Prediction of low birth weight delivery by maternal status and its validation: Decision curve analysis

Abstract

Background:In this study, we evaluated assessed elements connected with low birth weight (LBW) and used decision curve analysis (DCA) to define a scale to anticipate the probability of having a LBW newborn child.Methods:This hospital-based case–control study was led in Arak Hospital in Iran. The study included 470 mothers with LBW neonate and 470 mothers with natural neonates. Information were gathered by meeting moms utilizing preplanned organized questionnaire and from hospital records. The estimated probabilities of detecting LBW were calculated using the logistic regression and DCA to quantify the clinical consequences and its validation.Results:Factors significantly associated with LBW were premature membrane rupture (odds ratio [OR] = 3.18 [1.882–5.384]), former LBW infants (OR = 2.99 [1.510–5.932]), premature pain (OR = 2.70 [1.659–4.415]), hypertension in pregnancy (OR = 2.39 [1.429–4.019]), last trimester of pregnancy bleeding (OR = 2.58 [1.018–6.583]), mother age >30 (OR = 2.17 [1.350–3.498]). However, with DCA, the prediction model made on these 15 variables has a net benefit (NB) of 0.3110 is best predictive with the highest NB. NB has simple clinical interpretation and utilizing the model is what might as well be called a procedure that distinguished what might as well be called 31.1 LBW per 100 cases with no superfluous recognize.Conclusions:It is conceivable to foresee LBW utilizing a prediction model show in light of noteworthy hazard components connected with LBW. The majority of the hazard elements for LBW are preventable, and moms can be alluded amid early pregnancy to a middle which is furnished with facilities for administration of high hazard pregnancy and LBW infant.

Development and Validation of a Risk Score to Predict Low Birthweight Using Characteristics of the Mother: Analysis from BUNMAP Cohort in Ethiopia

“…However, some of the predictors they used such as inadequate weight gain during pregnancy and inadequate proteins in diet are not easily obtainable information in routine clinical and public health practice, which makes the model less practical. On the other hand, Rejali and his associates performed a decision curve analysis involving 15 predictor variables and found a net benefit (NB) of 0.311 [30]. Nevertheless, 4 of the variables included in the prediction model were obtained from factor analysis, reduced from other several variables.…”

“…However, no significant clinical attempt has been made to predict the probability of LBW. To our knowledge, two studies [29,30] tried to develop a prediction model, although they had less practical implication because the predictors used are not easily obtainable in primary healthcare settings. We developed and validated a model and risk score to predict LBW in primary care settings of LMICs.…”

Development and validation of a nomogram for predicting low birth weight among pregnant women who had antenatal care visits at Debre Markos Comprehensive and Specialized Hospital, Ethiopia

“…Infant morbidity and mortality rates are higher in cases where the newborn has LBW or is small for gestational age (8). It is associated with adverse effects on a child's health, such as decreased cognitive function, increased risk of infection, neurological abnormalities, hypertension, type 2 diabetes, and later cardiovascular diseases (2,6,(9)(10)(11)(12)(13)(14)(15). Infants with low birth weight have a mortality rate that is nearly 20 times higher than infants with a normal weight (1).…”

Development and Validation of a Risk Score to Predict Low Birthweight Using Characteristics of the Mother: A Prospective Cohort Study

“…However, no significant clinical attempt has been made to predict the probability of LBW. To our knowledge two studies [29,30], tried to develop a prediction model, though, they have less practical implication due to the predictors used are not easily obtainable in primary healthcare settings. We developed and validated a model and risk score to predict LBW in primary care settings of LMICs.…”