The role of the iron-chelating agent deferoxamine in spinal cord injury: a systematic review and meta-analysis of preclinical studies
Bibliographic record
Abstract
BACKGROUND CONTEXT: Despite advances in the medical, surgical and rehabilitation treatment of spinal cord injury (SCI), there remains a need to develop therapeutic strategies to address mechanisms of secondary injury. Numerous preclinical studies have investigated the efficacy of deferoxamine, an iron chelating agent, in improving functional outcomes in SCI models. Anti-inflammatory, antiferroptosis, and lipoperoxidation inhibitory mechanisms have been proposed as the underlying mechanisms of action. PURPOSE: Considering preclinical studies are the gate to translational medicine, we present a quantitative synthesis of the existing literature to shed light on gaps and guide future research in neuroprotection for SCI. STUDY DESIGN: Meta-analysis of preclinical studies involving the use of deferoxamine in in-vivo models of traumatic SCI, regardless of level of injury and/or animal species. METHODS: We conducted a comprehensive search in 3 databases (PubMed, Web of Science, Scopus) in accordance with PRISMA guidelines. Our review protocol was preregistered (PROSPERO registration ID: CRD420251007113). Ten preclinical studies that investigated deferoxamine administration and functional outcomes in animal models of SCI were chosen. We performed a meta-analysis, using a random effects approach, comparing normalized mean differences in deferoxamine-treated and control groups. To minimize heterogeneity, subgroup analysis and meta regression were conducted. We utilized the CAMARADES checklist for quality assessment of the included studies. RESULTS: Out of 157 articles, 10 were included for final analysis. Our results revealed that deferoxamine can improve functional scores in animal models of thoracic traumatic SCI (NMD=35.74% [18.74, 52.75]; p<.001). The funnel plot was symmetric and no publication bias was noted. Heterogeneity was high among included studies (I²: 95.98). The median score for CAMARADES was 5 (IQR range: 4-6), indicating moderate overall quality of include studies. Sample size calculation and allocation concealment were lacking in included studies. Meta regression was significant for assessment time (Coefficient: -0.574 [-0.905, -0.242]) and route of administration. CONCLUSION: We demonstrated that deferoxamine improves hindlimb motor function in animal models of SCI. Potential knowledge gaps exist, necessitating future animal studies across a more diverse range of injury levels and functional assessment tools before moving on to conducting clinical trials. Assessment time may play a critical role in preclinical models and needs to be adjusted to clinically plausible time points in future studies. More inter-species preclinical research, especially in nonhuman primates, is encouraged to foster generalizability and clinical applicability of the models. CLINICAL SIGNIFICANCE: Approved medical interventions for neuroprotection in SCI are lacking. Given the promising results of the included preclinical studies as well as the established clinical safety profile of deferoxamine, our paper provides a basic science foundation for the design and implementation of future randomized controlled trials. Notwithstanding, these trials may be withheld or approached with caution until more extensive preclinical research is available.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.022 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".