcomes, and low for its diagnostic accuracy in detecting DCI.The overall quality of evidence was limited by small sample sizes, high heterogeneity in study methods and patient populations, and potential publication bias. CONCLUSION: Cerebral desaturation events and impaired autoregulation detected by NIRS are consistently associated with poor outcomes and mortality in aSAH. However, NIRS alone provides only moderate diagnostic accuracy for DCI, with a considerable risk of false positives. The evidence is weakened by methodological limitations, heterogeneous thresholds, and the absence of a universally accepted reference standard for DCI diagnosis. Importantly, no interventional data are available to demonstrate an effect on patient outcomes. While incorporation into multimodal neuromonitoring strategies appears promising, robust prospective trials are needed before NIRS can be reliably adopted in routine clinical practice.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".