INCIDENCE RATES OF DISLOCATION, PULMONARY EMBOLISM, AND DEEP INFECTION DURING THE FIRST SIX MONTHS AFTER ELECTIVE TOTAL HIP REPLACEMENT
Bibliographic record
Abstract
BACKGROUND: The lengths of acute hospital stays following total hip replacement have diminished substantially in recent years. As a result, a greater proportion of complications occurs following discharge. Data on the incidence trends of major complications of total hip replacement would facilitate recognition and management of these adverse events. METHODS: We used Medicare claims data on beneficiaries sixty-five years and older who had had elective, primary total hip replacement for a reason other than a fracture (58,521 patients) or had had revision total hip replacement (12,956 patients) between July 1, 1995, and June 30, 1996. We calculated incidence rates of dislocation, pulmonary embolism, and deep hip infection per 10,000 person-weeks for four time-periods following the admission for the surgery (during the index hospitalization, from discharge to four weeks postoperatively, from five to thirteen weeks postoperatively, and from fourteen to twenty-six weeks postoperatively). We then used life-table methods to estimate the cumulative incidence of each complication over the first six postoperative months. RESULTS: Of the patients who had had a primary total hip replacement, 3.9% had a dislocation, 0.9% had a pulmonary embolism, and 0.2% had a deep infection in the first twenty-six postoperative weeks. In the revision total hip replacement cohort, the proportions with dislocation, pulmonary embolism, and deep infection were 14.4%, 0.8%, and 1.1%, respectively. The rates of these adverse outcomes were highest during the index hospitalization, diminished considerably in the period from discharge to four weeks postoperatively, and continued to drop in the periods from five to thirteen and fourteen to twenty-six weeks postoperatively. CONCLUSIONS: The incidence rates of dislocation, pulmonary embolism, and deep infection are highest immediately after total hip replacement, but they continue to be elevated throughout the first three postoperative months. With the lengths of hospital stays continuing to diminish, an increasing proportion of complications will occur in outpatients. These findings provide a basis for developing strategies to prevent these complications in the postdischarge management of patients who have had elective total hip replacement. LEVEL OF EVIDENCE: Prognostic study, Level II-1 (retrospective study). See p. 2 for complete description of levels of evidence.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".