Evidence map›Paper›PMID 40668552›Full record

Trial reportJAMA surgery2025

Near-Infrared Autofluorescence for Parathyroid Detection During Endocrine Neck Surgery: A Randomized Clinical Trial.

Alexandria G Cousart, Colleen M Kiernan, Parker A Willmon, Giju Thomas, Tracy S Wang, Paul G Gauger, Quan-Yang Duh, Hunter J Underwood, Anee Jackson, Anuradha Patel and 2 more

6 registry-linked trialsAbstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in JAMA surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 6 registered trials, which are not on this map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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.

NCT04281875 nacompletednot on this map

Assessing Benefits of Near Infrared Autofluorescence (NIRAF) Detection for Identifying Parathyroid Glands During Total Thyroidectomy.

TypeinterventionalSponsorVanderbilt-Ingram Cancer CenterRan2020 to 2024Enrolled160ConditionsPostoperative Hypoparathyroidism, Thyroid Neoplasms, Thyroid CancerArmsNIRAF Detection Technology
NCT04299425 nacompletednot on this map

Evaluating Impact of Near Infrared Autofluorescence (NIRAF) Detection for Identifying Parathyroid Glands During Parathyroidectomy

TypeinterventionalSponsorVanderbilt-Ingram Cancer CenterRan2020 to 2023Enrolled160ConditionsParathyroid Adenoma, Parathyroid Neoplasms, Parathyroid Hyperplasia, Parathyroid CancerArmsNIRAF Detection Technology
NCT05022641 nacompletednot on this map

Evaluating Impact of Near Infrared Autofluorescence (NIRAF) Detection for Identifying Parathyroid Glands During Parathyroidectomy

TypeinterventionalSponsorUniversity of MichiganRan2021 to 2024Enrolled160ConditionsParathyroid Adenoma, Parathyroid Neoplasms, Parathyroid Cancer, HypercalcemiaArmsPTeye, Standard of Care
NCT05022667 nacompletednot on this map

Assessing Benefits of Near Infrared Autofluorescence (NIRAF) Detection for Identifying Parathyroid Glands During Total Thyroidectomy

TypeinterventionalSponsorUniversity of MichiganRan2021 to 2024Enrolled114ConditionsThyroid Neoplasms, Thyroid Diseases, Hypoparathyroidism, Endocrine System DiseasesArmsPTeye
NCT05152927 nacompletednot on this map

Evaluating Impact of Near Infrared Autofluorescence (NIRAF) Detection for Identifying Parathyroid Glands During Parathyroidectomy

TypeinterventionalSponsorUniversity of California, San FranciscoRan2022 to 2024Enrolled79ConditionsParathyroid Diseases, Parathyroid Dysfunction, Parathyroid Neoplasms, Parathyroid AdenomaArmsParathyroid Eye (PTeye)
NCT05579782 nacompletednot on this map

Assessing Benefits of NIRAF Detection for Identifying Parathyroid Glands During Total Thyroidectomy

TypeinterventionalSponsorMedical College of WisconsinRan2022 to 2024Enrolled80ConditionsPostoperative Hypoparathyroidism, Thyroid Disease, Thyroid Neoplasms, Thyroid CancerArmsNIRAF Detection Technology
3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Alexandria G CousartVanderbilt Biophotonics Center, Vanderbilt University, Nashville, Tennessee.
Colleen M KiernanDepartment of Surgery, Vanderbilt University Medical Center, Nashville, Tennessee.
Parker A WillmonVanderbilt Biophotonics Center, Vanderbilt University, Nashville, Tennessee.
Giju ThomasVanderbilt Biophotonics Center, Vanderbilt University, Nashville, Tennessee.
Tracy S WangDepartment of Surgery, Medical College of Wisconsin, Milwaukee.
Paul G GaugerDepartment of Surgery, University of Michigan, Ann Arbor.
Quan-Yang DuhDepartment of Surgery, University of California, San Francisco.
Hunter J UnderwoodDepartment of Surgery, University of Michigan, Ann Arbor.
Anee JacksonDepartment of Surgery, University of Michigan, Ann Arbor.
Anuradha PatelDepartment of Surgery, Vanderbilt University Medical Center, Nashville, Tennessee.
Anita Mahadevan-JansenVanderbilt Biophotonics Center, Vanderbilt University, Nashville, Tennessee.
Carmen C SolórzanoDepartment of Surgery, Vanderbilt University Medical Center, Nashville, Tennessee.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Inadvertent removal and damage to parathyroid glands (PGs) can lead to hypoparathyroidism, making it crucial to accurately identify and preserve these glands during parathyroidectomy and thyroidectomy. Objective: To assess if fiber-based near-infrared autofluorescence (NIRAF) increases the number of intraoperatively identified PGs and reduces the occurrence of hypoparathyroidism. Design, Setting, and Participants: This multicenter randomized clinical trial with a 6-month follow-up was conducted between March 2020 and July 2024. It included 4 medical centers across the US, 4 senior (more than 10 years of experience) and 3 junior (less than 5 years of experience) surgeons. A total of 754 patients were enrolled and 752 were randomized, including 398 patients (2 withdrew) who underwent parathyroidectomy and 354 patients who had total/completion thyroidectomy. Data were analyzed from March 2020 to January 2025. Interventions: Use of fiber-based NIRAF during thyroidectomy and parathyroidectomy. Main Outcomes and Measures: The primary outcome was the mean number of PGs identified intraoperatively. The secondary outcome was the rate of hypoparathyroidism (transient and at last follow-up). Results: Of 752 patients randomized, 712 were analyzed for the primary outcome (94.4%) (overall median [IQR] age, 59 [25] years; 516 females [68.4%]). A total of 161 underwent parathyroidectomy with NIRAF, while 159 had conventional surgery. Additionally, 176 underwent thyroidectomy using NIRAF and 178 had traditional surgery. The mean number of PGs identified during parathyroidectomy was not significantly higher when using NIRAF for focused procedures (mean, NIRAF, 1.6; 95% CI, 1.4-1.8 vs control, 1.5; 95% CI, 1.4-1.7). During bilateral explorations, the surgeons improved in the mean number of PGs identified when using NIRAF (mean NIRAF, 3.5; 95% CI, 3.4-3.7 vs control, 3.2; 95% CI, 3.0-3.4; P < .001). During thyroidectomy, the mean number of PGs identified increased when using NIRAF (mean NIRAF, 3.3; 95% CI, 3.2-3.4 vs control, 2.8; 95% CI, 2.7-3.0; P < .001). There was no significant difference in hypoparathyroidism after thyroidectomy, either transient (NIRAF: 48 of 173 patients [27.8%]; control: 44 of 169 patients [26%]) or at the last follow-up (NIRAF: 3 of 176 patients [1.7%]; control: 6 of 176 patients [3.4%]). Conclusions and Relevance: Fiber-based NIRAF can increase the number of PGs identified during thyroidectomy and bilateral exploration parathyroidectomy without increasing the duration of the surgery. Trial Registration: ClinicalTrials.gov Identifiers: NCT05579782, NCT05022667, NCT05022641, NCT04281875, NCT04299425, NCT05152927.

Indexed as

HypoparathyroidismIntraoperative ComplicationsOptical ImagingParathyroidectomyParathyroid GlandsThyroidectomyAdultAgedFemaleHumansMaleMiddle Aged

Identifiers

PMID40668552
PMCPMC12268529

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.