Rotational problems and clinical reflections after locked intramedullary nailing in diaphyseal femur fractures: A minimum follow-up of 5 years
Bibliographic record
Abstract
BACKGROUND: Rotational malalignment following intramedullary nailing (IMN) of femoral shaft fractures remains a clinically significant concern, with previous studies reporting variable incidence rates and inconsistent risk factors. This study aimed to determine the incidence of rotational malalignment after closed static-locked intramedullary nailing for adult diaphyseal femoral fractures, identify contributing etiological factors, and evaluate its clinical impact on functional capacity and quality-of-life metrics. METHODS: A retrospective cohort study was conducted involving 54 adults treated with closed static-locked IMN for diaphyseal femur fractures between 2014 and 2019. Rotational alignment was assessed using computed tomography (CT)-measured femoral anteversion (FAV) differences, with a threshold of ≥15° defined as malalignment. Multivariate logistic regression was employed to examine associations with fracture pattern, nail entry site, surgical timing (day vs. night), and coronal alignment. Functional outcomes were assessed using the WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index) knee, Harris hip, Lower Extremity Functional Scale, and Kujala patellofemoral scores. Receiver operating characteristic (ROC) analysis was used to determine optimal FAV thresholds. RESULTS: Rotational malalignment (≥15° FAV difference) was observed in 33.3% of cases, with 94.4% involving internal rotation. Multivariate analysis identified no independent predictors among the following factors: fracture location (proximal 44.4% vs. middle 29.2%, p=0.625), AO classification (Type A 34.3% vs. Type C 33.3%, p=0.914), nail entry site (lateral trochanteric 40% vs. piriformis 16.6%, *p*=0.574), and surgical timing (night 26.1% vs. day 38.7%, p=0.228). Patients with malalignment demonstrated significantly poorer functional outcomes, as evidenced by higher WOMAC knee scores (12.7+-4.8 vs. 6.4+-4.8, p<0.001). ROC curve analysis identified 13.5° as the optimal FAV threshold (area under the curve, AUC: 0.78), although the 15° cutoff maintained strong clinical utility with a specificity of 83%. CONCLUSION: Rotational malalignment following IMN occurs in one-third of cases and has a significant negative impact on functional outcomes. However, it appears to be independent of commonly considered surgical variables such as entry site and timing. These findings support technical flexibility in IMN procedures while highlighting the need for improved intraoperative techniques to assess rotational alignment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".