Deficits in preference-based health-related quality of life after complications associated with tibial fracture
Bibliographic record
Abstract
Aims: The aims of this study were to quantify health state utility values (HSUVs) after a tibial fracture, investigate the effect of complications, to determine the trajectory in HSUVs that result in these differences and to quantify the quality-adjusted life years (QALYs) experienced by patients. Patients and Methods: This is an analysis of 2138 tibial fractures enrolled in the Fluid Lavage of Open Wounds (FLOW) and Study to Prospectively Evaluate Reamed Intramedullary Nails in Patients with Tibial Fractures (SPRINT) trials. Patients returned for follow-up at two and six weeks and three, six, nine and 12 months. Short-Form Six-Dimension (SF-6D) values were calculated and used to calculate QALYs. Results: Compared with those who did not have a complication, those with a complication treated either nonoperatively or operatively had lower HSUVs at all times after two weeks. The HSUVs improved in all patients with the passage of time. However, they did not return to the remembered baseline preinjury values nor to US age-adjusted normal values by 12 months after the injury. Conclusion: While the acute fracture and complications may have resolved clinically, the detrimental effect on a patient's quality of life persists up to 12 months after the injury. Cite this article: Bone Joint J 2018;100-B:1227-33.
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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 | 0.007 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".