Manisha Jhamb

2.8k total citations
62 papers, 1.5k citations indexed

About

Manisha Jhamb is a scholar working on Nephrology, Epidemiology and General Health Professions. According to data from OpenAlex, Manisha Jhamb has authored 62 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Nephrology, 12 papers in Epidemiology and 11 papers in General Health Professions. Recurrent topics in Manisha Jhamb's work include Dialysis and Renal Disease Management (33 papers), Palliative Care and End-of-Life Issues (7 papers) and Pain Management and Opioid Use (6 papers). Manisha Jhamb is often cited by papers focused on Dialysis and Renal Disease Management (33 papers), Palliative Care and End-of-Life Issues (7 papers) and Pain Management and Opioid Use (6 papers). Manisha Jhamb collaborates with scholars based in United States, United Kingdom and Australia. Manisha Jhamb's co-authors include Mark L. Unruh, Jennifer L. Steel, Steven D. Weisbord, Jonathan G. Yabes, Khaled Abdel-Kader, Mary Amanda Dew, Christos Argyropoulos, Nirav Shah, Laura Plantinga and Kelly V. Liang and has published in prestigious journals such as Journal of the American Society of Nephrology, American Journal of Kidney Diseases and Journal of Vascular Surgery.

In The Last Decade

Manisha Jhamb

56 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Manisha Jhamb United States 21 829 273 272 244 220 62 1.5k
Valeria Saglimbene Australia 25 1.1k 1.4× 438 1.6× 232 0.9× 270 1.1× 140 0.6× 51 2.2k
Mariacristina Vecchio France 17 922 1.1× 297 1.1× 197 0.7× 219 0.9× 241 1.1× 24 1.7k
Samir S. Patel United States 19 503 0.6× 124 0.5× 116 0.4× 145 0.6× 121 0.6× 46 1.4k
Nadia M. Chu United States 21 610 0.7× 254 0.9× 189 0.7× 52 0.2× 368 1.7× 68 1.3k
Frank Brennan Australia 20 619 0.7× 143 0.5× 311 1.1× 133 0.5× 181 0.8× 62 2.5k
Usama Feroze United States 17 725 0.9× 125 0.5× 147 0.5× 138 0.6× 309 1.4× 19 1.2k
D Levenson United States 8 646 0.8× 164 0.6× 126 0.5× 142 0.6× 72 0.3× 11 1.1k
Stig Mølsted Denmark 17 366 0.4× 106 0.4× 184 0.7× 107 0.4× 194 0.9× 84 1.0k
M.H.G. de Greef Netherlands 30 279 0.3× 255 0.9× 303 1.1× 146 0.6× 804 3.7× 60 2.5k
Thomas J. Wilkinson United Kingdom 23 920 1.1× 132 0.5× 327 1.2× 170 0.7× 735 3.3× 97 1.8k

Countries citing papers authored by Manisha Jhamb

Since Specialization
Citations

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

Fields of papers citing papers by Manisha Jhamb

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manisha Jhamb

This figure shows the co-authorship network connecting the top 25 collaborators of Manisha Jhamb. A scholar is included among the top collaborators of Manisha Jhamb 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 Manisha Jhamb. Manisha Jhamb 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.
Roumelioti, Maria‐Eleni, et al.. (2025). Post-Dialysis Syndrome. Kidney360.
2.
Yabes, Jonathan G., et al.. (2025). Using Ecological Momentary Assessment to Redefine Postdialysis Fatigue in Patients with Kidney Failure. Journal of the American Society of Nephrology. 36(8). 1603–1613.
3.
Nolin, Thomas D., et al.. (2025). Using Machine Learning to Predict Medication Therapy Problems among Patients with Chronic Kidney Disease. American Journal of Nephrology. 57(1). 120–130. 1 indexed citations
4.
5.
Rollman, Bruce L., et al.. (2024). Population Health Management and Guideline-Concordant Care in CKD. Journal of the American Society of Nephrology. 36(5). 869–881. 4 indexed citations
6.
Dember, Laura M., Jesse Y. Hsu, Rajnish Mehrotra, et al.. (2024). Pain Coping Skills Training for Patients Receiving Hemodialysis: The HOPE Consortium Randomized Clinical Trial. Journal of the American Society of Nephrology. 35(10S). 3 indexed citations
7.
Jhamb, Manisha, Jennifer L. Steel, Jonathan G. Yabes, et al.. (2023). Effects of Technology Assisted Stepped Collaborative Care Intervention to Improve Symptoms in Patients Undergoing Hemodialysis. JAMA Internal Medicine. 183(8). 795–795. 14 indexed citations
8.
Cavanaugh, Kerri L., Megan Hamm, Caroline Wilkie, et al.. (2023). Stakeholder-Driven Intervention Development for Dialysis Trials Using a Design Sprint Methodology. Kidney Medicine. 5(12). 100729–100729. 2 indexed citations
9.
10.
Jhamb, Manisha, Jonathan G. Yabes, Gary S. Fischer, et al.. (2023). Electronic health record based population health management to optimize care in CKD: Design of the Kidney Coordinated HeAlth Management Partnership (K-CHAMP) trial. Contemporary Clinical Trials. 131. 107269–107269. 6 indexed citations
11.
Chiang, Jung-Hsien, Ping‐Fang Chiu, Khaled Abdel-Kader, et al.. (2022). Predicting Mortality Using Machine Learning Algorithms in Patients Who Require Renal Replacement Therapy in the Critical Care Unit. Journal of Clinical Medicine. 11(18). 5289–5289. 13 indexed citations
12.
Yabes, Jonathan G., et al.. (2021). Prevalence and Demographic Correlates of Pain, Depression, Fatigue, and Readiness to Seek Treatment for These Symptoms in Hemodialysis Patients. Journal of the American Society of Nephrology. 32(10S). 289–289. 1 indexed citations
13.
Brintz, Carrie, Martin D. Cheatle, Laura M. Dember, et al.. (2021). Nonpharmacologic Treatments for Opioid Reduction in Patients With Advanced Chronic Kidney Disease. Seminars in Nephrology. 41(1). 68–81. 4 indexed citations
14.
Ernecoff, Natalie C., et al.. (2020). Implementation of Surprise Question Assessments Using the Electronic Health Record in Older Adults with Advanced CKD. Journal of the American Society of Nephrology. 31(10S). 224–224. 1 indexed citations
15.
Bohm, Clara, Jennifer M. MacRae, Paul N. Bennett, et al.. (2020). An International Delphi Survey on Exercise Priorities in CKD. Kidney International Reports. 6(3). 657–668. 5 indexed citations
16.
Robinson‐Cohen, Cassianne, Loren Lipworth, Aihua Bian, et al.. (2019). The Surprise Question and Self-Rated Health Are Useful Screens for Frailty and Disability in Older Adults with Chronic Kidney Disease. Journal of Palliative Medicine. 22(12). 1522–1529. 16 indexed citations
17.
Sridharan, Natalie, Larry Fish, Lan Yu, et al.. (2017). The associations of hemodialysis access type and access satisfaction with health-related quality of life. Journal of Vascular Surgery. 67(1). 229–235. 39 indexed citations
18.
Jhamb, Manisha, Mary McNulty, Julie Childers, et al.. (2016). Knowledge, barriers and facilitators of exercise in dialysis patients: a qualitative study of patients, staff and nephrologists. BMC Nephrology. 17(1). 192–192. 78 indexed citations
19.
Gemmell, Leigh, Lauren Terhorst, Manisha Jhamb, et al.. (2016). Gender and Racial Differences in Stress, Coping, and Health-Related Quality of Life in Chronic Kidney Disease. Journal of Pain and Symptom Management. 52(6). 806–812. 35 indexed citations
20.
Jhamb, Manisha, Francis Pike, Christos Argyropoulos, et al.. (2011). Impact of Fatigue on Outcomes in the Hemodialysis (HEMO) Study. American Journal of Nephrology. 33(6). 515–523. 95 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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