Evidence map›Paper›PMID 39764457›Full record

SynthesisFrontiers in artificial intelligence2024

The role of artificial intelligence in preoperative planning for Total Hip Arthroplasty: a systematic review.

Javad Khaje Mozafari, Seyed Ali Moshtaghioon, Seyed Mani Mahdavi, Alireza Ghaznavi, Morteza Behjat, Ali Yeganeh

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in artificial intelligence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

6 authors.

Javad Khaje MozafariTrauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran.
Seyed Ali MoshtaghioonDepartment of Orthopedic and Trauma Surgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Seyed Mani MahdaviDepartment of Orthopedic Surgery, Rasoul-e-Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.
Alireza GhaznaviDepartment of Orthopedic Surgery, Rasoul-e-Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.
Morteza BehjatDepartment of Orthopedic Surgery, Rasoul-e-Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.
Ali YeganehDepartment of Orthopedic Hip and Knee Surgery, Rasoul-e-Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Total Hip Arthroplasty (THA) is a transformative surgical intervention for hip joint disorders, necessitating meticulous preoperative planning for optimal outcomes. With the emergence of Artificial Intelligence (AI), preoperative planning paradigms have evolved, leveraging AI algorithms for enhanced decision support and imaging analysis. This systematic review aims to comprehensively evaluate the role of AI in THA preoperative planning, synthesizing evidence from studies exploring various AI techniques and their applications. Methods: A systematic search of PubMed, Scopus, and Web of Science databases was conducted to identify relevant articles. Inclusion criteria encompassed studies focusing on AI in THA preoperative planning, including randomized controlled trials (RCTs), observational studies, and comparative studies. Results: Six studies from China met the inclusion criteria, collectively analyzing 831 patients. AI-assisted planning demonstrated superior accuracy in estimating prosthesis size and positioning compared to traditional methods. However, limitations such as geographic bias and language constraints were noted. Conclusion: AI-assisted preoperative planning significantly enhances femoral positioning accuracy, providing superior outcomes compared to traditional methods. This improvement in precision, particularly in the placement of femoral and acetabular components, has been consistently observed across studies, making AI an indispensable tool in improving the overall success of Total Hip Arthroplasty. Despite promising findings, further research is warranted to address limitations and optimize the integration of AI technologies into routine clinical practice.

Indexed as

artificial intelligenceorthopedicpreoperative planningsystematic reviewTotal Hip Arthroplasty

Identifiers

PMID39764457
PMCPMC11701226

What OpenQuestion holds

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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.