The disparate impacts of college admissions policies on Asian American applicants.

There is debate over whether Asian American students face additional barriers, relative to white students, when applying to selective colleges. Here we present the results from analyzing 685,709 applications submitted over five application cycles to 11 highly selective colleges (the "Ivy-11"). We estimate that Asian American applicants had 28% lower odds of ultimately attending an Ivy-11 school than white applicants with similar academic and extracurricular qualifications. The gap was particularly pronounced for students of South Asian descent (49% lower odds). Given the high yield rates and competitive financial aid policies of the schools we consider, the disparity in attendance rates is likely driven, at least in part, by admissions decisions. In particular, we offer evidence that this pattern stems from two factors. First, many selective colleges give preference to the children of alumni in admissions. We find that white applicants were substantially more likely to have such legacy status than Asian applicants. Second, we identify geographic disparities potentially reflective of admissions policies that disadvantage students from certain regions of the United States. We hope these results inform discussions on equity in higher education.

Showing high-achieving college applicants past admissions outcomes increases undermatching.

More than 40% of US high school students have access to Naviance, a proprietary tool designed to guide college search and application decisions. The tool displays, for individual colleges, the standardized test scores, grade-point averages, and admissions outcomes of past applicants from a student's high school, so long as a sufficient number of students from previous cohorts applied to a given college. This information is intended to help students focus their efforts on applying to the most suitable colleges, but it may also influence application decisions in undesirable ways. Using data on 70,000 college applicants across 220 public high schools, we assess the effects of access to Naviance on application undermatch, or applying only to schools for which a candidate is academically overqualified. By leveraging variation in the year that high schools adopted the tool, we estimate that Naviance increased application undermatching by more than 50% among 17,000 high-achieving students in our dataset. This phenomenon may be due to increased conservatism: Students may be less likely to apply to colleges when they know their academic qualifications fall below the average of admitted students from their high school. These results illustrate how information on college competitiveness, when not appropriately presented and contextualized, can lead to unintended consequences.

Algorithm-Enabled, Personalized Glucose Management for Type 1 Diabetes at the Population Scale: Prospective Evaluation in Clinical Practice.

BACKGROUND: The use of continuous glucose monitors (CGMs) is recommended as the standard of care by the American Diabetes Association for individuals with type 1 diabetes (T1D). Few hardware-agnostic, open-source, whole-population tools are available to facilitate the use of CGM data by clinicians such as physicians and certified diabetes educators. OBJECTIVE: This study aimed to develop a tool that identifies patients appropriate for contact using an asynchronous message through electronic medical records while minimizing the number of patients reviewed by a certified diabetes educator or physician using the tool. METHODS: We used consensus guidelines to develop timely interventions for diabetes excellence (TIDE), an open-source hardware-agnostic tool to analyze CGM data to identify patients with deteriorating glucose control by generating generic flags (eg, mean glucose [MG] >170 mg/dL) and personalized flags (eg, MG increased by >10 mg/dL). In a prospective 7-week study in a pediatric T1D clinic, we measured the sensitivity of TIDE in identifying patients appropriate for contact and the number of patients reviewed. We simulated measures of the workload generated by TIDE, including the average number of time in range (TIR) flags per patient per review period, on a convenience sample of eight external data sets, 6 from clinical trials and 2 donated by research foundations. RESULTS: Over the 7 weeks of evaluation, the clinical population increased from 56 to 64 patients. The mean sensitivity was 99% (242/245; SD 2.5%), and the mean reduction in the number of patients reviewed was 42.6% (182/427; SD 10.9%). The 8 external data sets contained 1365 patients with 30,017 weeks of data collected by 7 types of CGMs. The rates of generic and personalized TIR flags per patient per review period were, respectively, 0.15 and 0.12 in the data set with the lowest average MG (141 mg/dL) and 0.95 and 0.22 in the data set with the highest average MG (207 mg/dL). CONCLUSIONS: TIDE is an open-source hardware-agnostic tool for personalized analysis of CGM data at the clinical population scale. In a pediatric T1D clinic, TIDE identified 99% of patients appropriate for contact using an asynchronous message through electronic medical records while reducing the number of patients reviewed by certified diabetes care and education specialists by 43%. For each of the 8 external data sets, simulation of the use of TIDE produced fewer than 0.25 personalized TIR flags per patient per review period. The use of TIDE to support telemedicine-based T1D care may facilitate sensitive and efficient guideline-based population health management.

Improved individual and population-level HbA1c estimation using CGM data and patient characteristics.

Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by COVID-19.

Differentiation of Baboon (Papio anubis) Induced-Pluripotent Stem Cells into Enucleated Red Blood Cells.

As cell culture methods and stem cell biology have progressed, the in vitro production of cultured RBCs (cRBCs) has emerged as a viable option to produce cells for transfusion or to carry therapeutic cargoes. RBCs produced in culture can be quality-tested either by xeno-transfusion of human cells into immuno-deficient animals, or by transfusion of autologous cells in immuno-competent models. Although murine xeno-transfusion methods have improved, they must be complemented by studies in immuno-competent models. Non-human primates (NHPs) are important pre-clinical, large animal models due to their high biological and developmental similarities with humans, including their comparable hematopoietic and immune systems. Among NHPs, baboons are particularly attractive to validate cRBCs because of the wealth of data available on the characteristics of RBCs in this species that have been generated by past blood transfusion studies. We report here that we have developed a method to produce enucleated cRBCs by differentiation of baboon induced pluripotent stem cells (iPSCs). This method will enable the use of baboons to evaluate therapeutic cRBCs and generate essential pre-clinical data in an immuno-competent, large animal model. Production of the enucleated baboon cRBCs was achieved by adapting the PSC-RED protocol that we previously developed for human cells. Baboon-PSC-RED is an efficient chemically-defined method to differentiate iPSCs into cRBCs that are about 40% to 50% enucleated. PSC-RED is relatively low cost because it requires no albumin and only small amounts of recombinant transferrin.

Scoring system for differentiating perforated and non-perforated pediatric appendicitis.

OBJECTIVES: Appendicitis is the most common indication for emergency pediatric surgery and its most significant complication is perforation. Perforated appendicitis (PA) may be managed conservatively, whereas non-perforated appendicitis (NP) is managed surgically. Recent studies have shown that ultrasound (US) is effective for differentiating between PA and NP, and does not expose pediatric patients to ionizing radiation. The purpose of this study is to enhance the accuracy of differentiation with a novel scoring system based on clinical, laboratory, and US findings. METHODS: This retrospective study included 243 patients aged 2-17 years who presented between 2006 and 2013 with surgically proven appendicitis, of whom 60 had perforation. Clinical and laboratory data were collected and US images evaluated by a pediatric radiologist. To create the scoring system, point values were assigned to each parameter. A randomly selected training sample of 137 subjects was used to create a scoring prediction model. The model was tested on the remaining 106 patients. RESULTS: Scores of ≥6, ≥11, and ≥15 yielded specificities of 64, 91, and 99%, and sensitivities of 96, 61, and 29%, respectively (p < 0.001). CONCLUSIONS: We have designed a scoring system incorporating clinical, laboratory, and sonographic findings which can differentiate PA from NP with high specificity.