Evidence map›Paper›PMID 40134500›Full record

ArticleAnnals of surgery open : perspectives of surgical history, education, and clinical approaches2025

Regenerative Peripheral Nerve Interface Surgery to Treat Chronic Postamputation Pain: A Prospective Study in Major Lower Limb Amputation Patients.

Jennifer C Lee, Carrie A Kubiak, Christine S W Best, Jennifer B Hamill, Jamie Ki, Hyungjin Myra Kim, Randy S Roth, Jeffrey H Kozlow, Melissa J Tinney, Michael E Geisser and 3 more

Registry-linked trialAbstract read
In one paragraph

Article in Annals of surgery open : perspectives of surgical history, education, and clinical approaches, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07285486 (Regenerative Peripheral Nerve Interfaces for the Treatment of Painful Neuromas in Major Limb Amputees), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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.

NCT07285486 completednot on this map

Regenerative Peripheral Nerve Interfaces for the Treatment of Painful Neuromas in Major Limb Amputees

TypeobservationalSponsorUniversity of MichiganRan2017 to 2023Enrolled132ConditionsAmputation NeuromaArmsAmputation with Regenerative Peripheral Nerve Interfaces (RPNI), Amputation Without RPNI
3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

13 authors.

Jennifer C LeeFrom the Department of Surgery, Section of Plastic Surgery, Michigan Medicine, Ann Arbor, MI.
Carrie A KubiakFrom the Department of Surgery, Section of Plastic Surgery, Michigan Medicine, Ann Arbor, MI.
Christine S W BestFrom the Department of Surgery, Section of Plastic Surgery, Michigan Medicine, Ann Arbor, MI.
Jennifer B HamillFrom the Department of Surgery, Section of Plastic Surgery, Michigan Medicine, Ann Arbor, MI.
Jamie KiConsulting for Statistics, Computing & Analytics Research, University of Michigan, Ann Arbor, MI.
Hyungjin Myra KimConsulting for Statistics, Computing & Analytics Research, University of Michigan, Ann Arbor, MI.
Randy S RothDepartment of Physical Medicine and Rehabilitation, Michigan Medicine, Ann Arbor, MI.
Jeffrey H KozlowFrom the Department of Surgery, Section of Plastic Surgery, Michigan Medicine, Ann Arbor, MI.
Melissa J TinneyDepartment of Physical Medicine and Rehabilitation, Michigan Medicine, Ann Arbor, MI.
Michael E GeisserDepartment of Physical Medicine and Rehabilitation, Michigan Medicine, Ann Arbor, MI.
Paul S CedernaFrom the Department of Surgery, Section of Plastic Surgery, Michigan Medicine, Ann Arbor, MI.
Stephen W P KempFrom the Department of Surgery, Section of Plastic Surgery, Michigan Medicine, Ann Arbor, MI.
Theodore A KungFrom the Department of Surgery, Section of Plastic Surgery, Michigan Medicine, Ann Arbor, MI.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The objective was to assess the postsurgical outcomes of regenerative peripheral nerve interface (RPNI) surgery in a prospective cohort of major lower extremity amputation patients with chronic postamputation pain. Background: Chronic pain in lower limb amputation patients is commonly the result of neuroma formation after traumatic peripheral nerve injury. By implanting more proximal transected nerve ends into autologous free muscle grafts, RPNI surgery can treat postamputation pain by diminishing the development of neuromas. RPNI surgery in prior retrospective studies has been shown to mitigate postamputation pain. Methods: Twenty-two lower limb amputation patients with established chronic postamputation pain were recruited from 2 studies in this prospective study. All patients underwent RPNI surgery to treat identified symptomatic neuromas within the residual limb. Patient-reported outcome instruments were administered preoperatively and postoperatively at 1 week, 4 months, and 12 months to examine residual limb pain (McGill Pain Questionnaire, PROMIS Pain Intensity, and PROMIS Pain Interference), phantom limb pain (modified PROMIS Pain Intensity and Phantom Limb sensation questionnaire), psychosocial status (PHQ-9, GAD-7, and PCS), and functional (OPUS) outcomes. Results: RPNI surgery significantly improved residual limb pain. While phantom limb sensation improved significantly, phantom limb pain demonstrated a modest decrease. Psychosocial outcomes also improved significantly after RPNI surgery. Prosthetic use slightly increased, and patients did not experience loss of function. Conclusions: RPNI surgery leverages the processes of reinnervation to successfully treat residual limb pain and improve psychosocial outcomes in patients with chronic postamputation pain. Phantom limb pain may be more difficult to treat in chronic pain patients who have central sensitization at the time of surgery.

Identifiers

PMID40134500
PMCPMC11932616

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Registered trials

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.