Development and internal validation of a prognostic scoring system for Conservative treatment outcomes in idiopathic neck extensor Myopathy-Dropped head syndrome.

Kobayashi, Takayuki; Endo, Kenji; Sawaji, Yasunobu; Nishimura, Hirosuke; Suzuki, Hidekazu; Aihara, Takato; Yamauchi, Hideya; Nagayama, Kyohei et al. · Eur Spine J · 2026

retrospective_cohort · Level III

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Abstract

PURPOSE: Prognostic factors for conservative treatment of dropped head syndrome (DHS) remain unclear. The objectives of this study were to identify prognostic factors for conservative treatment outcomes in patients with isolated neck extensor myopathy-related dropped head syndrome (INEM-DHS) and to develop a prognostic scoring system to support clinical treatment decision-making. METHODS: One hundred consecutive INEM-DHS patients who visited our hospital and could be followed for six months of conservative treatment were included. Patients were classified into two groups: the improved group (I group) and the non-improved group (N group) based on conservative treatment outcomes. Improvement rates and demographic, clinical, and radiographic parameters were compared between the groups using univariate and multivariate analysis, and a scoring system was developed. RESULTS: Multivariate analysis identified three independent prognostic factors: duration of symptoms (odds ratio [OR] = 4.78, 95% CI: 2.01–11.39), cervical kyphosis (OR = 0.38, 95% CI: 0.20–0.76), and pelvic tilt (OR = 2.99, 95% CI, 1.57–5.69) were factors associated with prognosis. The developed scoring system demonstrated good performance, having an AUC of 0.835. Based on total scores, the patients were stratified into low-risk, intermediate-risk, and high-risk groups. Their respective improvement rates were 81.7%, 37.6%, and 18.4%,. CONCLUSIONS: Conservative treatment prognosis in INEM-DHS patients can be predicted based on duration of symptoms, cervical kyphosis, and pelvic tilt. The scoring system developed using these three factors demonstrated potential clinical utility for prognostic prediction and treatment decision-making.