Persistent Postoperative Pain after Cardiac Surgery: Incidence, Characterization, Associated Factors and its impact in Quality of Life
Bibliographic record
Abstract
BACKGROUND: Cardiac surgery (CS) ranks among the most frequently performed interventions worldwide and persistent postoperative pain (PPP) has been recognized as a relevant clinical outcome in this context. We aimed to evaluate its incidence, characteristics, associated factors and patient's quality of life (QoL). METHODS: Observational prospective study conducted in patients undergoing CS in a tertiary university hospital. PPP was defined as persistent pain after surgery with higher than 3 months' duration, after excluding other causes of pain. We used a set of questionnaires for data collection: Pain Catastrophizing Scale, Duke Health Profile, Brief Pain Inventory Short Form, McGill Pain Questionnaire Short Form, Douleur Neuropathique en 4 Questions and standardized questions regarding pain periodicity. RESULTS: A total of 288 patients have completed the study and 43% presented PPP assessed at 3 months (PPP3M); out of which 84% were not under any treatment. PPP patients reported significantly lower QoL, and a neuropathic pain (NP) component was present in 50% of them. Younger age, female gender, higher body mass index, catastrophizing, coronary artery bypass graft, osteoarthritis, history of previous surgery (excluding sternotomy) and moderate to severe acute postoperative pain were independent predictors of PPP3M. CONCLUSION: This is the first study comprehensively describing PPP after CS and identifying NP in half of them. Our results support the important role that PPP plays after CS in considering its interference in patients' daily life and their lower QoL, which deserves the attention of health care professionals in order to improve prevention, assessment and treatment of these patients. WHAT DOES THIS STUDY ADD?: This study comprehensively describes persistent postoperative pain (PPP) after cardiac surgery (CS) and identifies neuropathic pain (NP) in half of them. Our results support the important role that PPP plays after CS in considering its interference in patients' daily life and their lower quality of life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".