Ocular immunotherapy-related adverse events (IRAEs), although rare, can be sight-threatening. Our objective was to analyze ocular IRAEs diagnosed in France from the marketing of immune checkpoint inhibitors (ICPIs) until June 2021 and to review the literature. We collected the cases of 28 patients (36 ocular IRAEs), occurring after an average of 17 weeks (±19). Forty-six percent of patients were treated for metastatic melanoma. Anti-PD1 agents were responsible for 57% of the IRAEs. Anterior uveitis was the most common (44%), followed by panuveitis (28%). Of 25 uveitis cases, 80% were bilateral and 60% were granulomatous. We found one case with complete Vogt-Koyanagi–Harada syndrome and one case of birdshot retinochoroidopathy. The other IRAEs were eight ocular surface disorders, one optic neuropathy, and one inflammatory orbitopathy. Seventy percent of the IRAEs were grade 3 according to the common terminology of AEs. ICPIs were discontinued in 60% of patients and 50% received local corticosteroids alone. The literature review included 230 uveitis cases, of which 7% were granulomatous. The distributions of ICPIs, cancer, and type of uveitis were similar to our cohort. Ocular IRAEs appeared to be easily controlled by local or systemic corticosteroids and did not require routine discontinuation of ICPIs. Further work is still warranted to define the optimal management of ocular IRAEs.

The sudden admission of many patients with similar needs caused by the COVID-19 (SARS-CoV-2) pandemic forced health care centers to temporarily transform units to respond to the crisis. This process greatly impacted the daily activities of the hospitals. In this paper, we propose a two-step approach based on process mining and discrete-event simulation for sizing a recovery unit dedicated to COVID-19 patients inside a hospital. A decision aid framework is proposed to help hospital managers make crucial decisions, such as hospitalization cancellation and resource sizing, taking into account all units of the hospital. Three sources of patients are considered: (i) planned admissions, (ii) emergent admissions representing day-to-day activities, and (iii) COVID-19 admissions. Hospitalization pathways have been modeled using process mining based on synthetic medico-administrative data, and a generic model of bed transfers between units is proposed as a basis to evaluate the impact of those moves using discrete-event simulation. A practical case study in collaboration with a local hospital is presented to assess the robustness of the approach. Note to Practitioners —In this paper we develop and test a new decision-aid tool dedicated to bed management, taking into account exceptional hospitalization pathways such as COVID-19 patients. The tool enables the creation of a dedicated COVID-19 intensive care unit with specific management rules that are fine-tuned by considering the characteristics of the pandemic. Health practitioners can automatically use medico-administrative data extracted from the information system of the hospital to feed the model. Two execution modes are proposed: (i) fine-tuning of the staffed beds assignment policies through a design of experiment and (ii) simulation of user-defined scenarios. A practical case study in collaboration with a local hospital is presented. The results show that our model was able to find the strategy to minimize the number of transfers and the number of cancellations while maximizing the number of COVID-19 patients taken into care was to transfer beds to the COVID-19 ICU in batches of 12 and to cancel appointed patients using ICU when the department hit a 90% occupation rate.

Type 1 Gaucher disease (GD) is a rare autosomal recessive lysosomal storage disorder caused by deficient activity of beta-glucocerebrosidase, leading to accumulation of its substrate (glucosylceramide) in macrophages of the reticuloendothelial system, which are then referred to as Gaucher cells. The most frequent symptoms are asthenia, spleen and liver enlargement, bone abnormalities and cytopenia due to bone marrow infiltration. Lung involvement in GD is a rare finding, and it is unclear whether it may regress under enzyme replacement therapy (ERT) or substrate reduction therapy (SRT). Here we report a case of type 1 GD recently diagnosed in an elderly patient complicated by infiltrative lung disease, which responded to ERT.

Introduction: Severe acute respiratory syndrome coronavirus 2 is a viral respiratory infection that can cause systemic disorders and lead to death, particularly in older people. Proton pump inhibitors (PPIs) increase the risk of enteric and lung infections. Considering the broad use of PPIs in older people, the potential role of PPIs in COVID-19 could be of dramatic significance. The objective of our study was to evaluate the link between PPIs and severe COVID-19 in older people. Method: We performed a retrospective cohort study, including all patients aged ≥65, hospitalised for a diagnosis of COVID-19. Epidemiological, clinical and biological data were extracted and we performed an Inverse Probability of Treatment Weighing method based on a propensity score. Results: From March 2020 to February 2021, a total of 834 patients were included, with a median age of 83 and 52.8% were male. A total of 410 patients had a PPIs prescription, 358 (87.3%) were long-term PPIs-users and 52 (12.7%) were recent PPIs-users. Among PPIs-users, 163 (39.8%) patients developed severe COVID-19 versus 113 (26.7%) in PPIs-non users (odds ratio (OR) = 1.59 [1.18–2.14]; P < 0.05). Moreover, the double dose PPI-users had a higher risk of developing severe COVID-19 (OR = 3.36 [1.17–9.66]; P < 0.05) than the full dose PPI-users (OR = 2.15 [1.22–3.76]; P < 0.05) and the half dose PPI-users (OR = 1.64 [1.13–2.37]; P < 0.05). Conclusion: Our study reports evidence that the use of PPIs was associated with an increased risk of severe COVID-19 in older people.