Radioisotope blood volume measurement in hemodialysis patients
Bibliographic record
Abstract
Accurate assessment of blood volume (BV) may be helpful for prescribing hemodialysis (HD) and for reducing complications related to hypovolemia and volume overload. Monitoring changes in relative BV (RBV) using hematocrit, e.g., Crit-Line Monitor (CLM-III), an indirect method, cannot be used to determine absolute BV. We report the first study of BV measurement for assessing volume status in HD patients using the indicator dilutional method. Ten adult HD patients were enrolled in this prospective observational study. BV measurement was performed before and after HD using BV analysis (BVA)-100 (Daxor Corporation, New York, NY, USA). BVA-100 calculates BV using radiolabeled albumin (Iodine-131) followed by serial measures of the radioisotope. Fluid loss from the extravascular space was calculated by subtracting the change in BV from total weight loss. Intradialytic changes in RBV were measured by CLM-III. Eight out of 10 cases had significant hypervolemia, two cases were normovolemic. The range of BV variation from predicted normal was 156 to 1990 mL. Significant inter-individual differences in extravascular space fluid loss ranged from 54% to 99% of total weight loss. Spearman correlation showed a good correlation in the measurement of RBV by BVA-100 and CLM-III in 8 out of 10 patients (r(2) = 0.64). BV measurement using BVA-100 is useful to determine absolute BV as well as changes in BV and correlates reasonably well with CLM-III measurements. Individual refilling ability can be determined as well. This may prove useful in prescribing and monitoring ultrafiltration rates, establishment of optimal BV in HD patients and reducing morbidity and mortality associated with chronic HD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".