Estimation and testing of Wilcoxon–Mann–Whitney effects in factorial clustered data designs

Clustered data arise frequently in many practical applications whenever units are repeatedly observed under a certain condition. One typical example for clustered data are animal experiments, where several animals share the same cage and should not be assumed to be completely independent. Standard methods for the analysis of such data are Linear Mixed Models and Generalized Estimating Equations—however, checking their assumptions is not easy, especially in scenarios with small sample sizes, highly skewed, count, and ordinal or binary data. In such situations, Wilcoxon–Mann–Whitney type effects are suitable alternatives to mean-based or other distributional approaches. Hence, no specific data distribution, symmetric or asymmetric, is required. Within this work, we will present different estimation techniques of such effects in clustered factorial designs and discuss quadratic- and multiple contrast type-testing procedures for hypotheses formulated in terms of Wilcoxon–Mann–Whitney effects. Additionally, the framework allows for the occurrence of missing data: estimation and testing hypotheses are based on all-available data instead of complete-cases. An extensive simulation study investigates the precision of the estimators and the behavior of the test procedures in terms of their type-I error control. One real world dataset exemplifies the applicability of the newly proposed procedures

Obesity is associated with myelin oligodendrocyte glycoprotein antibody-associated disease in acute optic neuritis

Optic neuritis (ON) is a frequent presentation at onset of multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). The pathophysiology underlying these diseases, especially MOGAD, is still being elucidated. While obesity has been reported to potentially be a risk factor for MS, this has not been explored in NMOSD or MOGAD. We aimed to investigate a possible association between obesity (body mass index [BMI] > 30 kg/m(2)) in patients with MOGAD, aquaporin 4-IgG positive NMOSD (AQP4-IgG+ NMOSD) or MS. In this multicenter non-interventional retrospective study, data was collected from patients with a first ever demyelinating attack of ON subsequently diagnosed with MOGAD (n = 44), AQP4-IgG+ NMOSD (n = 49) or MS (n = 90) between 2005 and 2020. The following data was collected: age, sex, ethnicity, BMI (documented before corticosteroid treatment), and the ON etiology after diagnostic work-up. A mixed model analysis was performed to assess the potential of obesity or BMI to predict MOGAD-ON, and to distinguish MOGAD-ON from AQP4-IgG+ NMOSD-ON and MS-ON. Main outcome measures included BMI in patients with acute ON and subsequent diagnosis of MOGAD, AQP4-IgG+ NMOSD or MS. A higher BMI was significantly associated with a diagnosis of MOGAD-ON (p < 0.001); in MOGAD patients the mean BMI was 31.6 kg/m(2) (standard deviation (SD) 7.2), while the mean BMI was 24.7 kg/m(2) (SD 5.3) in AQP4-IgG+ NMOSD patients, and 26.9 kg/m(2) (SD 6.2) in MS patients. Mixed-effects multinomial logistic regression, adjusted for age and sex, with obesity as a binary variable, revealed that obesity was associated with a higher odds ratio (OR) of a subsequent MOGAD diagnosis (OR 5.466, 95% CI [2.039, 14.650], p = 0.001) in contradistinction with AQP4-IgG+ NMOSD. This study suggests an association between obesity and MOGAD. Our findings require further exploration, but could have significant pathophysiologic implications if confirmed in larger prospective studies

Magnetic field-induced interactions between phones containing magnets and cardiovascular implantable electronic devices: Flip it to be safe?

BACKGROUND: Recent case reports and small studies have reported activation of the magnet-sensitive switches in cardiovascular implantable electronic devices (CIED) by the new iPhone 12 series, initiating asynchronous pacing in pacemakers and suspension of anti-tachycardia therapies in ICDs. OBJECTIVE AND METHODS: We performed a prospective single-center observational study to quantify the risk of magnetic field interactions of the iPhone 12 with CIEDs. A representative model of each CIED series from all manufacturers was tested ex vivo. Incidence and minimum distance necessary for magnet mode triggering were analyzed in 164 CIED patients with either the front or the back of the phone facing the device. The magnetic field of the iPhone 12 was analyzed using a 3-axis hall probe. RESULTS: Ex vivo, magnetic interferences occurred in 84.6% with the back compared to 46.2% with the front of the iPhone 12 facing the CIED. In vivo, activation of the magnet-sensitive switch occurred in 30 CIED patients (18.3%; 21 pacemaker, 9 ICDs) when the iPhone 12 was placed in close proximity over the CIED pocket and the back of the phone was facing the skin. Multiple binary logistic regression analysis identified the implantation depth (95% confidence interval [CI], 0.02 to 0.24) as independent predictor of magnet-sensitive switch activation. CONCLUSION: Magnetic field interactions occur only in close proximity, and with precise alignment of the iPhone 12 and CIEDs. It is important to advise CIED patients to not put the iPhone 12 directly on the skin above the CIED. Further recommendations are not necessary