Introduction
Check tags in PubMed/Medline are used to quickly identify key features of studies and study subjects, such as age groups. They are frequently incorporated in search strategies. However, such searches are reliant on check tags being dependable in their application. This study sought to evaluate some irregularities the author noticed around check tags.

Method
Searches were run in Ovid Medline for a series of commonly used check tags in records of publications from 2015 to 2024. The absolute number of records employing these tags and the proportion of records employing these tags was then compared to the results of similar searches in Embase, PsycINFO, and CINAHL.

Results
There was a sharp drop in both absolute and proportional numbers of most check tags on Medline records published over this time period. For example, use of female/ decreased from 30% of Medline records for papers published in 2019 to only 10% of records for papers published in 2023. However, PsycINFO and Embase indexing patterns differed markedly.

Discussion
The trends noted have significant implications for use of check tags for searching in PubMed or Medline. Results give insight into how indexing varies between PubMed/Medline and other commonly used biomedical databases.

Introduction: The search filter ‘exp animals/ not humans.sh’ is a well-established method in knowledge synthesis used to exclude non-human studies in Ovid Medline. We previously reported on the impact of the Medical Text Indexer-Auto (MTIA) algorithm for automated assignment of MeSH terms on the utility of this filter for knowledge synthesis projects. We sought to update our reporting to account for the 2024 implementation of the new Medical Text Indexer-NeXt Generation (MTIX) algorithm, which uses a machine-learning model for MeSH term assignment.

Methods: As in the previous study, we conducted a search in Ovid Medline using the Cochrane Highly Sensitive Search Strategy. We isolated the results indexed by the automated method and specifically excluded by the non-human-studies filter in the timeframe since MTIX was implemented. We screened these results using Covidence to identify human studies.

Results: The sample demonstrated a significant improvement over our assessment of MTIA: only 1% (25/2285) of studies screened were inappropriately excluded human studies - compared to 4.2% in the MTIA assessment - and none of these were in a clinical context. Records describing both animal and human studies continue to be a common source of inappropriate exclusion.

Discussion: Our findings suggest that the filter is much less likely to inappropriately exclude human studies indexed by MTIX (records indexed beginning April 2024) than MTIA (studies indexed between 2019 and April 2024). However, we still recommend caution with the use of the human studies filter, especially for records indexed between 2019-2024.