Evidence map›Paper›PMID 35607302›Full record

ArticleBioMed research international2022

Correlation Analysis of Nodular Sonographic Parameters with Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma.

Liuhua Zhou, Qiaodan Zhu, Jincao Yao, Chen Yang, Dong Xu

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 42% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 2 institutions in 1 country.

Liuhua ZhouZhejiang Chinese Medical University, Hangzhou, China.ORCID https://orcid.org/0000-0002-8276-3946
Qiaodan ZhuThe 2nd Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, China.
Jincao YaoCancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Chen YangCancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.ORCID https://orcid.org/0000-0002-9043-144X
Dong XuCancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.ORCID https://orcid.org/0000-0002-0583-240X
Chinese Academy of Sciences · CNZhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Papillary thyroid carcinoma (PTC) is the most common thyroid carcinoma and is prone to cervical lymph node metastases (CLNM). We aim to analyze the correlation between clinical information, ultrasonic parameters of PTC, and CLNM. Methods: 1335 patients who had pathologically confirmed unifocal PTC were enrolled in this retrospective cohort study. Univariate and multivariate logistic analyses were performed to predict CLNM in PTC patients. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance. Results: Univariate analysis showed that gender, age, maximum tumor diameter and volume, and cross-sectional and longitudinal aspect ratio were related to CLNM ( Conclusions: Younger age, male, and larger tumor were high risk factors for CLNM in patients with unifocal PTC. The cross-sectional aspect ratio had a more effective predictive value for CLNM in patients with larger thyroid tumors.

Indexed as

Thyroid NeoplasmsCross-Sectional StudiesHumansLymphatic MetastasisLymph NodesMaleRetrospective StudiesRisk FactorsThyroid Cancer, Papillary

Identifiers

PMID35607302
PMCPMC9124110
OpenAlexW4280537523

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.