Abstract
Context
Adrenal incidentalomas are increasingly being identified during unrelated imaging. Unlike AI clinical management, data on referral patterns in routine practice are lacking.
Objective
To identify factors associated with AI referral
Design
We linked data from imaging reports and outpatient bookings from a large UK teaching hospital. We examined; (i) AI prevalence and (ii) pattern of referral to endocrinology, stratified by age, imaging modality, scan anatomical site, requesting clinical specialty and temporal trends.
Patients
Utilising key radiology phrases to identify scans reporting potential AI, we identified 4,097 individuals from 479,945 scan reports (2015-19).
Main Outcome Measures
Prevalence of AI and referral rates
Results
Overall, AI lesions were identified in 1.2% of scans. They were more prevalent in abdomen CT and MRI scans (3.0% and 0.6%, respectively). Scans performed increased 7.7% year-on-year from 2015-19, with a more pronounced rise in the number with AI lesions (14.7% pa).
Only 394/4097 patients (9.6%) had a documented endocrinology referral code within 90 days, with medical (11.8%) more likely to refer than surgical (7.2%) specialties (p<0.001). Despite prevalence increasing with age, older patients were less likely to be referred (p<0.001).
Conclusions
While overall AI prevalence appeared low, scan numbers are large and rising; the number with identified AI are increasing still further. The poor AI referral rates, even in centres such as ours where dedicated AI multi-disciplinary team meetings and digital management systems are used, highlights the need for new streamlined, clinically-effective systems and processes to appropriately manage the AI workload.
Epidemiology and Management of Ectopic Pregnancy in Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Southeast, Nigeria
