European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
-
Unfortunately, figure 3 was incorrectly published in the original publication. The complete correct figure 3 is given below.
-
Artificial intelligence algorithms can now identify hidden data patterns within the scientific literature. In 2019, these algorithms identified a thermoelectric material within the pre-2009 chemistry literature; years before its discovery in 2012. This approach inspired us to apply this algorithm to the back pain literature as the cause of back pain remains unknown in 90% of cases. ⋯ Artificial intelligence algorithms can successfully extract complex concepts from back pain literature. While use of AI algorithms to discover potentially unknown word associations requires future validation, our results provide investigators with a novel tool to generate new hypotheses regarding the origins of LBP and other spine related topics. To encourage use of these tools, we have created a free web-based app for investigator-driven queries.
-
To investigate the impact of Scheuermann's Kyphosis (SK) on health -related quality of life (HRQOL) in adult patients and compare it to the general population. Moreover, to assess whether location of the kyphosis affects pelvic parameters, HRQOL, and pulmonary function. ⋯ We found a lower HRQOL in adult patients with SK 39 years after diagnosis regarding SRS-22r domains pain and self-image, and a tendency toward lower overall HRQOL compared with a background population. The location of the SK apex did not seem to have an overall impact on HRQOL. There was no difference in pelvic parameters in the two groups and no difference in pulmonary function. These slides can be retrieved under Electronic Supplementary Material.