PP37 Examining the potential for uncontrolled organ donation after out-of-hospital cardiac arrest in Canada – a sub analysis of the canROC registry
Bibliographic record
Abstract
Background In 2020, there were 4,352 people waiting for organ transplantation in Canada. A rise in demand has led to national exploration of non-traditional pathways for organ donation to increase the potential pool of donors and subsequent transplant recipients. Donation after Cardiac Death (DCD) has become a promising option across Canada and in other jurisdictions worldwide. One unexplored aspect to uncontrolled DCD (uDCD) in Canada is the inclusion of patients who suffer an out-of-hospital cardiac arrest (OHCA) into the pool of potential donors, of which there are an estimated 40,000 each year in Canada. The primary objective of this study is to quantify the potential pool of donors that would be eligible for uDCD subsequent to OHCA. This will allow us to understand how many potential donors are being missed when treated, but not transported after an OHCA. Methods A retrospective observational cohort study will be undertaken, using pre-existing data from the Canadian Resuscitation Outcomes Consortium (CanROC) registry, a pan- Canadian registry that collects prospective OHCA data. Consecutive OHCA cases from January 1, 2016 - December 31, 2018 meeting inclusion criteria will be included. Results Descriptive analysis will be used to examine patient and event characteristics, and determine the proportion of patients who meet the indication for uDCD. Results will be reported as mean (standard deviation [SD]) or median (interquartile range [IQR]) for continuous variables and frequency (%) for categorical variables. Conclusions Preliminary literature review suggests uDCD subsequent to OHCA is a viable opportunity to increase the donor pool in Canada. Presently, there is a lack of understanding of this pool of potential donors, and no programs exist in Canada to recruit from this population. In order to determine if pursuing uDCD subsequent to OHCA to improve organ donation rates is worthwhile, we must first quantify its potential.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".