Bhavna Chopra

485 total citations
30 papers, 341 citations indexed

About

Bhavna Chopra is a scholar working on Transplantation, Surgery and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Bhavna Chopra has authored 30 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Transplantation, 18 papers in Surgery and 16 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Bhavna Chopra's work include Renal Transplantation Outcomes and Treatments (24 papers), Organ Transplantation Techniques and Outcomes (14 papers) and Organ Donation and Transplantation (13 papers). Bhavna Chopra is often cited by papers focused on Renal Transplantation Outcomes and Treatments (24 papers), Organ Transplantation Techniques and Outcomes (14 papers) and Organ Donation and Transplantation (13 papers). Bhavna Chopra collaborates with scholars based in United States, India and Israel. Bhavna Chopra's co-authors include Kalathil K. Sureshkumar, Mireille El Ters, Borja G. Cosío, Patrick G. Dean, Joseph P. Grande, Mira T. Keddis, Emilio Rodrigo, Mark D. Stegall, Amy Tang and Marcelo Santos Sampaio and has published in prestigious journals such as Journal of the American Society of Nephrology, American Journal of Kidney Diseases and Transplantation.

In The Last Decade

Bhavna Chopra

24 papers receiving 339 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bhavna Chopra United States 10 279 193 123 61 50 30 341
Chow Heok P’ng Australia 8 227 0.8× 145 0.8× 53 0.4× 44 0.7× 69 1.4× 18 326
Masaki Muramatsu Japan 11 195 0.7× 134 0.7× 99 0.8× 92 1.5× 104 2.1× 61 357
Lam Chin Tan United Kingdom 10 254 0.9× 164 0.8× 69 0.6× 36 0.6× 82 1.6× 20 337
Albin Gritsch United States 6 204 0.7× 230 1.2× 116 0.9× 94 1.5× 19 0.4× 9 376
Ana Ávila Spain 11 161 0.6× 88 0.5× 53 0.4× 63 1.0× 83 1.7× 34 300
Eva Santos‐Nunez United Kingdom 9 444 1.6× 255 1.3× 88 0.7× 29 0.5× 144 2.9× 12 484
Kohei Unagami Japan 11 185 0.7× 108 0.6× 72 0.6× 50 0.8× 93 1.9× 57 294
T.W. Shroyer United States 9 259 0.9× 215 1.1× 68 0.6× 24 0.4× 32 0.6× 13 418
Ana Cristina Carvalho de Matos Brazil 11 89 0.3× 77 0.4× 49 0.4× 46 0.8× 58 1.2× 29 239
Paul Warner United States 13 236 0.8× 186 1.0× 39 0.3× 15 0.2× 54 1.1× 29 398

Countries citing papers authored by Bhavna Chopra

Since Specialization
Citations

This map shows the geographic impact of Bhavna Chopra'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 Bhavna Chopra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bhavna Chopra more than expected).

Fields of papers citing papers by Bhavna Chopra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bhavna Chopra. 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 Bhavna Chopra. The network helps show where Bhavna Chopra may publish in the future.

Co-authorship network of co-authors of Bhavna Chopra

This figure shows the co-authorship network connecting the top 25 collaborators of Bhavna Chopra. A scholar is included among the top collaborators of Bhavna Chopra 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 Bhavna Chopra. Bhavna Chopra 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.
Eckhoff, Devin E., et al.. (2025). Long Term Outcomes of Transplant Recipients Comparing Belatacept vs. Tacrolimus: A UNOS Database Analysis. Clinical Transplantation. 39(2). e70075–e70075.
2.
3.
Pavlakis, Martha, et al.. (2024). Impact of Cold Ischemia Time and Donor Age on Donation After Circulatory Death Kidney Transplant Outcomes: A UNOS Mate‐Kidney Analysis. Clinical Transplantation. 38(12). e70051–e70051. 1 indexed citations
4.
Pawar, Aditya S., et al.. (2024). Early Steroid Withdrawal Versus Steroid Maintenance in Adults Older than 65 Receiving Second Kidney Transplants. Transplantation Proceedings. 56(10). 2158–2162.
5.
6.
Chopra, Bhavna, et al.. (2022). Induction therapy and outcomes following kidney transplantation in recipients of previous heart or liver transplants. Indian Journal of Nephrology. 32(2). 116–116.
7.
Sureshkumar, Kalathil K., Bhavna Chopra, Michelle A. Josephson, Pratik Shah, & Rita L. McGill. (2021). Recipient Obesity and Kidney Transplant Outcomes: A Mate-Kidney Analysis. American Journal of Kidney Diseases. 78(4). 501–510.e1. 21 indexed citations
8.
Sureshkumar, Kalathil K., et al.. (2020). Unexplained Persistent Hypercalcemia After Liver Transplantation. Journal of the American Society of Nephrology. 31(10S). 161–161.
9.
Sureshkumar, Kalathil K. & Bhavna Chopra. (2019). Does Induction Type Influence Outcomes in Kidney Transplant Recipients at Different Phases of Hepatitis B Infection?. Experimental and Clinical Transplantation. 17(4). 457–460. 1 indexed citations
10.
Sureshkumar, Kalathil K. & Bhavna Chopra. (2019). Induction Type and Outcomes in HLA-DR Mismatch Kidney Transplantation. Transplantation Proceedings. 51(6). 1796–1800. 7 indexed citations
11.
Sureshkumar, Kalathil K. & Bhavna Chopra. (2019). Impact of Donor Ethnicity on Long-Term Kidney Transplant Outcomes: Analysis by Kidney Donor Profile Index Categories. Experimental and Clinical Transplantation. 18(2). 144–148. 3 indexed citations
12.
Chopra, Bhavna & Kalathil K. Sureshkumar. (2018). Kidney transplantation in older recipients: Preemptive high KDPI kidney vs lower KDPI kidney after varying dialysis vintage. World Journal of Transplantation. 8(4). 102–109. 17 indexed citations
13.
Chopra, Bhavna & Kalathil K. Sureshkumar. (2018). Limitation of Terminal Serum Creatinine as a Kidney Donor Profile Index Variable in Predicting Long-Term Kidney Transplant Outcomes. Transplantation Proceedings. 50(5). 1272–1275. 3 indexed citations
14.
Chopra, Bhavna & Kalathil K. Sureshkumar. (2017). Outcomes of Kidney Transplantation in Patients Exposed to Hepatitis B Virus: Analysis by Phase of Infection. Transplantation Proceedings. 49(2). 278–280. 5 indexed citations
15.
Sampaio, Marcelo Santos, Bhavna Chopra, & Kalathil K. Sureshkumar. (2016). Depleting Antibody Induction and Kidney Transplant Outcomes. Transplantation. 101(10). 2527–2535. 7 indexed citations
16.
Chopra, Bhavna & Kalathil K. Sureshkumar. (2015). Human Leukocyte Antigen Mismatch and Steroid Maintenance in Kidney Transplantation. Transplantation Proceedings. 47(10). 2852–2854. 2 indexed citations
17.
Chopra, Bhavna & Kalathil K. Sureshkumar. (2014). Co-stimulatory blockade with belatacept in kidney transplantation. Expert Opinion on Biological Therapy. 14(5). 563–567. 10 indexed citations
18.
Chopra, Bhavna. (2013). Health related quality of life studies in Indian patients after limb salvage surgery: Need of the hour. Medical Journal Armed Forces India. 69(3). 209–210. 3 indexed citations
19.
Ters, Mireille El, Joseph P. Grande, Mira T. Keddis, et al.. (2013). Kidney Allograft Survival After Acute Rejection, the Value of Follow-Up Biopsies. American Journal of Transplantation. 13(9). 2334–2341. 134 indexed citations
20.
Chauhan, Ashutosh, et al.. (2013). Limb Salvage Surgery in Bone Tumors: A Retrospective Study of 50 Cases in a Single Center. Indian Journal of Surgical Oncology. 4(3). 248–254. 17 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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