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Record W4414448542 · doi:10.7759/cureus.93065

Efficacy and Safety of Glucagon-Like Peptide-1 (GLP-1) Receptor Agonists for Spinal Fusion Outcomes: A Comprehensive Meta-Analysis

2025· review· en· W4414448542 on OpenAlexaboutno aff
Mohamed Zahed, Mahmoud Elmesalmi, Khaled F Al-Kharouf, Sara E Elbahnasawy, Ziad El Menawy, Salam Elhanash, Nour Elnaggar, Mohamed Hesham Gamal, Mahmoud M. Elhady

Bibliographic record

VenueCureus · 2025
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsnot available
Fundersnot available
KeywordsSpinal fusionCochrane LibraryReceptorMeta-analysisLumbarConfidence intervalAdverse effect

Abstract

fetched live from OpenAlex

Spinal fusion is a widely performed surgical procedure for treating various spinal disorders, with lumbar fusion showing remarkably rapid growth worldwide. Despite positive outcomes after the procedure, it carries significant complications, most notably pseudarthrosis. Compromised blood supply is a key factor disrupting normal bone fusion, making optimal vascularization crucial for successful outcomes. Glucagon-like peptide-1 (GLP-1) receptor agonists, primarily used for diabetes management, demonstrate promising effects including enhanced glycemic control, improved vascular endothelial function, and direct enhancement of osteoblastic cell activity through GLP-1 receptors on bone precursor cells. Theoretically, GLP-1 receptor agonists should be beneficial for optimizing spinal fusion outcomes. We aim to systematically review and analyze the current evidence on the efficacy and safety of GLP-1 receptor agonists in promoting bone fusion and reducing complications in patients undergoing spinal fusion surgery. We conducted a comprehensive systematic review following Cochrane guidelines. We searched PubMed, Web of Science, Scopus, Embase, and Cochrane Library for studies examining GLP-1 receptor agonists in spinal fusion procedures. We used the Newcastle-Ottawa Scale for the quality assessment of the included studies. We conducted a statistical analysis using RevMan 5.4 with risk ratios for dichotomous outcomes. In total, 11 studies with a total of 14,344 participants were analyzed. GLP-1 receptor agonists significantly reduced pseudoarthrosis at six months (risk ratio (RR) = 0.63, 95% confidence interval (CI) = 0.54-0.74) and 12 months (RR = 0.64, 95% CI = 0.57-0.72), and significantly increased acute kidney injury (RR = 1.30, 95% CI = 1.03-1.65). No significant differences were observed for pseudoarthrosis at 24 months (RR = 1.03, 95% CI = 0.53-2.03), readmission rates (RR = 0.85, 95% CI = 0.48-1.51), cerebrovascular accidents (RR = 1.01, 95% CI = 0.63-1.62), and deep vein thrombosis (RR = 1.16, 95% CI = 0.78-1.72). Additionally, no significant reoperations or adverse effects were found. We also performed a subgroup analysis considering the diabetic stage, which showed valuable insights. GLP-1 receptor agonists showed promising results in reducing pseudoarthrosis at short- to medium-term follow-up, indicating potential therapeutic benefits in bone healing applications. However, the increased risk of acute kidney injury suggests the need for careful patient monitoring and risk stratification. The lack of sustained benefit at 24 months and significant heterogeneity observed in several outcomes indicate that further investigation is warranted. Future research should focus on conducting larger, well-designed randomized controlled trials with standardized outcome definitions, longer follow-up periods, and comprehensive safety monitoring to establish optimal dosing protocols and patient selection criteria for GLP-1 receptor agonist therapy in orthopedic applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.609
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.004
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.129
GPT teacher head0.398
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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