Evidence map›Paper›PMID 37554849›Full record

ArticleAnnals of medicine and surgery (2012)2023

Stem cell-based combinatorial therapies for spinal cord injury: a narrative review of current research and future directions.

Nicholas Aderinto, Muili Opeyemi Abdulbasit, Deji Olatunji

Abstract read
In one paragraph

Article in Annals of medicine and surgery (2012), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Biomaterials and cell-based therapy post spinal cord injury.Journal of translational medicine · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nicholas AderintoDepartment of Medicine and Surgery, Ladoke Akintola University of Technology, Ogbomoso.
Muili Opeyemi AbdulbasitDepartment of Medicine and Surgery, Ladoke Akintola University of Technology, Ogbomoso.
Deji OlatunjiDepartment of Medicine and Surgery, University of Ilorin, Ilorin, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spinal cord injury (SCI) is a devastating condition that can result in lifelong disability. Despite significant progress in SCI research, current treatments only offer limited functional recovery. Stem cell-based combinatorial therapies have emerged promising to enhance neural repair and regeneration after SCI. Combining stem cells with growth factors, biomaterials, and other therapeutic agents can improve outcomes by providing a multifaceted approach to neural repair. However, several challenges must be addressed before these therapies can be widely adopted in clinical practice. Standardisation of stem cell isolation, characterisation, and production protocols ensures consistency and safety in clinical trials. Developing appropriate animal models that accurately mimic human SCI is crucial for successfully translating these therapies. Additionally, optimal delivery methods and biomaterials that support the survival and integration of stem cells into injured tissue must be identified. Despite these challenges, stem cell-based combinatorial therapies for SCI hold great promise. Innovative approaches such as gene editing and the use of neural tissue engineering may further enhance the efficacy of these therapies. Further research and development in this area are critical to advancing the field and providing effective therapies for SCI patients. This paper discusses the current evidence and challenges from the literature on the potential of stem cell-based combinatorial therapies for SCI.

Indexed as

combinatorial therapiesspinal cord injury (SCI)stem cells

Identifiers

PMID37554849
PMCPMC10406006

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.