Enisa Shevroja

1.4k total citations · 1 hit paper
35 papers, 739 citations indexed

About

Enisa Shevroja is a scholar working on Orthopedics and Sports Medicine, Surgery and Oncology. According to data from OpenAlex, Enisa Shevroja has authored 35 papers receiving a total of 739 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Orthopedics and Sports Medicine, 13 papers in Surgery and 8 papers in Oncology. Recurrent topics in Enisa Shevroja's work include Bone health and osteoporosis research (28 papers), Bone and Joint Diseases (15 papers) and Hip and Femur Fractures (11 papers). Enisa Shevroja is often cited by papers focused on Bone health and osteoporosis research (28 papers), Bone and Joint Diseases (15 papers) and Hip and Femur Fractures (11 papers). Enisa Shevroja collaborates with scholars based in Switzerland, United States and Netherlands. Enisa Shevroja's co-authors include Didier Hans, Olivier Lamy, William D. Leslie, Fernando Rivadeneira, Lynn Kohlmeier, Thomas Hügle, Francesco Pio Cafarelli, Giuseppe Guglielmi, Fjorda Koromani and Elena González Rodríguez and has published in prestigious journals such as Scientific Reports, Journal of Bone and Mineral Research and International Journal of Epidemiology.

In The Last Decade

Enisa Shevroja

33 papers receiving 728 citations

Hit Papers

Update on the clinical use of trabecular bone score (TBS)... 2023 2026 2024 2025 2023 25 50 75

Peers

Enisa Shevroja
Kendall F. Moseley United States
Sanchita Agarwal United States
Halley Rogers United States
Florian Hartl Switzerland
Kendall F. Moseley United States
Enisa Shevroja
Citations per year, relative to Enisa Shevroja Enisa Shevroja (= 1×) peers Kendall F. Moseley

Countries citing papers authored by Enisa Shevroja

Since Specialization
Citations

This map shows the geographic impact of Enisa Shevroja's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Enisa Shevroja with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Enisa Shevroja more than expected).

Fields of papers citing papers by Enisa Shevroja

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Enisa Shevroja. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Enisa Shevroja. The network helps show where Enisa Shevroja may publish in the future.

Co-authorship network of co-authors of Enisa Shevroja

This figure shows the co-authorship network connecting the top 25 collaborators of Enisa Shevroja. A scholar is included among the top collaborators of Enisa Shevroja based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Enisa Shevroja. Enisa Shevroja is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rodríguez, Elena González, Péter Vollenweider, Pedro Marques‐Vidal, et al.. (2025). Prediction of 10‐Year Fragility Fractures Using Muscle Health Indicators in Postmenopausal Women: The OsteoLaus Cohort. Journal of Cachexia Sarcopenia and Muscle. 16(3). e13837–e13837.
2.
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Rodríguez, Elena González, Péter Vollenweider, Pedro Marques‐Vidal, et al.. (2025). Prevalence and incidence of sarcopenia in Swiss postmenopausal women: findings from the OsteoLaus Cohort. Swiss Medical Weekly. 155(1). 4034–4034. 1 indexed citations
4.
Rodríguez, Elena González, et al.. (2024). Standardization of body composition parameters between GE Lunar iDXA and Hologic Horizon A and their clinical impact. JBMR Plus. 8(9). ziae088–ziae088. 5 indexed citations
5.
Shevroja, Enisa, et al.. (2024). Development and reporting of artificial intelligence in osteoporosis management. Journal of Bone and Mineral Research. 39(11). 1553–1573. 5 indexed citations
6.
Shevroja, Enisa, Elena González Rodríguez, Jolanda Elmers, et al.. (2024). Muscle parameters in fragility fracture risk prediction in older adults: A scoping review. Journal of Cachexia Sarcopenia and Muscle. 15(2). 477–500. 12 indexed citations
7.
Marques‐Vidal, Pedro, et al.. (2024). Relationship between dietary characteristics and heel quantitative ultrasound parameters in postmenopausal women from the OsteoLaus cohort. Scientific Reports. 14(1). 1638–1638. 1 indexed citations
8.
Shevroja, Enisa, et al.. (2023). Comparison between Horizon A System and Lunar iDXA in Bone Assessment and Osteoporosis Diagnosis: The OsteoLaus Cohort. Journal of Clinical Densitometry. 26(3). 101406–101406. 1 indexed citations
9.
Shevroja, Enisa, Jean‐Yves Reginster, Olivier Lamy, et al.. (2023). Update on the clinical use of trabecular bone score (TBS) in the management of osteoporosis: results of an expert group meeting organized by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO), and the International Osteoporosis Foundation (IOF) under the auspices of WHO Collaborating Center for Epidemiology of Musculoskeletal Health and Aging. Osteoporosis International. 34(9). 1501–1529. 81 indexed citations breakdown →
11.
Shevroja, Enisa, et al.. (2023). L’intelligence artificielle a-t-elle un rôle dans la prise en charge de l’ostéoporose ?. Revue Médicale Suisse. 19(823). 752–755.
12.
Shevroja, Enisa, et al.. (2022). Bone Texture Assessment on Lateral VFAs Using the Texture Research Investigational Platform (TRIP) and its Fracture Discrimination Ability. Journal of Clinical Densitometry. 25(4). 599–605. 2 indexed citations
13.
Hans, Didier, Enisa Shevroja, Michele McDermott, et al.. (2022). Updated trabecular bone score accounting for the soft tissue thickness (TBSTT) demonstrated significantly improved bone microstructure with denosumab in the FREEDOM TBS post hoc analysis. Osteoporosis International. 33(12). 2517–2525. 10 indexed citations
14.
Shevroja, Enisa, Francesco Pio Cafarelli, Giuseppe Guglielmi, & Didier Hans. (2021). DXA parameters, Trabecular Bone Score (TBS) and Bone Mineral Density (BMD), in fracture risk prediction in endocrine-mediated secondary osteoporosis. Endocrine. 74(1). 20–28. 86 indexed citations
15.
Cosman, Felicia, et al.. (2020). Effect of Abaloparatide on Bone Microarchitecture Assessed by Trabecular Bone Score in Women With Osteoporosis: Post Hoc Analysis of ACTIVE and ACTIVExtend. Journal of Bone and Mineral Research. 38(4). 464–470. 8 indexed citations
16.
Shevroja, Enisa, et al.. (2020). Machine Learning Solutions for Osteoporosis—A Review. Journal of Bone and Mineral Research. 36(5). 833–851. 119 indexed citations
17.
Shevroja, Enisa, Katerina Trajanoska, André G. Uitterlinden, et al.. (2019). Fractures in school age children in relation to sex and ethnic background: The Generation R Study. Bone. 121. 227–231. 7 indexed citations
18.
Rivadeneira, Fernando, Enisa Shevroja, Katerina Trajanoska, et al.. (2019). Femoral stress is prominently associated with fracture risk in children: The Generation R Study. Bone. 122. 150–155. 7 indexed citations
19.
Shevroja, Enisa, Brunilda Dhamo, André G. Uitterlinden, et al.. (2019). Skeletal maturation in relation to ethnic background in children of school age: The Generation R Study. Bone. 132. 115180–115180. 17 indexed citations
20.
Shevroja, Enisa, Olivier Lamy, Lynn Kohlmeier, et al.. (2017). Use of Trabecular Bone Score (TBS) as a Complementary Approach to Dual-energy X-ray Absorptiometry (DXA) for Fracture Risk Assessment in Clinical Practice. Journal of Clinical Densitometry. 20(3). 334–345. 121 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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