Basic principles and structure of risk assessment of Great obstetrical syndromes

N. Lemish
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Abstract

The objective: to develop a method for predicting the individual risk for great obstetric syndromes (GOS).Materials and methods. An analysis of the somatic, reproductive, and obstetric anamnesis was conducted in 572 pregnant women with clinical manifestations of GOS, in 81 of them (prediction group) signs of placental dysfunction were detected based on clinical, functional, laboratory, and ultrasound data. Control group (CG) – 50 practically healthy pregnant women with a favorable reproductive history and an uncomplicated course of this pregnancy.Functional, biophysical, hormonal, immunological and hemocoagulation indicators were calculated to determine the informative (prognostic) significance. Quantitative signs were divided into diagnostic intervals, and qualitative signs were assigned a code. The following indicators were included in the standard protocol: age, data on somatic and gynecological history, data on the pregnancy course, results of functional and laboratory examinations. Statistical processing of research results was carried out using standard Microsoft Excel 5.0 and Statistica 6.0 programs. Results. In the I trimester of pregnancy the concentration of placental lactogen (PL) in the prediction group was 29.4 % lower than the CG indicator, estradiol (E2) amount – by 27.4 %, estriol (E3) – by 28.6 %, progesterone (PG) – by 34.4%, human chorionic gonadotropin (hCG) – by 28.3 % lower, and cortisol (CR) – by 36.1 % higher. At the beginning of the II trimester of pregnancy in the prediction group the level of PL was already reduced by 33.8 %, E2 – by 26.2 %, E3 – by 32.3 %, PG – by 37.4 %, hCG – by 30.6 %, and CR – increased by 43.6 % compared to CG.The indicators of placenta hormonal activity in the early stages of pregnancy and at the beginning of the II trimester can be prognostic signs of further disruption of the adaptive compensatory and adaptive reactions of the fetal placental complex (FPC) in the II and III trimesters of pregnancy. Among a wide range of hemostasiological indicators in the I trimester of pregnancy in the prediction group the most informative were: activated partial thromboplastin time (-23 %) and activated recalcification time (+16.2 %), the changes of which remained at the beginning of the II trimester (-40% and - 11.7% respectively). During the evaluation of thromboelastogram data, the value of “r+k” was fixed by 33.3 % lower in the I trimester and by 36 % – at the beginning of the II trimester of pregnancy. As a result of the analysis the indicators with a high information value (more than 3.0 c.u.) were selected for quantitative assessment of the degree of individual risk for the development of maladaptive disorders in the FPC. The clinical trial of the scoring method of prediction proved its high sensitivity (91.8 %) and specificity (85.6 %). Conclusions. A multi-faceted analysis of anamnestic data, features of the pregnancy course, basic clinical, laboratory and functional indicators in women with clinical manifestations of GOS made possible to develop an effective methodology for predicting the risk for GOS development with high levels of sensitivity and specificity.
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产科大综合征风险评估的基本原则和结构
目的:发展一种预测大产科综合征个体风险的方法。材料和方法。对572例临床表现为GOS的孕妇进行躯体、生殖和产科记忆分析,其中81例(预测组)通过临床、功能、实验室和超声资料检测出胎盘功能障碍征象。对照组(CG) - 50名实际健康的孕妇,生育史良好,妊娠过程简单。计算功能、生物物理、激素、免疫和凝血指标,以确定信息(预后)意义。定量标志被划分为诊断区间,定性标志被分配一个代码。标准方案包括以下指标:年龄、躯体和妇科病史数据、妊娠过程数据、功能和实验室检查结果。采用标准的Microsoft Excel 5.0和Statistica 6.0程序对研究结果进行统计处理。结果。在妊娠早期,预测组胎盘乳原(PL)浓度比CG指标低29.4%,雌二醇(E2)含量低27.4%,雌三醇(E3)含量低28.6%,黄体酮(PG)含量低34.4%,人绒毛膜促性腺激素(hCG)含量低28.3%,皮质醇(CR)含量高36.1%。与CG相比,预测组妊娠早期PL水平已降低33.8%,E2 -降低26.2%,E3 -降低32.3%,PG -降低37.4%,hCG -降低30.6%,CR -升高43.6%。妊娠早期和妊娠中期初期胎盘激素活性指标可作为妊娠中期和妊娠中期胎儿胎盘复合体(FPC)适应性代偿和适应性反应进一步中断的预后信号。在广泛的止血指标中,预测组妊娠1个月最具信息性的是:活化的部分凝血活素时间(- 23%)和活化的再钙化时间(+ 16.2%),其变化在妊娠2个月开始时保持不变(分别为-40%和- 11.7%)。在评估血栓弹性图数据时,“r+k”的值在妊娠1个月固定低33.3%,在妊娠2个月开始时固定低36%。通过分析,选择具有较高信息价值(大于3.0 c.u.)的指标,定量评价FPC个体发生适应不良障碍的风险程度。预测评分法的临床试验证明其具有较高的敏感性(91.8%)和特异性(85.6%)。结论。通过对有GOS临床表现的妇女的记忆资料、妊娠过程特征、基本临床、实验室和功能指标的多方面分析,可以建立一种有效的方法来预测GOS发展的风险,具有高水平的敏感性和特异性。
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