The formal comment titled “Updated science-wide author databases of standardized citation indicators” by Ioannidis et al., which provides an update to their original 2019 article that introduced scientific standardized citation metrics databases of authors, included 26 Bangladeshi scientists in the top 2% of scientists based on career-long citation impact up until 2019. However, manual curation of the database revealed 41% error of their listed Bangladeshi researchers. We do not think these errors are entirely due to the shortcomings of the algorithms employed to create the database. The quality of indexing on Scopus can be poor and confusing, which was evident from our experience in manual searching, and the citation quality of Scopus was recently brought into question, he citation database struggles to correctly identify and group publications from scientists with similar or identical names, and its ‘affiliations’ section is often confusing. However, we realize the difficulty in correctly distinguishing between scientists of similar names and/or backgrounds and keeping track of their changes in institutions, and suggest that a unique identity be mandated to every scientist that publishes a scientific paper. As for the Ioannidis et. al. database, we think the algorithms could have been made to better represent data from confusing Scopus query results with conflicting entries by either marking such entries in the database as inconclusive, or going deeper into refining the query results. Author misindentification has major social and professional implications. We advise caution while interpreting results from the current one published, and suggest revisiting the database to improve the accuracy of its attribution. A Table of our manually checked articles for each researchers and details of our study can be found at Chowdhury, Farhan Rahman; Islam, Tofazzal (2021): Author misidentification results in highly misleading citation metrics. figshare. Journal contribution. https://doi.org/10.6084/m...