A qualitative exploratory case series of patient and family experiences with ECPR for out-of-hospital cardiac arrest
Bibliographic record
Abstract
OBJECTIVE: There is currently no existing data examining the opinions of patients and families after treatment with extracorporeal cardiopulmonary resuscitation (ECPR) for out-of-hospital cardiac arrest (OHCA). We sought to interview family members and patients to learn from their experiences and satisfaction with treatment. METHODS: We contacted family members and survivors for all cases treated with ECPR for refractory OHCA at St. Paul's Hospital between January 2014 and July 2018. We performed semi-structured interviews with participants, specifically within the topics of: information sharing (including impressions of an ECPR informational pamphlet), prognostication, organ donation, and perceived value of ECPR. Due to low participant enrolment, we described all interviews in a narrative approach. RESULTS: Within the study period, there were 23 OHCAs treated with ECPR; two survivors and three family members agreed to participate. Participants were satisfied with the treatment provided, including information sharing and prognostication. There were mixed opinions about the best method of information-sharing (verbal vs written), as well as the timing of organ donation conversations. All participants believed ECPR for OHCA to be of high value. CONCLUSION: Patient's conveyed satisfaction with ECPR treatment, with mixed views on the best information sharing strategy. Further study is needed to define the optimal methods and timing for discussions of organ donation, especially for treatments of with a relatively low likelihood success.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".