Effectiveness and Safety of Inelastic Versus Elastic Lumbosacral Orthoses on Low Back Pain Prevention in Healthy Nurses

A Randomized Controlled Trial

Abstract

Study Design. 

A randomized controlled trial.

Objective. 

To evaluate the effects of inelastic and elastic lumbosacral orthoses (LSOs) on the prevention of low back pain (LBP) in healthy nurses.

Summary of Background Data. 

Over 80% of people experience LBP during their lifetime. LSOs, as a device used to maintain lumbar stability, were widely used in LBP management. The effects of inelastic LSOs (iLSOs) and elastic LSOs (eLSOs) on the prevention of LBP are controversial.

Methods. 

A randomized clinical trial recruiting healthy nurses was conducted from November 2011 to June 2013 at a tertiary hospital in China. A total of 300 eligible participants aged 20 to 25 years were randomly assigned to iLSO, eLSO, or control groups. The intervention period was 6 months, and follow-ups were continued for an additional 6 months. Participants in both iLSO and eLSO groups were required to wear LSOs daily. Outcomes included the incidence of LBP, changes in trunk muscle endurance, and spinal range of motion assessed at baseline, 6months, and 12 months from the starting date. The incidence of LBP among groups was analyzed by ANOVA. Wilcoxon rank-sum test, Kruskal-Wallis H test, etc. were used for secondary outcomes comparison across groups.

Results. 

Two hundred seventy-eight out of 300 participants (92.7%) completed the trial. No statistically significant differences were observed in LBP incidence among the three groups. No difference was observed in abdominal/back muscle endurance among groups at 6 months. In secondary outcome analysis regarding spinal range of motion, flexion and extension improved in iLSO groups at 12 months compared with that at baseline (flexion, P = 0.01; extension, P = 0.01), whereas only extension motion improved at 12 months in the eLSO group (P = 0.00).

Conclusions. 

Six-month wearing of LSO showed neither a significant difference in preventing LBP nor causing adverse effects to participants.

Level of Evidence: 1

In Brief

A machine learning algorithm was developed for the automated identification of 15 types of ACDF plates from smartphone images of AP cervical spine radiographs. The algorithm performed with an overall accuracy of 85.8%. This algorithm will be deployed on a smartphone platform for further evaluation, improvement, and eventual widespread use.