Extravascular lung water index: A new method to determine dry weight in chronic hemodialysis patients
Bibliographic record
Abstract
To assess the dry weight of chronic hemodialysis (HD) patients, the extravascular lung water index (ELWI) as a volume parameter was investigated to identify fluid overload. Forty-two patients (30 males, 12 females) with a mean age of 55.7+/-13.0 years who were clinically not overhydrated were connected to the PiCCO system before starting HD treatment. We determined ELWI (normal range 3-7 mL/kg) and the following parameters: global end-diastolic volume index (GEDI, normal range 680-800 mL/m(2)) and intrathoracic blood volume index (ITBI, normal range 850-1000 mL/m(2)) before and after HD to assess the volume status. Brain natriuretic peptide (BNP), aldosterone, and renin as vasoactive hormones were measured at the beginning and at the end of HD treatment as well. In 28 of the 42 patients (67%), elevated values of ELWI were found, indicating interstitial volume overload. There were significant correlations between ELWI and cardiac function index (p=0.003; Pearson's coefficient -0.451), global ejection fraction (p=0.012; Pearson's coefficient -0.389), ITBI (p=0.004; Pearson's coefficient 0.437), and GEDI (p=0.004; Pearson's coefficient 0.437). No significant relations among ELWI and mean arterial pressure (MAP), BNP, aldosterone, and renin were found. In conclusion, the use of ELWI is safe in chronic HD patients and identifies fluid-overloaded patients, who show no obvious signs of hypervolemia. The determination of ELWI is an excellent method to quantify the exact volume in chronic HD patients.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".