ArticlePloS one2022
Novel elemental grading system for radiographic lumbar spondylosis in a population based-cohort study of a Japanese mountain village.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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6 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
purposeLumbar radiography is a primary screening tool for lumbar spondylosis (LS). Kellgren-Lawrence (KL) classification is widely used to evaluate LS; however, it cannot individually evaluate each radiographic feature. The purpose of this study was to 1) evaluate radiographic LS using a novel elemental grading system and 2) investigate the relationship between the grades of radiographic LS and low back pain (LBP) in a population-based cohort study.
methodsA total of 260 (75 men, 185 women; mean age, 71.5 ± 8.7 years) participants were included in this study. Participants were divided into two groups according to the presence of LBP (LBP- and LBP+ groups). Radiographic features, including osteophyte (OP), disc height narrowing (DHN), vertebral sclerosis (VS), and spondylolisthesis (SL), were classified between grades of 0-2 grades according to the extent of radiographic changes. The sum of grades at each intervertebral level was designated as the intervertebral grade (IG).
resultsIntra- and inter-observer reliability (kappa coefficient) of OP, DHN, VS, and SL were 0.82-0.92. OP, DHN, VS, and IG grades were significantly higher in the LBP+ group than in the LBP- group. There were no significant differences in KL grades between the LBP- and LBP+ groups. Logistic regression analysis demonstrated that VS grade was a significant independent factor associated with LBP.
conclusionThe novel elemental grading system of LS would reflect LBP more accurately than the KL classification by individually evaluating each radiographic feature.
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