A systematic review evaluating the association of atherosclerosis and lumbar degenerative disc disease
Bibliographic record
Abstract
Introduction: Lumbar disc herniation (LDH) and disc degeneration (DD) are associated with low back pain (LBP) and sciatica, which are common health problems. Emerging evidence suggests a link between vascular health, specifically abdominal aortic calcification (AAC) and systemic lipid profiles, and these spinal conditions. Research question: This study investigates the associations between AAC, systemic lipid profiles, lumbar Modic Changes (MC), DD/LDH, and the occurrence of LBP or sciatica. Material and methods: A literature search was performed (up to August 2023) in PubMed, Embase, Web of Science, Emcare, Cochrane Library, and Academic Search Premier utilizing a sensitive search strategy. Studies were chosen based on predefined criteria and assessed for bias using an adapted Cochrane checklist. Specifically, studies exploring the relationship between AAC or lipid status and DD/LDH and/or LBP/Sciatica were included. Results: Twenty-seven studies were included. Eight studies assessed the association between atherosclerosis or lipid status and clinical LBP/sciatica, with four showing a positive association between AAC/lumbar artery stenosis and these conditions. Twenty-one studies assessed atherosclerosis and DD/LDH, with seven showing a positive association between AAC and DD/LDH. Eight trials found a positive association between lipid status and DD/LDH, and two trails identified ApoL1 as a biomarker for LDH recovery. Discussion and conclusion: Evidence supports the hypothesis that inadequate blood supply contributes to disc degeneration, inflammation and clinical symptoms. Both local vascular issues and systemic lipid profiles appear to influence lumbar degeneration, highlighting the need for further research to better understand these relationships and develop preventive and therapeutic strategies.
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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 | 0.010 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".