Prediction of Mortality in Very Premature Infants: A Systematic Review of Prediction Models

Abstract

ContextBeing born very preterm is associated with elevated risk for neonatal mortality. The aim of this review is to give an overview of prediction models for mortality in very premature infants, assess their quality, identify important predictor variables, and provide recommendations for development of future models.MethodsStudies were included which reported the predictive performance of a model for mortality in a very preterm or very low birth weight population, and classified as development, validation, or impact studies. For each development study, we recorded the population, variables, aim, predictive performance of the model, and the number of times each model had been validated. Reporting quality criteria and minimum methodological criteria were established and assessed for development studies.ResultsWe identified 41 development studies and 18 validation studies. In addition to gestational age and birth weight, eight variables frequently predicted survival: being of average size for gestational age, female gender, non-white ethnicity, absence of serious congenital malformations, use of antenatal steroids, higher 5-minute Apgar score, normal temperature on admission, and better respiratory status. Twelve studies met our methodological criteria, three of which have been externally validated. Low reporting scores were seen in reporting of performance measures, internal and external validation, and handling of missing data.ConclusionsMultivariate models can predict mortality better than birth weight or gestational age alone in very preterm infants. There are validated prediction models for classification and case-mix adjustment. Additional research is needed in validation and impact studies of existing models, and in prediction of mortality in the clinically important subgroup of infants where age and weight alone give only an equivocal prognosis.

Predicting 2-y outcome in preterm infants using early multimodal physiological monitoring

“…Medlock et al (7) found that multivariate models of early clinical information predicted mortality in preterm infants better than BW or GA alone. Studies implementing the commonly used SNAP-II and SNAPPE-II scores showed a range of AUC values for the prediction of neonatal mortality, from 0.66 to 0.78 in SNAP-II studies and 0.60 to 0.91 in SNAPPE-II studies (8).…”

“…Early clinical information, including Apgar scores, gender, birth weight (BW), gestational age (GA) (4)(5)(6)(7), and illness severity scores, such as SNAP-II and SNAPPE-II have been used to predict short-term outcome (8). Quantitative analysis of multiple risk factors combined in a multivariate model can improve outcome prediction (7).…”

Prediction of Neonatal Outcomes in Extremely Preterm Neonates

“…Moreover, the predictive ability of our multipleoutcome model is comparable to recent models developed to predict mortality or survival free of severe morbidity. 8,15,19,34 Because the goal was to predict outcomes after initiation of intensive care, we excluded infants declared moribund or admitted for palliative care. The severity of each morbidity was ranked based on existing classification systems, [21][22][23] and the most common and debilitating morbidities, with proven cumulative and additive effects on long-term outcomes in neonates, 3,35 were classified as severe.…”

“…8 Furthermore, prediction models examining a combined outcome of mortality and morbidities did not have better performance than models predicting mortality alone. [16][17][18][19] Therefore, for improved prediction it is important to distinguish between mortality and morbidities and to develop multivariable prediction models that reflect a range of outcomes along the severity spectrum.…”

“…Numerous studies have developed statistical models to predict mortality 7,8 or specific morbidities [9][10][11][12][13][14] in infants born very preterm. Investigators have also derived statistical models to predict survival without major morbidities by combining infants who die with those who survive with severe morbidities.…”