Fetal Growth RestrictionNCT06372938
Role of Inflammatory Markers and Doppler Parameters in Late-Onset Fetal Growth Restriction: A Machine Learning Approach
An observational study of Fetal Growth Restriction and Inflammatory Response, run by Ankara Etlik City Hospital at 1 site in Turkey (Türkiye).
Trial summary
Fetal growth restriction (FGR) is a serious complication in pregnancy that can lead to various adverse outcomes. It's classified into early-onset (before 32 weeks) and late-onset (after 32 weeks), with late-onset associated with long-term risks like hypoxemia and developmental delays. Read more about this study
- Who is it for?
- Ages 18 to 45 years, women onlyHealthy volunteers can take part
- Conditions the study is for
- Fetal Growth Restriction, Inflammatory Response
- What is being tested?
- Ultrasound measurement and Laboratory Tests and Inflammatory Markers
- How many people
- 240 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 31 Jan 2024to 20 Jul 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 45 years
- Women only
- Healthy volunteers accepted
- Adult
Study population: This study will include 240 patients between 32-37 weeks of gestational age who were admitted to the Perinatology Clinic, Ministry of Health, Etlik City Hospital, Ankara/Turkey between 2023 and 2024. Head-hip length in the first trimester was used to confirm gestational age. Of the patients included in the study, 120 patients diagnosed with late-onset FGR and 120 patients with developing fetuses according to gestational age will be included in the control group.
Who may be able to join
- Between the ages of 18-45
- Completed their pregnancy follow-up in our center
- Pregnant women whose data can be accessed
- Singleton pregnancies without systemic maternal comorbidities other than FGR
Who cannot join
- Multiple pregnancies
- Having a maternal disease
- Fetal congenital and chromosomal anomalies
- Chronic drug use, alcohol and cigarette use
- Accompanying additional pregnancy complications during follow-up
- Cases whose data cannot be accessed
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site
Etlik City Hospital
Ankara, Yenimahalle, 06170
About this study
Fetal growth restriction (FGR) is a serious complication in pregnancy that can lead to various adverse outcomes. It's classified into early-onset (before 32 weeks) and late-onset (after 32 weeks), with late-onset associated with long-term risks like hypoxemia and developmental delays. The study focuses on the role of inflammation in FGR, introducing new blood markers for better understanding and diagnosis. It also addresses the challenges of using advanced diagnostic tools in low-resource settings and explores the use of machine learning to predict FGR based on inflammatory markers, highlighting the potential of artificial intelligence in overcoming these challenges.
Read the detailed description
Fetal growth restriction (FGR), also known as intrauterine growth restriction, is a prevalent pregnancy complication with potentially negative outcomes for newborns. The condition's causes are varied, involving genetic factors, maternal inflammation, infections, and other pathologies. FGR is categorized based on its onset: early-onset FGR occurs before 32 weeks' gestation, while late-onset happens after 32 weeks. Late-onset FGR, though less risky in perinatal complications compared to early-onset, is linked to an increased risk of hypoxemia and neurodevelopmental delays. Diagnosis primarily relies on ultrasound measurements and Doppler flow analysis of specific arteries. The study highlights the complexity of diagnosing and managing late-onset FGR, emphasizing the unclear pathophysiological mechanisms. It proposes the exploration of inflammatory processes and the potential role of new markers such as the systemic immune inflammation index (SII), systemic inflammatory response index (SIRI), and neutrophil-percentage-to-albumin ratio (NPAR) for understanding FGR. These markers are easily measured through blood tests and are significant in various diseases. The text also discusses the challenges of applying advanced diagnostic methods in low-income countries due to the need for sophisticated equipment, contrasting with the accessibility of artificial intelligence and machine learning models via the internet. The study aimed to assess the impact of inflammatory processes on late-onset FGR by analyzing NPAR, along with other markers, and evaluating their predictive value using machine learning algorithms.
- Conditions
- Fetal Growth Restriction, Inflammatory Response
- Being tested
- Ultrasound measurement, Laboratory Tests and Inflammatory Markers
- Keywords
- fetal growth restriction, inflammatory markers, machine learning algorithms
- Medical subject headings
- Fetal Growth Retardation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Ultrasound measurementDiagnostic test
The diagnosis of FGR was made according to the following Delphi criteria . EFW <3rd percentile or EFW <10th percentile with Doppler evidence of placental dysfunction (Umbilical artery Doppler (UA) pulsatility index (PI) >95th percentile, absence of umbilical artery end-diastolic flow (UAEDF), or reverse-UAEDF and/or cerebroplacental ratio (CPR) <5th percentile).
Laboratory Tests and Inflammatory MarkersDiagnostic test
The laboratory values were measured at the time of FGR diagnosis (between 32 and 37 weeks of pregnancy). After evaluation of hemoglobin (g/dl), leukocytes (103/μL), monocytes (103/μL), lymphocytes (103/μL), neutrophils (103/μL), platelets (103/μL) and albumin (g/dl), the inflammation values were calculated as follows: ;
- SII = Absolute platelet count (APC)* Absolute neutrophil count (ANC) / Absolute lymphocyte count (ALC);
- SIRI = Absolute monocyte count (AMC) * ANC/ ALC;
- NPAR = Proportion of neutrophils (in total leukocytes) (%) × 100/albumin (g/dL).
| Study group | Role | What they receive |
|---|---|---|
| Pregnant Women with Fetal Growth Restriction | 120 patients will be included diagnosed with late-onset Fetal Growth Restriction. Receives: Diagnostic Test: Ultrasound measurement; Diagnostic Test: Laboratory Tests and Inflammatory Markers | |
| Healthy Pregnancies | 120 patients will be included in a control group of developing fetuses according to gestational age. Receives: Diagnostic Test: Ultrasound measurement; Diagnostic Test: Laboratory Tests and Inflammatory Markers |
What is being measured
The primary outcome is the main question the study is designed to answer.
Evaluation of data
To determine the statistical correlation of demographic data and inflammatory indices of pregnancy period with diagnostic ultrasonographic measurements (fetal biometric measurements and fetal doppler findings) related to fetal growth retardation in SPSS environment and to reveal the importance of the relationship.
Measured: Within 1 month of data collection
Secondary outcomes (1)
Machine learning modeling
The RandomForestClassifier class classification model will be developed by moving the data from the SPSS environment to the Python environment. Machine learning system modeling will be developed where the model will learn from the training set using patient data and use this information to predict future data.
Measured: Within 1 month of data after data analysis
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Apr 2024
- Study start31 Jan 2024
- Primary completion6 Jul 2024 (estimated)
- Study completion20 Jul 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Fetal Growth RestrictionStudies of the same condition, open and under way.
- More trials run by Ankara Etlik City HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 240 participants (actual)
Sponsor and investigators
- Lead sponsor
- Ankara Etlik City Hospital
- Sponsor type
- Other government
- Responsible party
- Principal investigator, Can Ozan Ulusoy, Ankara Etlik City Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06372938
- Sponsor's protocol ID
- AEŞH-BADEK-2024-43
- Status last verified
- Jul 2024
- First submitted
- 7 Apr 2024
- Last updated
- 8 Jul 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Due to hospital policy, data cannot be shared. However, if necessary, the principal investigator can be contacted.
Publications
Ulusoy CO, Kurt A, Seyhanli Z, Hizli B, Bucak M, Agaoglu RT, Oguz Y, Yucel KY. Role of Inflammatory Markers and Doppler Parameters in Late-Onset Fetal Growth Restriction: A Machine-Learning Approach. Am J Reprod Immunol. 2024 Oct;92(4):e70004. doi: 10.1111/aji.70004.
PubMed 39422068
Study at a glance
From the registry record, last updated by the sponsor on 8 Jul 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Role of Inflammatory Markers and Doppler Parameters in Late-Onset Fetal Growth Restriction: A Machine Learning Approach
- ClinicalTrials.gov ID
- NCT06372938
- Acronym / sponsor ID
- AEŞH-BADEK-2024-43
- Conditions
- Fetal Growth Restriction, Inflammatory Response
- Keywords
- fetal growth restriction, inflammatory markers, machine learning algorithms
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 240 participants (actual)
- Lead sponsor
- Ankara Etlik City HospitalOther government
- Study start
- 31 Jan 2024 (actual)
- Primary completion
- 6 Jul 2024 (estimated)
- Study completion
- 20 Jul 2024 (estimated)
- First posted
- 18 Apr 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Fetal growth restriction (FGR) is a serious complication in pregnancy that can lead to various adverse outcomes. It's classified into early-onset (before 32 weeks) and late-onset (after 32 weeks), with late-onset associated with long-term risks like hypoxemia and developmental delays. The study focuses on the role of inflammation in FGR, introducing new blood markers for better understanding and diagnosis. It also addresses the challenges of using advanced diagnostic tools in low-resource settings and explores the use of machine learning to predict FGR based on inflammatory markers, highlighting the potential of artificial intelligence in overcoming these challenges.
Detailed description
Fetal growth restriction (FGR), also known as intrauterine growth restriction, is a prevalent pregnancy complication with potentially negative outcomes for newborns. The condition's causes are varied, involving genetic factors, maternal inflammation, infections, and other pathologies. FGR is categorized based on its onset: early-onset FGR occurs before 32 weeks' gestation, while late-onset happens after 32 weeks. Late-onset FGR, though less risky in perinatal complications compared to early-onset, is linked to an increased risk of hypoxemia and neurodevelopmental delays. Diagnosis primarily relies on ultrasound measurements and Doppler flow analysis of specific arteries. The study highlights the complexity of diagnosing and managing late-onset FGR, emphasizing the unclear pathophysiological mechanisms. It proposes the exploration of inflammatory processes and the potential role of new markers such as the systemic immune inflammation index (SII), systemic inflammatory response index (SIRI), and neutrophil-percentage-to-albumin ratio (NPAR) for understanding FGR. These markers are easily measured through blood tests and are significant in various diseases. The text also discusses the challenges of applying advanced diagnostic methods in low-income countries due to the need for sophisticated equipment, contrasting with the accessibility of artificial intelligence and machine learning models via the internet. The study aimed to assess the impact of inflammatory processes on late-onset FGR by analyzing NPAR, along with other markers, and evaluating their predictive value using machine learning algorithms.
Study design
- Observational model
- Case-control
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Pregnant Women with Fetal Growth Restriction | – | Diagnostic Test: Ultrasound measurement, Diagnostic Test: Laboratory Tests and Inflammatory Markers120 patients will be included diagnosed with late-onset Fetal Growth Restriction. |
| Healthy Pregnancies | – | Diagnostic Test: Ultrasound measurement, Diagnostic Test: Laboratory Tests and Inflammatory Markers120 patients will be included in a control group of developing fetuses according to gestational age. |
Who may qualify
- Ages
- 18 to 45 years
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Adult
- Study population
- This study will include 240 patients between 32-37 weeks of gestational age who were admitted to the Perinatology Clinic, Ministry of Health, Etlik City Hospital, Ankara/Turkey between 2023 and 2024. Head-hip length in the first trimester was used to confirm gestational age. Of the patients included in the study, 120 patients diagnosed with late-onset FGR and 120 patients with developing fetuses according to gestational age will be included in the control group.
Key inclusion criteria (4 listed)
- Between the ages of 18-45
- Completed their pregnancy follow-up in our center
- Pregnant women whose data can be accessed
- Singleton pregnancies without systemic maternal comorbidities other than FGR
Key exclusion criteria (6 listed)
- Multiple pregnancies
- Having a maternal disease
- Fetal congenital and chromosomal anomalies
- Chronic drug use, alcohol and cigarette use
- Accompanying additional pregnancy complications during follow-up
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Ultrasound measurementThe diagnosis of FGR was made according to the following Delphi criteria . EFW <3rd percentile or EFW <10th percentile with Doppler evidence of placental dysfunction (Umbilical artery Doppler (UA) pulsatility index (PI) >95th percentile, absence of umbilical artery end-diastolic flow (UAEDF), or reverse-UAEDF and/or cerebroplacental ratio (CPR) <5th percentile). | Diagnostic test | Healthy Pregnancies, Pregnant Women with Fetal Growth Restriction |
| Laboratory Tests and Inflammatory MarkersThe laboratory values were measured at the time of FGR diagnosis (between 32 and 37 weeks of pregnancy). After evaluation of hemoglobin (g/dl), leukocytes (103/μL), monocytes (103/μL), lymphocytes (103/μL), neutrophils (103/μL), platelets (103/μL) and albumin (g/dl), the inflammation values were calculated as follows: ; * SII = Absolute platelet count (APC)* Absolute neutrophil count (ANC) / Absolute lymphocyte count (ALC); * SIRI = Absolute monocyte count (AMC) * ANC/ ALC; * NPAR = Proportion of neutrophils (in total leukocytes) (%) × 100/albumin (g/dL). | Diagnostic test | Healthy Pregnancies, Pregnant Women with Fetal Growth Restriction |
Primary outcome
Evaluation of data
Time frame: Within 1 month of data collection
To determine the statistical correlation of demographic data and inflammatory indices of pregnancy period with diagnostic ultrasonographic measurements (fetal biometric measurements and fetal doppler findings) related to fetal growth retardation in SPSS environment and to reveal the importance of the relationship.
1 secondary outcome
Machine learning modeling
Time frame: Within 1 month of data after data analysis
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Jul 2024.
- Derived from this study: PubMed 39422068Ulusoy CO, Kurt A, Seyhanli Z, Hizli B, Bucak M, Agaoglu RT, Oguz Y, Yucel KY. Role of Inflammatory Markers and Doppler Parameters in Late-Onset Fetal Growth Restriction: A Machine-Learning Approach. Am J Reprod Immunol. 2024 Oct;92(4):e70004. doi: 10.1111/aji.70004.
- Individual participant dataSharing planned: No. Due to hospital policy, data cannot be shared. However, if necessary, the principal investigator can be contacted.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Fetal Growth Restriction and Inflammatory Response, run by Ankara Etlik City Hospital at 1 site in Turkey (Türkiye).
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 8 Jul 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Turkey (Türkiye). Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Evaluation of data (time frame: Within 1 month of data collection). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06372938, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Jul 2024.