Predicting functional outcome after nonoperative treatment of proximal humeral fractures involving the surgical neck

Abstract

Background: In nonoperative treated proximal humeral fractures (PHFs), uncertainty remains regarding functional outcome. Therefore, the aim was to identify predictors of functional outcome following nonoperative treatment of PHF and to develop predictive models.

Methods: Adults with a nonoperatively treated PHF involving the surgical neck were followed for 1 year. Radiographic parameters included fracture configuration, displacement, bone quality, and the critical shoulder angle. The neck-shaft angle and humeral head offset assessed displacement. The greater tuberosity index (GTI) addressed greater tuberosity (GT) displacement relative to the articular surface while the impingement index addressed GT-displacement relative to the acromion. Multivariate regression models determined predictors of impaired function as measured by Constant score (CS), flexion, and external rotation (ER). Recursive partitioning created a decision tree model over dichotomized functional outcome that combined flexion and ER (good = flexion ≥120° and ER ≥ 40°).

Results: In 272 consecutive patients (mean age: 66 years, 69% women and 31% men), mean functional outcomes were a CS of 74 points, 138° flexion, and 50° ER. Older age was a predictor for impaired CS, flexion, and ER (P < .001), while sex only influenced CS (P = .040). Every 10% increase in GTI assessed on the Y-view explained a decrease of 3 CS points, 7° of flexion, and 5° of ER (P < .001). Every 10° of varus angulation assessed on anterior-posterior views in internal rotation resulted in a decrease of 1 CS point and 4° of flexion (P ≤ .004). Subgroups of combined important GT-displacement (GTI ≥1.15) with age >76 years or < 119° varus angulation demonstrated the worst function. Linear prediction models estimated flexion, ER, and CS with a mean difference of 10°, 3°, and 3 points, respectively. The decision tree model predicted good function with 80% accuracy (positive predictive value = 81%; negative predictive value = 78%).

Conclusion: Demographic and radiographic predictors were identified allowing for accurate functional prognosis of nonoperatively treated PHF involving the surgical neck. A combined assessment of the anterior-posterior-view in internal rotation and Y-view is sufficient for accurate function prediction. The identified subgroups resulting in good or impaired function and the predictive models may be useful for patient counseling and guidance of treatment-related expectations.

Keywords: Proximal humerus fracture; conservative treatment; machine learning; prediction model; recursive partitioning; surgical neck fracture.