HUDEČEK, Robert, Pavel VENTRUBA, Vít UNZEITIG, Eva RAČANSKÁ and Jana ŠARMANOVÁ. Ovarian hyperstimulation syndrome development in assisted reproduction treatment – risk factors analysis using data mining. Scripta medica. Brno: LF MU, 2006, vol. 2006, No 6, p. 329-340, 11 pp. ISSN 1211-3395.
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Basic information
Original name Ovarian hyperstimulation syndrome development in assisted reproduction treatment – risk factors analysis using data mining
Name in Czech Ovarian hyperstimulation syndrome development in assisted reproduction treatment – risk factors analysis using data mining
Name (in English) Ovarian hyperstimulation syndrome development in assisted reproduction treatment – risk factors analysis using data mining
Authors HUDEČEK, Robert (203 Czech Republic, guarantor), Pavel VENTRUBA (203 Czech Republic), Vít UNZEITIG (203 Czech Republic), Eva RAČANSKÁ (203 Czech Republic) and Jana ŠARMANOVÁ (203 Czech Republic).
Edition Scripta medica, Brno, LF MU, 2006, 1211-3395.
Other information
Original language Czech
Type of outcome Article in a journal
Field of Study 30214 Obstetrics and gynaecology
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
RIV identification code RIV/00216224:14110/06:00018871
Organization unit Faculty of Medicine
Keywords in English Ovarian hyperstimulation syndrome; assisted reproduction treatment;
Tags assisted reproduction treatment, Ovarian hyperstimulation syndrome
Changed by Changed by: doc. MUDr. Robert Hudeček, Ph.D., učo 77349. Changed: 27/9/2006 13:49.
Abstract
BACKGROUND: Aim of this study is to define the risk factors of ovarian hyperstimulation syndrome onset during assisted reproduction treatment using in vitro fertilization technique. Exploratory computer analysis of electronically stored data about assisted reproduction treatment cycles in clinical registry with the use of data mining system. MATERIALS: Analyzed file included data of 12 527 monitored cycles from 1989 to 2003. Cycles which leaded to development of ovarian hyperstimulation syndrom were analyzed (2456 cases, 19,6 % of cycles). METHODS: Both the ovarian hyperstimulation syndrome complicated cases and cases without ovarian hyperstimulation were tested by data mining method which is designed to find statistically significant differences among input attributes of ovarian stimulation phase of therapeutic cycles. The observed differences between input attributes were statistically tested and the value of statistical significance was evaluated. RESULTS: Significantly higher incidence of a clinically important form of ovarian hyperstimulation syndrome development was observed among patients under 30 years old who were affected by hyperstimulation syndrome in previous treatment cycles. We can predict a higher risk in patients with oligomenorrhoea and in cases of immunological and andrological sterility factor. Higher incidence of clinically significant form of hyperstimulation syndrome is noticed with stimulation protocols with highly effective gonadotrophine hormones where the total dose of gonadotrophins is greater than 1125 IU and maximum 17-beta estradiol levels are greater than 20 nmol/l. CONCLUSIONS: We have proved the applicability of the data mining system for the analysis of the risk factors with influence on the Assisted reproduction treatment results. Data mining method can be used to define statistically significant relations among all attributes of ovarian stimulation part of therapeutic cycle and to define the risk factors of hyperstimulation syndrome occurrence. Key words: ovarian hyperstimulation syndrom, risk factors, sterility treatment, data mining.
Abstract (in English)
BACKGROUND: Aim of this study is to define the risk factors of ovarian hyperstimulation syndrome onset during assisted reproduction treatment using in vitro fertilization technique. Exploratory computer analysis of electronically stored data about assisted reproduction treatment cycles in clinical registry with the use of data mining system. MATERIALS: Analyzed file included data of 12 527 monitored cycles from 1989 to 2003. Cycles which leaded to development of ovarian hyperstimulation syndrom were analyzed (2456 cases, 19,6 % of cycles). METHODS: Both the ovarian hyperstimulation syndrome complicated cases and cases without ovarian hyperstimulation were tested by data mining method which is designed to find statistically significant differences among input attributes of ovarian stimulation phase of therapeutic cycles. The observed differences between input attributes were statistically tested and the value of statistical significance was evaluated. RESULTS: Significantly higher incidence of a clinically important form of ovarian hyperstimulation syndrome development was observed among patients under 30 years old who were affected by hyperstimulation syndrome in previous treatment cycles. We can predict a higher risk in patients with oligomenorrhoea and in cases of immunological and andrological sterility factor. Higher incidence of clinically significant form of hyperstimulation syndrome is noticed with stimulation protocols with highly effective gonadotrophine hormones where the total dose of gonadotrophins is greater than 1125 IU and maximum 17-beta estradiol levels are greater than 20 nmol/l. CONCLUSIONS: We have proved the applicability of the data mining system for the analysis of the risk factors with influence on the Assisted reproduction treatment results. Data mining method can be used to define statistically significant relations among all attributes of ovarian stimulation part of therapeutic cycle and to define the risk factors of hyperstimulation syndrome occurrence. Key words: ovarian hyperstimulation syndrom, risk factors, sterility treatment, data mining.
Links
NO7696, research and development projectName: Ovariální karcinom a léčba neplodnosti metodami in vitro fertilizace - analýza rizikových faktorů pomocí systému pro dolování znalostí z databází SHLUK a umělé neuronové sítě NEUL 3
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