Economic burden of surgical management of surgical site infections following hip and knee replacements in Calgary, Alberta, Canada
Bibliographic record
Abstract
OBJECTIVE: To evaluate the cost of 1-stage and 2-stage revisions, debridement, antibiotic and implant retention (DAIR) and DAIR with liner exchange for complex surgical site infections (SSIs) following hip and knee replacements. DESIGN: Retrospective population-based economic analysis of patients undergoing intervention for SSIs between April 1, 2012 and March 31, 2019. SETTING: The study was conducted in the Calgary zone of Alberta Health Services (AHS) in Canada. PARTICIPANTS: Individuals >18 years with complex SSI following hip or knee replacement. METHODS: Patients with complex SSIs were identified using the AHS infection prevention and control database. A combination of microcosting and gross costing methods were used to estimate 12- and 24-month costs following the initial hospital admission for arthroplasty. Subgroup, inverse Gaussian and γ regression analyses were used to evaluate the impact of age and comorbidities on cost. RESULTS: In total, 142 patients with complex SSIs were identified, with a mean age of 66.8 years. Total direct medical costs in United States dollars of 2-stage revisions were ($100,992 (95% CI, 34,587-167,396) at 12 months. The 1-stage revision ($41,176; 95% CI, 23,361-58,991), DAIR with liner exchange ($41,267; 95% CI, 29,923-52,612) and DAIR ($46,605; 95% CI, 15,277-76,844) were associated with fewer costs at 12 months. Age >65 years and chronic complications of diabetes and hypertension were associated with increased costs in subgroup and regression analysis. CONCLUSIONS: Medical costs are highest at 12 months and for 2-stage revisions in hip and knee complex SSI cases. Further work should explore surgical outcomes correlated with costs to enhance patient care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".