Evidence map›Paper›PMID 34659683›Full record

ArticleJournal of healthcare engineering2021

Computed Tomography Image under Three-Dimensional Reconstruction Algorithm Based in Diagnosis of Renal Tumors and Retroperitoneal Laparoscopic Partial Nephrectomy.

Haijie Zhang, Fu Yin, Liyang Yang, Anqi Qi, Weiwei Cui, Shanshan Yang, Ge Wen

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

7 authors at 2 institutions in 1 country.

Haijie ZhangDepartment of Imaging, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.ORCID 0000-0003-3398-8409
Fu YinSchool of Information Engineering, Shenzhen University, Shenzhen 518000, China.ORCID 0000-0003-1631-4509
Liyang YangDepartment of Imaging, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.ORCID 0000-0002-5548-6939
Anqi QiDepartment of Imaging, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.ORCID 0000-0003-0424-9404
Weiwei CuiDepartment of Imaging, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.ORCID 0000-0002-4446-1963
Shanshan YangDepartment of Imaging, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.ORCID 0000-0002-1939-755X
Ge WenDepartment of Imaging, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.ORCID 0000-0002-7717-0142
Nanfang Hospital · CNShenzhen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was to explore the clinical application value of computed tomography (CT) images based on a three-dimensional (3D) reconstruction algorithm for laparoscopic partial nephrectomy (LPN) in patients with renal tumors. 30 cases of renal cell carcinoma (RCC) patients admitted to the hospital were selected as the research objects and were rolled into two groups using a random table method. The patients who received PLN under the three-dimensional reconstruction and laparoscopic technique were included in the experimental group (group A), and the patients who received LPN using CT images only were included in the control group (group B). In addition, the treatment results of the two groups of patients were compared and analyzed.

Indexed as

Kidney NeoplasmsLaparoscopyAlgorithmsHumansImaging, Three-DimensionalNephrectomyRetrospective StudiesTomography, X-Ray ComputedTreatment Outcome

Identifiers

PMID34659683
PMCPMC8514888
OpenAlexW3203196108

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.