Evidence map›Paper›PMID 38250208›Full record

ArticlePlastic and reconstructive surgery. Global open2024

TMR for Peripheral Sensory Nerve Neuroma around the Wrist Utilizing the Distal Anterior Interosseous Nerve.

Mohammed Muneer

Open access · goldAbstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Algorithm for Surgical Management of Symptomatic Hand and Digital Neuromas.Plastic and reconstructive surgery. Global open · 2026
    Article
  2. Article
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

1 author at 1 institution in 1 country.

Mohammed MuneerFrom the Plastic Surgery Department, Hamad Medical Corporation, Doha, Qatar.
Creative Commons · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Injury to the peripheral sensory nerves of the hand and wrist is common and can lead to debilitating neuromas and significantly impair patients' quality of life. Target-muscle reinnervation (TMR) is a novel method for treating neuromas that can result in significant clinical improvement. However, TMR for the peripheral sensory nerves in the hand and wrist is restricted by the limited options for motor branches. The adaptability of the anterior interosseous nerve (AIN) as a target for TMR treating peripheral sensory neuroma has not been thoroughly investigated or implemented therapeutically. This study aimed to evaluate the use of AIN as a viable recipient of TMR for treating peripheral sensory neuromas around the wrist. In this retrospective study, eight patients were included over 18 months from June 2021 to January 2023 at Hamad Medical Corporation. The average follow-up time after TMR was 13 months. The peripheral sensory nerves involved were the radial sensory nerve in five cases, the palmar cutaneous branch of the median nerve in one case, and the median nerve in one case. The preoperative average VAS pain score was 7 of 10 compared with the postoperative pain score of 2 of 10. In conclusion, the AIN can be used as a first-choice motor target for all peripheral sensory neuromas around the wrist for the following reasons: first, it can be reached by the peripheral sensory nerves around the wrist; second, the pronator quadratus muscle is expandable; and third, the AIN can be taken with a long proximal tail for flexible coaptation with the peripheral sensory nerves.

Identifiers

PMID38250208
PMCPMC10798704
OpenAlexW4391025588

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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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.