Management of non-union of rib fractures secondary to trauma: A scoping review
Bibliographic record
Abstract
OBJECTIVE: Rib fracture non-union is an uncommon complication of traumatic rib fractures. Our objective was to perform a scoping review of the literature for the management of rib fracture non-union. This included analysis of the variations in surgical technique, complications experienced, and reported outcomes. METHODS: We conducted a scoping review and searched databases (MEDLINE, CINAHL, and Embase). We performed abstract and full-text screening, and abstracted data related to pre-operative assessment, surgical technique, complications, and reported outcome measures. RESULTS: We included 29 articles of which 19 were case reports and 10 were case series. The data quality was generally heterogeneous. The studies included 229 patients and the commonest symptoms of rib fracture non-union included chest pain, clicking, dyspnea and deformities. The patients underwent surgical management of rib fracture non-union (excluding first rib fractures) using various techniques. The majority used surgical stabilization of rib fracture with or without a graft. The reported outcomes were inconsistent between studies, but showed high rates of union (>94 %), reduction in reported VAS scores, and improved return to work when included. Implant failure occurred in 10 % of the 229 total patients reported in our studies, the re-operation rate was 13 %, and the overall complication rate was 27 %. CONCLUSION: Surgical management of rib fracture non-union often involving locking plates and screws with or without a graft has been shown in several case reports and series as an effective treatment with acceptable implant failure and complication rates. Surgical management is therefore a viable option for symptomatic patients. Further research is required to determine optimal management strategies that further reduce surgical complications for these patients.
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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| 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".