Near infrared spectroscopy for frontal lobe oxygenation during non‐vascular abdominal surgery
Bibliographic record
Abstract
PURPOSE: Cerebral deoxygenation, as determined by near infrared spectroscopy (NIRS), seems to predict postoperative complications following cardiac surgery. We identify the type of non-vascular abdominal surgery associated with cerebral deoxygenation and/or hyperoxygenation, how such deviations affect patient outcome, and whether maintained cerebral oxygenation improves outcome. METHODS: A systematic literature search was performed on PubMed, EMBASE, Web of Science and Clinicaltrials.gov. RESULTS: A total of 901 patients from 24 publications are described. A decrease in NIRS (>15% relative to baseline) manifested with reverse Trendelenburg's positioning and in 24% (median) of especially elderly patients undergoing open surgery and demonstrated a correlation to hospital stay (LOS). However, if cerebral deoxygenation was reversed promptly, improved postoperative cognitive function (28 versus 26; mini-mental state examination) and reduced LOS (14 versus 23 days) were seen. Also, during liver transplantation (LTx), impaired cerebral autoregulation (25%), cerebral deoxygenation in the anhepatic phase (36%) and cerebral hyperoxygenation with reperfusion of the grafted liver (14%) were identified by NIRS and could lead to adverse neurological outcome, that is seizures, transient hemiparesis and stroke. CONCLUSION: NIRS seems important for predicting neurological complications associated with LTx. Also, surgery in reverse Trendelenburg's position and in other types of abdominal surgery about one-fourth of the patients are subjected to episodes of cerebral deoxygenation that seems to predict a poor outcome. Although there are currently only few studies available for patients going through abdominal surgery, the available evidence points to that it is an advantage to maintain the NIRS-determined cerebral oxygenation.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".