NIRS Measurement of Peripheral Fractional Oxygen Extraction (FOE) after Cardiopulmonary Bypass
Bibliographic record
Abstract
Objectives: To compare peripheral fractional oxygen extraction (FOE), as measured by near infrared spectroscopy (NIRS), with conventional indicators of tissue perfusion in haemodynamically stable and unstable children after cardiopulmonary bypass. Design: Observational study. Setting: Paediatric Intensive Care Unit of a large teaching hospital. Patients: 17 children immediately after cardiopulmonary bypass. Male : female = 9 : 8, median age 7 months (range, newborn to 16 years). Methods: On admission, children were classified as “stable” or “unstable” based on the haemodynamic support they needed. Peripheral venous oxyhaemoglobin saturation (SvO2) was measured non‐invasively using NIRS with venous occlusion. FOE was calculated from SvO2 and arterial saturation measured by pulse oximetry. Repeated measurements of peripheral SvO2 were made for up to 8 hours. In 5 children who had pulmonary artery catheters, simultaneous mixed SvO2 measurements were recorded. Results: Median FOE was 7.9% higher in the unstable group than in the stable group (p = 0.013). Peripheral SvO2 and mixed SvO2 were correlated (R2 = 0.65, p < 0.0001). Conclusions: Peripheral FOE is higher in unstable children. Changes in peripheral SvO2 are related to changes in mixed SvO2. These measurements may provide useful information about haemodynamic status in critically ill children. Further evaluation of the technique is warranted.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".