E. Masiello

562 total citations
8 papers, 299 citations indexed

About

E. Masiello is a scholar working on Endocrinology, Diabetes and Metabolism, Pathology and Forensic Medicine and Molecular Biology. According to data from OpenAlex, E. Masiello has authored 8 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Endocrinology, Diabetes and Metabolism, 4 papers in Pathology and Forensic Medicine and 1 paper in Molecular Biology. Recurrent topics in E. Masiello's work include Thyroid Disorders and Treatments (8 papers), Ophthalmology and Eye Disorders (4 papers) and Pituitary Gland Disorders and Treatments (3 papers). E. Masiello is often cited by papers focused on Thyroid Disorders and Treatments (8 papers), Ophthalmology and Eye Disorders (4 papers) and Pituitary Gland Disorders and Treatments (3 papers). E. Masiello collaborates with scholars based in Italy and Netherlands. E. Masiello's co-authors include Maria Laura Tanda, P. Premoli, Eliana Piantanida, Daniela Gallo, Luigi Bartalena, Claudio Cusini, Silvia Ippolito, S. Rosetti, Giovanni Veronesi and Francesco Trimarchi and has published in prestigious journals such as Journal of Endocrinological Investigation.

In The Last Decade

E. Masiello

8 papers receiving 296 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
E. Masiello Italy	8	225	116	54	25	25	8	299
P. Premoli Italy	10	241 1.1×	140 1.2×	58 1.1×	26 1.0×	32 1.3×	11	337
Claudio Cusini Italy	7	152 0.7×	91 0.8×	60 1.1×	16 0.6×	11 0.4×	7	238
J. W. M. Nin Netherlands	5	221 1.0×	50 0.4×	26 0.5×	5 0.2×	23 0.9×	7	402
Christine P. Limonte United States	8	63 0.3×	31 0.3×	22 0.4×	8 0.3×	19 0.8×	18	171
H C Lee South Korea	10	97 0.4×	69 0.6×	80 1.5×	9 0.4×	8 0.3×	13	356
Jiashu Yu China	5	181 0.8×	33 0.3×	11 0.2×	38 1.5×	24 1.0×	7	215
Keitarou Kawasaki Japan	10	181 0.8×	39 0.3×	197 3.6×	29 1.2×	25 1.0×	14	420
Kazuhide Ishikura Japan	6	88 0.4×	15 0.1×	94 1.7×	14 0.6×	46 1.8×	12	203
María Luz Muzzio Argentina	7	150 0.7×	31 0.3×	71 1.3×	6 0.2×	15 0.6×	14	298
Silvia A. Eskes Netherlands	7	200 0.9×	30 0.3×	21 0.4×	17 0.7×	43 1.7×	9	311

Countries citing papers authored by E. Masiello

Since Specialization

Citations

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

Fields of papers citing papers by E. Masiello

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of E. Masiello

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

All Works

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8 of 8 papers shown

Ippolito, Silvia, Claudio Cusini, Paolo Lasalvia, et al.. (2020). Change in newly diagnosed Graves’ disease phenotype between the twentieth and the twenty-first centuries: meta-analysis and meta-regression. Journal of Endocrinological Investigation. 44(8). 1707–1718. 28 indexed citations

Piantanida, Eliana, Silvia Ippolito, Daniela Gallo, et al.. (2020). The interplay between thyroid and liver: implications for clinical practice. Journal of Endocrinological Investigation. 43(7). 885–899. 88 indexed citations

Rosetti, S., Maria Laura Tanda, Giovanni Veronesi, et al.. (2019). Oral steroid prophylaxis for Graves’ orbitopathy after radioactive iodine treatment for Graves’ disease is not only effective, but also safe. Journal of Endocrinological Investigation. 43(3). 381–383. 16 indexed citations

Masiello, E., Giovanni Veronesi, Daniela Gallo, et al.. (2018). Antithyroid drug treatment for Graves’ disease: baseline predictive models of relapse after treatment for a patient-tailored management. Journal of Endocrinological Investigation. 41(12). 1425–1432. 50 indexed citations

Gallo, Daniela, Eliana Piantanida, Giovanni Veronesi, et al.. (2017). Physical performance in newly diagnosed hypothyroidism: a pilot study. Journal of Endocrinological Investigation. 40(10). 1099–1106. 15 indexed citations

Bartalena, Luigi, Giovanna Rotondo Dottore, Eliana Piantanida, et al.. (2016). Effects of selenium on short-term control of hyperthyroidism due to Graves’ disease treated with methimazole: results of a randomized clinical trial. Journal of Endocrinological Investigation. 40(3). 281–287. 45 indexed citations

Gallo, Daniela, Giovanni Veronesi, E. Masiello, et al.. (2016). Masked hypertension in newly diagnosed hypothyroidism: a pilot study. Journal of Endocrinological Investigation. 39(10). 1131–1138. 17 indexed citations

Bartalena, Luigi, E. Masiello, Flavia Magri, et al.. (2016). The phenotype of newly diagnosed Graves’ disease in Italy in recent years is milder than in the past: results of a large observational longitudinal study. Journal of Endocrinological Investigation. 39(12). 1445–1451. 40 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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