Correlation of near-infrared spectroscopy with perfusion parameters at the hepatic and systemic levels in an endotoxemic shock model.
Bibliographic record
Abstract
BACKGROUND: To determine the correlation of near-infrared spectrophotometry (NIRS) readings from the liver surface with invasive measurements of blood flow and tissue perfusion parameters in an animal model of endotoxemic shock. MATERIAL/METHODS: Laparotomy was performed in 12 Yorkshire piglets, and ultrasound blood flow probes were placed on the hepatic artery and portal vein. Hepatic vein, portal vein, and femoral artery catheters were inserted for intermittent blood sampling, and a pulmonary artery catheter was inserted via the jugular vein for cardiac output measurements. Near-infrared spectrophotometry optodes were placed across the right hepatic lobe. Endotoxemic shock was induced by continuous infusion of Escherichia coli lipopolysaccharide 055: B5. Pearson correlations were calculated between the perfusion parameters and the near-infrared spectrophotometry (NIRS) readings. RESULTS: After endotoxemic shock induction, liver blood flow decreased from 144 +/- 36 to 62 +/- 24 ml*min(-1)*100 g(-1) and oxygen delivery to the liver decreased from 20 +/- 6 to 7 +/- 4 ml*min(-1)*100 g(-1). Near-infrared spectrophotometry readings of oxyhemoglobin concentration decreased by 11.7+/-15.1 micromol*L(-1), and readings of deoxyhemoglobin concentration increased by 12.3 +/- micromol*L(-1). There were significant correlations (p < 0.05 for r2 > 0.11) between the oxyhemoglobin readings and liver oxygen delivery (r2 = 0.58), liver blood flow (r2 = 0.73) and cardiac output (r2 = 0.80). Deoxyhemoglobin readings highly correlated (p < 0.05 for r2 > 0.11) with mixed venous lactate (r2 = 0.87) and with hepatic vein lactate (r2 = 0.82). CONCLUSIONS: Noninvasive near-infrared spectrophotometry measurements of hepatic oxyhemoglobin and deoxyhemoglobin correlate with liver hemodynamics as well as with global and specific organ perfusion parameters and may serve, in the future, as a useful tool to monitor tissue perfusion in septic patients.
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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 | 0.000 | 0.001 |
| 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".