Evidence map›Paper›PMID 34234746›Full record

SynthesisFrontiers in endocrinology2021

The Accuracy of Near Infrared Autofluorescence in Identifying Parathyroid Gland During Thyroid and Parathyroid Surgery: A Meta-Analysis.

Bin Wang, Chun-Rong Zhu, Hong Liu, Xin-Min Yao, Jian Wu

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Frontiers in endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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  18. The current status and future prospects for molecular imaging-guided precision surgery.Cancer imaging : the official publication of the International Cancer Imaging Society · 2022
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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

5 authors.

Bin WangDepartment of Thyroid and Breast Surgery, Chengdu Third People's Hospital, Chengdu, China.
Chun-Rong ZhuDepartment of Chemistry, School of Basic Medical Science, North Sichuan Medical College, Nanchong, China.
Hong LiuDepartment of Thyroid and Breast Surgery, Chengdu Third People's Hospital, Chengdu, China.
Xin-Min YaoDepartment of Thyroid and Breast Surgery, Chengdu Third People's Hospital, Chengdu, China.
Jian WuDepartment of Thyroid and Breast Surgery, Chengdu Third People's Hospital, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: We aim to assess the accuracy of near infrared autofluorescence in identifying parathyroid gland during thyroid and parathyroid surgery. Method: A systematic literature search was conducted by using PubMed, Embase, and the Cochrane Library electronic databases for studies that were published up to February 2021. The reference lists of the retrieved articles were also reviewed. Two authors independently assessed the methodological quality and extracted the data. A random-effects model was used to calculate the combined variable. Publication bias in these studies was evaluated with the Deeks' funnel plots. Result: A total of 24 studies involving 2,062 patients and 6,680 specimens were included for the meta-analysis. The overall combined sensitivity and specificity, and the area under curve of near infrared autofluorescence were 0.96, 0.96, and 0.99, respectively. Significant heterogeneities were presented (Sen: I Conclusion: Near infrared autofluorescence is an excellent indicator for identifying parathyroid gland during thyroid and parathyroid surgery.

Indexed as

AnimalsHumansOptical ImagingParathyroidectomyParathyroid GlandsParathyroid NeoplasmsSpectroscopy, Near-InfraredThyroidectomyThyroid Neoplasmsautofluorescencemeta-analysisnear infraredparathyroid glandsurgery

Identifiers

PMID34234746
PMCPMC8255791

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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.