Evidence map›Paper›PMID 38236336›Full record

SynthesisNeurosurgical review2024

Assessing the benefits of digital twins in neurosurgery: a systematic review.

Sorayouth Chumnanvej, Siriluk Chumnanvej, Susmit Tripathi

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Neurosurgical review, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Digital Twins and Health Care: an Umbrella Review.Journal of medical systems · 2025
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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

3 authors.

Sorayouth ChumnanvejNeurosurgery Division, Department of Surgery, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.ORCID http://orcid.org/0000-0002-5099-0247
Siriluk ChumnanvejDepartment of Anesthesiology and Operating Room, Phramongkutklao Hospital, Bangkok, Thailand.ORCID http://orcid.org/0000-0001-8658-450X
Susmit TripathiDepartment of Neurology, New York Presbyterian-Weill Cornell Medical Center, New York, NY, USA. sut9038@nyp.org.ORCID http://orcid.org/0000-0001-7594-0855

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital twins are virtual replicas of their physical counterparts, and can assist in delivering personalized surgical care. This PRISMA guideline-based systematic review evaluates current literature addressing the effectiveness and role of digital twins in many stages of neurosurgical management. The aim of this review is to provide a high-quality analysis of relevant, randomized controlled trials and observational studies addressing the neurosurgical applicability of a variety of digital twin technologies. Using pre-specified criteria, we evaluated 25 randomized controlled trials and observational studies on the applications of digital twins, including navigation, robotics, and image-guided neurosurgeries. All 25 studies compared these technologies against usual surgical approaches. Risk of bias analyses using the Cochrane risk of bias tool for randomized trials (Rob 2) found "low" risk of bias in the majority of studies (23/25). Overall, this systematic review shows that digital twin applications have the potential to be more effective than conventional neurosurgical approaches when applied to brain and spinal surgery. Moreover, the application of these novel technologies may also lead to fewer post-operative complications.

Indexed as

NeurosurgeryBrainHumansNeurosurgical ProceduresObservational Studies as TopicPostoperative ComplicationsBrain surgeryDigital twinNeuronavigationNeurosurgerySpinal surgery

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.