Just how much does it cost? A cost study of chronic pain following cardiac surgery
Bibliographic record
Abstract
OBJECTIVE: The study objective was to determine use of pain-related health care resources and associated direct and indirect costs over a two-year period in cardiac surgery patients who developed chronic post-surgical pain (CPSP). METHODS: This multicentric observational prospective study recruited patients prior to cardiac surgery; these patients completed research assistant-administered questionnaires on pain and psychological characteristics at 6, 12 and 24 months post-operatively. Patients reporting CPSP also completed a one-month pain care record (PCR) (self-report diary) at each follow-up. Data were analyzed using descriptive statistics, multivariable logistic regression models, and generalized linear models with log link and gamma family adjusting for sociodemographic and pain intensity. RESULTS: Out of 1,247 patients, 18%, 13%, and 9% reported experiencing CPSP at 6, 12, and 24 months, respectively. Between 16% and 28% of CPSP patients reported utilizing health care resources for their pain over the follow-up period. Among all CPSP patients, mean monthly pain-related costs were CAN$207 at 6 months and significantly decreased thereafter. More severe pain and greater levels of pain catastrophizing were the most consistent predictors of health care utilization and costs. DISCUSSION: Health care costs associated with early management of CPSP after cardiac surgery seem attributable to a minority of patients and decrease over time for most of them. Results are novel in that they document for the first time the economic burden of CPSP in this population of patients. Longer follow-up time that would capture severe cases of CPSP as well as examination of costs associated with other surgical populations are warranted. SUMMARY: Economic burden of chronic post-surgical pain may be substantial but few patients utilize resources. Health utilization and costs are associated with pain and psychological characteristics.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".