Evidence map›Paper›PMID 41366578›Full record

ArticleJournal of robotic surgery2025

Adverse events and device malfunctions in da Vinci robotic surgery: an analysis of MAUDE data from the recent decade.

Tsung-Yi Hsieh, Kuo-How Huang

Abstract read
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Article in Journal of robotic surgery, 2025. 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
–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

3 citing papers in PubMed.

  1. Article
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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

2 authors.

Tsung-Yi HsiehDepartment of Urology, National Taiwan University Hospital, 7 Chung-Shan South Road, Taipei, 10002, Taiwan.
Kuo-How HuangDepartment of Urology, National Taiwan University Hospital, 7 Chung-Shan South Road, Taipei, 10002, Taiwan. khhuang123@ntu.edu.tw.ORCID http://orcid.org/0000-0002-0989-0578

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The role of robotic surgery has expanded rapidly over the past decade. Although clinical outcomes of the widely adopted da Vinci surgical systems are well reported, large-scale evaluations of adverse events and device safety remain limited. The United States Food and Drug Administration Manufacturer and User Facility Device Experience (MAUDE) database provides a useful resource for characterizing malfunctions and safety outcomes across platforms. MAUDE reports involving da Vinci surgical systems from January 2015 to June 2025 were reviewed. Events were classified as malfunctions, injuries, or deaths, with malfunctions further characterized by type. Conversions and procedure abortions were identified and analyzed. The rates of adverse events were calculated and compared between robotic platforms. Among an estimated 15.9 million da Vinci robotic surgeries performed during the study period, 66,651 MAUDE reports were identified. There were 420.1 MAUDE reports, including 55.2 injuries, 3.1 deaths, 21.8 conversions, and 2.1 procedure abortion events, per 100,000 procedures. Compared with the da Vinci X/Xi, the da Vinci SP showed significantly higher risks of reported injury (RR 29.9, P < 0.001), death (RR 6.2, P < 0.001), conversion (RR 9.4, P < 0.001), and procedure abortion (RR 16.1, P < 0.001). Although adverse events and malfunctions associated with da Vinci robotic surgeries are relatively uncommon, the widespread use of these systems results in a substantial number of events. These findings highlight the need for prospective registry-based surveillance to validate platform-specific safety profiles as robotic surgery becomes increasingly integrated into clinical practice.

Indexed as

Equipment FailureRobotic Surgical ProceduresDatabases, FactualFemaleHumansPregnancyUnited StatesUnited States Food and Drug AdministrationAdverse eventsDa vinciMalfunctionRobotic surgery

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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.