Comparison of four different hematocrit assays and the effect of albumin on their measurements
Bibliographic record
Abstract
Clinical decisions are influenced by hematocrit values. Centrifugation (reference standard), conductivity, optical and impedance methods are often used interchangeably to measure hematocrit. The effects of albumin, which are known to affect conductivity methods, have not been evaluated for limits of agreement (LOA) between hematocrit assays in small animals. Canine venous blood was collected from 74 clinical cases and measured by centrifugation ( n = 72), conductivity ( n = 73), impedance ( n = 24) and optical ( n = 50) methods. Bland-Altman analysis determined bias (± SD) and 95% LOA between methods. There was a statistically significant difference between centrifugation hematocrit values and values obtained via conductivity ( p < 0.0001), optical ( p < 0.0001), and impedance ( p = 0.0082) methods. The conductivity method underestimated hematocrit by 2.1 ± 2.9% (95% LOA −3.54 to 7.88), the optical method by 3.1 ± 3.6% (95% LOA −4.0 to 10.2), and the impedance method by 2.3 ± 3.7% (95% LOA −5 to 9.6) when compared to centrifuged hematocrit values. The hematocrit difference between conductivity and centrifugation methods was statistically different for low (4%, 0–5%), within reference limits (3%, −5 to 8%), and high (2%, −2 to 5%) albumin values, respectively ( p = 0.02), with post-hoc analysis demonstrating that the difference occurred between the low and high albumin groups. This study confirms that albumin values outside reference limits can affect the conductivity method and that hematocrit values obtained via conductivity, optical and impedance methods underestimate values obtained via centrifugation. Therefore, the hematocrit methods cannot be used interchangeably. The wide limits of agreement also demonstrates that care must be taken when making clinical decisions with different hematocrit methodologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".