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出境医 / 临床实验 / Development of an Screening System in Children With Congenital Heart Disease Based on Cloud Computing and Big Data

Development of an Screening System in Children With Congenital Heart Disease Based on Cloud Computing and Big Data

Study Description
Brief Summary:
This study intends to establish an automatic system for screening on children with congenital heart disease, the system include the auscultation of cardiac murmur and the test of oxygen saturation, the data was analyzed based on the cloud computing.

Condition or disease Intervention/treatment
Heart Diseases Device: automatic screening machine on congenital heart disease

Detailed Description:
This study intends to establish a system for screening of children with congenital heart disease,with the combination of cardiac auscultation , the test of oxygen saturation, the use of cloud computing and data base. The investigators decide to do this project from three main points.1:How to establish a data-base system? 2:How to get heart sound signal? 3.How to analyze so many signals?
Study Design
Layout table for study information
Study Type : Observational
Estimated Enrollment : 1000 participants
Observational Model: Cohort
Time Perspective: Cross-Sectional
Official Title: Development of an Screening System in Children With Congenital Heart Disease Based on Cloud Computing and Big Data
Study Start Date : January 2017
Estimated Primary Completion Date : December 2019
Estimated Study Completion Date : December 2019
Arms and Interventions
Outcome Measures
Primary Outcome Measures :
  1. Positive Predictive Value [ Time Frame: 2days ]
    The ratio of truly congenital heart disease cases divide by the total positive cases detected by the screening test.


Eligibility Criteria
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Ages Eligible for Study:   up to 10 Years   (Child)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Probability Sample
Study Population
This study include between between newborn to 10 years old.Heart sound signal need to be collected to analyze children's heart health status and creat a special model of each kind of CHD.
Criteria

Inclusion Criteria:

  • Neonatal ward patients
  • Patients with echocardiography reports

Exclusion Criteria:

  • Severe pneumonia
Contacts and Locations

Contacts
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Contact: Zhao Pengjun, MD 13918109566 ext 02125078485 pjunzhao@sina.com

Locations
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China, Shanghai
Zhao Pengjun Recruiting
Shanghai, Shanghai, China, 200082
Contact: Zhao Pengjun, MD    13918109566    pjunzhao@sina.com   
Sponsors and Collaborators
Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Shanghai Jiao Tong University School of Medicine
Investigators
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Study Director: Zhao Pengjun, MD Pediatric cardiovascular department, Shanghai xinhua hospital
Tracking Information
First Submitted Date November 22, 2016
First Posted Date April 26, 2019
Last Update Posted Date April 26, 2019
Study Start Date January 2017
Estimated Primary Completion Date December 2019   (Final data collection date for primary outcome measure)
Current Primary Outcome Measures
 (submitted: April 24, 2019) 		Positive Predictive Value [ Time Frame: 2days ]
The ratio of truly congenital heart disease cases divide by the total positive cases detected by the screening test.
Original Primary Outcome Measures Same as current
Change History No Changes Posted
Current Secondary Outcome Measures Not Provided
Original Secondary Outcome Measures Not Provided
Current Other Pre-specified Outcome Measures Not Provided
Original Other Pre-specified Outcome Measures Not Provided
 
Descriptive Information
Brief Title Development of an Screening System in Children With Congenital Heart Disease Based on Cloud Computing and Big Data
Official Title Development of an Screening System in Children With Congenital Heart Disease Based on Cloud Computing and Big Data
Brief Summary This study intends to establish an automatic system for screening on children with congenital heart disease, the system include the auscultation of cardiac murmur and the test of oxygen saturation, the data was analyzed based on the cloud computing.
Detailed Description This study intends to establish a system for screening of children with congenital heart disease,with the combination of cardiac auscultation , the test of oxygen saturation, the use of cloud computing and data base. The investigators decide to do this project from three main points.1:How to establish a data-base system? 2:How to get heart sound signal? 3.How to analyze so many signals?
Study Type Observational
Study Design Observational Model: Cohort
Time Perspective: Cross-Sectional
Target Follow-Up Duration Not Provided
Biospecimen Not Provided
Sampling Method Probability Sample
Study Population This study include between between newborn to 10 years old.Heart sound signal need to be collected to analyze children's heart health status and creat a special model of each kind of CHD.
Condition Heart Diseases
Intervention Device: automatic screening machine on congenital heart disease
Study Groups/Cohorts Not Provided
Publications *
  • van der Linde D, Konings EE, Slager MA, Witsenburg M, Helbing WA, Takkenberg JJ, Roos-Hesselink JW. Birth prevalence of congenital heart disease worldwide: a systematic review and meta-analysis. J Am Coll Cardiol. 2011 Nov 15;58(21):2241-7. doi: 10.1016/j.jacc.2011.08.025. Review.
  • Ho TC, Ouyang H, Lu Y, Young AH, Chintala K, Detrano RC. Postprocedural outcomes of rural children undergoing correction of congenital heart lesions in Yunnan Province, China. Pediatr Cardiol. 2011 Aug;32(6):811-4. doi: 10.1007/s00246-011-9991-y. Epub 2011 Apr 11.
  • Zhao QM, Ma XJ, Ge XL, Liu F, Yan WL, Wu L, Ye M, Liang XC, Zhang J, Gao Y, Jia B, Huang GY; Neonatal Congenital Heart Disease screening group. Pulse oximetry with clinical assessment to screen for congenital heart disease in neonates in China: a prospective study. Lancet. 2014 Aug 30;384(9945):747-54. doi: 10.1016/S0140-6736(14)60198-7. Epub 2014 Apr 22. Erratum in: Lancet. 2014 Aug 30;384(9945):746.
  • G. Douglas et al., Macleod's Clinical Examination. New York, NY, USA: Elsevier Health Sciences, 2009
  • A. G. Tilkian and M. B. Conover, Understanding Heart Sounds and Murmurs: With an Introduction to Lung Sounds.NewYork,NY, USA: ElsevierHealth Sciences, 2001.
  • KUN-HIS TSAI. METHOD, SYSTEM AND DEVICE FOR AUSCULTATION：US，US2016/0143612 A1[P]. 2016
  • Barry Poplaw. PORTABLE SMART STETHOSCOPE FORMED OF SMART MOBILE DEVICE AND CASING ASSEMBLY：US，US 2015/0327812 A1[P]. 2015
  • Winther S, Schmidt SE, Holm NR, Toft E, Struijk JJ, Bøtker HE, Bøttcher M. Diagnosing coronary artery disease by sound analysis from coronary stenosis induced turbulent blood flow: diagnostic performance in patients with stable angina pectoris. Int J Cardiovasc Imaging. 2016 Feb;32(2):235-245. doi: 10.1007/s10554-015-0753-4. Epub 2015 Sep 3.
  • Visagie C, Scheffer C, Lubbe WW, Doubell AF. Autonomous detection of heart sound abnormalities using an auscultation jacket. Australas Phys Eng Sci Med. 2009 Dec;32(4):240-50.
  • Huang GY. Screening markers of congenital heart disease and their clinical values. Chinese Journal of Practical Pediatrics , 2013(7):503-504
  • Zhang HX,Cheng XF.Heart sound analysis virtual instrument based on LabVIEW platform. Computer Technology and Development,2010,11:217-220

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Recruitment Information
Recruitment Status Unknown status
Estimated Enrollment
 (submitted: April 24, 2019) 		1000
Original Estimated Enrollment Same as current
Estimated Study Completion Date December 2019
Estimated Primary Completion Date December 2019   (Final data collection date for primary outcome measure)
Eligibility Criteria

Inclusion Criteria:

  • Neonatal ward patients
  • Patients with echocardiography reports

Exclusion Criteria:

  • Severe pneumonia
Sex/Gender
Sexes Eligible for Study: All
Ages up to 10 Years   (Child)
Accepts Healthy Volunteers Yes
Contacts Contact information is only displayed when the study is recruiting subjects
Listed Location Countries China
Removed Location Countries  
 
Administrative Information
NCT Number NCT03929133
Other Study ID Numbers XH-16-040
Has Data Monitoring Committee No
U.S. FDA-regulated Product Not Provided
IPD Sharing Statement
Plan to Share IPD: No
Plan Description: The investigator do not plan to share the data until the project is totally completed
Responsible Party Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Study Sponsor Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Collaborators Shanghai Jiao Tong University School of Medicine
Investigators
Study Director: Zhao Pengjun, MD Pediatric cardiovascular department, Shanghai xinhua hospital
PRS Account Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Verification Date December 2018

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