Background Adrenoleukodystrophy (ALD) encompasses different neurological phenotypes, ranging from the most severe cerebral forms (C-ALD) to the less severe adrenomyeloneuropathy (AMN). As visual system can be varyingly involved, we aimed at exploring whether optical coherence tomography (OCT) may detect retinal abnormalities and their longitudinal changes in adult ALD patients. Methods In this cross-sectional and longitudinal study, we measured the thicknesses of peripapillary retinal nerve fiber layer (pRNFL), macular ganglion cell complex (mGCC), and segmented inner and outer macula at baseline and their changes over time in 11 symptomatic adult ALD males and 10 age-and sex-matched healthy controls. Statistical analyses were performed for the patients as complete group, and splitting them into two subgroups, one (C-ALD) with and the other (AMN) without cerebral parieto-occipital white matter (WM) lesions. Results In the complete ALD group and in the C-ALD subgroup, the average pRNFL, mGCC, and inner macula were significantly thinner than in controls (p ≤ 0.01), whereas in the AMN subgroup, they were constantly, though non-significantly, thinner. Significant outer macula thinning was also observed (p < 0.01). In the complete ALD group, follow-up assessment (mean 26.8 months, range 8-48) showed mildly progressive thinning of inferior pRNFL, average mGCC, and inner macula. Conclusions In adult ALD patients, OCT can reveal retinal abnormalities which are prominent in the more compromised patients, namely those with parieto-occipital WM lesions. The inferior pRNFL, average mGCC and inner macula thicknesses might be sensitive-to-change OCT parameters, but their utility and consistency for short-term longitudinal studies deserve further investigations.

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Background Overcrowding occurs when the identified need for emergency services outweighs the available resources in the emergency department (ED). Literature shows that ED overcrowding impacts the overall quality of the entire hospital production system, as confirmed by the recent COVID-19 pandemic. This study aims to identify the most relevant variables that cause ED overcrowding using the input-process-output model with the aim of providing managers and policy makers with useful hints for how to effectively redesign ED operations. Methods A mixed-method approach is used, blending qualitative inquiry with quantitative investigation in order to: i) identifying and operationalizing the main components of the model that can be addressed by hospital operation management teams and ii) testing and measuring how these components can influence ED LOS. Results With a dashboard of indicators developed following the input-process-output model, the analysis identifies the most significant variables that have an impact on ED overcrowding: the type (age and complexity) and volume of patients (input), the actual ED structural capacity (in terms of both people and technology) and the ED physician-to-nurse ratio (process), and the hospital discharging process (output). Conclusions The present paper represents an original contribution regarding two different aspects. First, this study combines different research methodologies with the aim of capturing relevant information that by relying on just one research method, may otherwise be missed. Second, this study adopts a hospitalwide approach, adding to our understanding of ED overcrowding, which has thus far focused mainly on single aspects of ED operations.

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