Evidence map›Paper›PMID 42246014›Full record

ArticleThe archives of bone and joint surgery2026

Same-Day Discharge Total Joint Arthroplasty: A Bibliometric Analysis.

Hassaan Abdel Khalik, Mohammed Al-Asadi, Darius L Lameire, Thomas J Wood

Abstract read
In one paragraph

Article in The archives of bone and joint surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Hassaan Abdel Khalik
Mohammed Al-Asadi
Darius L Lameire
Thomas J Wood

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Same-day discharge (SDD) total joint arthroplasty (TJA) continues to increase in prevalence globally, especially following the coronavirus disease (COVID-19) pandemic. The purpose of this analysis is to utilize bibliometric methodology to assess publication trends, key figures, and institutions, as well as geographic variations in SDD TJA research. Methods: The Web of Science Core Collection was searched from inception to January 23, 2025, for studies on SDD TJA. Publication rates were assessed using the compound annual growth rate (CAGR) and segmented regression analysis. Top publishing authors, institutions, and countries were tabulated as frequencies. International collaboration was assessed by the prevalence of publications with authors from different nationalities. Results: A total of 121 studies published between 2014 and 2024 were eligible for final analysis, with a CAGR of 44%. Segmented regression demonstrated a significant increase in slope pre-2023 to post-2023 (2.1 vs. 19 publications per year, R2=0.94, P<0.001). Original research comprised 83% of studies, with most being retrospective in nature (66%) and only three being of randomized controlled design (3%). Only four of 15 original studies with a designated primary outcome performed appropriate a priori sample size power analysis. Over half of the studies (53%) were published in the USA, with only seven studies (5.8%) demonstrating international collaboration. Conclusion: SDD TJA research continues to grow at a rapid rate, with a nine-fold increase in publication rate since 2023. Future directions for SDD TJA research include research from varying healthcare delivery models, international collaborative efforts, and methodologically robust randomized controlled trials.

Indexed as

ArthroplastyBibliometricDay surgerySame-day dischargeTotal hip arthroplastyTotal knee arthroplasty

Identifiers

PMID42246014
PMCPMC13231251

What OpenQuestion holds

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LicenceCC BY-NC
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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.