Expanding the phenotypic spectrum of PROS: reclassifying isolated lateralised overgrowth.

Lateralised overgrowth (LO) is characterised by the asymmetric increase in the size of any part of the body exceeding 10% compared with the unaffected contralateral one. LO is a key feature in various syndromic overgrowth disorders, such as Beckwith-Wiedemann spectrum and -related overgrowth spectrum (PROS). However, it can also present as isolated (ILO).

Anesthesia for pregnant patients with symptomatic neurological disease: 13 years' experience from a tertiary care center.

Background: Improvements in diagnostics and clinical care have allowed more women of childbearing age, suffering from neurological diseases, to safely have pregnancy, reducing peripartum complications. However, these patients remain at risk and are a constant challenge for anesthesiologists in the delivery room.

Methods: To assess the type of anesthesiologic management performed for delivery in obstetric patients with preexisting neurological disease and who reported significant neurological symptoms during pregnancy, a retrospective observational study was carried out between 1 October 2008 and 30 September 2021.

Consistency in Self-Reported Race-and-Ethnicity Over Time: Implications for Improving the Accuracy of Imputations and Making the Best Use of Self-Report.

Background: Medicare Bayesian Improved Surname and Geocoding (MBISG), which augments an imperfect race-and-ethnicity administrative variable to estimate probabilities that people would self-identify as being in each of 6 mutually exclusive racial-and-ethnic groups, performs very well for Asian American and Native Hawaiian/Pacific Islander (AA&NHPI), Black, Hispanic, and White race-and-ethnicity, somewhat less well for American Indian/Alaska Native (AI/AN), and much less well for Multiracial race-and-ethnicity.

Objectives: To assess whether temporal inconsistency of self-reported race-and-ethnicity might limit improvements in approaches like MBISG.

Methods: Using the Medicare Health Outcomes Survey (HOS) baseline (2013-2018) and 2-year follow-up data (2015-2020), we evaluate the consistency of self-reported race-and-ethnicity coded 2 ways: the 6 mutually exclusive MBISG categories and individual endorsements of each racial-and-ethnic group.

Comparison of Alternative Approaches to Using Race-and-Ethnicity Data in Estimating Differences in Health Care and Social Determinants of Health.

Objective: The objective of this study was to compare 2 approaches for representing self-reported race-and-ethnicity, additive modeling (AM), in which every race or ethnicity a person endorses counts toward measurement of that category, and a commonly used mutually exclusive categorization (MEC) approach. The benchmark was a gold-standard, but often impractical approach that analyzes all combinations of race-and-ethnicity as distinct groups.

Methods: Data came from 313,739 respondents to the 2021 Medicare Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys who self-reported race-and-ethnicity.