Rate and Risk Factors for Contralateral Slippage in Adolescents Treated for Slipped Capital Femoral Epiphysis: A Comprehensive Analysis of 3,528 Cases.

BACKGROUND: After a unilateral slipped capital femoral epiphysis (SCFE), the contralateral hip is at risk for a subsequent SCFE. However, further information with regard to risk factors involved in the development of contralateral SCFE must be investigated. The purpose of this study was to report the rate and risk factors for subsequent contralateral SCFE in adolescents treated for unilateral SCFE by exploring a mix of known and potential risk factors. METHODS: A case-control study utilizing aggregated multi-institutional electronic medical record data between January 2003 and March 2023 was conducted. Patients <18 years of age diagnosed with SCFE who underwent surgical management were included. Variables associated with contralateral SCFE were identified using multivariable logistic regression models that adjusted for patient characteristics and time of the surgical procedure, providing adjusted odds ratios (ORs). The false discovery rate was accounted for via the Benjamini-Hochberg method. RESULTS: In this study, 15.3% of patients developed contralateral SCFE at a mean (and standard error) of 296.53 ± 17.23 days and a median of 190 days following the initial SCFE. Increased thyrotropin (OR, 1.43 [95% confidence interval (CI), 1.04 to 1.97]; p = 0.022), diabetes mellitus (OR, 1.67 [95% CI, 1.22 to 2.49]; p = 0.005), severe obesity (OR, 1.81 [95% CI, 1.56 to 2.57]; p < 0.001), history of human growth hormone use (OR, 1.85 [95% CI, 1.10 to 3.38]; p = 0.032), low vitamin D (OR, 5.75 [95% CI, 2.23 to 13.83]; p < 0.001), younger age in boys (under 12 years of age: OR, 1.85 [95% CI, 1.37 to 2.43]; p < 0.001) and in girls (under 11 years of age: OR, 1.47 [95% CI, 1.05 to 2.02]; p = 0.026), and tobacco exposure (OR, 2.43 [95% CI, 1.49 to 3.87]; p < 0.001) were significantly associated with increased odds of developing contralateral SCFE. CONCLUSIONS: In the largest study on this topic, we identified the rate, odds, and risk factors associated with development of contralateral SCFE. We found younger age, hypothyroidism, severe obesity, low vitamin D, diabetes mellitus, and a history of human growth hormone use to be independent risk factors. Our findings can aid clinical decision-making in at-risk patients. LEVEL OF EVIDENCE: Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

A mixed-methods study on the design of Artificial Intelligence and data science-based strategies to inform public health responses to COVID-19 in different local health ecosystems: A study protocol for COLEV.

Background: Artificial Intelligence (AI) and data science research are promising tools to better inform public policy and public health responses, promoting automation and affordability. During the COVID-19 pandemic, AI has been an aid to forecast outbreak spread globally. The overall aim of the study is to contribute to the ongoing public health, socioeconomic, and communication challenges caused by COVID-19. Protocol: COLEV is a five-pronged interdisciplinary mixed methods project based on AI and data science from an inclusive perspective of age and gender to develop, implement, and communicate useful evidence for COVID-19-related response and recovery in Colombia. The first objective is identification of stakeholders' preferences, needs, and their use of AI and data science relative to other forms of evidence. The second objective will develop locally relevant mathematical models that will shed light on the possible impact, trajectories, geographical spread, and uncertainties of disease progression as well as risk assessment. The third objective focuses on estimating the effect of COVID-19 on other diseases, gender disparities and health system saturation. The fourth objective aims to analyze popular social networks to identify health-related trending interest and users that act as 'super spreaders' for information and misinformation. Finally, the fifth objective, aims at designing disruptive cross-media communication strategies to confront mis- and dis-information around COVID-19. To understand stakeholders' perspectives, we will use semi-structured interviews and ethnographic work. Daily cases and deaths of COVID-19 reported from the National Surveillance System (INS) of Colombia will be used for quantitative analysis, and data regarding the online conversation will be obtained from Facebook and Twitter. Conclusions: COLEV intends to facilitate the dialogue between academia and health policymakers. The results of COLEV will inform on the responsible, safe and ethical use of AI and data science for decision-making in the context of sanitary emergencies in deeply unequal settings.

Imagining Macondo: Interacting with García Márquez's Literary Landscape.

Imagining Macondo is a public artwork that commemorates Nobel Prize-winning author Gabriel García Márquez. It was first showcased at the Bogota International Book Fair in April 2015 to an audience of more than 300,000 over the course of two weeks. The project involved extensive collaboration between an international team of artists, designers, and programmers. This article explores the historical and artistic contexts for the creation of the work, discusses the audience reception to the work, and describes the significant software and production requirements necessary to create an installation with thousands of participants and hundreds of thousands of viewers.