The Lower Limb Functional Index: development and clinimetric properties

Background Existing lower-limb, region-specific, patient-reported outcome measures have clinimetric limitations, including limitations in psychometric characteristics (eg, lack of internal consistency, lack of responsiveness, measurement error) and the lack of reported practical and general characteristics. A new patient-reported outcome measure, the Lower Limb Functional Index (LLFI), was developed to address these limitations. Objective The purpose of this study was to overcome recognized deficiencies in existing lower-limb, region-specific, patient-reported outcome measures through: (1) development of a new lower-extremity outcome scale (ie, the LLFI) and (2) evaluation of the clinimetric properties of the LLFI using the Lower Extremity Functional Scale (LEFS) as a criterion measure. Design This was a prospective observational study. Methods The LLFI was developed in a 3-stage process of: (1) item generation, (2) item reduction with an expert panel, and (3) pilot field testing (n=18) for reliability, responsiveness, and sample size requirements for a larger study. The main study used a convenience sample (n=127) from 10 physical therapy clinics. Participants completed the LLFI and LEFS every 2 weeks for 6 weeks and then every 4 weeks until discharge. Data were used to assess the psychometric, practical, and general characteristics of the LLFI and the LEFS. The characteristics also were evaluated for overall performance using the Measurement of Outcome Measures and Bot clinimetric assessment scales. Results The LLFI and LEFS demonstrated a single-factor structure, comparable reliability (intraclass correlation coefficient [2,1]=.97), scale width, and high criterion validity (Pearson r=.88, with 95% confidence interval [CI]). Clinimetric performance was higher for the LLFI compared with the LEFS on the Measurement of Outcome Measures scale (96% and 95%, respectively) and the Bot scale (100% and 83%, respectively). The LLFI, compared with the LEFS, had improved responsiveness (standardized response mean=1.75 and 1.64, respectively), minimal detectable change with 90% CI (6.6% and 8.1%, respectively), and internal consistency (α=.91 and .95, respectively), as well as readability with reduced user error and completion and scoring times. Limitations Limitations of the study were that only participants recruited from outpatient physical therapy clinics were included and that no specific conditions or diagnostic subgroups were investigated. Conclusion The LLFI demonstrated sound clinimetric properties. There was lower response error, efficient completion and scoring, and improved responsiveness and overall performance compared with the LEFS. The LLFI is suitable for assessment of lower-limb function.

Functional connectivity in BOLD and CBF data: similarity and reliability of resting brain networks

Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2×2×2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905±0.033 between-sessions; 0.885±0.052 between-scanners) than ASL (0.545±0.048; 0.575±0.059). Nevertheless, ASL provided highly reproducible (0.955±0.021; 0.970±0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.