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Clinical Assessment of Pain and Sensory Function in Peripheral Nerve Injury and Recovery: A Systematic Review of Literature
Abstract Peripheral nerve injuries (PNIs) often present with variable symptoms, making them difficult to diagnose, treat, and monitor. When neurologic compromise is inadequately assessed, suboptimal treatment decisions can result in lasting functional deficits. There are many available tools for eva...
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Published in: | Archives of plastic surgery 2022, 49(3), , pp.427-439 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Abstract
Peripheral nerve injuries (PNIs) often present with variable symptoms, making them difficult to diagnose, treat, and monitor. When neurologic compromise is inadequately assessed, suboptimal treatment decisions can result in lasting functional deficits. There are many available tools for evaluating pain and functional status of peripheral nerves. However, the literature lacks a detailed, comprehensive view of the data comparing the clinical utility of these modalities, and there is no consensus on the optimal algorithm for sensory and pain assessment in PNIs. We performed a systematic review of the literature focused on clinical data, evaluating pain and sensory assessment methods in peripheral nerves. We searched through multiple databases, including PubMed/Medline, Embase, and Google Scholar, to identify studies that assessed assessment tools and explored their advantages and disadvantages. A total of 66 studies were selected that assessed various tools used to assess patient's pain and sensory recovery after a PNI. This review may serve as a guide to select the most appropriate assessment tools for monitoring nerve pain and/or sensory function both pre- and postoperatively. As the surgeons work to improve treatments for PNI and dysfunction, identifying the most appropriate existing measures of success and future directions for improved algorithms could lead to improved patient outcomes. |
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ISSN: | 2234-6163 2234-6171 |
DOI: | 10.1055/s-0042-1748658 |