Evidence map›Paper›PMID 39624323›Full record

ArticleHeliyon2024

The advantages of artificial intelligence-assisted total hip arthroplasty: A randomized controlled trial followed by 12 months.

Gang Zhang, Zixuan Liu, Diaodiao Wang, Zhuang Tian, Qi Yao

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
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  6. 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

5 authors.

Gang ZhangDepartment of Joint Surgery, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Beijing, 100038, China.
Zixuan LiuDepartment of Joint Surgery, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Beijing, 100038, China.
Diaodiao WangDepartment of Joint Surgery, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Beijing, 100038, China.
Zhuang TianDepartment of Joint Surgery, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Beijing, 100038, China.
Qi YaoDepartment of Joint Surgery, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Beijing, 100038, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objection: The rapid advancement of artificial intelligence has brought significant breakthroughs to various medical disciplines,This study aimed to compare perioperative factors and postoperative hip function recovery in primary total hip arthroplasty (THA)by evaluating the use of an artificial intelligence (AI) preoperative planning system versus traditional two-dimensional X-ray planning. Patients and methods: A total of 45 eligible patients underwent primary THA at Beijing Shijitan Hospital, Capital Medical University, between July 2022 and August 2022. The patients were randomly assigned to either the experimental group (n = 19) or the control group (n = 26). The experimental group utilized AI planning, while the control group employed traditional two-dimensional X-ray planning. Statistical analysis was performed to compare the accuracy of prosthesis prediction, operation time, intraoperative blood loss, frequency of intraoperative model testing, length of hospital stay, postoperative imaging data, and postoperative hip function scores. These comparisons were made to assess the effects of different preoperative planning methods on perioperative and postoperative hip function recovery. Results: The accuracy of preoperative planning for the acetabular and femoral sides in AI-assisted total hip arthroplasty was 84.2 % and 89.5 %, respectively, which was significantly better than that of the traditional two-dimensional X-ray planning group ( Conclusion: Artificial intelligence-assisted total hip arthroplasty demonstrated superior accuracy in prosthesis prediction, shorter operation time, higher average Harris score at postoperative follow-up, and better hip function recovery at 3 months compared to traditional two-dimensional X-ray planning. Level of evidence: III, case-control study.

Indexed as

Artificial intelligencePreoperative PlanningTotal hip arthroplasty

Identifiers

PMID39624323
PMCPMC11609650

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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.