Evidence map›Paper›PMID 41246715›Full record

ArticleCureus2025

The Effect of Diabetic Neuropathy on Recurrent Laryngeal Nerve Monitoring During Thyroid Surgery.

Eustratios Kofopoulos-Lymperis, Dimitrios Papakonstantinou, Konstantinos Chaidas, Alexander Delides, Matthew Stamelos, Danae Kakabakou, Emmanouil Pikoulis, Evangelos Missiakos, Melpomeni Peppa, Konstantinos Nastos

Abstract read
In one paragraph

Article in Cureus, 2025. 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

10 authors.

Eustratios Kofopoulos-LymperisThird Department of Surgery, "Attikon" University General Hospital/National and Kapodistrian University of Athens, School of Medicine, Athens, GRC.
Dimitrios PapakonstantinouThird Department of Surgery, "Attikon" University General Hospital/National and Kapodistrian University of Athens, School of Medicine, Athens, GRC.
Konstantinos ChaidasDepartment of Ear, Nose, and Throat, University Hospital of Alexandroupolis, Democritus University of Thrace, School of Medicine, Alexandroupolis, GRC.
Alexander DelidesSecond Department of Otolaryngology, "Attikon" University General Hospital/National and Kapodistrian University of Athens, School of Medicine, Athens, GRC.
Matthew StamelosDepartment of Surgery, Evgenidion Hospital, Athens, GRC.
Danae KakabakouDepartment of Surgery, Evgenidion Hospital, Athens, GRC.
Emmanouil PikoulisThird Department of Surgery, "Attikon" University General Hospital/National and Kapodistrian University of Athens, School of Medicine, Athens, GRC.
Evangelos MissiakosThird Department of Surgery, "Attikon" University General Hospital/National and Kapodistrian University of Athens, School of Medicine, Athens, GRC.
Melpomeni PeppaSecond Department of Propaedeutic Internal Medicine, "Attikon" University General Hospital/National and Kapodistrian University of Athens, School of Medicine, Athens, GRC.
Konstantinos NastosThird Department of Surgery, "Attikon" University General Hospital/National and Kapodistrian University of Athens, School of Medicine, Athens, GRC.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecurrent laryngeal nerve (RLN) injury remains a significant complication of thyroid surgery, potentially leading to vocal cord paresis and compromised quality of life. Intraoperative nerve monitoring (IONM) enables real-time assessment of RLN function but may be affected by underlying neuropathies. Diabetes mellitus (DM) induces peripheral nerve damage, potentially altering RLN electrophysiology during surgery. This study investigates the impact of DM on RLN amplitude and latency during thyroidectomy.

methodsWe prospectively analyzed 245 patients (485 RLNs at risk) who underwent thyroidectomy with IONM between 2020 and 2024. Patients were classified as diabetic or non-diabetic according to American Diabetes Association (ADA) criteria. Standardized surgical and anesthetic protocols were followed. RLN amplitude and latency were measured before and after dissection using consistent stimulation parameters, and group comparisons were performed using non-parametric tests.

resultsThirty-four patients (13.9%) had diabetes, representing a more aged cohort with a higher prevalence of comorbidities than non-diabetic patients. Pre-dissection RLN amplitude and latency did not differ significantly between groups (0.72 mV vs. 0.74 mV, p = 0.87; 2.2 ms vs. 1.9 ms, p = 0.11, respectively). After dissection, diabetic patients showed a significantly greater reduction in RLN amplitude (median 0.58 mV vs. 0.77 mV in non-diabetics, p = 0.01), whereas latency remained comparable (p = 0.92). Within-group analysis confirmed a significant amplitude drop among diabetics (p = 0.008) but not among non-diabetics. Temporary unilateral vocal fold palsy occurred in three patients (one diabetic, two non-diabetic), all resolving within two weeks.

conclusionsDiabetic patients demonstrated greater RLN amplitude reduction during thyroidectomy, suggesting impaired neural resilience to surgical manipulation. However, these electrophysiological changes had minimal short-term clinical impact when nerve integrity was preserved. Awareness of this subclinical vulnerability may guide intraoperative decision-making within the context of neuroprotective strategies that involve IONM during thyroidectomy.

Indexed as

amplitudeintraoperative neuromonitoring (ionm)latencyrecurrent laryngeal nerve (rln)thyroid surgerytypes 2 diabetes

Identifiers

PMID41246715
PMCPMC12616193

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.