Stem cell therapy for reconstruction of alveolar cleft and trauma defects in adults: A randomized controlled, clinical trial
Bibliographic record
Abstract
BACKGROUND: Stem cell therapy with bone marrow-derived mesenchymal stem cells is a promising tissue engineering strategy to promote regeneration of craniofacial bone. PURPOSE: To determine whether cell therapy with ex vivo expanded stem cell populations would be safe and efficacious in the regeneration of large alveolar defects in patients with a history of cleft palate or craniofacial trauma. MATERIALS AND METHODS: Eighteen patients (10 patients with traumatic injury and 8 patients with cleft palate) presenting with missing teeth associated with horizontal alveolar bone deficiencies were included in this randomized controlled clinical trial. Patients were randomized to receive either conventional autogenous block grafts or stem cell therapy. After a healing period of 4 months the treated sites were re-entered and the bone width re-assessed prior to implant placement. Implant stability was evaluated through torque testing of the implant upon insertion and at 6 months postloading. RESULTS: The mean gain in bone width was 1.5 ± 1.5 mm in the stem cell therapy group and 3.3 ± 1.4 mm in the control group. Overall, bone gain was higher in trauma patients as compared to patients with cleft palate, for both the control and the stem cell therapy groups. Most postoperative complications were wound dehiscences and incision line openings. Implants were placed successfully in 5 out of 10 patients in the stem cell therapy group and in all 8 patients in the control group. One implant from the control/cleft palate group failed before loading, while the rest of the implants were loaded successfully and remained stable at 6 months. The patients who did not receive implants were re-treated with autogenous block bone graft. CONCLUSION: The ability of stem cells to treat large alveolar defects is safe, yet, their ability to completely reconstitute large alveolar defects is limited. This approach requires further optimization to meet the outcomes seen using current methods to treat large defects, particularly those resultant of cleft palate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".