O-21: Using Virtual Technology to Preserve the Lifespan of Central Venous Access Devices
Bibliographic record
Abstract
Aim: To use a web based management platform to prevent occlusions and preserve the lifespan of a central venous access devices (CVAD) for Home Parenteral Nutrition (HPN). Background: Despite many techniques, adjuncts and pharmaceutical agents there are some CVADs that remain troublesome with frequent partial and full occlusions that require CVAD exchanges. The CVAD for a child or young person that requires HPN can be described as a “lifeline” and all options to maintain long term patency should be utilised. MicrelCare have a web based care management platform that monitors real time infusion pressures relaying information from the home to the hospital Methodology: Using one teenage male on HPN (who had experienced 3 CVAD exchanges in 2 years) as a candidate for MicrelCare, we virtually monitored his CVAD pressure’s and infusion alarms via a real time platform. This virtual platform alongside clinical correlation (patient consultations and physical assessment) allowed for the determination of pressure range monitoring and the early detection of line stiffness and pre cursors to occlusion. Results: We were able to determine that for this patient when the CVAD pressure levels reached 0.2 bar it was imperative that we physically assessed the CVAD and followed the in house protocol of Urokinase/Alteplase instilment followed by an Ethanol treatment if required (including hub inspection and POP technique) to prevent irreversible occlusion. Interestingly the pressure bar for this young man is lower than MicrelCare would expect and that of our patient cohort. Conclusion: MicrelCare can be a useful tool to virtually monitor and predict precursors to CVAD stiffness and occlusion when used with clinical correlation.This allows the development of a robust tailored care plan, which prolongs the life of a CVAD and in turn preserves venous access.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".