Assessment of the relationship between cerebral and splanchnic oxygen saturations measured by near-infrared spectroscopy and direct measurements of systemic haemodynamic variables and oxygen transport after the Norwood procedure
Bibliographic record
Abstract
OBJECTIVES: To evaluate the clinical utility of near-infrared spectroscopic (NIRS) monitoring of cerebral (ScO2) and splanchnic (SsO2) oxygen saturations for estimation of systemic oxygen transport after the Norwood procedure. METHODS: ScO2 and SsO2 were measured with NIRS cerebral and thoracolumbar probes (in humans). Respiratory mass spectrometry was used to measure systemic oxygen consumption (O2). Arterial (SaO2), superior vena caval (SvO2) and pulmonary venous oxygen saturations were measured at 2 to 4 h intervals to derive pulmonary (Qp) and systemic blood flow (Qs), systemic oxygen delivery (DO2) and oxygen extraction ratio (ERO2). Mixed linear regression was used to test correlations. A study of 7 pigs after cardiopulmonary bypass (study 1) was followed by a study of 11 children after the Norwood procedure (study 2). RESULTS: Study 1. ScO2 moderately correlated with SvO2, mean arterial pressure, Qs, DO2 and ERO2 (slope 0.30, 0.64. 2.30, 0.017 and -32.5, p < 0.0001) but not with SaO2, arterial oxygen pressure (PaO2), haemoglobin and O2. Study 2. ScO2 correlated well with SvO2, SaO2, PaO2 and mean arterial pressure (slope 0.43, 0.61, 0.99 and 0.52, p < 0.0001) but not with haemoglobin (slope 0.24, p > 0.05). ScO2 correlated weakly with O2 (slope -0.07, p = 0.05) and moderately with Qs, DO2 and ERO2 (slope 3.2, 0.03, -33.2, p < 0.0001). SsO2 showed similar but weaker correlations. CONCLUSIONS: ScO2 and SsO2 may reflect the influence of haemodynamic variables and oxygen transport after the Norwood procedure. However, the interpretation of NIRS data, in terms of both absolute values and trends, is difficult to rely on clinically.
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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 | 0.003 |
| 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 | 0.001 |
| 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".