Evidence map›Paper›PMID 33123196›Full record

ArticleInternational journal of endocrinology2020

Value of CT Features in the Diagnosis of Papillary Thyroid Tumors in Incidental Thyroid Nodules.

Fengyan Zhang, Ying Qiao, Hui Zhang

Abstract read
In one paragraph

Article in International journal of endocrinology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. 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

3 authors.

Fengyan ZhangDepartment of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China.
Ying QiaoDepartment of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China.ORCID https://orcid.org/0000-0001-9275-0113
Hui ZhangCollege of Medical Imaging, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China.ORCID https://orcid.org/0000-0002-0565-0411

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present work has investigated the value of computed tomography (CT) features in the diagnosis of papillary thyroid tumors in the incidental thyroid nodules (ITNs). In the 82 enrolled patients, 101 thyroid nodules were incidentally found by the neck CT scanning, among which 49 were histologically confirmed to be papillary thyroid carcinoma (PTC) while the other 52 were nodular goiter (NG). The tumor location, size, shape, tiny calcification, cystic change, and signs of an irregular ring, marginal defects, and enhanced blurring were all depicted by CT features. Both univariate and multivariate analyses were employed to identify independent predictors of PTC. The univariate analysis of PTC and NG showed that four CT features were statistically significant, including tiny calcification and signs of an irregular ring, marginal defects, and enhanced blurring. Furthermore, the multivariate logistic regression model indicated that signs of an irregular ring, marginal defects, and enhanced blurring were strongly correlated with PTC, of which the odds ratio (OR) was 27.374 (95% CI: 5.871∼127.636), 28.587 (95% CI: 4.139∼197.460), and 4.315 (95% CI: 0.858∼21.694), respectively. In the predictive model of PTC, the value of sensitivity, specificity, accuracy, and Youden index was 87.8%, 94.2%, 91.1%, and 0.82 with a likelihood ratio of 15.1. Therefore, the signs of an irregular ring, marginal defects, and enhanced blurring may be helpful in the diagnosis of PTC in incidentally found thyroid nodules.

Identifiers

PMID33123196
PMCPMC7585655

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.