Evidence map›Paper›PMID 37332059›Full record

ArticleWorld journal of urology2023

A three-dimensional renal tumor anatomy and intrarenal relationship nephrometry (ADDD) for robot-assisted partial nephrectomy : 3D-CT based nephrometry for RAPN.

Xinfei Li, Dapeng Wu, Xuepei Zhang, Xiang Wang, Yangyang Xu, Shubo Fan, Zhihua Li, Kunlin Yang, Xiaoteng Yu, Zhongyuan Zhang and 7 more

Abstract read
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In one paragraph

Article in World journal of urology, 2023. 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
1.6field-weighted citation impact, top 16% 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, 6 citations in OpenAlex.

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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

17 authors at 4 institutions in 1 country.

Xinfei Li *Department of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.ORCID http://orcid.org/0000-0002-4201-2443
Dapeng Wu *Department of Urology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
Xuepei Zhang *Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Xiang WangDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Yangyang XuDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Shubo FanDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Zhihua LiDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Kunlin YangDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Xiaoteng YuDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Zhongyuan ZhangDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Lin CaiDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Zheng ZhangDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Cheng ShenDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.
Jin TaoDepartment of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Hailong HuDepartment of Urology, The Second Affiliated Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Hexi District, Tianjin, 300211, China. hhllove2004@163.com.
Liqun ZhouDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China. zhoulqmail@sina.com.
Xuesong LiDepartment of Urology, Peking University First Hospital, National Urological Cancer Center, Institute of Urology, Peking University, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China. pineneedle@sina.com.
Peking University · CNFirst Affiliated Hospital of Zhengzhou University · CNFirst Affiliated Hospital of Xi'an Jiaotong University · CNSecond Hospital of Tianjin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a 3D scoring system of tumor anatomy and intrarenal relationship for assessing surgical complexity and outcomes of robot-assisted partial nephrectomy (RAPN).

methodsWe prospectively enrolled patients with a renal tumor who had a 3D model and underwent RAPN between Mar 2019 and Mar 2022. The ADDD nephrometry consisted of the contact surface area between tumor and parenchyma (A), the depth of tumor invasion into the renal parenchyma (D

resultsWe enrolled a total of 301 patients. The mean tumor size was 2.93 ± 1.44 cm. There were 104 (34.6%) patients, 119 (39.5%) patients, and 78 (25.9%) patients in the low-, intermediate-, and high-risk groups, respectively. Each point increase in the ADDD score increased the risk of complications [hazard ratio (HR) 1.501]. A lower grade indicated a lower risk of failed trifecta (HR low group 15.103, intermediate group 9.258) and renal function damage (HR low risk 8.320, intermediate risk 3.165) compared to the high-risk group. The AUC of ADDD score and grade were 0.738 and 0.645 for predicting major complications, 0.766 and 0.714 for predicting trifecta outcome, and 0.746 and 0.730 for predicting postoperative renal function reservation.

conclusionThe 3D-ADDD scoring system shows the tumor anatomy and its intraparenchymal relationships and has better efficacy in predicting surgical outcomes of RAPN.

Indexed as

Kidney NeoplasmsRoboticsRobotic Surgical ProceduresHumansNephrectomyPostoperative ComplicationsRetrospective StudiesTomography, X-Ray ComputedTreatment OutcomeNephron sparing surgeryPartial nephrectomyRenal tumorRobotic surgeryVirtual model

Identifiers

PMID37332059
OpenAlexW4381105006

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.