Evidence map›Paper›PMID 37964157›Full record

Trial reportInternational orthopaedics2024

Clinical application of artificial intelligence-assisted three-dimensional planning in direct anterior approach hip arthroplasty.

Weihua Yang, Tianyi Gao, Xingyu Liu, Kaiwei Shen, Feitai Lin, Yan Weng, Bei Lin, Deng Liang, Eryou Feng, Yiling Zhang

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in International orthopaedics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. [Advances in application of digital orthopedic technology in total hip arthroplasty for developmental dysplasia of hip].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2026
    Review
  11. Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. Review
  17. Article
  18. Review
  19. Review
  20. Review
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

10 authors.

Weihua YangDepartment of Arthrosis Surgery, Fuzhou Second Hospital, Fuzhou, China.
Tianyi GaoLongwood Valley MedTech, No.2 Ronghua South Road, Daxing District, Beijing, China.
Xingyu LiuLongwood Valley MedTech, No.2 Ronghua South Road, Daxing District, Beijing, China.
Kaiwei ShenDepartment of Arthrosis Surgery, Fuzhou Second Hospital, Fuzhou, China.
Feitai LinDepartment of Arthrosis Surgery, Fuzhou Second Hospital, Fuzhou, China.
Yan WengDepartment of Arthrosis Surgery, Fuzhou Second Hospital, Fuzhou, China.
Bei LinDepartment of Arthrosis Surgery, Fuzhou Second Hospital, Fuzhou, China.
Deng LiangDepartment of Arthrosis Surgery, Fuzhou Second Hospital, Fuzhou, China.
Eryou FengDepartment of Arthrosis Surgery, Fujian Medical University Union Hospital, No. 29, Xinquan Road, Gulou District, Fuzhou, China. fey9001@126.com.
Yiling ZhangLongwood Valley MedTech, No.2 Ronghua South Road, Daxing District, Beijing, China. ylzhang@changmugu.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe objective of this study was to investigate the efficacy of an artificial intelligence-assisted 3D planning system (AIHIP) in total hip arthroplasty by direct anterior approach and assess the reliability of the AIHIP preoperative program in terms of both interobserver and intraobserver agreement.

methodsA retrospective analysis was conducted on patients who underwent unilateral primary THA via direct anterior approach from June 2019 to March 2022. Participants were randomly assigned to receive either the AIHIP system (n = 220) or the 2D template (control group) (n = 220) for preoperative planning. The primary outcome aimed to evaluate the correspondence between the prosthesis selected intro-operation and the one planned preoperatively, as well as to calculate the intraclass correlation coefficient (ICC). Secondary outcomes included operation time, intraoperative blood loss, fluoroscopy times, Harris hip score (HHS), lower limb length difference (LLD), femoral offset (FO), and bilateral femoral offset difference.

resultsNo significant differences were observed in gender, age, body mass index (BMI), aetiology, and American Society of Anesthesiologists (ASA) score between the two groups. Both planning methods exhibited good intraobserver agreement for component planning (ICC: 0.941-0.976). Interobserver agreement for component planning was comparable between the two methods (ICC: 0.882-0.929). In the AIHIP group, the accuracy of acetabular cup and femoral stem prosthetics planning significantly improved, with accuracies within the size range of ± 0 and ± 1 being 76.8% and 90.5% and 79.5% and 95.5%, respectively. All differences between two groups were statistically significant (p < 0.05). Patients receiving AIHIP preoperative planning experienced shorter operation times, reduced intraoperative blood loss, fewer fluoroscopy times, and lower leg length discrepancy (LLD) (p < 0.05). Moreover, they demonstrated a higher Harris hip score (HHS) at three days post-surgery (p < 0.05). However, no significant differences were found in femoral offset (FO), difference of bilateral femoral offsets, and HHS at 1 month after the operation.

conclusionUtilizing AIHIP for preoperative planning of direct anterior approach THA can significantly enhance the accuracy of prosthetic sizing with good reliability, decrease operation time, reduce intraoperative blood loss, and more effectively restore the length of both lower limbs. This approach has greater clinical application value.

Indexed as

Arthroplasty, Replacement, HipHip ProsthesisArtificial IntelligenceBlood Loss, SurgicalHumansLeg Length InequalityReproducibility of ResultsRetrospective StudiesTreatment Outcome3D preoperative planningArtificial intelligenceTotal hip arthroplasty

Identifiers

PMID37964157
PMCPMC10902092

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.