Use of NIMH for determination of dry weight and prevention of dialysis associated morbidity in children.
Bibliographic record
Abstract
The majority of hemodialysis (HD) treatments incorporate a prescription for fluid removal targeted to a patients “dry” weight. Hypotension, cramps or headache often complicates fluid removal in children. The purpose of this study was to evaluate whether non-invasive blood volume monitoring by hematocrit could be used for the determination of dry weight and prevention of intra-dialytic complaints in children on chronic HD. Patients and methods: 128 dialysis sessions in 16 patients, aged 3–17 years, were evaluated. Non-invasive monitoring of hematocrit (NIMH) (Crit-lineTM, HemaMetrics) was performed during the whole HD session and expressed as % Δ of blood volume (%BVΔ). Results: Changes in blood volume significantly correlated with the changes of patient's weight during hemodialysis treatments (p = 0.001). Thirty HD sessions were complicated by symptomatic hypotension in 12 patients. Conclusion: Changes in blood volume measured by Crit-line correlate with the changes of patient's weight during hemodialysis treatments. Complicated HD sessions were associated with lower halfway %BVΔ. This indicates that NIMH might be useful for the determination of dry weight and for prevention of intra-dialytic morbidity in children by remodeling of the ultrafiltration profile.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".