Total cost of surgical site infection in the two years following primary knee replacement surgery
Bibliographic record
Abstract
OBJECTIVE: The disease burden of surgical site infection (SSI) following total knee (TKA) replacement is considerable and is expected to grow with increased demand for the procedure. Diagnosing and treating SSI utilizes both inpatient and outpatient services, and the timing of diagnosis can affect health service requirements. The purpose of this study was to estimate the health system costs of infection and to compare them across time-to-diagnosis categories. METHODS: Administrative data from 2005-2016 were used to identify cases diagnosed with SSI up to 1 year following primary TKA. Uninfected controls were selected matched on age, sex and comorbidities. Costs and utilization were measured over the 2-year period following surgery using hospital and out-of-hospital data. Costs and utilization were compared for those diagnosed within 30, 90, 180, and 365 days. A subsample of cases and controls without comorbidities were also compared. RESULTS: We identified 238 SSI cases over the study period. On average, SSI cases cost 8 times more than noninfected controls over the 2-year follow-up period (CaD$41,938 [US$29,965] vs CaD$5,158 [US$3,685]) for a net difference of CaD$36,780 (US$26,279). The case-to-control ratio for costs was lowest for those diagnosed within 30 days compared to those diagnosed later. When only patients without comorbidities were included, costs were >7 times higher. CONCLUSION: Our results suggest that considerable costs result from SSI following TKA and that those costs vary depending on the time of diagnosis. A 2-year follow-up period provided a more complete estimate of cost and utilization.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".