Evidence map›Paper›PMID 40170673›Full record

ReviewJournal of hand and microsurgery2025

Navigating the future: A comprehensive review of technology in shoulder arthroplasty.

J Ryan Hill, Garrett R Jackson, William To, Benjamin Zmistowski, Aghdas Movassaghi, Vani J Sabesan

Abstract readReview
In one paragraph

Review in Journal of hand and microsurgery, 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
  2. Article
  3. 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

6 authors.

J Ryan HillUniversity of Arkansas for Medical Sciences (UAMS), Little Rock, AR, USA.
Garrett R JacksonUniversity of Missouri, Department of Orthopaedic Surgery, Columbia, MO, USA.
William ToCharles E. Schmidt College of Medicine at Florida Atlantic University, Boca Raton, FL, USA.
Benjamin ZmistowskiWashington University Orthopedics, St. Louis, MO, USA.
Aghdas MovassaghiMichigan State University College of Human Medicine, East Lansing, MI, USA.
Vani J SabesanMichigan State University College of Human Medicine, East Lansing, MI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The volume of shoulder arthroplasty (SA) procedures has increased significantly in recent years, outpacing the growth of hip and knee arthroplasty. As a relatively young area in orthopedics, shoulder arthroplasty offers many opportunities for innovation, often borrowing from established practices in other subspecialties. Degenerative shoulder pathology presents unique challenges that can be difficult to adequately address with conventional reconstructive methods alone. Currently, three-dimensional preoperative planning is the most widely utilized technology in shoulder arthroplasty. Implementation of patient-specific instrumentation is increasing, primarily for patients with severe deformity. Computer-assisted navigation, widely used in hip and knee reconstruction, is gaining traction. These technologies have demonstrated increased accuracy and precision in correcting glenoid deformity and implant positioning, which are known to influence the long-term performance of SA. However, studies specifically evaluating the long-term clinical benefits of these innovations are lacking. In the near future, the application of robotic and immersive technologies like augmented reality for SA demonstrates promise for enhancing the surgeon's ability to address glenoid deformity intraoperatively. These advancements provide exciting opportunities to transform the field of shoulder arthroplasty, yet they must be critically evaluated for their cost and impact to outcomes clinical cohorts with long-term follow-up. Level of evidence: Level V; Narrative Review.

Indexed as

And robotic surgeryComputer-assisted navigationPreoperative planningShoulder arthroplastyTechnology

Identifiers

PMID40170673
PMCPMC11957521

What OpenQuestion 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 OpenQuestion graph.