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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Predicting whether patients will achieve minimal clinically important differences following hip or knee arthroplasty
Benedikt Langenberger, Daniel Schrednitzki, Andreas M. Halder, et al.
Bone and Joint Research (2023) Vol. 12, Iss. 9, pp. 512-521
Open Access | Times Cited: 23

Showing 23 citing articles:

Who Benefits From Hip Arthroplasty or Knee Arthroplasty? Preoperative Patient-reported Outcome Thresholds Predict Meaningful Improvement
Benedikt Langenberger, Viktoria Steinbeck, Reinhard Busse
Clinical Orthopaedics and Related Research (2024) Vol. 482, Iss. 5, pp. 867-881
Closed Access | Times Cited: 7
Performance of baseline quartile-stratified minimal clinically important difference estimates was superior to individual minimal clinically important difference estimates when compared with a gold standard comparator of important change
Daniel L. Riddle, Levent Dumenci
Pain (2025)
Closed Access
Leveraging machine learning for duration of surgery prediction in knee and hip arthroplasty – a development and validation study
Benedikt Langenberger, Daniel Schrednitzki, Andreas M. Halder, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Using artificial intelligence to predict patient outcomes from patient-reported outcome measures: a scoping review
Zuzanna Wójcik, Vania Dimitrova, Lorraine Warrington, et al.
Health and Quality of Life Outcomes (2025) Vol. 23, Iss. 1
Open Access
Applications of artificial intelligence in Orthopaedic surgery: A systematic review and meta-analysis
M. W. Geda, Yuk Ming Tang, C.K.M. Lee
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108326-108326
Closed Access | Times Cited: 4
Artificial Intelligence for Clinically Meaningful Outcome Prediction in Orthopedic Research: Current Applications and Limitations
Seong J. Jang, Jake Rosenstadt, Eugenia Lee, et al.
Current Reviews in Musculoskeletal Medicine (2024) Vol. 17, Iss. 6, pp. 185-206
Open Access | Times Cited: 4
Satisfied with the worst health outcomes or unsatisfied with the best: explaining the divergence between good patient-reported outcomes and low satisfaction and vice versa among knee arthroplasty patients – a retrospective cohort study
Lukas Schöner, Viktoria Steinbeck, Reinhard Busse, et al.
Journal of Orthopaedic Surgery and Research (2025) Vol. 20, Iss. 1
Open Access
Preoperatively predicting failure to achieve the minimum clinically important difference and the substantial clinical benefit in patient-reported outcome measures for total hip arthroplasty patients using machine learning
Jaeyoung Park, Xiang Zhong, Emilie N. Miley, et al.
BMC Musculoskeletal Disorders (2025) Vol. 26, Iss. 1
Open Access
Artificial intelligence and machine learning in knee arthroplasty
Hugo C. Rodriguez, Brandon Rust, Martin W. Roche, et al.
The Knee (2025) Vol. 54, pp. 28-49
Closed Access
Gender health gap pre- and post-joint arthroplasty: identifying affected patient-reported health domains
Viktoria Steinbeck, Anja Yvonne Bischof, Lukas Schöner, et al.
International Journal for Equity in Health (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 3
High Expectations Among Patients Who Have Undergone TKA Do Not Correlate With Satisfaction
Nicole Vogel, Raphael Kaelin, Thomas Rychen, et al.
Clinical Orthopaedics and Related Research (2024) Vol. 482, Iss. 5, pp. 756-765
Open Access | Times Cited: 3
Understanding the role of machine learning in predicting progression of osteoarthritis
Simone Castagno, Benjamin Gompels, Estelle Strangmark, et al.
The Bone & Joint Journal (2024) Vol. 106-B, Iss. 11, pp. 1216-1222
Open Access | Times Cited: 3
Predicting Functional Outcomes of Total Hip Arthroplasty Using Machine Learning: A Systematic Review
Nicholas D. Clement, Rosie Clement, Abigail Clement
Journal of Clinical Medicine (2024) Vol. 13, Iss. 2, pp. 603-603
Open Access | Times Cited: 2
Can blood flow restriction therapy improve quality of life and function in dissatisfied knee arthroplasty patients?
Lenka Stroobant, E Jacobs, Nele Arnout, et al.
The Bone & Joint Journal (2024) Vol. 106-B, Iss. 12, pp. 1416-1425
Closed Access | Times Cited: 2
Outcomes Vary by Pre-Operative Physical Activity Levels in Total Knee Arthroplasty Patients
Roberta E. Redfern, David A. Crawford, Adolph V. Lombardi, et al.
Journal of Clinical Medicine (2023) Vol. 13, Iss. 1, pp. 125-125
Open Access | Times Cited: 6
Use of a fluoroscopy-based robotic-assisted total hip arthroplasty system produced greater improvements in patient-reported outcomes at one year compared to manual, fluoroscopic-assisted technique
Graham Buchan, Christian B. Ong, Christian J. Hecht, et al.
Archives of Orthopaedic and Trauma Surgery (2024) Vol. 144, Iss. 4, pp. 1843-1850
Open Access | Times Cited: 1
Letter to the Editor in Response to “Are 20% of Patients Actually Dissatisfied Following Total Knee Arthroplasty? A Systematic Review of the Literature”
Abdul K. Zalikha
The Journal of Arthroplasty (2024) Vol. 39, Iss. 4, pp. e27-e28
Closed Access | Times Cited: 1
The Role of Risk Tolerance in a Patient’s Decision to Undergo Total Knee and Hip Arthroplasty
Amy Z. Blackburn, A Prasad, Bryan L. Scott, et al.
The Journal of Arthroplasty (2024) Vol. 40, Iss. 1, pp. 40-44
Closed Access
Predicting Pain Response to a Remote Musculoskeletal Care Program for Low Back Pain Management: Development of a Prediction Tool
Anabela C. Areias, Robert Moulder, Maria Molinos, et al.
JMIR Medical Informatics (2024) Vol. 12, pp. e64806-e64806
Open Access
Patients with High Pre-Operative Physical Activity Take Longer to Return to Baseline
Roberta E. Redfern, David A. Crawford, Adolph V. Lombardi, et al.
Surgeries (2024) Vol. 5, Iss. 2, pp. 220-233
Open Access
Preoperative prediction for periprosthetic bone loss and individual evaluation of bisphosphonate effect after total hip arthroplasty using artificial intelligence
Akira Morita, Y Iida, Yutaka Inaba, et al.
Bone and Joint Research (2024) Vol. 13, Iss. 4, pp. 184-192
Open Access
Predicting Pain Response to a Remote Musculoskeletal Care Program for Low Back Pain Management: Development of a Prediction Tool (Preprint)
Anabela C. Areias, Robert Moulder, Maria Molinos, et al.
(2024)
Closed Access
Hip & Pelvis

Bone and Joint 360 (2023) Vol. 12, Iss. 6, pp. 17-20
Closed Access
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