June 10, 2019
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June 25, 2019
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January 29, 2021
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June 1, 2019
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May 30, 2025 (Final data collection date for primary outcome measure)
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- Changes in Peabody Developmental Motor Scales 2(PDMS-2) test results within 6 months of age [ Time Frame: 6 months ]
The PDMS-2 test performed at the age of 1 month,3 months,6 months, to compare the differences in test results between the children of the GDM group and the non-GDM group.The PDMS-2 scale included two relatively independent parts, gross motion assessment Scale and fine motion assessment scales. The gross motion assessment scale for infants younger than 1 years of age tests the ability of three areas: reflexes, stationary and locomotion,the fine motion assessment scale tests grasping,visual-motor Integration.The results are expressed in terms of gross motor quotient (GMQ),fine motor quotient (FMQ),and total motor quotient (TMQ).There are seven grades according to quotient(MQ is excellent between 131 and 165, MQ is good between 121 and 130, MQ is medium up between 111 and 120,MQ is medium between 90 and 100,MQ is medium down between 80 and 89, MQ is poor between 70 and 79, MQ is very poor between 35 and 69).
- Changes in Gesell developmental scale test results within 6 months of age [ Time Frame: 72 months ]
The Gesell developmental scale test was performed at the age of 6 months,12 months,24 months,36 months,48 months,60 months and 72 months,to compare the differences in test results between the children of the GDM group and the non-GDM group.The Gesell developmental scale mainly measures five areas:adaptive behavior, gross motor, fine motor, Language behavior,personal-social behavior, the evaluation finally calculates the developmental quotient (DQ) of each area. Diagnostic criteria: DQ is more than or equal to 86 is normal, DQ is marginal between 76 and 85, DQ is mild mental retardation between 55 and 75, DQ is moderate mental retardation between 40 and 54, DQ is severe mental retardation between 25 and 39, and DQ is less than or equal to 25 is extremely severe mental retardation.
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Same as current
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- Change of weight for height Z-score(WHZ) [ Time Frame: 72 months ]
To measure body length/height and weight(mean values were measured three times continuously) at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,and 72 months of age,respectively. And then,WHZ is calculated using WHO2011v3.2.2 software,to compare the differences in WHZ of the children of the GDM group and the non-GDM group.
- Change of the height for age Z-score(HAZ)blood routines [ Time Frame: 72 months ]
To measure body length/height(mean values were measured three times continuously) at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,and 72 months of age,respectively. And then,HAZ is calculated using WHO2011v3.2.2 software,to compare the differences in HAZ of the children of the GDM group and the non-GDM group.
- Change of the BMI for Age Z-score(BAZ) [ Time Frame: 72 months ]
To measure body length/height and weight(mean values were measured three times continuously) at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,and 72 months of age,respectively. weight and length/height will be combined to report BMI in kg/m^2.And then,BAZ is calculated using WHO2011v3.2.2 software,to compare the differences in BAZ of the children of the GDM group and the non-GDM group.
- Change of the weight for Age Z-score(WAZ) [ Time Frame: 72 months ]
To measure body weight(mean values were measured three times continuously) at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,and 72 months of age,respectively. And then,WAZ is calculated using WHO2011v3.2.2 software,to compare the differences in WAZ of the children of the GDM group and the non-GDM group.
- Changes in hemoglobin [ Time Frame: 72 months ]
Blood routine examinations performed at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,72 months of age,respectively,to compare the differences in hemoglobin of the children of the GDM group and the non-GDM group.
- Changes in mean red blood cell volume (MCV) [ Time Frame: 72 months ]
Blood routine examinations performed at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,72 months of age,respectively,to compare the differences in mean red blood cell volume (MCV) of the children of the GDM group and the non-GDM group.
- Changes in mean red blood cell hemoglobin (MCH) [ Time Frame: 72 months ]
Blood routine examinations performed at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,72 months of age,respectively,to compare the differences in mean red blood cell hemoglobin (MCH) of the children of the GDM group and the non-GDM group.
- Changes in mean red blood cell hemoglobin concentration (MCHC) [ Time Frame: 72 months ]
Blood routine examinations performed at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,72 months of age,respectively,to compare the differences in mean red blood cell hemoglobin concentration (MCHC) of the children of the GDM group and the non-GDM group.
- Changes in platelet count (PLT) [ Time Frame: 72 months ]
Blood routine examinations performed at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,72 months of age,respectively,to compare the differences in platelet count (PLT) of the children of the GDM group and the non-GDM group.
- Changes in percentage of RBC width distribution(RDW%) [ Time Frame: 72 months ]
Blood routine examinations performed at 1 month,3 months,6 months,12 months,24 months,36 months,48months,60 months,72 months of age,respectively,to compare the differences in percentage of RBC width distribution(RDW%) of the children of the GDM group and the non-GDM group.
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Same as current
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Not Provided
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Not Provided
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Effects of Gestational Diabetes Mellitus on Children
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Effects of Gestational Giabetes Mellitus on Neuropsychological Development and Physique Growth in Children:a Cohort Study
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Abstract Gestational diabetes mellitus (GDM) refers to different degrees of glucose intolerance or impaired glucose tolerance,which are commonly found on non-diabetic persons during pregnancy.GDM is an important public health issue that has a huge impact on children's health.According to statistics,the global occurrence of GDM in 2017 was as high as 16.2%.As well as lifestyle changes that are leading to an increased number of women with overweightness and obesity,the increasing number of"older mothers"responding to the second-child policy are raising up the percentile of GDM by the year.infancy and pre-school age are the important stages of physical growth and psychomotor development.At present,there are few domestic and International studies on the impact of GDM on the health of children,and the conclusions are not the same.There is a lack of long-term follow-up and Chinese samples. This study focuses on the current new hotspot in the research of the children's health problems, based on the 1000-day life concept and theory of DOHaD. Prospective cohort study methods and real-world studies were used. To study and clarify the effect of GDM on the neuropsychological development and physical growth indicators of children in China, and further explore the possible mechanism of action and the related indicators of predictive value, looking for possible early intervention targets. The results are expected to expand the data sources of this type of research in China, improve the data quality and clarify the characteristics of this type of population in China, and provide data support for the revision of maternal and child health related policies.
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Introduction:
According to statistics, the occurrence of GDM in 2017 of China was roughly 14.8%. A preliminary test performed by the obstetrics outpatient department of the First People's Hospital of Chongqing Liangjiang New Area, China (Project partner) revels that the GDM percentile was 17.5%.
It is currently believed that GDM can affect the perinatal health of next generation including "giant children". Recently, the impact of GDM on the health of children in childhood has become a research hot spot. GDM is an important public health issue that has a huge impact on children's health.
"1000 days in the early life" refers to the period from the combination of sperm and egg to the second year of life, which has a profound impact on children's growth and development and adulthood health and even the health of their children. Children at this age are in the window period of interaction between genetics and environmental factors, and yet, are also in the "opportunity window" of epigenetic regulation. The disease and nutrition of pregnant mothers will greatly affect the growth and development of children in the first 1000 days of their lives, as well as the long-term health of the children and that of the children's children.
International studies have shown that the children of GDM mothers may have abnormalities in nervous system development, including cognitive memory impairment and bradykinesia. Recent studies have found that GDM diagnosed before 26 weeks of gestation can increase the risk of autism spectrum disorders in the 18-24-month-old children, and GDM treatment cannot reduce the risk. A study in Spain found that GDM significantly reduced test scores for language and gross motor development in 18 months old children(P<0.05).
The mechanism of GDM on the development of children psychomotor development is more complicated. Studies have shown that the middle and late pregnancy is an important stage of nervous system development. chronic hypoxia in GDM fetuses prompts the body to mobilize iron from other tissues, including the brain, to produce sufficient hemoglobin for oxygen. Iron is involved in the differentiation of neurons in the brain, the synthesis and decomposition of neurotransmitters and the myelin sheath of the brain, etc. Iron deficiency in the brain can lead to changes in the structure and function of the hippocampus and striatum, thus affecting the development of sensation, movement, emotion, learning, memory and behavior. Currently considered, Some indicators of blood routine can comprehensively reflect the iron storage in the body. Iron deficiency in developing children causes irreparable damage to cognitive and memory functions.
Researchers believe that GDM during pregnancy affects children's iron metabolism, thereby increasing the risk of impaired neuropsychological development such as cognitive memory and exercise after birth, and that the iron nutrition status after returning to normal cannot reverse this damage.
The new concept of the origin of human disease ,"The developmental origins of health and disease (DOHaD)."theory, that is, environmental factors (such as maternal nutrition, diseases, etc.) in early life (such as fetal period) will affect some adult non-communicable diseases (such as obesity and metabolic diseases),and even affects the health of multiple generations.
Foreign related studies had found that the birth weight of the children in the GDM group was higher than that of the non-GDM mothers (P<0.01), and the height of the children in the GDM group was lower than that of non-GDM group when the children were 1.5 years old (P<0.01). At the age of 7.7 years, the children weight of GDM group was significantly higher than that of the non-GDM group (P<0.01).
Researchers believe that GDM during pregnancy affects fetal fat synthesis and weight, further affects the weight and body symmetry of the children after delivery, and increase the risk of physique growth deviation of the children.
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Purpose and Significance of Research 2.1 Purpose 2.1.1 To clarify whether GDM during pregnancy affects children's iron metabolism, thereby increasing the risk of postnatal cognitive memory, motion and other neuropsychological development level damage, and whether the postnatal iron nutrition status returns to normal cannot reverse this damage.
2.1.2 To clarify whether GDM during pregnancy affects fetal fat synthesis and weight gain,further affects the weight and body symmetry of the children after delivery, and increasing the risk of physique growth deviation of the children.
2.2 Significance The results of this study may provide a basis for the scientific judgment of the prognosis of the children of GDM mothers and the formulation of early intervention plans, as well as data support for further health policy formulation.
- Target 3.1 To clarify the influence of GDM on children's neuropsychological development level and progression; 3.2 To clarify the influence of GDM on children's physique growth; 3.3 To clarify the effect of GDM on Hb, MCV, MCHC, RDW%, and PLT in neonatal blood routines; 3.4 To understand whether GDM at different stages of pregnancy has different effects on the physique growth and neuropsychological development of the children, and whether it may have a predictive effect; 3.5 To understand whether the impaired neuropsychological development level of infants and preschool children in the GDM group with normal Hb, MCV, MCHC,RDW% and PLT has been repaired.
- Research Steps In the obstetrics department of the First People's Hospital of Chongqing Liangjiang New Area,China, the pregnant women diagnosed as GDM by IADPSG2010 standard and delivery children were enrolled into the GDM group, and the healthy pregnant women and delivery children in the same period were enrolled into the non-GDM group according to 1:1 ratio. To Collect data of pre-pregnancy, pregnancy and pregnancy outcomes of the two groups, and fill in the "Questionnaire", including the age of pregnant women, permanent residence, pre-pregnancy weight, pre-pregnancy weight, height, educational status, Number of pregnancies, number of births, pregnancy-related conditions, etc. Husband's age, educational status, weight, height, average monthly household income, etc. The physique growth index and blood routine were monitored at the age of 1 month,3 months,6 months,12 months,24 months,36 months,48 months,60 months and 72 months, respectively. Physique growth indicators and blood routine were monitored. PDMS-2 was used to evaluate the motor development of infants at the age of 1 months,3 months and 6 months, and the Gesell developmental scale was used to comprehensively evaluate the neuropsychological development of infants at the age of 6 months,12 months,24 months,36 months,48 months,60 months and 72 months.
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The calculation formula of sample size is as follows:
Nkeley =((Z_(α/2)+Z_β )^2 P(1-P)(γ+1))/〖γ(P_(0-) P_1)〗^2 p = (p_0+γp_1)/(γ+1) N=The sample size of each group,α=standard deviation,α=0.05,Zα/2=1.96,β=0.2,Zβ=0.842,r=1.It is ca6.lculated that each group needs 255 samples.
- Recruitment Process Since July 1, 2019, the subject recruitment was implemented in the obstetrics department of the First People's Hospital of Chongqing Liangjiang New Area, China. 255 pregnant women diagnosed with GDM by IADPSG2010 standard and their children will be enrolled into the GDM group, whereas, the same number of healthy pregnant women and their children will be enrolled into the project.
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Statistical Analysis Plan
Excel software was used for data entry and SPSS 19.0 statistical software was used for data analysis. GDM was used as the exposure factor to analyze the differences between exposed group (study group) and unexposed group (control group).Specific analysis includes:
7.1 Chi-square test was used to analyze the general demographic characteristics and other baseline characteristics between the two groups; 7.2 Chi-square test was used to analyze the feeding conditions, complementary food addition conditions, nursing conditions and main diseases between the two groups; 7.3 The height and weight values of the two groups were calculated according to the standard: LAZ, WAZ, WLZ and BMIZ, and the results were analyzed by student's t test.
7.4 GMQ, FMQ and TMQ values in PDMS-2 motor development scale assessment results between the two groups were analyzed by nonparametric tests, while the development quotient (DQ) of the five area assessed by the Gesell developmental scale was analyzed using nonparametric tests.
7.5 Student's t test was used to analyze the blood routine values between the two groups.
7.6 Multiple linear regression analysis was used to analyze the factors affecting physical, motor and intellectual development between the two groups.
7.7 Incomplete Data Disposal Method 7.7.1 Deletion of cases containing missing data: there are mainly simple deletion method and weight method. If the number of missing data is small, cases with missing data can be deleted or bias reduced by weighting the complete data. After marking cases with incomplete data, complete data cases are assigned with different weights, which can be obtained by logistic or probit regression.
7.7.2 Fill in the missing data with the possible data
Mean value interpolation:
If the null value is numeric, the missing attribute value is filled in based on the average value of the value of the attribute on all other objects; If the null value is non-numeric, the value that the attribute takes the most times in all other objects (that is, the value with the highest occurrence frequency) is used to make up the missing attribute value according to the mode principle in statistics.
7.7.3 Lost to follow-up to the processing method last observation carried forward(LOCF) and baseline observation carried forward(BOCF)
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Quality Control Plan Site quality control will be carried out regularly, at least once a month, to ensure that the plan is strictly followed, and the data collected are accurately recorded.
8.1 Ethics This study has been approved by the Ethics Review Board of Children's Hospital of Chongqing Medical University.
8.2 Selection of Research Subjects The person in charge of screening and enrollment must screen the subjects in strict accordance with the inclusion and exclusion criteria and maintain consistency of the inclusion and exclusion criteria Upon signing of the contract, screener will collect data of pre-pregnancy, pregnancy and pregnancy outcome of the two groups of mothers and have them fill out a questionnaire.
8.3 Follow-Up Visits One researcher will keep track of follow-up visit, keep telephone numbers, provide health consultation, pay home visits, keep touch with the parents in any other possible forms and remind the parents of their appointments.
8.4 Measures and Physical Evaluation One researcher will be responsible for physical measurements. This researcher will be trained on the standard physical measurement prior to the beginning of research, and the average value of three measurements will be taken. In terms of accuracy, two appraisers must go through the professional training of regular medical institutions and obtain the qualification certificate, and then begin the evaluation after the accuracy and consistency of the evaluation results.
8.5 Data Collection Special personnel are assigned to collect and save paper data every day, and timely input the paper data into the computer for real and correct storage.
8.6 Data Entry The research data are loaded into the electronic record form and cloud platform database timely, completely, correctly and clearly to ensure the authenticity and reliability of the content.
- Safety Evaluation There were no additional interventions in this study, so there was no additional risk to children beyond routine care.
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Observational
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Observational Model: Cohort Time Perspective: Prospective
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Not Provided
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Not Provided
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Probability Sample
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In the obstetrics department of the First People's Hospital of Chongqing Liangjiang New Area,China, the pregnant women diagnosed as GDM by IADPSG2010 standard and delivery children were enrolled into the GDM group, and the healthy pregnant women and delivery children in the same period were enrolled into the non-GDM group according to 1:1 ratio.
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- Gestational Diabetes Mellitus
- Children
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Not Provided
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- the DGM group
The subject recruitment was implemented in the obstetrics department of the First People's Hospital of Chongqing Liangjiang New Area, China. 255 pregnant women diagnosed with GDM by IADPSG2010 standard and their children will be enrolled into the GDM group.
- the Non-GDM group
In the obstetrics department of Chongqing First People's Hospital of Liangjiang New Area,China,the healthy pregnant women and delivery children in the same period were enrolled into the non-GDM group in a 1:1 ratio.
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- Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW, Malanda B. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract. 2018 Apr;138:271-281. doi: 10.1016/j.diabres.2018.02.023. Epub 2018 Feb 26.
- Gao C, Sun X, Lu L, Liu F, Yuan J. Prevalence of gestational diabetes mellitus in mainland China: A systematic review and meta-analysis. J Diabetes Investig. 2019 Jan;10(1):154-162. doi: 10.1111/jdi.12854. Epub 2018 May 27.
- Xiang AH. Association of Maternal Diabetes With Autism in Offspring. JAMA. 2017 Feb 7;317(5):537-538. doi: 10.1001/jama.2016.20122.
- Torres-Espínola FJ, Berglund SK, García S, Pérez-García M, Catena A, Rueda R, Sáez JA, Campoy C; PREOBE team. Visual evoked potentials in offspring born to mothers with overweight, obesity and gestational diabetes. PLoS One. 2018 Sep 12;13(9):e0203754. doi: 10.1371/journal.pone.0203754. eCollection 2018.
- Lahat E, Heyman E, Livne A, Goldman M, Berkovitch M, Zachor D. Iron deficiency in children with attention deficit hyperactivity disorder. Isr Med Assoc J. 2011 Sep;13(9):530-3.
- Hanson M. The birth and future health of DOHaD. J Dev Orig Health Dis. 2015 Oct;6(5):434-7. doi: 10.1017/S2040174415001129. Epub 2015 May 25. Review.
- Liu G, Li N, Sun S, Wen J, Lyu F, Gao W, Li L, Chen F, Baccarelli AA, Hou L, Hu G. Maternal OGTT glucose levels at 26-30 gestational weeks with offspring growth and development in early infancy. Biomed Res Int. 2014;2014:516980. doi: 10.1155/2014/516980. Epub 2014 Feb 13.
- Li C, Zhou P, Cai Y, Peng B, Liu Y, Yang T, Li Y, Hu Y, Fu Y, Wang Z, Peng H, Zhang Y, Chen J, Li T, Chen L. Associations between gestational diabetes mellitus and the neurodevelopment of offspring from 1 month to 72 months: study protocol for a cohort study. BMJ Open. 2020 Nov 24;10(11):e040305. doi: 10.1136/bmjopen-2020-040305.
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Recruiting
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510
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Same as current
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September 30, 2025
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May 30, 2025 (Final data collection date for primary outcome measure)
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Inclusion Criteria:
- term infant;
- Apgar score>=7 at birth;
- single birth;
- no obvious birth defects;
- no other perinatal diseases that seriously affecting growth and development;
- no congenital or genetic metabolic diseases that affect intelligence development;
Exclusion Criteria:
- mother with type 1 or type 2 diabetes before pregnancy;
- the mother had no OGTT diagnosis results and was not diagnosed in strict accordance with the diagnostic criteria of GDM;
- the mother had suffered from severe acute and chronic infectious diseases;
- the mother has other pregnancy complications during pregnancy (hypertensionkidney disease,cardiovascular disease,liver disease,thyroid-related disease,cholestasis,severe anemia,etc.);
- Mother's age>35 years old;
- the infants developed diseases that severely affected metabolism or normal growth and development during the follow-up.
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Sexes Eligible for Study: |
All |
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1 Month to 72 Months (Child)
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No
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Contact: Li Chen, MD |
(+86)136 7762 0103 ext +86 |
chenli2012@126.com |
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China
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NCT03997396
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LC
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No
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Studies a U.S. FDA-regulated Drug Product: |
No |
Studies a U.S. FDA-regulated Device Product: |
No |
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Plan to Share IPD: |
No |
Plan Description: |
Data is confidential during the study. |
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Chen Li, Children's Hospital of Chongqing Medical University
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Chen Li
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Not Provided
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Study Director: |
Li Chen, MD |
Children's Hospital of Chongqing Medical University |
Principal Investigator: |
Chao Li, MB |
Chongqing First People's Hospital of Liangjiang New Area |
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Children's Hospital of Chongqing Medical University
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January 2021
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