Ryoji Tominaga, Noriaki Kurita, Yoshiyuki Kokubun, Takuya Nikaido, Miho Sekiguchi, Koji Otani, Masumi Iwabuchi, Osamu Shirado, Shunichi Fukuhara, Shin-ichi Konno
September 2021, pp 1 - 9 Original Article Read Full Article 10.1007/s00586-021-06965-3
First Online: 13 September 2021
To determine whether abnormalities of the sagittal modifiers (SMs) of the Scoliosis Research Society (SRS)-Schwab classification truly reflect back pain (BP)-specific quality of life (QOL), it is necessary to examine their dose–response relationships and to determine clinically impactful thresholds for declines in BP-specific QOL. This study aimed to analyse the continuous dose–response relationship between each SM and BP-specific QOL.
This cross-sectional study, using data from a Japanese population-based cohort study, included 519 community-dwelling residents aged ≥ 50 years who participated in the annual health examination. The participants completed the Roland–Morris Disability Questionnaire (RDQ) on BP-specific QOL. Spino-pelvic alignment based on SMs was assessed by whole-spine X-ray examinations. We fitted general linear models with or without nonlinear terms to estimate the dose–response relationship between each SM and BP-specific QOL.
Pelvic tilt, pelvic incidence minus lumbar lordosis (PI-LL), and sagittal vertical axis showed dose–response relationships with BP-specific QOL measured as the RDQ score. PI-LL was most likely to predict a minimally clinically important RDQ score when its value exceeded the 90th percentile. A nonlinear relationship between PI-LL and the BP-specific QOL score was found. RDQ increased when PI-LL exceeded 10°.
PI-LL might be the most sensitive of the three modifiers of the SRS-Schwab classification for determining BP-specific QOL. Moreover, BP-specific QOL worsens rapidly when the compensatory mechanism against malalignment exceeds a critical value. Therefore, we suggest that traditional classifications and surgical strategies should be re-examined regarding the dose-dependent abnormalities of the SMs to develop a more reliable classification strategy.
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