Ectopic pregnancy. Diagnostic and therapeutic algorithms minimizing surgical intervention

Area of Science:

• Reproductive Medicine
• Diagnostic Imaging
• Clinical Management

Background:

• Ectopic pregnancy diagnosis and treatment traditionally involve invasive procedures.
• Timely and accurate diagnosis is crucial to prevent life-threatening complications.

Purpose of the Study:

• To present novel diagnostic and treatment algorithms for ectopic pregnancy.
• To evaluate the impact of these algorithms on diagnostic accuracy, management strategies, and patient outcomes.

Main Methods:

• Development of a comprehensive diagnostic algorithm including patient history, physical exam, human chorionic gonadotropin (hCG), progesterone levels, Doppler sonography, and endometrial curettage.
• Integration of a treatment algorithm encompassing expectant, medical (methotrexate), and surgical management options.

Main Results:

• Earlier diagnosis of ectopic pregnancy and a significant reduction in ruptured cases.
• Virtual elimination of diagnostic laparoscopy and culdocentesis.
• Increased utilization of methotrexate for medical management and a rise in expectant (non-invasive) treatment approaches.

Conclusions:

• The proposed algorithms facilitate earlier and more accurate ectopic pregnancy diagnosis, minimizing the need for invasive procedures.
• These strategies enhance the use of conservative management options, including medical and expectant treatments.
• The algorithms are adaptable for various clinical settings, particularly for at-risk populations or when ectopic pregnancy is suspected.