Accuracy of Online Conductivity Monitor Compared with Daugirdas (dPVV/Kt/V) Model. Use in the Clinical Field
Bibliographic record
Abstract
The influence of dialysis prescription on outcome is well established. Hemodialysis dose has been shown to have a distinct impact upon the morbidity and mortality rate in patients on regular treatment therapy. Hence, adequacy of dialysis should be guaranteed. New devices based in online conductivity measures have been developed to achieve an adequate dialysis dose. The aim of this study was to compare online conductivity monitor (OCM) with dialysis dose standard methods (Daugirdas Kt/V). 24 anuric patients were included in a cross‐sectional study: 20.8% were diabetics, mean age 64.7 ± 18.2 years; 16% females. Access blood were AVFi and the effective dialyzed blood flow was set at 350 mL/min, with recirculation <5%. BMI was 25.4 ± 3.8 kg/m2 and body weight was 69.7 ± 12 kg. All patients were dialyzed thrice weekly (245 ± 21 min) with dialysis machine 4008H (Fresenius Medical Care) equipped with OCM monitor and the hollow fiber high‐flux polysulfone membrane (HF‐80 1.8 m2) and helixone (Fx‐60, 1.6 m2). Dialysate flow was maintained at 500 mL/min, with standard dialysate liquid. Drug therapy was not varied. Each patient was subjected to OCM on midweek day, during 3 consecutive weeks on the same day that blood Kt/V samples were taken as well. Each patient got 3 OCM measurements and Kt/V samples. Data were processed and statistically analyzed with SPSS 11.0 software package. Kt/V OCM relation to other baseline characteristics was assessed by using contingency tables, t‐tests, analysis of variance, and linear regression, as appropriate. All the tests were performed for a 0.05 significance level. Descriptives (n = 24) Mean SD Age (year) 64.75 18.243 Dry weight 69.7125 12.01178 Interdialysis weight gain 2266.67 1016.673 BMI 25.4155 3.83630 HD time 245.21 21.340 OCM 1.29921 0.201072 Daugirdas Kt/V 1.3287 0.21043 Watson volume (L) 36.833 6.3095 Linear regression analysis: Kt/V OCM relationship Variable Regression coefficient (β) r2 p Age (year) −0.631 0.398 <0.001 Daugirdas Kt/V −0.981 0.962 <0.001 BMI −0.327 0.107 NS Watson volume (L) −0.833 0.694 <0.001 The OCM option correlates well with Daugirdas Kt/V obtained from blood samples, in 96.2%, and provides a safe and accurate tool for hemodialysis, adding efficiency to dialysis adequacy monitoring in clinical practice. Also, OCM allows for an individualized dialysis dose. Furthers studies are required to evaluate its influence on patients' evolution.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".