Author Correction: Early pregnancy ultrasound measurements and prediction of first trimester pregnancy loss: A logistic model (Scientific Reports, (2020), 10, 1, (1545), 10.1038/s41598-020-58114-3)

The original version of this Article contained an error in the spelling of the author Patricia J. Goedecke which was incorrectly given as Patricia J. Goeske. The original Article has been corrected

Safety and pharmacokinetics of multiple dose myo-inositol in preterm infants

BACKGROUND: Preterm infants with respiratory distress syndrome (RDS) given inositol had reduced bronchopulmonary dysplasia (BPD), death and severe retinopathy of prematurity (ROP). We assessed the safety and pharmacokinetics of daily inositol to select a dose providing serum levels previously associated with benefit, and to learn if accumulation occurred when administered throughout the normal period of retinal vascularization. METHODS: Infants ≤ 29 wk GA (n = 122, 14 centers) were randomized and treated with placebo or inositol at 10, 40, or 80 mg/kg/d. Intravenous administration converted to enteral when feedings were established, and continued to the first of 10 wk, 34 wk postmenstrual age (PMA) or discharge. Serum collection employed a sparse sampling population pharmacokinetics design. Inositol urine losses and feeding intakes were measured. Safety was prospectively monitored. RESULTS: At 80 mg/kg/d mean serum levels reached 140 mg/l, similar to Hallman's findings. Levels declined after 2 wk, converging in all groups by 6 wk. Analyses showed a mean volume of distribution 0.657 l/kg, clearance 0.058 l/kg/h, and half-life 7.90 h. Adverse events and comorbidities were fewer in the inositol groups, but not significantly so. CONCLUSION: Multiple dose inositol at 80 mg/kg/d was not associated with increased adverse events, achieves previously effective serum levels, and is appropriate for investigation in a phase III trial

Racial differences in healthcare expenditures for prevalent multimorbidity combinations in the USA: a cross-sectional study

Abstract Background We aimed to model total charges for the most prevalent multimorbidity combinations in the USA and assess model accuracy across Asian/Pacific Islander, African American, Biracial, Caucasian, Hispanic, and Native American populations. Methods We used Cerner HealthFacts data from 2016 to 2017 to model the cost of previously identified prevalent multimorbidity combinations among 38 major diagnostic categories for cohorts stratified by age (45–64 and 65 +). Examples of prevalent multimorbidity combinations include lipedema with hypertension or hypertension with diabetes. We applied generalized linear models (GLM) with gamma distribution and log link function to total charges for all cohorts and assessed model accuracy using residual analysis. In addition to 38 major diagnostic categories, our adjusted model incorporated demographic, BMI, hospital, and census division information. Results The mean ages were 55 (45–64 cohort, N = 333,094) and 75 (65 + cohort, N = 327,260), respectively. We found actual total charges to be highest for African Americans (means $78,544 [45–64],$176,274 [65 +]) and lowest for Hispanics (means $29,597 [45–64],$66,911 [65 +]). African American race was strongly predictive of higher costs (p < 0.05 [45–64]; p < 0.05 [65 +]). Each total charge model had a good fit. With African American as the index race, only Asian/Pacific Islander and Biracial were non-significant in the 45–64 cohort and Biracial in the 65 + cohort. Mean residuals were lowest for Hispanics in both cohorts, highest in African Americans for the 45–64 cohort, and highest in Caucasians for the 65 + cohort. Model accuracy varied substantially by race when multimorbidity grouping was considered. For example, costs were markedly overestimated for 65 + Caucasians with multimorbidity combinations that included heart disease (e.g., hypertension + heart disease and lipidemia + hypertension + heart disease). Additionally, model residuals varied by age/obesity status. For instance, model estimates for Hispanic patients were highly underestimated for most multimorbidity combinations in the 65 + with obesity cohort compared with other age/obesity status groupings. Conclusions Our finding demonstrates the need for more robust models to ensure the healthcare system can better serve all populations. Future cost modeling efforts will likely benefit from factoring in multimorbidity type stratified by race/ethnicity and age/obesity status