Comparison of Three Point-of-Care Analyzers for the Measurement of Lactate Concentration in Chelonians
Bibliographic record
Abstract
Abstract Blood lactate concentration has been identified as a prognostic indicator in chelonians. However, comparison among various studies about lactate concentration is hindered by the fact that various point-of-care analyzers are used. This study evaluated agreement, correlation and biases between three commonly used analyzers, the Lactate Plus (Nova), i-STAT (Abbott), and EPOC (Heska). Forty chelonians of 10 different species were included in the study. The animals were recruited from a rehabilitation center and from the clientele of a veterinary teaching hospital, and presented with a variety of health statuses and a wide range of lactate concentration. A single blood sample obtained from each individual was placed in a heparinized tube and analyzed concomitantly by two analyzers per sample (20 chelonians for each analyzer). Agreement between the lactate and blood analyzers was evaluated via a Bland–Altman plot and correlation via a Spearman correlation coefficient. Bias was determined using a Passing–Bablok regression analysis. There was a fair agreement between the three techniques, but agreement was decreased for lactate concentrations above 5 mmol/L. Both blood analyzers reported consistently greater lactate concentrations compared to values obtained with the Lactate Plus, with a positive proportional bias. Correlations between the Lactate Plus and the two other point-of-care analyzers were excellent, 97.0% and 92.8% with the i-STAT and the EPOC analyzers, respectively. This study highlights the need to conduct studies in various reptile species to evaluate the performance of point-of-care analyzers.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".