<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03831490</url>
  </required_header>
  <id_info>
    <org_study_id>Dnr 2018-231</org_study_id>
    <nct_id>NCT03831490</nct_id>
  </id_info>
  <brief_title>Study for Improving Maternal, Pregnancy and Child Outcomes</brief_title>
  <acronym>IMPACT</acronym>
  <official_title>IMPACT - Study for Improving Maternal, Pregnancy and Child Outcomes</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Uppsala University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Thermo Fisher Scientific, Inc</agency>
      <agency_class>Industry</agency_class>
    </collaborator>
    <collaborator>
      <agency>Perkin Elmer Inc.</agency>
      <agency_class>Industry</agency_class>
    </collaborator>
    <collaborator>
      <agency>Roche Pharma AG</agency>
      <agency_class>Industry</agency_class>
    </collaborator>
  </sponsors>
  <source>Uppsala University</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The overall aims of this proposal are to improve, facilitate, optimize and equalize the&#xD;
      existing screening system for adverse pregnancy outcomes in early pregnancy in order to limit&#xD;
      adverse consequences for both the mother and infant, by:&#xD;
&#xD;
        1. Creating a Swedish prediction model with population-specific risk factors, optimized for&#xD;
           the Swedish health care system, identifying high-risk women for preterm preeclampsia and&#xD;
           validate the model within the cohort. This would give us the possibility to start&#xD;
           aspirin prophylaxis in time, which has been proven to reduce the risk of developing&#xD;
           preterm preeclampsia by 50%.&#xD;
&#xD;
        2. Validating the Fetal Medicine Foundation prediction model for detection of preterm (&lt; 37&#xD;
           gestational weeks) preeclampsia in a Swedish population.&#xD;
&#xD;
        3. Creating a prediction model identifying high-risk women for overall preeclampsia during&#xD;
           pregnancy and birth of a small for gestational age infant in order to plan&#xD;
           individualized surveillance for early detection, which has been proven beneficial for&#xD;
           both the mother and infant.&#xD;
&#xD;
        4. Creating a national pregnancy biobank with blood samples and individual clinical&#xD;
           registry data, including pregnancy outcomes, enabling future research on prevention and&#xD;
           early detection for various adverse pregnancy outcomes which could be such as preterm&#xD;
           birth and intrauterine growth restriction.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Preeclampsia is a pregnancy-specific syndrome that affects 3-5% of all pregnancies and&#xD;
      traditionally defined as new onset hypertension (blood pressure ≥ 140/90) and proteinuria&#xD;
      after gestational week 20. The syndrome is one of the leading causes of maternal and&#xD;
      perinatal acute morbidity and long-term disability and accounts for about 50 000 maternal&#xD;
      deaths annually worldwide. Morbidity risks for the mother include seizures, intracranial&#xD;
      hemorrhage, kidney failure, heart failure and pulmonary edema. Risks for the fetus include&#xD;
      fetal growth restriction, preterm birth and hypoxia. Generally preterm preeclampsia (delivery&#xD;
      before 37 weeks) is more severe than term preeclampsia.&#xD;
&#xD;
      Risk assessment for preeclampsia enables both prevention and early prediction of the disease.&#xD;
&#xD;
      Swedish risk assessment for preeclampsia in early pregnancy is still obtained by maternal&#xD;
      history and characteristics, without medical examinations, which only detects about 30% of&#xD;
      women that will develop preeclampsia. Risk factors are evaluated individually without being&#xD;
      incorporated into a combined model that would allow multivariable analysis. This approach has&#xD;
      been proven to be poor due to low specificity and sensitivity. Lately a more complex&#xD;
      prediction model has been developed by the Fetal Medicine Foundation, using multivariable&#xD;
      analysis and including serum biomarkers and physiological measurements reflecting maternal&#xD;
      adaption to pregnancy. Intervention with aspirin given to identified high-risk pregnancies&#xD;
      according this model has been shown to decrease the incidence of preterm (&lt; 37 gestational&#xD;
      weeks) preeclampsia (OR: 0.38; 95% CI 0.20-0.74), compared to placebo. Detection rates and&#xD;
      cut-off values have been shown to vary between populations, depending on differences in&#xD;
      population characteristics and incidence of disease, overfitting of the original model and&#xD;
      differences in healthcare systems. Therefore, the model needs to be validated in Sweden.&#xD;
      Further, the Fetal Medicine Foundation prediction model includes expensive covariates such as&#xD;
      several biochemical markers and uterine artery Doppler. There is a need to create, validate&#xD;
      and implement a cost-effective prediction model for first trimester screening for&#xD;
      preeclampsia in a Swedish population, with the purpose to select who might benefit from&#xD;
      aspirin prophylaxis to prevent preterm preeclampsia. We will study preeclampsia both&#xD;
      according to the definition used in Sweden prior to 2020 and the definition used hereafter.&#xD;
&#xD;
      Early detection of preeclampsia remains one of the major focuses of maternal health care and&#xD;
      is emphasized by the WHO, since it has proven to be beneficial for both the mother and unborn&#xD;
      child. Small-for-gestational-age fetuses not identified before delivery have an increased&#xD;
      risk of adverse perinatal outcomes, compared to those identified during pregnancy.&#xD;
      Identification of high-risk pregnancies is therefore important in early pregnancy not only to&#xD;
      plan for prophylactic interventions, but also to optimize surveillance and to plan&#xD;
      deliveries. Today most Swedish women attend the same maternal health care program with&#xD;
      increasing number of visits in the end of pregnancy. By risk identification in early&#xD;
      pregnancy we can individualize maternal health care and target women at high risk early in&#xD;
      pregnancy. High-risk pregnancies can be referred to specialized health care and normal&#xD;
      pregnancies followed at the basic maternal health care.&#xD;
&#xD;
      The Swedish registry data is unique and combining it with a biobank containing blood samples&#xD;
      from the first trimester could improve maternal healthcare and in the long run reduce adverse&#xD;
      outcomes for Swedish women. A national first trimester pregnancy biobank would facilitate&#xD;
      future research on prevention and prediction of pregnancy complications.&#xD;
&#xD;
      A total of 13000 enrolled individuals will be needed for creating the model and for&#xD;
      validation.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Active, not recruiting</overall_status>
  <start_date type="Actual">November 9, 2018</start_date>
  <completion_date type="Anticipated">October 1, 2023</completion_date>
  <primary_completion_date type="Anticipated">September 30, 2023</primary_completion_date>
  <study_type>Observational [Patient Registry]</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <target_duration>9 Months</target_duration>
  <primary_outcome>
    <measure>Preterm Preeclampsia</measure>
    <time_frame>delivery &lt;37 gestational weeks</time_frame>
    <description>Preeclampsia according to the Swedish definition, currently new onset hypertension (blood pressure ≥ 140/90) and proteinuria after gestational week 20.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Small for gestational age</measure>
    <time_frame>at delivery</time_frame>
    <description>birthweight ≤ - 2 SD according to the Swedish reference curve</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Overall preeclampsia</measure>
    <time_frame>At delivery</time_frame>
    <description>Preeclampsia according to the Swedish definition, currently new onset hypertension (blood pressure ≥ 140/90) and proteinuria after gestational week 20.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Preterm preeclampsia</measure>
    <time_frame>delivery &lt;37 gestational weeks</time_frame>
    <description>Preeclampsia according to the Swedish definition prior to 2020 as well as the definition hereafter</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Term preeclampsia</measure>
    <time_frame>delivery &gt;/=37 gestational weeks</time_frame>
    <description>Preeclampsia according to the Swedish definition prior to 2020 as well as the definition hereafter</description>
  </secondary_outcome>
  <enrollment type="Actual">13000</enrollment>
  <condition>Pre-Eclampsia</condition>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>history</intervention_name>
    <description>combining these 4 interventions will great an algorithm predicting preeclampsia</description>
    <other_name>mean material blod pressure</other_name>
    <other_name>PlGF - blood sample</other_name>
    <other_name>a- uterine doppler</other_name>
  </intervention>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      At centers with biobank possibilities, serum, plasma and buffy-coat samples will be collected&#xD;
      at the same time as the serum sample for analyze of Placental Growth Factor. The samples for&#xD;
      the biobank will be stored for future research related to prediction, diagnosis and&#xD;
      prevention of pregnancy complications.&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        All women attending a first trimester ultrasound at the study sites, which involves both&#xD;
        tertiary as well as secondary hospitals and out-patient clinics.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Women with a Swedish personal identity number, who adhere to maternal care program&#xD;
             before the end of the first trimester and have a planned first trimester scan (weeks&#xD;
             11-13) are eligible for the study.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Maternal age &lt;18 years or language-barrier despite interpreter and written&#xD;
             information.&#xD;
      </textblock>
    </criteria>
    <gender>Female</gender>
    <gender_based>Yes</gender_based>
    <gender_description>pregnant women</gender_description>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Lina Bergman, MD, PhD</last_name>
    <role>Study Chair</role>
    <affiliation>Uppsala University</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Peter Lindgren, MD, PhD</last_name>
    <role>Study Chair</role>
    <affiliation>Karolinska Institutet</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Anna Sandström, MD, PhD</last_name>
    <role>Study Chair</role>
    <affiliation>Karolinska Institutet</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Peter Conner, Ass Prof</last_name>
    <role>Study Chair</role>
    <affiliation>Karolinska Institutet</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Marius Kublickas, Ass Prof</last_name>
    <role>Study Chair</role>
    <affiliation>Karolinska Institutet</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Stefan Hansson, Professor</last_name>
    <role>Study Chair</role>
    <affiliation>Lund University</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Eskilstuna hospital</name>
      <address>
        <city>Eskilstuna</city>
        <state>Sörmland</state>
        <country>Sweden</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Södra Älvsborgs sjukhus</name>
      <address>
        <city>Borås</city>
        <state>Västra Götalandsregionen</state>
        <country>Sweden</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Norra Älvsborgs sjukhus</name>
      <address>
        <city>Trollhättan</city>
        <state>Västra Götalandsregionen</state>
        <country>Sweden</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>County Council Dalarna</name>
      <address>
        <city>Falun</city>
        <country>Sweden</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Gothenburg University, Sahlgrenska academy, dept of obstetrics and gynecology</name>
      <address>
        <city>Gothenburg</city>
        <country>Sweden</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Lund University Hospital, dept of obstetrics and gynecology</name>
      <address>
        <city>Lund</city>
        <country>Sweden</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Karolinska Institute</name>
      <address>
        <city>Stockholm</city>
        <country>Sweden</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Uppsala University Hopsital, department of women's and children's health</name>
      <address>
        <city>Uppsala</city>
        <country>Sweden</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Örebro University Hospital</name>
      <address>
        <city>Örebro</city>
        <country>Sweden</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Sweden</country>
  </location_countries>
  <results_reference>
    <citation>Duley L. The global impact of pre-eclampsia and eclampsia. Semin Perinatol. 2009 Jun;33(3):130-7. doi: 10.1053/j.semperi.2009.02.010.</citation>
    <PMID>19464502</PMID>
  </results_reference>
  <results_reference>
    <citation>Mol BWJ, Roberts CT, Thangaratinam S, Magee LA, de Groot CJM, Hofmeyr GJ. Pre-eclampsia. Lancet. 2016 Mar 5;387(10022):999-1011. doi: 10.1016/S0140-6736(15)00070-7. Epub 2015 Sep 2.</citation>
    <PMID>26342729</PMID>
  </results_reference>
  <results_reference>
    <citation>Wikstrom AK, Larsson A, Eriksson UJ, Nash P, Norden-Lindeberg S, Olovsson M. Placental growth factor and soluble FMS-like tyrosine kinase-1 in early-onset and late-onset preeclampsia. Obstet Gynecol. 2007 Jun;109(6):1368-74. doi: 10.1097/01.AOG.0000264552.85436.a1.</citation>
    <PMID>17540809</PMID>
  </results_reference>
  <results_reference>
    <citation>Wright D, Syngelaki A, Akolekar R, Poon LC, Nicolaides KH. Competing risks model in screening for preeclampsia by maternal characteristics and medical history. Am J Obstet Gynecol. 2015 Jul;213(1):62.e1-62.e10. doi: 10.1016/j.ajog.2015.02.018. Epub 2015 Feb 25.</citation>
    <PMID>25724400</PMID>
  </results_reference>
  <results_reference>
    <citation>Akolekar R, Syngelaki A, Poon L, Wright D, Nicolaides KH. Competing risks model in early screening for preeclampsia by biophysical and biochemical markers. Fetal Diagn Ther. 2013;33(1):8-15. doi: 10.1159/000341264. Epub 2012 Aug 16. Erratum In: Fetal Diagn Ther. 2013;34(1):43.</citation>
    <PMID>22906914</PMID>
  </results_reference>
  <results_reference>
    <citation>Rolnik DL, Wright D, Poon LC, O'Gorman N, Syngelaki A, de Paco Matallana C, Akolekar R, Cicero S, Janga D, Singh M, Molina FS, Persico N, Jani JC, Plasencia W, Papaioannou G, Tenenbaum-Gavish K, Meiri H, Gizurarson S, Maclagan K, Nicolaides KH. Aspirin versus Placebo in Pregnancies at High Risk for Preterm Preeclampsia. N Engl J Med. 2017 Aug 17;377(7):613-622. doi: 10.1056/NEJMoa1704559. Epub 2017 Jun 28.</citation>
    <PMID>28657417</PMID>
  </results_reference>
  <results_reference>
    <citation>Mosimann B, Pfiffner C, Amylidi-Mohr S, Risch L, Surbek D, Raio L. First trimester combined screening for preeclampsia and small for gestational age - a single centre experience and validation of the FMF screening algorithm. Swiss Med Wkly. 2017 Aug 25;147:w14498. doi: 10.4414/smw.2017.14498. eCollection 2017.</citation>
    <PMID>28871576</PMID>
  </results_reference>
  <results_reference>
    <citation>Oliveira N, Magder LS, Blitzer MG, Baschat AA. First-trimester prediction of pre-eclampsia: external validity of algorithms in a prospectively enrolled cohort. Ultrasound Obstet Gynecol. 2014 Sep;44(3):279-85. doi: 10.1002/uog.13435. Epub 2014 Aug 13.</citation>
    <PMID>24913190</PMID>
  </results_reference>
  <results_reference>
    <citation>O'Gorman N, Wright D, Syngelaki A, Akolekar R, Wright A, Poon LC, Nicolaides KH. Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 11-13 weeks gestation. Am J Obstet Gynecol. 2016 Jan;214(1):103.e1-103.e12. doi: 10.1016/j.ajog.2015.08.034. Epub 2015 Aug 19.</citation>
    <PMID>26297382</PMID>
  </results_reference>
  <results_reference>
    <citation>WHO Recommendations for Prevention and Treatment of Pre-Eclampsia and Eclampsia. Geneva: World Health Organization; 2011. Available from http://www.ncbi.nlm.nih.gov/books/NBK140561/</citation>
    <PMID>23741776</PMID>
  </results_reference>
  <results_reference>
    <citation>Lindqvist PG, Molin J. Does antenatal identification of small-for-gestational age fetuses significantly improve their outcome? Ultrasound Obstet Gynecol. 2005 Mar;25(3):258-64. doi: 10.1002/uog.1806.</citation>
    <PMID>15717289</PMID>
  </results_reference>
  <results_reference>
    <citation>Sreeja Sarojini AG, Andrew Pecora and K. Stephen Suh. Proactive Biobanking to Improve Research and Health Care. Journal of Tissue Science &amp; Engineering.</citation>
  </results_reference>
  <results_reference>
    <citation>Stephansson O, Petersson K, Bjork C, Conner P, Wikstrom AK. The Swedish Pregnancy Register - for quality of care improvement and research. Acta Obstet Gynecol Scand. 2018 Apr;97(4):466-476. doi: 10.1111/aogs.13266. Epub 2017 Dec 14.</citation>
    <PMID>29172245</PMID>
  </results_reference>
  <verification_date>March 2023</verification_date>
  <study_first_submitted>February 1, 2019</study_first_submitted>
  <study_first_submitted_qc>February 4, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">February 5, 2019</study_first_posted>
  <last_update_submitted>March 14, 2023</last_update_submitted>
  <last_update_submitted_qc>March 14, 2023</last_update_submitted_qc>
  <last_update_posted type="Actual">March 15, 2023</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>screening</keyword>
  <keyword>biomarkers</keyword>
  <keyword>prediction</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Eclampsia</mesh_term>
    <mesh_term>Pre-Eclampsia</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>There is a plan to make IPD and related data dictionaries available with a similar project in Denmark.</ipd_description>
    <ipd_info_type>Clinical Study Report (CSR)</ipd_info_type>
    <ipd_time_frame>2021</ipd_time_frame>
    <ipd_access_criteria>The steering committee will review requests. Requests can be sent to:&#xD;
Anna-karin.wikstrom@kbh.uu.se or ylva.carlsson@vgregion.se</ipd_access_criteria>
    <ipd_url>http://www.impactstudien.se</ipd_url>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03831490
org study id: Dnr 2018-231
nct id: NCT03831490
lead sponsor: 
collaborator: 
collaborator: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
The overall aims of this proposal are to improve, facilitate, optimize and equalize the
      existing screening system for adverse pregnancy outcomes in early pregnancy in order to limit
      adverse consequences for both the mother and infant, by:

        1. Creating a Swedish prediction model with population-specific risk factors, optimized for
           the Swedish health care system, identifying high-risk women for preterm preeclampsia and
           validate the model within the cohort. This would give us the possibility to start
           aspirin prophylaxis in time, which has been proven to reduce the risk of developing
           preterm preeclampsia by 50%.

        2. Validating the Fetal Medicine Foundation prediction model for detection of preterm (< 37
           gestational weeks) preeclampsia in a Swedish population.

        3. Creating a prediction model identifying high-risk women for overall preeclampsia during
           pregnancy and birth of a small for gestational age infant in order to plan
           individualized surveillance for early detection, which has been proven beneficial for
           both the mother and infant.

        4. Creating a national pregnancy biobank with blood samples and individual clinical
           registry data, including pregnancy outcomes, enabling future research on prevention and
           early detection for various adverse pregnancy outcomes which could be such as preterm
           birth and intrauterine growth restriction.
Preeclampsia is a pregnancy-specific syndrome that affects 3-5% of all pregnancies and
      traditionally defined as new onset hypertension (blood pressure ≥ 140/90) and proteinuria
      after gestational week 20. The syndrome is one of the leading causes of maternal and
      perinatal acute morbidity and long-term disability and accounts for about 50 000 maternal
      deaths annually worldwide. Morbidity risks for the mother include seizures, intracranial
      hemorrhage, kidney failure, heart failure and pulmonary edema. Risks for the fetus include
      fetal growth restriction, preterm birth and hypoxia. Generally preterm preeclampsia (delivery
      before 37 weeks) is more severe than term preeclampsia.

      Risk assessment for preeclampsia enables both prevention and early prediction of the disease.

      Swedish risk assessment for preeclampsia in early pregnancy is still obtained by maternal
      history and characteristics, without medical examinations, which only detects about 30% of
      women that will develop preeclampsia. Risk factors are evaluated individually without being
      incorporated into a combined model that would allow multivariable analysis. This approach has
      been proven to be poor due to low specificity and sensitivity. Lately a more complex
      prediction model has been developed by the Fetal Medicine Foundation, using multivariable
      analysis and including serum biomarkers and physiological measurements reflecting maternal
      adaption to pregnancy. Intervention with aspirin given to identified high-risk pregnancies
      according this model has been shown to decrease the incidence of preterm (< 37 gestational
      weeks) preeclampsia (OR: 0.38; 95% CI 0.20-0.74), compared to placebo. Detection rates and
      cut-off values have been shown to vary between populations, depending on differences in
      population characteristics and incidence of disease, overfitting of the original model and
      differences in healthcare systems. Therefore, the model needs to be validated in Sweden.
      Further, the Fetal Medicine Foundation prediction model includes expensive covariates such as
      several biochemical markers and uterine artery Doppler. There is a need to create, validate
      and implement a cost-effective prediction model for first trimester screening for
      preeclampsia in a Swedish population, with the purpose to select who might benefit from
      aspirin prophylaxis to prevent preterm preeclampsia. We will study preeclampsia both
      according to the definition used in Sweden prior to 2020 and the definition used hereafter.

      Early detection of preeclampsia remains one of the major focuses of maternal health care and
      is emphasized by the WHO, since it has proven to be beneficial for both the mother and unborn
      child. Small-for-gestational-age fetuses not identified before delivery have an increased
      risk of adverse perinatal outcomes, compared to those identified during pregnancy.
      Identification of high-risk pregnancies is therefore important in early pregnancy not only to
      plan for prophylactic interventions, but also to optimize surveillance and to plan
      deliveries. Today most Swedish women attend the same maternal health care program with
      increasing number of visits in the end of pregnancy. By risk identification in early
      pregnancy we can individualize maternal health care and target women at high risk early in
      pregnancy. High-risk pregnancies can be referred to specialized health care and normal
      pregnancies followed at the basic maternal health care.

      The Swedish registry data is unique and combining it with a biobank containing blood samples
      from the first trimester could improve maternal healthcare and in the long run reduce adverse
      outcomes for Swedish women. A national first trimester pregnancy biobank would facilitate
      future research on prevention and prediction of pregnancy complications.

      A total of 13000 enrolled individuals will be needed for creating the model and for
      validation.
observational model: Cohort
time perspective: Prospective
measure: Preterm Preeclampsia
time frame: delivery <37 gestational weeks
description: Preeclampsia according to the Swedish definition, currently new onset hypertension (blood pressure ≥ 140/90) and proteinuria after gestational week 20.
measure: Small for gestational age
time frame: at delivery
description: birthweight ≤ - 2 SD according to the Swedish reference curve
measure: Overall preeclampsia
time frame: At delivery
description: Preeclampsia according to the Swedish definition, currently new onset hypertension (blood pressure ≥ 140/90) and proteinuria after gestational week 20.
measure: Preterm preeclampsia
time frame: delivery <37 gestational weeks
description: Preeclampsia according to the Swedish definition prior to 2020 as well as the definition hereafter
measure: Term preeclampsia
time frame: delivery >/=37 gestational weeks
description: Preeclampsia according to the Swedish definition prior to 2020 as well as the definition hereafter
intervention type: Diagnostic Test
intervention name: history
description: combining these 4 interventions will great an algorithm predicting preeclampsia
other name: mean material blod pressure
other name: PlGF - blood sample
other name: a- uterine doppler
At centers with biobank possibilities, serum, plasma and buffy-coat samples will be collected
      at the same time as the serum sample for analyze of Placental Growth Factor. The samples for
      the biobank will be stored for future research related to prediction, diagnosis and
      prevention of pregnancy complications.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: Female
gender based: Yes
gender description: pregnant women
minimum age: 18 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Lina Bergman, MD, PhD
role: Study Chair
affiliation: Uppsala University
last name: Peter Lindgren, MD, PhD
role: Study Chair
affiliation: Karolinska Institutet
last name: Anna Sandström, MD, PhD
role: Study Chair
affiliation: Karolinska Institutet
last name: Peter Conner, Ass Prof
role: Study Chair
affiliation: Karolinska Institutet
last name: Marius Kublickas, Ass Prof
role: Study Chair
affiliation: Karolinska Institutet
last name: Stefan Hansson, Professor
role: Study Chair
affiliation: Lund University
facility: 
facility: 
facility: 
facility: 
facility: 
facility: 
facility: 
facility: 
facility: 
country: Sweden
citation: Duley L. The global impact of pre-eclampsia and eclampsia. Semin Perinatol. 2009 Jun;33(3):130-7. doi: 10.1053/j.semperi.2009.02.010.
PMID: 19464502
citation: Mol BWJ, Roberts CT, Thangaratinam S, Magee LA, de Groot CJM, Hofmeyr GJ. Pre-eclampsia. Lancet. 2016 Mar 5;387(10022):999-1011. doi: 10.1016/S0140-6736(15)00070-7. Epub 2015 Sep 2.
PMID: 26342729
citation: Wikstrom AK, Larsson A, Eriksson UJ, Nash P, Norden-Lindeberg S, Olovsson M. Placental growth factor and soluble FMS-like tyrosine kinase-1 in early-onset and late-onset preeclampsia. Obstet Gynecol. 2007 Jun;109(6):1368-74. doi: 10.1097/01.AOG.0000264552.85436.a1.
PMID: 17540809
citation: Wright D, Syngelaki A, Akolekar R, Poon LC, Nicolaides KH. Competing risks model in screening for preeclampsia by maternal characteristics and medical history. Am J Obstet Gynecol. 2015 Jul;213(1):62.e1-62.e10. doi: 10.1016/j.ajog.2015.02.018. Epub 2015 Feb 25.
PMID: 25724400
citation: Akolekar R, Syngelaki A, Poon L, Wright D, Nicolaides KH. Competing risks model in early screening for preeclampsia by biophysical and biochemical markers. Fetal Diagn Ther. 2013;33(1):8-15. doi: 10.1159/000341264. Epub 2012 Aug 16. Erratum In: Fetal Diagn Ther. 2013;34(1):43.
PMID: 22906914
citation: Rolnik DL, Wright D, Poon LC, O'Gorman N, Syngelaki A, de Paco Matallana C, Akolekar R, Cicero S, Janga D, Singh M, Molina FS, Persico N, Jani JC, Plasencia W, Papaioannou G, Tenenbaum-Gavish K, Meiri H, Gizurarson S, Maclagan K, Nicolaides KH. Aspirin versus Placebo in Pregnancies at High Risk for Preterm Preeclampsia. N Engl J Med. 2017 Aug 17;377(7):613-622. doi: 10.1056/NEJMoa1704559. Epub 2017 Jun 28.
PMID: 28657417
citation: Mosimann B, Pfiffner C, Amylidi-Mohr S, Risch L, Surbek D, Raio L. First trimester combined screening for preeclampsia and small for gestational age - a single centre experience and validation of the FMF screening algorithm. Swiss Med Wkly. 2017 Aug 25;147:w14498. doi: 10.4414/smw.2017.14498. eCollection 2017.
PMID: 28871576
citation: Oliveira N, Magder LS, Blitzer MG, Baschat AA. First-trimester prediction of pre-eclampsia: external validity of algorithms in a prospectively enrolled cohort. Ultrasound Obstet Gynecol. 2014 Sep;44(3):279-85. doi: 10.1002/uog.13435. Epub 2014 Aug 13.
PMID: 24913190
citation: O'Gorman N, Wright D, Syngelaki A, Akolekar R, Wright A, Poon LC, Nicolaides KH. Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 11-13 weeks gestation. Am J Obstet Gynecol. 2016 Jan;214(1):103.e1-103.e12. doi: 10.1016/j.ajog.2015.08.034. Epub 2015 Aug 19.
PMID: 26297382
citation: WHO Recommendations for Prevention and Treatment of Pre-Eclampsia and Eclampsia. Geneva: World Health Organization; 2011. Available from http://www.ncbi.nlm.nih.gov/books/NBK140561/
PMID: 23741776
citation: Lindqvist PG, Molin J. Does antenatal identification of small-for-gestational age fetuses significantly improve their outcome? Ultrasound Obstet Gynecol. 2005 Mar;25(3):258-64. doi: 10.1002/uog.1806.
PMID: 15717289
citation: Sreeja Sarojini AG, Andrew Pecora and K. Stephen Suh. Proactive Biobanking to Improve Research and Health Care. Journal of Tissue Science & Engineering.
citation: Stephansson O, Petersson K, Bjork C, Conner P, Wikstrom AK. The Swedish Pregnancy Register - for quality of care improvement and research. Acta Obstet Gynecol Scand. 2018 Apr;97(4):466-476. doi: 10.1111/aogs.13266. Epub 2017 Dec 14.
PMID: 29172245
responsible party type: Sponsor
mesh term: Eclampsia
mesh term: Pre-Eclampsia
sharing ipd: Yes
ipd description: There is a plan to make IPD and related data dictionaries available with a similar project in Denmark.
ipd info type: Clinical Study Report (CSR)
ipd time frame: 2021
ipd access criteria: The steering committee will review requests. Requests can be sent to:
Anna-karin.wikstrom@kbh.uu.se or ylva.carlsson@vgregion.se
ipd url: http://www.impactstudien.se