The Effect of Inadequate Presample Blood Volume Withdrawal from Intravenous Catheter and Extension Sets on Measured Circulating L-Blood Lactate Concentration in Horses Receiving Lactated Ringer's Solution
Bibliographic record
Abstract
BACKGROUND: Circulating l-lactate concentration is commonly measured in hospitalized horses by sampling from indwelling intravenous (IV) catheters. However, there are no published evidence-based recommendations to prevent contamination by lactated Ringer's solution (LRS). HYPOTHESIS: Withdrawing 10 mL of blood from the LRS-containing extension set connected to the IV catheter before obtaining the sample for analysis should be adequate to obtain accurate measurement of blood lactate concentration (BLC). ANIMALS: Thirty-three adult hospitalized horses receiving constant rate infusion of LRS. METHODS: Immediately after disconnecting the LRS, 5 sequential 5 mL blood samples were obtained by aspiration from an extension set connected to an indwelling IV catheter, followed by 3 samples collected by direct venipuncture of the contralateral jugular vein. Samples were analyzed with 1 portable blood lactate analyzer. A linear mixed model was used to examine differences in lactate concentrations among samples collected from the catheter and by direct venipuncture. RESULTS: After considering differences in age, breed, sex, and reason for hospitalization, BLCs were higher (P < .001) in the first and second 5 mL samples collected through the extension set/catheter than in all other extension set/catheter samples or the direct venipuncture samples. The largest difference observed between the third and subsequent catheter or venipuncture samples was 0.34 mmol/L with an upper 95% CI of 1.12 mmol/L. CONCLUSIONS AND CLINICAL IMPORTANCE: Withdrawing 15 mL of blood from a LRS-containing extension set connected to an IV catheter (5.9 mL total volume capacity) before obtaining the sample for blood lactate analysis is suggested to optimize accuracy of BLC measurements.
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| 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".