Abstract
Preterm births account for almost 1 million deaths globally. The objective of this study is to develop and evaluate a model that assists clinicians in assessing the risk of preterm birth, using fuzzy multicriteria analysis. The model allows experts to incorporate their intuition and judgment into the decision-making process and takes into consideration six (6) risk dimensions reflecting the socio-economic, behavioral and medical profile of pregnant women, thus adopting a holistic approach to risk assessment. Each risk dimension is further analyzed and measured in terms of risk factors associated with it. Data were collected from a selected group of 35 experts, each one with more than 20 years of obstetric experience. The model criteria were selected after a thorough literature analysis, so as to ensure a holistic approach to risk assessment. The criteria were reviewed by the experts and the model structure was finalized. The fuzzy analytic hierarchy method was applied to calculate the relative importance of each criterion and subsequent use of the model in assessing and ranking pregnant women by their preterm risk. The proposed model utilizes fuzzy logic and multicriteria analysis. It addresses the multifactorial nature of decision making when assessing the preterm birth risk. It also incorporates the obstetricians’ intuitive judgment during risk assessment, and it can be used to classify cases based on their risk level. In addition, it can be applied to evaluate the risk of individual cases in a personalized manner. The proposed model is compared and validated for its predictive value against judgments made by experts.
Highlights
Preterm birth has long been recognised as a primary cause of death, in children younger than 5 years of age [1, 2]
There is only a 50% chance of survival for a baby born at 32 weeks, due to lack of available resources and poor quality of expert support in low-income countries, as opposed to the economically advanced, where babies born as early as 24 weeks, have survival chances that reach 50% [5]. Behavioural factors such as smoking, alcoholism, substance use [1, 20, 22, 23], as well as gynaecologic history [23, 24], induced abortion [1, 20, 23], demographics, periodontal disease [22, 23], pregnancy complications, maternal vitamin D deficiency, vaginal bleeding, polyhydramnios [23], depression, stress [20, 23], genital tract infections, increase the chances of preterm labour [22]. When it comes to assisted reproductive technologies (ARTs), it seems that frozen embryo transfers (FETs) are associated with a decrease in small for gestational age (SGA) and low birth weight (LBW) neonates, as well as lower preterm birth rates [29,30,31,32,33,34,35]
Multiple logistic regression models and certain statistical methods are popular, but they are not without limitations [20, 39]. They fail to test for multiple interactions among independent factors, they fall short in identifying conditions that hold true only in subgroups and they largely ignore intuition, despite its well-recognized contribution to decision making in preterm birth risk assessment
Summary
Preterm birth has long been recognised as a primary cause of death, in children younger than 5 years of age [1, 2]. There is only a 50% chance of survival for a baby born at 32 weeks, due to lack of available resources and poor quality of expert support in low-income countries, as opposed to the economically advanced, where babies born as early as 24 weeks, have survival chances that reach 50% [5] Behavioural factors such as smoking, alcoholism, substance use [1, 20, 22, 23], as well as gynaecologic (medical) history [23, 24], induced abortion [1, 20, 23], demographics, periodontal disease [22, 23], pregnancy complications, maternal vitamin D deficiency, vaginal bleeding, polyhydramnios [23], depression, stress [20, 23], genital tract infections, increase the chances of preterm labour [22]. The proposed approach addresses the multifactorial nature of the topic, integrates experts’ intuition, can identify conditions that characterize subgroups and can provide the means for the development of more effective scoring systems
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