Bibliographic record
Abstract
Sternotomy and sternal closure occur prior to and post cardiac surgery, respectively. Although post-operative complications associated with poor sternal fixation can result in morbidity, mortality, and considerable resource utilization, sternotomy is preferred over other methods such as lateral thoracotomy. Rigid sternal fixation is associated with stability and reduced incidence of post-operative complications. This is a comprehensive review of the literature evaluating in vivo, in vitro, and clinical responses to applying commercial and experimental surgical tools for sternal fixation after median sternotomy. Wiring, interlocking, plate-screw, and cementation techniques have been examined for closure, but none have experienced widespread adoption. Although all techniques have their advantages, serious post-operative complications were associated with the use of wiring and/or plating techniques in high-risk patients. A fraction of studies have analyzed the use of sternal interlocking systems and only a single study analyzed the effect of using kryptonite cement with wires. Plating and interlocking techniques are superior to wiring in terms of stability and reduced rate of post-operative complications; however, further clinical studies and long-term follow-up are required. The ideal sternal closure should ensure stability, reduced rate of post-operative complications, and a short hospitalization period, alongside cost-effectiveness.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".