Evidence map›Paper›PMID 42221281›Full record

ArticlePlastic and reconstructive surgery. Global open2026

Nerve Assessment Index: A New Rating Tool for Peripheral Nerve Coaptations in Sharp Nerve Transections.

Vincent G J Guillaume, Tim Leypold, Leonie Scheve, Justus P Beier, Benedikt Schäfer

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Vincent G J GuillaumeFrom the Department of Plastic Surgery, Hand - and Burn Surgery, University Hospital RWTH Aachen, Aachen, Germany.
Tim LeypoldFrom the Department of Plastic Surgery, Hand - and Burn Surgery, University Hospital RWTH Aachen, Aachen, Germany.
Leonie ScheveFrom the Department of Plastic Surgery, Hand - and Burn Surgery, University Hospital RWTH Aachen, Aachen, Germany.
Justus P BeierFrom the Department of Plastic Surgery, Hand - and Burn Surgery, University Hospital RWTH Aachen, Aachen, Germany.
Benedikt SchäferFrom the Department of Plastic Surgery, Hand - and Burn Surgery, University Hospital RWTH Aachen, Aachen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peripheral nerve injuries represent a significant clinical challenge, often resulting in long-term sensory and motor deficits, disability, and reduced quality of life. Despite advances in microsurgical techniques and regenerative medicine, the functional outcomes following nerve repair remain highly variable and unpredictable. One critical factor influencing success is the quality of the initial nerve coaptation. Currently, there is no standardized, objective tool for assessing the quality of nerve coaptation during surgery. This lack of uniform assessment criteria hinders meaningful comparison between surgical techniques and limits the reproducibility of experimental and clinical studies. To address this gap, we proposed the development of a novel rating system-the "Nerve Assessment Index"-designed to evaluate the anatomical and morphological quality of nerve coaptation. By providing a structured, reproducible framework for scoring nerve repairs, the Nerve Assessment Index aims to harmonize reporting standards in both clinical and preclinical settings, improve intraoperative decision-making, and facilitate more robust comparisons across studies. Ultimately, this tool may promote more consistency, transparency, and higher quality evidence in peripheral nerve surgery.

Identifiers

PMID42221281
PMCPMC13218756

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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.