Moving from physical survival to psychologic recovery: a qualitative study of survivor perspectives on long-term outcome after sudden cardiac arrest
Bibliographic record
Abstract
BACKGROUND: Over 400,000 adults suffer out-of-hospital cardiac arrests (OHCA) each year in North America. Despite a very high mortality rate, even 10% survival means that a minimum of 3500 people return to their lives and their families. However, their experience of living and their health-related quality of life after such a life-changing event are quite variable, much more complex than just having lived or died, and should not be reduced to crude measures of neurological functioning. METHODS: We conducted 32 in-depth qualitative interviews with survivor/family member dyads at various stages of survival. The interviews focused on the recovery journey, long-term issues most important to them and how measuring such concepts could help. Interviews were audio-taped, transcribed verbatim and analyzed using constant comparative thematic analysis techniques. RESULTS: During in-depth interviews with more than 30 survivors and caregivers we have heard that despite being a relatively high functioning group, their lives have been deeply affected by their cardiac arrest experience. They speak about the importance of both psychologic and physical recovery, the impact of return to work or changes in work identity and the necessity of support from family members in the recovery process. Spouses/family members also mentioned differences in perspective on their loved one's recovery and how they manage the fear of recurrence. CONCLUSIONS: This work purposively brings a unique lens to the concept of cardiac arrest outcomes by placing priority on what is important to survivors and their families and what we may be missing in standard outcomes measures. There is a clear need for a more patient-centred outcome set for this population and our work indicates that psychologic assessment, return to work status and family input are key domains to be considered.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".