Pseudohyperkalemia in horses with rhabdomyolysis reported by an enzymatic chemistry analyzer
Bibliographic record
Abstract
OBJECTIVE: To investigate pseudohyperkalemia occurring in horses experiencing rhabdomyolysis when serum chemistry profiles are run on an VetScan VS2 analyzer (Abaxis). ANIMALS: 18 horses with rhabdomyolysis (creatine kinase [CK] > 1,000 U/L). METHODS: In 3 horses with serum CK activities > 5,800 U/L and persistent serum potassium concentrations of > 8.5 mmol/L (VetScan VS2), potassium concentrations were reevaluated with either i-STAT Alinity Base Station (Abbott), Catalyst (Idexx), or Cobas c501 (Roche) ion-specific analyzers. Paired serum samples from 15 additional horses (median serum CK activity, 7,601 U/L; range, 1,134 to 192,447 U/L) were analyzed on both VetScan VS2 and Cobas c501 machines. Serum potassium concentrations were compared between the VetScan VS2 and ion-specific analyzers by Bland-Altman and Wilcoxon ranked tests and correlated to log10 CK activity via Pearson correlation. RESULTS: Serum potassium concentrations were significantly higher on the VetScan VS2 (6.7 ± 1.6 mmol/L) versus the ion-specific analyzers (4.0 ± 1.1 mmol/L; P < .0001), with high bias shown in Bland-Altman analysis (43.1 ± 27.9). Potassium concentrations positively correlated with log10 CK activity with the VetScan VS2 (R2 = 0.51; P = .003) but not the Cobas (R2 = 0.09; P = .3) analyzer. CLINICAL RELEVANCE: An alternate analyzer to the VetScan VS2 should be used to evaluate serum potassium concentrations in horses with rhabdomyolysis because the VetScan VS2 methodology uses lactate dehydrogenase, which increases in serum with rhabdomyolysis and falsely elevates potassium concentrations.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".