Preoperative low muscle mass is a predictor of falls within 12 months of surgery in patients with lumbar spinal stenosis.
2020
BACKGROUND Patients with lumbar spinal stenosis (LSS) may be at high risk of falls due to various factors. No effective fall risk assessments or fall prevention measures have been performed for patients with LSS because only a few studies have evaluated falls in these patients. This study aimed to evaluate the incidence and preoperative predictors of falls within 12 months of surgery in patients with LSS. METHODS In this prospective study of 82 consecutive preoperative patients with LSS, preoperative demographic data, previous fall history, leg pain, low back pain, Japanese Orthopaedic Association (JOA) score, Hospital Anxiety and Depression Scale (HADS) scores, lower extremity muscle strength, walking speed, grip strength, and muscle mass were assessed at baseline. Falls were assessed at 3, 6, 9, and 12 months after surgery. Participants were categorized as fallers and non-fallers and baseline variables were compared. Binomial logistic regression was used to identify predictors of falls within 12 months of surgery. RESULTS Seventy-four patients (90.2%) completed the 12-month follow-up after surgery, of whom 24 patients (32.4%) experienced falls. A higher proportion of fallers were female and had a history of falls compared to non-fallers. Fallers had a significantly lower JOA score and a higher HADS-depression score compared to non-fallers. Fallers had significantly lower tibialis anterior muscle strength, gait speed, grip strength, and skeletal muscle mass index. Fallers had a higher prevalence of low muscle mass compared with non-fallers. The presence of low muscle mass was significantly predictive of falls within 12 months of surgery (odds ratio, 4.46; 95% confidence interval, 1.02-19.63). CONCLUSIONS Patients with LSS have a high incidence of falls after surgery and preoperative low muscle mass may be a predictor of postoperative falls.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
39
References
2
Citations
NaN
KQI