Evidence map›Paper›PMID 30681552›Full record

ArticleMedicine2019

The assessment of the accuracy of clinical preoperative lymph node.

Yongming Qiao, Ying Wang, Peng Kang, Rui Li, Yiming Liu, Wei He

Abstract read
In one paragraph

Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. A Novel Teaching-Learning Method of Utilizing Ultrasonography as a Tool to Enhance Clinical Examination Skills of House Surgeons in Evaluating Cervical Lymph Nodes.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2023
    Article
  5. 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

6 authors.

Yongming QiaoDepartment of Stomatology, The First Affiliated Hospital of Zhengzhou University.
Ying WangDepartment of Oral and Maxillofacial Surgery, Zhengzhou Stomatologic Hospital, China.
Peng KangDepartment of Stomatology, The First Affiliated Hospital of Zhengzhou University.
Rui LiDepartment of Stomatology, The First Affiliated Hospital of Zhengzhou University.
Yiming LiuDepartment of Stomatology, The First Affiliated Hospital of Zhengzhou University.
Wei HeDepartment of Stomatology, The First Affiliated Hospital of Zhengzhou University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of the present study is to assess the accuracy of clinical preoperative lymph node and to define the degree of relation between the clinical preoperative assessment and histopathological examination in patients with head and neck cancer and cN+.

methodsThis retrospective study was performed on 125 patients (85 males and 40 females) at the Department of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Zhengzhou University, between December 2012 and December 2014.

resultOf all the patients who underwent neck dissection, 37 were found with no neck metastasis. Positive or suspected lymph nodes were detected at computed tomography (CT) in 44 and detected at ultrasonogram diagnosis (USG) in 38 of 125 patients, and the necks were assessed as normal in 55 (44%) by both USG and CT.

conclusionFurther investigation is needed to evaluate the rates of overall survival and disease-free survival of these N0 patients with neck dissection.

Indexed as

AdultAgedAged, 80 and overFemaleHead and Neck NeoplasmsHumansLymphatic MetastasisLymph NodesMaleMiddle AgedNeck DissectionNeoplasm StagingRetrospective StudiesSensitivity and SpecificityTomography, X-Ray ComputedUltrasonography

Identifiers

PMID30681552
PMCPMC6358328

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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.