Evidence map›Paper›PMID 42005189›Full record

ArticleCureus2026

Electrodiagnostic Findings in COVID-19 ICU Survivors.

Daniel A Hu, Benjamin Abramoff, Timothy R Dillingham

Abstract read
In one paragraph

Article in Cureus, 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

3 authors.

Daniel A HuPhysical Medicine and Rehabilitation, University of Pennsylvania, Philadelphia, USA.
Benjamin AbramoffPhysical Medicine and Rehabilitation, University of Pennsylvania, Philadelphia, USA.
Timothy R DillinghamPhysical Medicine and Rehabilitation, University of Pennsylvania, Philadelphia, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background The long-term effects of COVID-19 on the peripheral nervous system remain incompletely understood. The objective of this study is to characterize electrodiagnostic findings in COVID-19 survivors who required intensive care admissions resulting in persistent weakness and marked functional impairments. Methodology A retrospective chart review was conducted on patients who were referred for electrodiagnostic testing between May 2020 and May 2021 and had persistent weakness. This cohort consisted of nine patients: seven males and two females, between 31 and 75 years old. Results Nerve conduction studies revealed absent sensory responses in at least one sampled nerve in all patients and absent motor responses in at least one sampled nerve in seven patients. Electromyography in all nine patients demonstrated neuropathic denervation, evidenced by varying degrees of fibrillation potentials and positive sharp waves, as well as long-duration, polyphasic motor units and reduced, neuropathic recruitment. None of the patients had electromyographic evidence of myopathy. Conclusions Overall, the electrodiagnostic findings are most consistent with a distal mixed sensorimotor axonal polyneuropathy as the primary pathological process underlying persistent weakness in this cohort. This pattern is consistent with critical illness polyneuropathy and may represent a form of peripheral nerve injury related to severe COVID-19 infection. Further research is needed to better characterize the long-term outcomes and underlying peripheral nerve pathophysiology of COVID-19-associated critical illness polyneuropathy. This may provide important insights into prevention and treatment strategies.

Indexed as

covid-19electrodiagnostic findingsneurophysiologyphysical medicine and rehabilitationsensorimotor polyneuropathy

Identifiers

PMID42005189
PMCPMC13089981

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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.