Impact of postoperative venous thromboembolism on Medicare recipients undergoing total hip replacement or total knee replacement surgery
Bibliographic record
Abstract
PURPOSE: The impact of postoperative venous thromboembolism (VTE) during initial hospitalization for total hip replacement (THR) or total knee replacement (TKR) surgery was assessed. METHODS: Using Medicare Provider Analysis and Review files, patients who underwent THR, TKR, or hip fracture surgery from 2005 to 2007 were identified using appropriate procedure codes from the International Classification of Diseases, 9th Revision, Clinical Modification. Medicare managed care patients were excluded from the study. Eligible patients were classified as having had deep venous thrombosis (DVT), pulmonary embolism (PE), DVT and PE, or no VTE during their initial hospitalization. Risk adjustment was performed using propensity score matching. Medicare cost, cost to beneficiaries, and cost to primary payers were analyzed to determine risk-adjusted differences in outcome measures, including mortality, rehospitalization, bleeding, length of stay, and total health care expenditures related to VTE events. RESULTS: A total of 170,047 patients were identified. Postoperative VTE events occurred in 3,014 patients (1.77%) during their initial hospitalization. Risk-adjusted mortality rates were three to four times higher for patients with VTE compared with those without VTE. Patients with VTE were more likely to be rehospitalized and experience bleeding within 30 days. Risk-adjusted differences in annual mean cost, including Medicare cost and costs to beneficiaries and primary payers, were significantly greater for patients with VTE. CONCLUSION: Patients who developed VTE after THR or TKR had a higher likelihood of mortality, bleeding, and rehospitalization; were hospitalized longer; and incurred higher costs to Medicare, Medicare beneficiaries, and private payers compared with patients without VTE.
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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 | 0.001 |
| 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".