Evidence map›Paper›PMID 39524740›Full record

ArticleHeliyon2024

Three-dimensional visualization techniques improve surgical Decision Making of robotic-assisted partial nephrectomy.

Yuchao Wang, Qiliang Teng, Zhihong Dai, Chunyu Chen, Liren Zhang, Jiaxin Xie, Hao Wang, Zihan Xin, Sishan Chen, Yu Tai and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. 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
–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

2 citing papers in PubMed.

  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

13 authors.

Yuchao WangDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Qiliang TengDepartment of Urology, Pelvic Floor Disorders Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong Province, China.
Zhihong DaiDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Chunyu ChenDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Liren ZhangThe Third People's Hospital of Dalian, Dalian, 116011, Liaoning Province, China.
Jiaxin XieInstitute of Urology, Peking University, Beijing, 100034, Beijing, China.
Hao WangDepartment of Clinical Medicine, First Clinical School of Dalian Medical University, Dalian, 116044, Liaoning Province, China.
Zihan XinDepartment of Clinical Medicine, First Clinical School of Dalian Medical University, Dalian, 116044, Liaoning Province, China.
Sishan ChenDepartment of Anesthesia, Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Yu TaiDepartment of Anesthesia, Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Liang WangDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Bo FanDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Zhiyu LiuDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Complete preoperative comprehension of the adjacent structures of the kidney and location of renal vessels is essential for robot-assisted partial nephrectomy (RAPN). The effectiveness of three-dimensional (3D) visualization techniques in improving perioperative outcomes of RAPN has been inconsistent and has not been reported in Northeastern China. Methods: In this cohort study, we reviewed patients with renal tumours who underwent RAPN between April 2019 and April 2024. Three-dimensional visualization models were reconstructed to evaluate resectability parameters, including vascular variations, collection system infiltration, and lymphatic involvement. Subsequently, a meta-analysis combining previous studies utilising 3D visualization techniques for partial nephrectomy was conducted. Results: Of the 324 patients in the cohort, 147 were preoperatively evaluated using the 3D technology. Group 3D had significantly less estimated blood loss (P < 0.001) and a shorter operative time (P = 0.016) than in group No 3D. We also found that the rates of intraoperative ultrasound use (P = 0.015), intraoperative complications (P = 0.007), intraoperative transfusions (P = 0.007), and postoperative Clavien complications (P < 0.001) in group 3D were significantly lower than in group No 3D. The above findings were consistent in the subgroup with R.E.N.A.L. ≥ 8 points partly. Furthermore, a meta-analysis identified 11 studies that included 1522 patients who underwent RAPN. Use of 3D visualization technology resulted in decreased 55 % risk of opening the collecting system (Risk Ratio [RR] = 0.45[0.22-0.92], P = 0.030) and 79 % incidence of conversion to radical nephrectomy (RR = 0.21[0.08-0.57], P = 0.002). The RAPN group assisted by 3D visualization techniques showed an 81 % reduction in the risk of blood transfusion than in the control group (RR = 0.19[0.08-0.44], P < 0.001). Conclusions: The application of 3D technology in RAPN appears to be superior for improving precise tumour removal and reducing adverse perioperative outcomes and should be considered for wide use in clinical practice.

Indexed as

Cohort studiesKidney neoplasmsMeta-analysisNephrectomyThree-dimensional

Identifiers

PMID39524740
PMCPMC11550665

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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.