Evidence map›Paper›PMID 41969328›Full record

ArticleCurrent urology2026

Robot-assisted urological tumor surgery using the MP1000 system: A prospective, single-center, single-arm clinical study.

Mingxin Diao, Wenzhi Gao, Kunlin Yang, Yaming Gu, Zhihua Li, Xinfei Li, Zihui Gao, Xuesong Li, Zheng Zhang

Abstract read
In one paragraph

Article in Current urology, 2026. 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
–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

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

9 authors.

Mingxin DiaoDepartment of Urology, Peking University First Hospital, Miyun Hospital, Beijing, China.
Wenzhi GaoDepartment of Urology, Peking University First Hospital, Miyun Hospital, Beijing, China.ORCID https://orcid.org/0000-0002-5944-017X
Kunlin YangDepartment of Urology, Peking University First Hospital, Beijing, China.
Yaming GuDepartment of Urology, Peking University First Hospital, Miyun Hospital, Beijing, China.
Zhihua LiDepartment of Urology, Peking University First Hospital, Beijing, China.
Xinfei LiDepartment of Urology, Peking University First Hospital, Beijing, China.
Zihui GaoDepartment of Urology, Peking University First Hospital, Miyun Hospital, Beijing, China.
Xuesong LiDepartment of Urology, Peking University First Hospital, Beijing, China.
Zheng ZhangDepartment of Urology, Peking University First Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study is aimed to evaluate the safety and efficacy of the MP1000 robotic system in urological tumor surgery. Materials and methods: This prospective, single-center, single-arm clinical study evaluated data from urological tumor surgeries between June 2023 and December 2023. Patient demographics and perioperative outcomes were prospectively collected, and postoperative complications and success rates were analyzed. Ergonomics were assessed using the National Aeronautics and Space Administration Task Load Index. Results: A total of 28 patients underwent surgery during the study period. All procedures were successfully completed without conversion to standard laparoscopic or open surgery. All cases had negative surgical margins postoperatively, and no recurrences were observed within 3 months. The median glomerular filtration rate (GFR) at the third month after partial nephrectomy was 87.4 mL/min/1.73 m Conclusions: Based on our single-center experience, the MP1000 system demonstrated promising safety and efficacy in a variety of urological tumor surgeries.

Indexed as

EfficacyMP1000Robot-assisted surgerySafetyUrological tumors

Identifiers

PMID41969328
PMCPMC13068480

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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.