clinical statistics
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2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
E De La Rochebrochard

Abstract Assisted reproductive technologies (ART) regularly hit the media. Most people have an idea of ART that is based only on this prism. This restrictive view may lead to major discrepancy between what the general population thinks of these treatments and the everyday reality of ART. The most striking example of this discrepancy is probably the use of third party donors (sperm, oocyte, embryo or gestational donation). In France, the media focus almost exclusively on ART with a third party donor. The personalities who relate their experience in the media or in autobiographies are all children (now adults or adolescents) who were conceived with a third-party donor. Nevertheless, 95% of children conceived by ART in France have not been conceived through a third party. The media also highlight exceptional individual stories that give rise to strong societal controversies, such as Natalie Suleman (USA) who was called “Octomom” after she gave birth to octoplets, or Maria del Carmen Bousada de Lara (Spain) and Adriana Iliescu (Romania) who gave birth at age 66, or more recently Lulu and Nana (China) who were genetically modified twin sisters. Such reports can arouse wonder or fear, but both lead to a social representation of ART as an “omnipotent” technique. Infertile couples whose knowledge of ART is based on the media coverage may venture into these treatments thinking that as their case is an “ordinary” one, there should be no problem for them in having a baby through these technologies. Clinical statistics on ART show that even if the success rate is high, there is a gap between social expectations and reality. These statistics can be misleading, as they often assume that the couple has undergone several ART cycles. The objective of clinical statistics is usually to measure the efficacy of ART from a medical viewpoint, not from the standpoint of the couples’ care pathways. The gap between the two is considerable. The pathways of couples who undertake ART are marked by pitfalls that strongly affect success rates because of the risk of treatment dropout. In some countries, economic factors are a major reason for dropout because of the high cost of ART. France is a very interesting textbook case to explore this issue, as all infertility treatments are fully reimbursed for up to six artificial inseminations and four in vitro fertilizations for each birth. Economic barriers to ART access are minimal in such a favorable national context. Nevertheless, only about half of couples treated by ART finally become parents and success rates drop dramatically in older women. This epidemiological statistical reality is difficult to reconcile with the media presentation of ART as “omnipotent”. However, “natural miracles” can also occur as spontaneous births have been observed among couples unsuccessfully treated by ART. There are also other pathways to parenthood, such as adoption of a child. Thanks to ART, every year numerous couples become parents. But for infertile couples, the everyday reality is far from the “omnipotence” acclaimed by media headlines. The social representation of ART must move toward a more balanced perception of these technologies, bearing in mind its successes and also its limitations, especially with the current demographic trend towards childbearing at a later age that may lead to an increase in demand for ART. Change in the social representation of ART will probably need to go far beyond classic public health campaigns. ART will need to be approached differently in cultural spaces such as the media but also in movies, series or novels that have a major influence on collective social imaginaries and representations.


Author(s):  
P.Priya Et. al.

The health region produces a massive quantity of facts. This statistics is not always made use to the full quantity and is frequently underutilized the usage of this big quantity of statistics, a ailment can be detected, predicated or maybe cured. A large hazard to human type is caused by sicknesses like heart disease, most cancers, tumour, and Alzheimer’s disease prediction. Using machine getting to know strategies, the coronary heart ailment may be expected. Clinical data which includes blood strain, hypertension, diabetes, the quantity of each day cigarettes smoked, and so forth. Are used as input, so these traits are modeled to expect. This model can then be used to are expecting future clinical statistics. The algorithms like Decision Tree , k – Nearest Neighbor and Support Vector Machine are used. The accuracy of the model the use of every of the algorithm is calculated. Then the only with the good accuracy is taken because the version for predicting the coronary heart diseases.


2021 ◽  
Vol 27 (1) ◽  
pp. 13-20
Author(s):  
Hiroyoshi YAMAMOTO ◽  
Akihiro NISHIYAMA ◽  
Kei SUGIURA ◽  
Sei TANAKA ◽  
Azusa YAMAZAKI ◽  
...  

2021 ◽  
Vol 27 (1) ◽  
pp. 1-6
Author(s):  
Souichirou TADOKORO ◽  
Noboru NOMA ◽  
Daiki TAKANEZAWA ◽  
Kana OZASA ◽  
Akiko OKADA ◽  
...  

2020 ◽  
Author(s):  
Jincheng Liu ◽  
Suqin Huang ◽  
Bao Li ◽  
Jian Liu ◽  
Hao Sun ◽  
...  

Abstract In this study, we explored the effect of vessel diameter of coronary artery where the stenosis is located on FFR at the same vascular level. This study is divided into two parts: clinical statistics and numerical simulation. In the clinical statistics section, we compared the blood vessel diameter where the stenosis is located of the ischemic group and the non-ischemic group. In the numerical simulation section, we further explored the effect of diameter on myocardial ischemia by using an ideal model. With the increase in stenosis rate and stenotic vessel flow, the FFR rate of the larger stenotic vessels was higher than that of smaller stenotic vessels. The larger blood vessels are more prone to ischemia when coronary artery stenosis occurs.


2017 ◽  
Vol 28 (2) ◽  
Author(s):  
Wataru Yamagami ◽  
Satoru Nagase ◽  
Fumiaki Takahashi ◽  
Kazuhiko Ino ◽  
Toru Hachisuga ◽  
...  

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