Emergency Department Visits After Total Joint Arthroplasty for Concern for Deep Vein Thromboses
Bibliographic record
Abstract
BACKGROUND: Concern for deep vein thrombosis (DVT) is the most common reason for emergency department (ED) referral after total joint arthroplasty (TJA) at our institution. We aim to investigate the referral pathway, together with the cost and outcomes associated with patients who access an ED because of concern for DVT after TJA. METHODS: We reviewed a consecutive series of all primary hip and knee arthroplasty patients who accessed the ED for concern for DVT within 90 days of surgery over a one-year period. The referral source and costs associated with the ED visit were collected. A propensity-matched control cohort (n = 252) that was not referred to the ED for DVT was used to compare patient-reported outcomes measures. RESULTS: In 2018, 108/10,445 primary TJA patients (1.0%) accessed the ED for concern about DVT. The most common reason for accessing the ED was self-referral (69, 64%), followed by orthopaedic on-call referral (21, 19%). Only 15 patients (14%) were found to have ultrasonography evidence of DVT. The mean cost for accessing the ED for DVT for patients with public insurance was $834 (range $394-$2,877). When compared with the control cohort, patients who accessed the ED for DVT had significantly lower postoperative functionality scores (52.5 versus 65.9, P < 0.001). DISCUSSION: At our institution, 1% of patients who undergo primary TJA accessed the ED for concern for DVT at substantial cost, with only a small portion testing positive for DVT. Self-referral is by far the most common pathway. Additional investigations will be aimed at determining better pathways for DVT work-up, while ensuring appropriate management.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".