Association of paraspinal muscle morphology or composition with sagittal spinopelvic alignment: a systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: The aim of this study was to evaluate the association of paraspinal muscle morphology and composition with sagittal spinopelvic alignment (SSA). METHODS: This review was registered at PROSPERO (CRD42022371879). Four databases including PubMed, Embase, Cochrane, and Web of Science were searched from their inception until December 15, 2024. The scope of paraspinal muscles included multifidus (MF), erector spinae (ES), psoas major (PM), and paraspinal extensor muscles (PEM; combined multifidus and erector spinae). The cross-sectional area (CSA) and fat signal fraction (FSF) were the metrics for quantifying paraspinal muscle morphology and composition, respectively. The outcomes of interest were SSA parameters, including C7-S1 sagittal vertical axis (SVA), thoracic kyphosis (TK), lumbar lordosis (LL), pelvic tilt (PT), sacral slope (SS), pelvic incidence (PI), and PI minus LL mismatch (PI - LL). The methodological quality and risk of bias of each included studies was assessed using the Newcastle-Ottawa Scale and its adapted form. Correlation coefficients extracted from included studies were transformed to a Fisher's z correlational coefficient to perform a meta-analysis and to generate a pooled effect size (z) and 95% confidence intervals (CIs). RESULTS: Sixteen observational studies with 1535 participants were included in the meta-analysis. We found a positive association of paraspinal muscle CSA with TK (MFCSA, z = 0.17, 95% CI: 0.01 to 0.32, p = 0.041; PEMCSA, z = 0.17, 95% CI: 0.06 to 0.28, p = 0.002) and LL (PMCSA, z = 0.12, 95% CI: 0.02 to 0.22, p = 0.019), whereas a negative correlation with SVA (MFCSA, z = - 0.35, 95% CI: -0.67 to - 0.02, p = 0.036; PEMCSA, z = - 0.25, 95% CI: -0.45 to - 0.05, p = 0.015), PT (PMCSA, z = - 0.22, 95% CI: -0.39 to - 0.05, p = 0.012), PI (PMCSA, z = - 0.13, 95% CI: -0.23 to - 0.02, p = 0.020), and PI-LL (MFCSA, z = - 0.50, 95% CI: -0.69 to - 0.30, p < 0.00001; PMCSA, z = - 0.20, 95% CI: -0.34 to - 0.05, p = 0.007; PEMCSA, z = - 0.28, 95% CI: -0.38 to - 0.18, p < 0.00001). Meanwhile, paraspinal muscle FSF showed a positive correlation with SVA (PEMFSF, z = 0.39, 95% CI: 0.30 to 0.47, p < 0.00001), PT (PEMFSF, z = 0.45, 95% CI: 0.35 to 0.54, p < 0.00001), and PI-LL (PEMFSF, z = 0.29, 95% CI: 0.17 to 0.41, p < 0.00001), while a negative correlation with PI (PMFSF, z = - 0.14, 95% CI: -0.27 to - 0.01, p = 0.029) and SS (PEMFSF, z = - 0.25, 95% CI: -0.41 to - 0.08, p = 0.004). We also observed the associations were stronger in populations without degenerative spinal diseases, in studies that used computed tomography for paraspinal muscle morphology and composition assessment, and in studies with moderate study quality. Of the 15 significant associations reported here, only 3 were supported by moderate to high-level evidence, while others were supported by very low to low evidence certainty. CONCLUSION: Paraspinal muscle morphology and composition were associated with SSA. Further studies are warranted to establish causality and to elucidate the underlying mechanisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.024 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".