Comparison between clinical judgment and integrated lung and inferior vena cava ultrasonography for dry weight estimation in hemodialysis patients
Bibliographic record
Abstract
INTRODUCTION: Correct dry weight estimation is very crucial for hemodialysis (HD) patients to maintain euvolemia. Most dialysis centers practice clinical judgment for dry weight estimation, which is subjective and can differ significantly from the actual weight. We designed this study to redefine the clinically estimated dry weight of patients on HD using integrated lung-inferior vena cava (IVC) ultrasonography (USG) and compare the symptoms arising due to volume overload and/or volume depletion before and after modifying the dry weight. METHODS: Breathlessness and orthostatic giddiness were scored and documented for 2 weeks while patients were on HD based on clinically estimated dry weight and again for 2 weeks after redefining dry weight using lung-IVC USG. New dry weight was defined as the weight of the patient at which the number of B-lines was <4 on eight site lung USG and IVC collapsibility index was between 50% and 75%. FINDINGS: After redefining the dry weight, 34 patients (group I) had change in dry weight and 40 (group II) had no change. There was 0.21 ± 1.80 reduction in the score for orthostatic giddiness in group I and 0.03 ± 0.16 in group II (P = 0.147). The score for breathlessness during the 24 hours following dialysis reduced by 0.21 ± 0.41 in group I, but did not change in group II (P = 0.003). Score for breathlessness in the predialysis day reduced by 0.56 ± 0.56 in group I and by 0.05 ± 0.22 in group II (P < 0.001). DISCUSSION: Symptoms related to volume overload and depletion were less when HD prescription was based on lung-IVC USG defined dry weight.
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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 | 0.000 |
| 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".