Objective-Radiofrequency ablation (RFA) of the medial branch nerves for facet-mediated low back pain demonstrates clinical benefit for 6-12 months and possibly up to 2 years. This study investigated function, pain, and medication use outcomes of RFA for lumbar facet syndrome in a cohort with long-term follow-up.Methods-Individuals evaluated in a tertiary academic pain practice between January, 2007-December, 2013, 18-60 years of age, with a clinical and radiologic diagnosis of lumbar facet syndrome, who underwent ≥1set of diagnostic medial branch blocks with resultant >75% pain relief and subsequent RFA were included. Outcomes measured were the proportion of individuals who reported ≥50% improvement in function, ≥50% improvement in pain; change in median NRS pain score, daily morphine equivalent consumption (DME), Medication Quantification Scale III (MSQ III) score and procedure complications.Results-Sixty-two consecutive individuals with a median age and 25%-75% interquartile range (IQR) of 34 years (35, 52) met inclusion criteria. Seven individuals were lost to follow-up. Duration of pain was <2 years in 42%, 2-5 years in 40%, >5 years in 18% of individuals. Median duration of follow-up was 39 months (16, 60). Function and pain improved by ≥50% in 58% (CI 45%, 71%) and 53% (CI 40%, 66%) of individuals, respectively. The median reduction in MQS III score was 3.4 points (0, 8.8). No complications occurred in this cohort.Conclusions-This study demonstrates a durable treatment effect of RFA for lumbar facet syndrome at long-term follow-up, as measured by improvement in function, pain, and analgesic use.

This study aims to evaluate the effectiveness and potential utility of using machine learning and natural language processing techniques to develop models that can reliably predict the relative difficulty of incoming chat reference questions. Using a relatively large sample size of chat transcripts (N = 15,690), an empirical experimental design was used to test and evaluate 640 unique models. Results showed the predictive power of observed modeling processes to be highly statistically significant. These findings have implications for how library service managers may seek to develop and refine reference services using advanced analytical methods.

No abstract

Advances in multimodal characterization methods fuel a generation of increasing immense hyper-dimensional datasets. Color mapping is employed for conveying higher dimensional data in two-dimensional (2D) representations for human consumption without relying on multiple projections. How one constructs these color maps, however, critically affects how accurately one perceives data. For simple scalar fields, perceptually uniform color maps and color selection have been shown to improve data readability and interpretation across research fields. Here we review core concepts underlying the design of perceptually uniform color map and extend the concepts from scalar fields to two-dimensional vector fields and three-component composition fields frequently found in materials-chemistry research to enable high-fidelity visualization. We develop the software tools PAPUC and CMPUC to enable researchers to utilize these colorimetry principles and employ perceptually uniform color spaces for rigorously meaningful color mapping of higher dimensional data representations. Last, we demonstrate how these