Effect of Intravenous Infusion Solutions on Bioelectrical Impedance Spectroscopy
Bibliographic record
Abstract
BACKGROUND: Bioelectrical impedance (BIA) is often used to measure body fluid spaces and thereby body composition. However, in acute animal studies, we found that impedance was driven by the saline content of intravenous (IV) fluids and not by the volume. The aim of the study was to investigate the effect of 3 different fluids acutely administered on the change in impedance, specifically resistance (R). MATERIALS AND METHODS: Nine healthy adults participated in 3 treatment (0.9% saline, 5% dextrose, and a mixture of 0.3% saline + 3.3% dextrose) experiments on nonconsecutive days. They all received 1 L of one of the treatments intravenously over a 1-hour period. Repeated BIA measurements were performed prior to IV infusion and then every 5 minutes for the 1-hour infusion period, plus 3 more measurements up to 15 minutes after the completion of the infusion. RESULTS: The change in R in the 0.9% saline infusion experiment was significantly lower than that of the glucose and mixture treatment ( P < .001). CONCLUSION: Bioelectrical impedance spectroscopy and BIA measure salt rather than the volume changes over the infusion period. Hence, in patients receiving IV fluids, BIA of any kind (single frequency or multifrequency) cannot be used to measure body fluid spaces or body composition.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".