Intradialytic Blood Volume Monitoring in Ambulatory Hemodialysis Patients
Bibliographic record
Abstract
Complications related to inadequate volume management are common during hemodialysis. This trial tested the hypothesis that availability of an intradialytic blood volume monitoring (IBVM) device improves fluid removal, reducing morbidity. A six-center, randomized trial with 6 mo of intervention comparing IBVM using Crit-Line versus conventional clinical monitoring was conducted. The average rate of non-access-related hospitalizations was compared across treatment groups using Poisson regression. Mortality analysis used the Kaplan Meier method. A total of 227 patients were randomized to Crit-Line, and 216 were randomized to conventional monitoring. Both groups had similar baseline characteristics. During the study, no differences in weight, BP, or number of dialysis-related complications were observed. There were 120 and 81 non-access-related hospitalizations in the Crit-Line and conventional monitoring groups. The adjusted risk ratio for non-access-related and access-related hospitalization was 1.61 (95% confidence interval 1.15 to 2.25; P = 0.01) and 1.52 (95% confidence interval 1.02 to 2.28; P = 0.04) for the Crit-Line monitoring group. Mortality was 8.7% in the Crit-Line monitoring group and 3.3% in the conventional group (P = 0.021). Standardized mortality ratios comparing the Crit-Line and conventional monitoring groups to the prevalent hemodialysis population were 0.77 (NS) and 0.26 (P < 0.001). Hospitalization rates were 1.51 and 1.03 events/yr in the Crit-Line and standard monitoring groups, compared with 2.01 for the prevalent hemodialysis population. IBVM was associated with higher nonvascular and vascular access-related hospitalizations and mortality compared with conventional monitoring. The atypically low hospitalization and mortality rates for the conventional monitoring group suggest that these findings should be generalized to the US hemodialysis population with caution.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".