Wellness and burnout in cardiac surgery: not black and white
Bibliographic record
Abstract
PURPOSE OF REVIEW: Despite a growing emphasis on burnout in medicine, there remains a paucity of data in cardiac surgery. Herein, we summarize recent data on cardiac surgeon well being and identify factors for consideration in future burnout inquiries and management. RECENT FINDINGS: Overall, 70-90% of cardiothoracic surgeons report job satisfaction in the United States. However, 35-60% still endorse burnout symptoms, and the specialty reports some of the highest rates of depression (35-40%) and suicidal ideation (7%). Such negative experiences are greater among early-stage and female surgeons and may be addressed through targeted, program-specific wellness policies. Canada's single-payer healthcare system might exacerbate surgeon burnout due to lower financial compensation and job autonomy. SUMMARY: Cardiothoracic surgeons appear simultaneously burnt out and professionally fulfilled. They report a high incidence of depression and clock in the most hours, yet the majority would choose this specialty again. These findings reveal a more nuanced state of well being than previously appreciated and speak to ambiguities in how burnout is conceived and measured. A broader examination across surgical and social contexts highlights the hierarchical nature of burnout factors and potential ways forward. Collectively, these insights can inform assessments of burnout in Canadian cardiac surgery that remain absent to date.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".