The Effectiveness of Advanced Decision Support Tool (OPT-IVF) for IVF Treatment

NCT06179420 | Not Yet Recruiting

• 1 other identifier: UKMPPI/111/8/JEP-2023-735
• Study Type: observational
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

This prospective study is subject to approval of institutional medical research ethics committee. Patient undergoing second cycle IVF will be enrolled into the intervention group. Intervention involved using a clinical decision support tool, Opt-IVF to guide gonadotrophins dosing and trigger dates for a personalized controlled ovarian stimulation cycle based on the distribution of follicle sizes on day 1 and day 5, and hormone dosages given on day 1 to 4. Patients will undergo transvaginal ultrasound exam on day 1 and day 5 of the cycle to determine the number and size of follicles present. The data is used in the Opt-IVF decision support tool to suggest Gonadotropin dosage for D5 and beyond and to recommend the antagonist start day and trigger day. Clinical investigators will not override the Opt-IVF recommended dosage in any patients.

Conditions

Fertility Issues

Outcome Measures

Primary Outcomes (3)

• total cumulative dosage of Gonadotropins

  number of total dosage that utilize during one cycle of IVF treatment

  for 1 year duration

• Total number of matured oocytes

  number of matured oocytes following the stimulation protocol

  for 1 year duration

• total number of good quality blastocyst

  total blastocyst achieved after each sti,ulation protocol

  for 1 year duration

Study Arms (2)

standard IVF regime protocol based on clinician decision

The dosage of gonadotrophin and time of transvaginal ultrasound decided by clinician

Other: total cumulative gonadotrophin usage

clinical decision support tool, Opt-IVF for IVF regime protocol

The dosage of gonadotrophin and time of transvaginal ultrasound decided by a clinical decision support tool ( OPt -IVF)

Other: total cumulative gonadotrophin usage

Interventions

total cumulative gonadotrophin usage OTHER

total dosage in IU

Also known as: number of matured oocytes, number of qood quality blastocyst

clinical decision support tool, Opt-IVF for IVF regime protocol; standard IVF regime protocol based on clinician decision

Eligibility Criteria

• Age: 18 Years - 45 Years
• Sex: female
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Probability Sample

Study Population

Patient who had failed their first IVF treatment

You may qualify if:

• Patient undergoing 2nd cycle of IVF

You may not qualify if:

• Polycystic ovarian syndrome patient

Sponsors & Collaborators

• National University of Malaysia: lead

Study Sites (1)

Advanced Reproductive Centre

Kuala Lumpur, Kuala Lumpur, 56000, Malaysia

Location

Related Publications (6)

• Leahy BD, Racowsky C, Needleman D. Inferring simple but precise quantitative models of human oocyte and early embryo development. J R Soc Interface. 2021 Sep;18(182):20210475. doi: 10.1098/rsif.2021.0475. Epub 2021 Sep 8.

  PMID: 34493094 RESULT

• Simopoulou M, Sfakianoudis K, Antoniou N, Maziotis E, Rapani A, Bakas P, Anifandis G, Kalampokas T, Bolaris S, Pantou A, Pantos K, Koutsilieris M. Making IVF more effective through the evolution of prediction models: is prognosis the missing piece of the puzzle? Syst Biol Reprod Med. 2018 Oct;64(5):305-323. doi: 10.1080/19396368.2018.1504347. Epub 2018 Aug 8.

  PMID: 30088950 RESULT

• Hariton E, Chi EA, Chi G, Morris JR, Braatz J, Rajpurkar P, Rosen M. A machine learning algorithm can optimize the day of trigger to improve in vitro fertilization outcomes. Fertil Steril. 2021 Nov;116(5):1227-1235. doi: 10.1016/j.fertnstert.2021.06.018. Epub 2021 Jul 10.

  PMID: 34256948 RESULT

• Fanton M, Nutting V, Rothman A, Maeder-York P, Hariton E, Barash O, Weckstein L, Sakkas D, Copperman AB, Loewke K. An interpretable machine learning model for individualized gonadotrophin starting dose selection during ovarian stimulation. Reprod Biomed Online. 2022 Dec;45(6):1152-1159. doi: 10.1016/j.rbmo.2022.07.010. Epub 2022 Jul 28.

  PMID: 36096871 RESULT

• Correa N, Cerquides J, Arcos JL, Vassena R. Supporting first FSH dosage for ovarian stimulation with machine learning. Reprod Biomed Online. 2022 Nov;45(5):1039-1045. doi: 10.1016/j.rbmo.2022.06.010. Epub 2022 Jun 18.

  PMID: 35915001 RESULT

• Curchoe CL, Flores-Saiffe Farias A, Mendizabal-Ruiz G, Chavez-Badiola A. Evaluating predictive models in reproductive medicine. Fertil Steril. 2020 Nov;114(5):921-926. doi: 10.1016/j.fertnstert.2020.09.159.

  PMID: 33160514 RESULT

MeSH Terms

Conditions

Infertility

Condition Hierarchy (Ancestors)

Genital Diseases; Urogenital Diseases

Study Officials

• Muhammad Azrai Abu, MD

  Department Of Obstetrics And Gynecology, Ukm Medical Centre

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Muhammad Azrai Abu

CONTACT

+60196410944; azraiabu1983@gmail.com

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Prof

Study Record Dates

• First Submitted: December 10, 2023
• First Posted: December 21, 2023
• Study Start: March 13, 2024
• Primary Completion: January 31, 2026
• Study Completion: January 31, 2026
• Last Updated: March 15, 2024

Record last verified: 2024-03

Data Sharing

• IPD Sharing: Will not share

Locations

MY (1)