Evidence map›Paper›PMID 35821887›Full record

ArticleContrast media & molecular imaging2022

Manifestation of Urinary Tract Injury during Cervical Cancer Surgery Based on CT Urography Secretion Phase Images.

Song Lin, Xiaoshan Li, Yan Zhang, Xiaowen Mao, Xingchi Liang, Shigang Cheng, Lingli Zhang

Abstract read
In one paragraph

Article in Contrast media & molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Song LinDepartment of Surgery, Maternal and Child Health Hospital of Hubei Province, Wuhan 430070, Hubei, China.
Xiaoshan LiDepartment of Urology, Yangtze River Shipping General Hospital, Wuhan 430014, Hubei, China.
Yan ZhangDepartment of Women's Health, Maternal and Child Health Hospital of Hubei Province, Wuhan 430070, Hubei, China.
Xiaowen MaoDepartment of Surgery, Maternal and Child Health Hospital of Hubei Province, Wuhan 430070, Hubei, China.
Xingchi LiangDepartment of Surgery, Maternal and Child Health Hospital of Hubei Province, Wuhan 430070, Hubei, China.
Shigang ChengDepartment of Surgery, Maternal and Child Health Hospital of Hubei Province, Wuhan 430070, Hubei, China.
Lingli ZhangDepartment of Gynecology, Maternal and Child Health Hospital of Hubei Province, Wuhan 430070, Hubei, China.ORCID 0000-0001-9426-8101

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Methods: We grouped the patients who had undergone cervical cancer surgery in a hospital in this article and compared the nanodrug carrier system under CT imaging with traditional laparoscopy. The postoperative physical parameters of surgical patients are collected from cervical cancer patients of different degrees, and the parameters and prognostic health of patients after different operations are compared. Results: The results of the study show that the postoperative patient's body parameters of the nanodrug delivery system under the CT imaging technology used in this article are better than those of the traditional surgery group, and the average intraoperative blood loss is about 20% less than that of the traditional surgery. Postoperative complications occur. The situation is even lower, more than 30% lower than traditional surgery. Conclusion: This shows that the operation of the nanodrug delivery system based on CT imaging technology has broken through some of the limitations of the development of laparoscopic technology and has played an important role in the surgical treatment of cervical cancer.

Indexed as

LaparoscopyUrinary TractUterine Cervical NeoplasmsFemaleHumansTomography, X-Ray ComputedUrography

Identifiers

PMID35821887
PMCPMC9217568

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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.