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Ante partum new-born baby risk predicting method for heart disease pregnant patient, system and medium

A risk prediction and neonatal technology, applied in health index calculation, medical data mining, medical informatics, etc., can solve the problems of complexity, low estimation accuracy, low analysis efficiency, etc., and achieve the effect of reducing difficulty and improving efficiency

Active Publication Date: 2019-05-14
SHANDONG UNIV QILU HOSPITAL
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Existing prenatal risk prediction for pregnant patients with heart disease is generally based on the doctor's work experience, but judging the newborn risk through work experience has the following defects: due to the complexity of the cause and mechanism of heart disease, the doctor's work experience is subjective. It is difficult to predict the risk of newborns, the analysis efficiency is low, and the estimation accuracy is low

Method used

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  • Ante partum new-born baby risk predicting method for heart disease pregnant patient, system and medium
  • Ante partum new-born baby risk predicting method for heart disease pregnant patient, system and medium
  • Ante partum new-born baby risk predicting method for heart disease pregnant patient, system and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0049] Such as figure 1 As shown, the methods for predicting the risk of newborns in pregnancy patients with heart disease before delivery include:

[0050] Perform data screening and feature extraction on the pre-collected medical data of pregnant patients with congenital heart disease and their newborns to obtain the impact factors corresponding to the risk of delivery; the impact factors include: whether neonatal adverse events occur, the age of the patient at delivery , pregnancy and childbirth history, type of congenital heart disease, previous treatment history, New York heart function class, electrocardiogram, cardiac color Doppler ultrasound results, blood test results, cardiac adverse events, obstetric complications, gestational week of delivery, delivery method, neonatal Apager score and newborn weight;

[0051] Perform single-factor logistic regression analysis on the impact factors, and screen out all variables whose probability value p is less than the set thresh...

Embodiment 2

[0087] Such as figure 2 As shown, the neonatal risk prediction system for pregnant patients with heart disease before delivery includes:

[0088] Impact factor acquisition module: perform data screening and feature extraction on pre-collected medical data of pregnant patients with congenital heart disease and their newborns, and obtain impact factors corresponding to childbirth risk; the impact factors include: whether neonatal adverse events occur , patient's age at delivery, pregnancy and childbirth history, congenital heart disease type, previous treatment history, New York heart function class, electrocardiogram, cardiac color Doppler ultrasound results, blood test results, cardiac adverse events, obstetrical complications, gestational week of delivery, delivery method, Neonatal Apager score and neonatal weight;

[0089] Variable screening module: perform single-factor logistic regression analysis on the impact factors, and screen out all variables whose probability valu...

Embodiment 3

[0096] The present disclosure also provides an electronic device, including a memory, a processor, and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, each operation in the method is completed. For brevity, I won't repeat them here.

[0097] Described electronic device can be mobile terminal and non-mobile terminal, and non-mobile terminal comprises desktop computer, and mobile terminal comprises smart phone (Smart Phone, such as Android mobile phone, IOS mobile phone etc.), smart glasses, smart watch, smart bracelet, tablet computer , laptops, personal digital assistants and other mobile Internet devices that can communicate wirelessly.

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Abstract

The invention discloses an ante partum new-born baby risk predicting method for a heart disease pregnant patient, a system and a medium. The method comprises the steps of performing data screening andcharacteristic extraction on pre-acquired medical data of a congenital heart disease pregnant patient and a new-born baby, and acquiring an influence factor which corresponds with a production risk;performing single-factor logistic regression analysis on the influence factor, and screening all variables with probability p smaller than a preset threshold; performing multiple-factor logistic regression analysis on all the screened variables, and establishing a logistic regression model; inputting a left ventricular ejection fraction, a left atrial diameter, a left ventricular diameter, an ascending aorta inner diameter, pulmonary artery systolic pressure and pulmonary artery average pressure into the logistic regression model, thereby obtaining an ante partum new-born baby risk evaluationresult of a to-be-predicted target.

Description

technical field [0001] The present disclosure relates to a method, system and medium for predicting the risk of a newborn in a pregnant patient with heart disease before delivery. Background technique [0002] The statements in this section merely mention background art related to the present disclosure and do not necessarily constitute prior art. [0003] Patients with congenital heart disease usually have the characteristics of low blood oxygen saturation and poor cardiac function. In the state of pregnancy, as the gestational age increases, the probability of serious cardiac complications such as decreased cardiac function and heart failure is extremely high. In this state, the fetus has a relatively low blood oxygen saturation state, and as the mother's condition worsens, there is a risk of premature birth at any time, so the probability of adverse complications in the newborn is extremely high after birth, endangering life safety . [0004] Existing prenatal risk pred...

Claims

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Application Information

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IPC IPC(8): G16H50/30G16H50/70
Inventor 宋坤褚然谯旭姚舒孔北华
Owner SHANDONG UNIV QILU HOSPITAL
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