Clinician Bias May be a Factor in Underdiagnoses of Prediabetes, According to Research Presented at ENDO 2022

ENDO 2022. Age, body mass index, gender, race, and certain comorbidities may influence a diagnosis of prediabetes in primary care settings, suggests new study.

A patient’s age, body mass index (BMI), gender, race, and certain comorbidities may influence a diagnosis of prediabetes in primary care settings, according to new research presented at ENDO 2022, the Endocrine Society’s annual meeting held June 11-14, 2022, in Atlanta.

Estimates from the US Centers for Disease Control and Prevention (CDC) show 80% to 90% of patients with prediabetes are unaware of their diagnosis, according to one of the study’s authors An V. Nguyen, MD, a resident with a focus on general endocrinology at Scripps Clinic/Scripps Green Hospital in La Jolla, California.

“This study demonstrates that the condition is often appropriately screened, but diagnosis and treatment were less consistent,” said Nguyen in an Endocrine Society press release. “Healthcare providers seem to rely heavily on a Hemoglobin A1c (HbA1c) test, which measures average blood glucose over three months, to make the diagnosis.”

Nguyen and colleagues conducted a retrospective chart review of patients seen in primary care clinics at Scripps Clinics’ 5 locations from January 1, 2018, through December 31, 2019. The team first identified all adults who qualified for a prediabetes diagnosis based on fasting blood glucose (FBG) or HbA1c levels. Persons with a billable condition were included in the intervention group and the remaining participants were part of the control group.

Researchers examined whether factors such as age, BMI, gender, race, and certain comorbidities were associated with a correct diagnosis of prediabetes, according to the press release.

In total, 20 061 patients were included in the study, of whom 7575 were correctly diagnosed with prediabetes. Only 37% of participants were diagnosed with prediabetes or impaired FBG; of those, 93% qualified by HbA1c levels.

Having obesity or overweight, being female, of Asian race, and living with comorbidities including lipid disorders and conditions requiring steroids were associated with an accurate diagnosis. Other factors, such as being male, Black, and having comorbidities requiring immunosuppressants, antineoplastics, and iron replacements were negatively correlated with an accurate diagnosis of prediabetes.

“Overall, this research reveals inherent biases that health care providers might have when diagnosing prediabetes and serves as a call for reflection within the provider’s practice,” said Nguyen.