Factors associated with maintaining reduction following locking plate fixation of proximal humerus fractures: a population-based retrospective cohort study
Bibliographic record
Abstract
Background Loss of reduction (LoR) can occur after locking plate fixation of proximal humerus fractures (PHFs). This study determined biomechanical features of fracture fixation associated with preventing LoR postoperatively. One-year reoperation rates were also compared between those with/without LoR. Methods Population-based administrative data for 359 adults treated using a locking plate for PHF between 2010 and 2016 were examined. Two trained assessors reviewed standardized shoulder radiographs. LoR (Yes/No) was defined as any fracture displacement >0.5 cm, and/or >10° change in neck-shaft angle (NSA) alignment relative to intraoperative imaging. Multiple logistic regression assessed how the following affected maintaining reduction: (1) sex, (2) age, (3) Neer classification, (4) shaft impaction (SI), (5) shaft medialization (SM), (6) calcar reduction (CR), (7) NSA alignment, and (8) screw use. Results LoR was seen in 79 (22%) patients. LoR was significantly associated with increasing age (odds ratio [OR] = 1.06/yr, P < .001), fracture severity (4-part vs. 2-part fracture; OR = 4.63, P = .001), and varus NSA alignment (<125° vs. ≥145°: OR = 5.6, P = .02; <125° vs. 125-145°, OR = 2.2, P = .02]). Patients achieving simultaneous SI, SM, and CR were significantly less likely (OR = 0.009, P < .001) to lose reduction, after controlling for age, fracture severity, and NSA alignment. If only SI was achieved, patients were still significantly less likely to lose reduction relative to achieving none of these mechanical features (OR = 0.17, P = .006). Reoperations were higher when LoR occurred (n = 26/77 [33.4%]) compared with no LoR (n = 20/276 [7.2%]) ( P < .001). Conclusions SI was strongly associated with preventing LoR in patients treated using a locking plate for PHF. SI with concurrent SM, CR, and a neutral or valgus NSA had the lowest rates of LoR. LoR was associated with higher rates of reoperation.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".