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Global Translational Medicine Clinical algorithms in ART

patient questionnaire with good prognostic value . This 3.2. Gamete production estimation
[21]
screening can distinguish patients at risk of endometriosis Gamete production and reservoir are prerequisites for
early, with bigger treatment possibilities (Table 2).
couples’ fertility and the efficiency of infertility treatments
The algorithm introduced by Chapron et al. is (Table 2).
[21]
known as well as the endometriosis fertility index
(EFI) [22] and is used as a screening tool for the diagnosis 3.3. Sperm
of endometriosis in women with infertility. The The gold standards for sperm counts and motility
algorithm introduced by Chapron et al. is known as the assessment are already established by continuous time-
EFI and is used as a screening tool for the diagnosis of related adjustment according to the big data collection ,
[25]
endometriosis in women with infertility . The risk and a simple algorithm is implemented to ease the
[21]
calculator is based on a patient questionnaire that diagnostic procedure (Table 2). More specifically, the
includes several factors related to endometriosis, such user is required to enter details such as seminal volume,
as symptoms, clinical history, and imaging findings. nemaspermic concentration, progressive motility, vitality,
The risk calculator questionnaire includes six questions and morphology; then, for each of these parameters, the
related to age, duration of infertility, history of surgery for algorithm automatically checks whether any seminal
endometriosis, ovarian reserve, anatomical factors such as alteration is present. According to the 2021 guidelines
tubal patency and uterine anomalies, and the severity of of the World Health Organization, the threshold values
endometriosis based on imaging findings. Each factor is separating the normal range from abnormally low values
assigned a score, and the total score is used to predict the are defined, for each parameter, to represent the fifth
likelihood of endometriosis and the chances of achieving percentile in a sample of almost 3500 fertile men of
a pregnancy. The risk calculator has been shown to have different ages and from 12 different countries around the
good predictive value. For example, the higher the score, globe.
the lower the chances of achieving a pregnancy and the
greater the likelihood of endometriosis. However, it is 3.4. Oocytes
important to note that the risk calculator is not a definitive Oocyte reservoir was more recently divided as hypo-, poor,
diagnostic tool and should be used with other diagnostic normal, and hyper-responders in terms of specific values
methods, such as laparoscopy and histological analysis. of anti-mullerian hormone (AMH) and/or antral follicular
The added value of this presumptive diagnosis count (AFC) for a potential response to the ovarian
obtained with a simple but effective algorithm is obtaining stimulation with gonadotropins [26,27] . A simple algorithm
an early diagnosis with the benefit of its surgical treatment based on the collected data of large communities of fertile
or slowing down its potential evolution. To validate the and infertile women eases the decision-making for ART
benefits of adopting the algorithm, an initial population (Table 2). Similarly to the previously described algorithm
of 2527 patients was used to test its development. The for seminal alteration, the user simply needs to specify the
population was divided into two groups, including AMH blood level (in ng/mL) to implemental classification
1,195 patients in the study group with histologically into one of five possible tiers, ranging from “very low” to
proven endometriosis, and 1332 patients in the control “very high” level.
group who did not have any endometriotic lesions 3.5. COS
during surgery. However, the use of these algorithms is
still too recent to further validate the advantages of their COS is a medical procedure used to stimulate the ovaries
adoption . to produce multiple eggs, typically for use in ART such as
[21]
IVF. Monitoring the response to COS is essential to ensure
It should be emphasized that patients with clinically
diagnosed endometriosis reportedly experience a decrease optimal outcomes. Several algorithms have been developed
to adequately monitor COS, including predicting the
in endometrial receptivity [23,24] . Although the exact response to COS, optimizing treatment protocols, and
mechanism by which endometriosis impairs endometrial
receptivity is not fully understood, ongoing research is personalizing treatment based on individual patient
investigating changes in endometrial gene expression, characteristics.
sex hormone receptors, and cell adhesion molecules . Machine learning is an approach to optimizing COS
[24]
However, the role of specific gene expression mutation monitoring using the dynamics simulation of ovarian
(HOXA 10) in the cyclical endometrial growth and response to COS. Machine learning algorithms can
differentiation may affect the steroid hormones’ effects on be trained on large datasets of patient characteristics,
the tissue for progesterone resistance . including age, body mass index, hormonal levels, and other
[24]

Volume 2 Issue 2 (2023) 4 https://doi.org/10.36922/gtm.0308