Evaluation of the patient satisfaction of using a 3D printed medical casting in fracture treatment
Bibliographic record
Abstract
OBJECTIVES: This study aims to assess, through a questionnaire, the functionality, and efficacy of using three-dimensional (3D) printed medical casts. PATIENTS AND METHODS: Between February 2017 and March 2019, a total of 24 patients (14 males, 10 females; mean age: 33.1±9.4 years, range, 12 to 62 years) with upper extremity fracture who were applied 3D printed medical cast were included. Patient satisfaction was evaluated using the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 (QUEST 2.0). Each item is scored on a five-point scale. RESULTS: The mean follow-up was 14 (range, 6 to 18) months. All fractures healed within four to six weeks without any complications. In all cases, there was no loss of reduction. The total mean QUEST 2.0 satisfaction score for the participants was 4.7. The ratings on each scale ranged from 4.5 to 4.9. CONCLUSION: Almost all patients with upper extremity fractures were satisfied with the 3D printed medical cast. The patients found the 3D printed medical cast to be comfortable, safe, easy-to-apply, lightweight, and effective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".