Risk factors for infection, revision, death, blood transfusion and longer hospital stay 3 months and 1 year after primary total hip or knee arthroplasty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Total joint replacement (TJR) is increasingly performed in older patients with more comorbidities, who are considered at higher risk for postoperative complications. We aimed to identify and calculate the odds ratio of the risk factors for infection, revision and death 3 months and 1 year after TJR as well as for postoperative blood transfusion and longer hospital stay. METHODS: We analyzed all primary total hip arthroplasty (THA) and total knee arthroplasty (TKA) cases in Nova Scotia between Apr. 1, 2000, and Mar. 31, 2014, as identified from the Discharge Abstract Database. We used the Charlson Comorbidity Index as a surrogate measure of comorbidities. We used hospital and physician billings data and Nova Scotia Vital Statistics data to identify the postoperative events in this cohort. RESULTS: A total of 10 123 primary THA and 17 243 primary TKA procedures were performed during the study period. The mean patient age was 66.1 (standard deviation 11.7) years and 67.1 (standard deviation 9.3) years, respectively. With THA, the risk of infection was higher in patients with heart failure and those with diabetes. For TKA, liver disease and blood transfusion were associated with a higher risk of infection. Revision rates were higher among patients with hypertension and those with paraparesis/hemiparesis for THA, and among patients with metastatic disease for TKA. Significant risk factors for death included metastatic disease, older age, heart failure, myocardial infarction, dementia, rheumatologic disease, renal disease, blood transfusion and cancer. Multiple medical comorbidities and older age were associated with higher rates of blood transfusion and longer hospital stay. CONCLUSION: We have identified the risk factors associated with higher rates of postoperative complications and longer hospital stay after TJR. The results enable individualized risk stratification during the preoperative consultation.
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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 | 0.000 | 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 it