Effects of pre‐analytical sample care and analysis methodology on measures of metabolic acidosis in hemodialysis patients
Bibliographic record
Abstract
Abstract Introduction We evaluated the effects of pre‐analytical care on total carbon dioxide (tCO2) in hemodialysis patients, as calculated by blood gas analysis (ctCO2) or measured by an enzymatic assay (mtCO2). Methods Blood samples were collected via vascular access before dialysis sessions. For blood gas analysis, eight aliquots were collected, refrigerated or non‐refrigerated, and analyzed at 0, 4, 8, and 24 h after collection. A blood sample was then collected for the enzymatic method and distributed into 14 aliquots. Half of the aliquots were refrigerated. The samples analyzed at time point 0 were centrifuged immediately. The remaining aliquots of both the refrigerated and non‐refrigerated clusters were centrifuged before storage. Samples were analyzed at 4, 8, and 24 h post‐collection. Findings By blood gas analysis, no significant change was found in bicarbonate values over time, either in the non‐refrigerated or refrigerated samples. ctCO2 values during the experiment showed a minor but statistically significant increase of questionable clinical relevance in both non‐refrigerated and refrigerated aliquots. In the enzymatic assay, the reduction in mtCO2 levels during the experiment was negligible. The median absolute reductions at the end of the experiment were 1.77, 1.21, 1.04, and 1.12 mmol/L for the non‐centrifuged/non‐refrigerated, centrifuged/non‐refrigerated, non‐centrifuged/refrigerated, and centrifuged/refrigerated aliquots, respectively. Discussion Our results suggest that measured or calculated tCO2 levels of capped and cooled samples are adequate for analyzing the acid–base status of hemodialysis patients, even when such determination is not performed immediately after collection.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".