Factors influencing decision making in neonatology: inhaled nitric oxide in preterm infants.

ObjectiveWe studied decision making regarding inhaled nitric oxide (iNO) in preterm infants with Pulmonary Hypertension (PH).Study designWe asked members of the AAP-Society of Neonatal-Perinatal Medicine and Division-Chiefs to select from three management options- initiate iNO, engage parents in shared decision making or not consider iNO in an extremely preterm with PH followed by rating of factors influencing their decision.ResultsThree hundred and four respondents (9%) completed the survey; 36.5% chose to initiate iNO, 42% to engage parents, and 21.5% did not consider iNO. Provider's prior experience, safety, and patient-centered care were rated higher by those who initiated or offered iNO; lack of effectiveness and cost considerations by participants who did not chose iNO.ConclusionsMost neonatologists offer or initiate iNO therapy based on their individual experience. The minority who chose not to consider iNO placed higher value on lack of effectiveness and cost. These results demonstrate a tension between evidence and pathophysiology-based-therapy/personal experience

The Impact of Maternal Characteristics on the Moderately Premature Infant: An Antenatal Maternal Transport Clinical Prediction Rule

Background: Moderately premature infants, defined here as those born between 30 $\frac{0}{7}$ and 34 $\frac{6}{7}$ weeks gestation, comprise 3.9% of all births in the United States and 32% of all preterm births. While long-term outcomes for these infants are better than for less mature infants, morbidity and mortality are still substantially increased in comparison to infants born at term. There is an added survival benefit resulting from birth at a tertiary neonatal care center, and although many of these infants require tertiary level care, delivery at lower level hospitals and subsequent neonatal transfer are still common. Objective: Our primary aim was to determine the impact of maternal characteristics and antenatal medical management on the early neonatal course of the moderately premature infant. The secondary aim was to create a clinical prediction rule to determine which infants require intubation and mechanical ventilation in the first 24 hours of life. Such a prediction rule could inform the decision to transfer maternal-fetal patients prior to delivery to a facility with a Level III Neonatal Intensive Care Unit (NICU), where optimal care could be provided without the requirement for a neonatal transfer. Methods: Data for this analysis came from the cohort of infants in the Moderately Premature Infant Project (MPIP) database, a multi-center cohort study of 850 infants born at gestational age 30 $\frac{0}{7}$ to 34 $\frac{6}{7}$ weeks, who were discharged home alive. We built a logistic regression model to identify maternal characteristics associated with need for tertiary care, as measured by administration of surfactant. Using statistically significant covariates from this model, we then created a numerical decision rule to predict need for tertiary care. Results: In multivariate modeling, 4 factors were associated with reduction in the need for tertiary care, including, surfactant administration, including non-White race (OR=0.5, [0.3, 0.7], older gestational age, female gender (OR=0.6 [0.4, 0.8]) and use of antenatal corticosteroids (OR=0.5, [0.3, 0.8]). The clinical prediction rule to discriminate between infants who received surfactant, versus those who did not, had an area under the curve of 0.77 [0.73, 0.8]. Conclusions: Four antenatal risk factors are associated with a requirement for Level III NICU care as defined by the need for surfactant administration. Future analyses will examine a broader spectrum of antenatal characteristics and revalidate the prediction rule in an independent cohort

Health state preferences associated with weight status in children and adolescents

Abstract Background Childhood obesity is a substantial public health problem. The extent to which health state preferences (utilities) are related to a child's weight status has not been reported. The aims of this study were (1) to use a generic health state classification system to measure health related quality of life and calculate health utilities in a convenience sample of children and adolescents and (2) to determine the extent to which these measures are associated with weight status and body mass index (BMI). Methods We enrolled 76 children 5-18 years of age from a primary care clinic and an obesity clinic in Boston MA. We administered the Health Utilities Index (HUI) and used the HUI Mark 3 single- and multi-attribute utility functions to calculate health utilities. We determined BMI percentile and weight status based on CDC references. We examined single-attribute and overall utilities in relation to weight status and BMI. Results Mean (range) age was 10.8 (5-18) years. Mean (SD) BMI percentile was 76 (26); 55% of children were overweight or obese. The mean (SD) overall utility was 0.79 (0.17) in the entire sample. For healthy-weight children, the mean overall utility was higher than for overweight or obese children (0.81 vs. 0.78), but the difference was not statistically significant (difference 0.04, 95% CI -0.04, 0.11). Conclusions Our results provide a quantitative estimate of the health utility associated with overweight and obesity in children, and will be helpful to researchers performing cost effectiveness analyses of interventions to prevent and/or treat childhood obesity.</p

Factors influencing decision making in neonatology: inhaled nitric oxide in preterm infants.

ObjectiveWe studied decision making regarding inhaled nitric oxide (iNO) in preterm infants with Pulmonary Hypertension (PH).Study designWe asked members of the AAP-Society of Neonatal-Perinatal Medicine and Division-Chiefs to select from three management options- initiate iNO, engage parents in shared decision making or not consider iNO in an extremely preterm with PH followed by rating of factors influencing their decision.ResultsThree hundred and four respondents (9%) completed the survey; 36.5% chose to initiate iNO, 42% to engage parents, and 21.5% did not consider iNO. Provider's prior experience, safety, and patient-centered care were rated higher by those who initiated or offered iNO; lack of effectiveness and cost considerations by participants who did not chose iNO.ConclusionsMost neonatologists offer or initiate iNO therapy based on their individual experience. The minority who chose not to consider iNO placed higher value on lack of effectiveness and cost. These results demonstrate a tension between evidence and pathophysiology-based-therapy/personal experience

Clinical and economic evaluation of a proteomic biomarker preterm birth risk predictor: Cost-effectiveness modeling of prenatal interventions applied to predicted higher-risk pregnancies within a large and diverse cohort

AbstractObjectivesPreterm birth occurs in more than 10% of U.S. births and is the leading cause of U.S. neonatal deaths, with estimated annual costs exceeding 25 billion USD. Using real-world data, we modeled the potential clinical and economic utility of a prematurity-reduction program comprising screening in a racially and ethnically diverse population with a validated proteomic biomarker risk predictor, followed by case management with or without pharmacological treatment.MethodsThe ACCORDANT microsimulation model used individual patient data from a prespecified, randomly selected sub-cohort (N=847) of a multicenter, observational study of U.S. subjects receiving standard obstetric care with masked risk predictor assessment (TREETOP; NCT02787213). All subjects were included in three arms across 500 simulated trials: standard of care (SoC, control); risk predictor/case management comprising increased outreach, education and specialist care (RP-CM, active); and risk predictor/case management with pharmacological treatment (RP-MM, active). In the active arms, only subjects stratified as higher-risk by the predictor were modeled as receiving the intervention, whereas lower-risk subjects received standard care. Higher-risk subjects’ gestational ages at birth were shifted based on published efficacies, and dependent outcomes, calibrated using national datasets, were changed accordingly. Subjects otherwise retained their original TREETOP outcomes. Arms were compared using survival analysis for neonatal and maternal hospital length of stay, bootstrap intervals for neonatal cost, and Fisher’s exact test for neonatal morbidity/mortality (significance, p<0.05).ResultsThe model predicted improvements for all outcomes. RP-CM decreased neonatal and maternal hospital stay by 19% (p=0.029) and 8.5% (p=0.001), respectively; neonatal costs’ point estimate by 16% (p=0.098); and moderate-to-severe neonatal morbidity/mortality by 29% (p=0.025). RP-MM strengthened observed reductions and significance. Point estimates of benefit did not differ by race/ethnicity.ConclusionsModeled evaluation of a biomarker-based test-and-treat strategy in a diverse population predicts clinically and economically meaningful improvements in neonatal and maternal outcomes.Plain language summaryPreterm birth, defined as delivery before 37 weeks’ gestation, is the leading cause of illness and death in newborns. In the United States, more than 10% of infants is born prematurely, and this rate is substantially higher in lower-income, inner-city and Black populations. Prematurity associates with substantially increased risk of short- and long-term medical complications and can generate significant costs throughout the lives of affected children. Annual U.S. health care costs to manage short- and long-term prematurity complications are estimated to exceed 25 billion.Clinical interventions, including case management (increased patient outreach, education and specialist care), pharmacological treatment and their combination, can provide benefit to pregnancies at higher risk for preterm birth. Early and sensitive risk detection, however, remains a challenge.We have developed and validated a proteomic biomarker risk predictor for early identification of pregnancies at increased risk of preterm birth. The ACCORDANT study modeled treatments with real-world patient data from a racially and ethnically diverse U.S. population to compare the benefits of risk predictor testing plus clinical intervention for higher-risk pregnancies versus no testing and standard care. Measured outcomes included neonatal and maternal length of hospital stay, associated costs and neonatal morbidity and mortality. The model projected improved outcomes and reduced costs across all subjects, including ethnic and racial populations, when predicted higher-risk pregnancies were treated using case management with or without pharmacological treatment. The biomarker risk predictor shows high potential to be a clinically important component of risk stratification for pregnant women, leading to tangible gains in reducing the impact of preterm birth