Martín Ragusa

1.1k total citations · 1 hit paper
19 papers, 575 citations indexed

About

Martín Ragusa is a scholar working on Infectious Diseases, Public Health, Environmental and Occupational Health and Statistics, Probability and Uncertainty. According to data from OpenAlex, Martín Ragusa has authored 19 papers receiving a total of 575 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Infectious Diseases, 4 papers in Public Health, Environmental and Occupational Health and 4 papers in Statistics, Probability and Uncertainty. Recurrent topics in Martín Ragusa's work include COVID-19 Clinical Research Studies (8 papers), Meta-analysis and systematic reviews (4 papers) and Health Sciences Research and Education (3 papers). Martín Ragusa is often cited by papers focused on COVID-19 Clinical Research Studies (8 papers), Meta-analysis and systematic reviews (4 papers) and Health Sciences Research and Education (3 papers). Martín Ragusa collaborates with scholars based in Argentina, Chile and United States. Martín Ragusa's co-authors include Ariel Izcovich, Gabriel Rada, Fernando Tortosa, Camila Agnoletti, Ezequiel Saavedra, Arnav Agarwal, A Bengolea, Federico Espinosa, Farid Foroutan and Verónica Sanguine and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of Infectious Diseases.

In The Last Decade

Martín Ragusa

17 papers receiving 558 citations

Hit Papers

Prognostic factors for se... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martín Ragusa Argentina 7 389 168 142 110 58 19 575
Fernando Tortosa Argentina 6 319 0.8× 149 0.9× 132 0.9× 103 0.9× 53 0.9× 15 504
Verónica Sanguine Argentina 4 288 0.7× 136 0.8× 126 0.9× 84 0.8× 51 0.9× 5 433
Federico Espinosa Chile 4 286 0.7× 136 0.8× 126 0.9× 75 0.7× 51 0.9× 4 423
Ezequiel Saavedra Argentina 3 286 0.7× 137 0.8× 126 0.9× 75 0.7× 51 0.9× 4 421
A Bengolea Argentina 3 288 0.7× 136 0.8× 126 0.9× 75 0.7× 51 0.9× 7 424
Su Aung United States 8 469 1.2× 205 1.2× 128 0.9× 124 1.1× 61 1.1× 18 704
Camila Agnoletti Chile 3 286 0.7× 136 0.8× 126 0.9× 75 0.7× 51 0.9× 4 420
Lanbo Yang United States 6 360 0.9× 170 1.0× 114 0.8× 80 0.7× 47 0.8× 12 599
Shuibao Xu China 7 534 1.4× 246 1.5× 138 1.0× 123 1.1× 62 1.1× 19 753
Fajuan Rui China 6 273 0.7× 153 0.9× 93 0.7× 162 1.5× 58 1.0× 22 589

Countries citing papers authored by Martín Ragusa

Since Specialization
Citations

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

Fields of papers citing papers by Martín Ragusa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martín Ragusa

This figure shows the co-authorship network connecting the top 25 collaborators of Martín Ragusa. A scholar is included among the top collaborators of Martín Ragusa 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 Martín Ragusa. Martín Ragusa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
2.
Hultcrantz, Monica, David Tovey, Nancy Santesso, et al.. (2025). Rating certainty when the target threshold is the null and the point estimate is close to the null. BMJ evidence-based medicine. 30(3). 202–207. 2 indexed citations
3.
Neumann, Ignacio, Ariel Izcovich, A Bengolea, et al.. (2025). Encouraging the use of the best available evidence in journal clubs for practising clinicians. BMJ evidence-based medicine. 30(6). 401–405.
4.
Tortosa, Fernando, Gerardo M. Castillo, Ariel Izcovich, et al.. (2024). Revisión sistemática viva de las manifestaciones clínicas de la fiebre de Oropouche: claves para diferenciarla del dengue y otras arbovirosis. Revista Panamericana de Salud Pública. 48. 1–1. 4 indexed citations
5.
Ragusa, Martín, Fernando Tortosa, Ana Torres, et al.. (2023). Viral reactivations and co-infections in COVID-19 patients: a systematic review. BMC Infectious Diseases. 23(1). 259–259. 21 indexed citations
6.
Izcovich, Ariel, Martín Ragusa, Fernando Tortosa, et al.. (2022). Correction: Prognostic factors for severity and mortality in patients infected with COVID-19: A systematic review. PLoS ONE. 17(5). e0269291–e0269291. 5 indexed citations
7.
Mazzitelli, Ignacio, et al.. (2021). Immunoglobulin G Immune Complexes May Contribute to Neutrophil Activation in the Course of Severe Coronavirus Disease 2019. The Journal of Infectious Diseases. 224(4). 575–585. 20 indexed citations
8.
Ragusa, Martín, et al.. (2021). BIGG, the international database of GRADE Guidelines. The Lancet Regional Health - Americas. 6. 100099–100099. 5 indexed citations
9.
Izcovich, Ariel, Martín Ragusa, Fernando Tortosa, et al.. (2021). Bias as a source of inconsistency in ivermectin trials for COVID-19: A systematic review. Ivermectin's suggested benefits are mainly based on potentially biased results. Journal of Clinical Epidemiology. 144. 43–55. 17 indexed citations
10.
Izcovich, Ariel, Martín Ragusa, Fernando Tortosa, et al.. (2021). Bias as a source of inconsistency in ivermectin trials for COVID-19: A systematic review. medRxiv. 1 indexed citations
11.
Izcovich, Ariel, Martín Ragusa, Fernando Tortosa, et al.. (2020). Prognostic factors for severity and mortality in patients infected with COVID-19: A systematic review. PLoS ONE. 15(11). e0241955–e0241955. 396 indexed citations breakdown →
12.
Ragusa, Martín, et al.. (2020). Development of Simple and Sensitive Score to Assess the Risk of Pneumonia in COVID-19 Patients. Revista de investigaci�n Cl�nica. 73(1). 52–58. 3 indexed citations
13.
Verdugo‐Paiva, Francisca, Ariel Izcovich, Martín Ragusa, & Gabriel Rada. (2020). Lopinavir/ritonavir for COVID-19: A living systematic review. SHILAP Revista de lepidopterología. 20(6). e7966–e7966. 38 indexed citations
14.
Izcovich, Ariel, Martín Ragusa, Fernando Tortosa, et al.. (2020). Prognostic Factors for Severity and Mortality in Patients Infected with COVID-19: A Systematic Review. SSRN Electronic Journal. 19 indexed citations
15.
Ragusa, Martín, et al.. (2020). Índice leucoglucémico como predictor de complicaciones en pacientes con accidente cerebrovascular isquémico. Neurología Argentina. 12(3). 159–164. 1 indexed citations
16.
Barletta, José, et al.. (2020). COVID-19 associated with AIDS-related disseminated histoplasmosis: a case report. International Journal of STD & AIDS. 31(12). 1222–1224. 36 indexed citations
18.
Ragusa, Martín, et al.. (2013). [Importance of pharmacovigilance in current medical practice].. PubMed. 73(1). 35–8. 4 indexed citations
19.
Avenia, Nicola, et al.. (1991). [Picotamide: use in chronic obliterative arteriopathies of the lower limbs].. PubMed. 137(6). 399–402. 1 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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