Background Few, if any, patient reported symptoms have been shown to be related to objective measures of spine function. Recently, patient-reported measures of disability following spinal manipulative therapy have been associated with an immediate decrease in spinal stiffness obtained by instrumented L3 indentation. Given this novel relation, we anticipate that stiffness measures obtained from locations in addition to L3 may yield valuable information. As such, our research team has developed a new technique to acquire stiffness data continuously over an entire spinal region. The reliability of stiffness measurements obtained by this new technique has yet to be quantified. Methods Continuous stiffness testing employs a weighted roller that moves uninterrupted over the spine while measuring the resulting spinal deflection along a subject-specific, laser-defined trajectory. A volunteer sample of asymptomatic participants were assessed in 2 sessions occurring 1 to 4 days apart, with each session scheduled at the same time of day. Each session consisted of 3 trials each beginning at a baseline of ~ 17 N then progressing to a maximally tolerable load as defined from pre-test familiarization trials (~ 61, 72 or 83 N). Reliability was evaluated with the intraclass correlation coefficient, the standard error of measurement and Bland & Altman analysis. Results A total of 17 asymptomatic participants (mean age 29.2 +/− 6 years, 53% female) took part in the study. Overall, the within and between-session reliability of lumbar spine stiffness measures at the maximal tolerable load was excellent ranging from 0.95–1.00 and good to excellent ranging from 0.82–0.93, respectively. Trial averaging was found to reduce standard error of measurement by a mean of 35.2% over all measurement conditions compared to a single trial. Bland and Altman plots for agreement in lumbar spine stiffness measurements varied from − 0.3 +/− 1.2 at unloaded condition to − 0.2 +/− 1.2 at loaded condition. Data from two participants were removed due to the development of back pain between two sessions. Conclusion This study introduced a new technique for measuring spinal stiffness over an entire spinal region in asymptomatic human participants. The new technique produced reliable measurements quantifying the load-displacement values for within-session and between-session assessments.

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Background Spinal manipulative therapy (SMT) is among the nonpharmacologic interventions that has been recommended in clinical guidelines for patients with low back pain, however, some patients appear to benefit substantially more from SMT than others. Several investigations have examined potential factors to modify patients’ responses prior to SMT application. The objective of this study was to determine if the baseline prediction of SMT responders can be improved through the use of a restricted, non-pragmatic methodology, established variables of responder status, and newly developed physical measures observed to change with SMT. Materials and methods We conducted a secondary analysis of a prior study that provided two applications of standardized SMT over a period of 1 week. After initial exploratory analysis, principal component analysis and optimal scaling analysis were used to reduce multicollinearity among predictors. A multiple logistic regression model was built using a forward Wald procedure to explore those baseline variables that could predict response status at 1-week reassessment. Results Two hundred and thirty-eight participants completed the 1-week reassessment (age 40.0± 11.8 years; 59.7% female). Response to treatment was predicted by a model containing the following 8 variables: height, gender, neck or upper back pain, pain frequency in the past 6 months, the STarT Back Tool, patients’ expectations about medication and strengthening exercises, and extension status. Our model had a sensitivity of 72.2% (95% CI, 58.1–83.1), specificity of 84.2% (95% CI, 78.0–89.0), a positive likelihood ratio of 4.6 (CI, 3.2–6.7), a negative likelihood ratio of 0.3 (CI, 0.2–0.5), and area under ROC curve, 0.79. Conclusion It is possible to predict response to treatment before application of SMT in low back pain patients. Our model may benefit both patients and clinicians by reducing the time needed to re-evaluate an initial trial of care.