Fake citations surged 12-fold since 2023, audit of 2.5 million biomedical papers reveals

New Delhi: An audit of 2.5 million biomedical research papers has revealed that nearly 3,000 contained fake citations absent in scientific databases, highlighting an alarming trend in academic publishing as the use of artificial intelligence (AI) grows.

The papers were published between January 1, 2023, and February 18, 2026, in PubMed Central's Open Access database, managed by the US' National Institutes of Health.

The findings, published in a correspondence article in The Lancet journal, also showed that among 97.1 million verified references, researchers identified 4,046 fake citations across 2,810 papers -- a more than 12-fold growth since 2023, with the sharpest increase beginning mid-2024, coinciding with the rise of AI writing tools.

"This discovery directly impacts patients as medical professionals make treatment decisions based on clinical guidelines," lead researcher Maxim Topaz, associate professor at Columbia University's school of nursing and data science institute, said.

"A medical professional or clinical guideline developer has no way of knowing that the evidence they are relying on does not exist. For example, one paper we reviewed had 18 out of 30 fake references. Some of those citations are already being cited by other papers and appear in systematic reviews that inform clinical care," Topaz said.

The authors wrote, "Among 97.1 million verified references, we identified 4,046 fabricated references across 2,810 papers." "The fabrication rate increased more than 12 times, from approximately four per 10,000 papers in 2023, to 51.3 per 10,000 papers in the fourth quarter of 2025, reaching 56.9 per 10,000 papers in early 2026," they said.

The researchers recommended publishers to verify references with each paper submission and that indexing services add a metadata to records, so that users can assess the accuracy of references.

They also urged major research integrity databases to establish a dedicated category for fake references to enable a systematic tracking and accountability.

The team called on publishers to retroactively screen existing publications and issue corrections or retractions where fake references compromise a paper's conclusions.