Measurement of leg fluid volume using bioelectrical impedance (1156.14)
Bibliographic record
Abstract
Background: Fluid volume (FV) of body segments can be measured non‐invasively and continuously using bioelectrical impedance (BI). Electrical impedance of the cell membrane is high at low frequencies suggesting that BI using low frequencies will detect mainly extracellular fluid (ECF). The objective of this study was to determine relationships between leg FV measured using BI and changes in leg volume (LV) calculated geometrically. Methods: We measured FV between the knee and ankle using BI at low frequencies (50 &amp; 100 KHz, Biopac) and leg circumferences at the knee, ankle and widest part of the calf in both legs of 7 healthy subjects (5 men, age 50.7±7.1 yrs, BMI 23.6±2.8 kg/m2). Measurements were made every 30 min while sitting for 4 hrs. LV was calculated geometrically by assuming a shape of a truncated cone. We also measured FV between the left knee and ankle every hour using a Xitron device that uses multiple frequencies up to 1 MHz to distinguish between ECF and intracellular fluid volumes. Paired t‐tests were used to compare changes (Δ) in Biopac FV (FV‐B) with ΔLV and Xitron measurements of ECF (ECF‐X) and total FV (TFV‐X). Findings: Relative to ΔLV, ΔFV‐B was lower in the first 2 hours of sitting (ΔLV 188.7±31.5, ΔFV‐B 79.8.9±121.3 ml, p<0.0001) but similar between 2 and 4 hours (ΔLV 68.8±45.7 ml, ΔFV‐B 56.2±22.2 ml, p=0.50). In the left leg, all estimates of ΔFV‐B were consistent with ΔECF‐X and lower than ΔTFV‐X and ΔLV (at 4 hrs, ΔFV‐B 0.06±0.01 L, ΔECF‐X 0.06±0.01 L, ΔTFV‐X 0.08±0.07 L, ΔLV 0.14±0.04 L). Conclusions: FV measured using Biopac at low frequencies seems to quantify changes in ECF volume. Expansion of ECF volume accounts for only about half the volume expansion below the knees during the first 2 hours of sitting but accounts for most of it between 2 and 4 hours.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".