Spectroscopic Whole‐Blood Indicators of End‐Stage Renal Disease and the Hemodialysis Treatment
Bibliographic record
Abstract
The diffuse reflection spectrum in the 500-1670 nm region for whole blood taken from healthy subjects and end-stage renal disease (ESRD) patients was measured to test the feasibility of optically monitoring ESRD and its treatment by hemodialysis. Spectral regions where optical absorption significantly differed between healthy subjects and ESRD patients were used to form a multiple linear discriminant classification model. With this model a total of 41 whole-blood samples were classified into healthy, pretreatment and posttreatment ESRD classes. 96.7% of original and cross-validated cases and 100% of independent validation cases were correctly classified, indicating ESRD and its treatment exhibit characteristic spectral features in whole blood. Upon comparison of the discriminant model variables with a few key clinical blood parameters, model variables were found to significantly correlate with hematocrit and plasma levels of urea and potassium (P<0.05). The results of this study suggest that the optical signature of whole blood conveys basic clinical status information, and provides a path for investigating improved indices of hemodialysis toxicity, adequacy and patient outcome.
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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 | 0.000 |
| 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".