Abstract
Objective
To evaluate clinical outcomes for patients undergoing IVF treatment where an artificial intelligence (AI) platform was utilized by clinicians to help determine the optimal starting dose of FSH and timing of trigger injection.
Design
Prospective clinical trial with historical control arm
Setting
Four physicians from two assisted reproductive technology treatment centers in the United States participated in the study.
Patients
The treatment arm included patients undergoing autologous IVF cycles between December 2022 - April 2023 where the physician use AI to help select starting dose of follicle stimulating hormone (FSH) and trigger injection timing (N = 246). The control arm included historical patients treated where the same doctor did not use AI between September 2021 - September 2022.
Intervention
None.
Main Outcome Measure
Total FSH used and average number of mature metaphase II (MII)oocytes.
Results
There was a non-significant trend towards improved patient outcomes and a reduction in FSH with physician use of AI. Overall, the average number of MIIs in the treatment vs. control arm was 12.20 vs 11.24 (improvement = 0.96, p=0.16). The average number of oocytes retrieved in the treatment vs. control arm was 16.01 vs 14.54 (improvement = 1.47, p = 0.08). The average total FSH in the treatment arm was 3671.95 IUs and the average in the control arm was 3846.29 IUs (difference=-174.35 IUs, p=0.13).
Conclusion
There was a trend towards improved laboratory outcomes with physician use of AI.. Together, this suggests that AI can safely assist in refining the starting dose of FSH while narrowing down the timing of the trigger injection during ovarian stimulation, benefiting the patient in optimizing the count of MII oocytes retrieved,