Evidence map›Paper›PMID 37700356›Full record

SynthesisJournal of orthopaedic surgery and research2023

Treatment options for digital nerve injury: a systematic review and meta-analysis.

Yi Zhang, Nianzong Hou, Jian Zhang, Bing Xie, Jiahui Liang, Xiaohu Chang, Kai Wang, Xin Tang

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of orthopaedic surgery and research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% of its field
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 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
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

8 authors at 4 institutions in 1 country.

Yi ZhangDepartment of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning, China.
Nianzong HouDepartment of Hand and Foot Surgery, Zibo Central Hospital, No. 54 Gongqingtuan West Road, Zibo, Shandong, China.
Jian ZhangDepartment of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning, China.
Bing XieDepartment of Hand and Foot Surgery, Zibo Central Hospital, No. 54 Gongqingtuan West Road, Zibo, Shandong, China.
Jiahui LiangDepartment of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning, China.
Xiaohu ChangDepartment of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning, China.
Kai WangDepartment of Critical Care Medicine, Zibo Central Hospital, No. 54 Gongqingtuan West Road, Zibo, Shandong, China. tangxin202303@163.com.
Xin TangDepartment of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning, China. xiaoyi830219@163.com.
Central Hospital of Zibo · CNFirst Affiliated Hospital of Dalian Medical University · CNDalian Medical University · CNShanghai East Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurgical treatment of finger nerve injury is common for hand trauma. However, there are various surgical options with different functional outcomes. The aims of this study are to compare the outcomes of various finger nerve surgeries and to identify factors associated with the postsurgical outcomes via a systematic review and meta-analysis.

methodsThe literature related to digital nerve repairs were retrieved comprehensively by searching the online databases of PubMed from January 1, 1965, to August 31, 2021. Data extraction, assessment of bias risk and the quality evaluation were then performed. Meta-analysis was performed using the postoperative static 2-point discrimination (S2PD) value, moving 2-point discrimination (M2PD) value, and Semmes-Weinstein monofilament testing (SWMF) good rate, modified Highet classification of nerve recovery good rate. Statistical analysis was performed using the R (V.3.6.3) software. The random effects model was used for the analysis. A systematic review was also performed on the other influencing factors especially the type of injury and postoperative complications of digital nerve repair.

resultsSixty-six studies with 2446 cases were included in this study. The polyglycolic acid conduit group has the best S2PD value (6.71 mm), while the neurorrhaphy group has the best M2PD value (4.91 mm). End-to-side coaptation has the highest modified Highet's scoring (98%), and autologous nerve graft has the highest SWMF (91%). Age, the size of the gap, and the type of injury were factors that may affect recovery. The type of injury has an impact on the postoperative outcome of neurorrhaphy. Complications reported in the studies were mainly neuroma, cold sensitivity, paresthesia, postoperative infection, and pain.

conclusionOur study demonstrated that the results of surgical treatment of digital nerve injury are generally satisfactory; however, no nerve repair method has absolute advantages. When choosing a surgical approach to repair finger nerve injury, we must comprehensively consider various factors, especially the gap size of the nerve defect, and postoperative complications. Type of study/level of evidence Therapeutic IV.

Indexed as

Peripheral Nerve InjuriesPlastic Surgery ProceduresAutograftsDatabases, FactualHumansNeurosurgical ProceduresPostoperative ComplicationsDigital nerveDigital nerve gap repairDigital nerve injuryDigital nerve reconstructionDigital nerve repair

Identifiers

PMID37700356
PMCPMC10496177
OpenAlexW4386639910

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.