P385 Results of a teleconsultation campaign for Inflammatory Bowel Disease (IBD) patients to check their treatment adherence and assess their level of anxiety during the first COVID-19 lockdown

Background Long-term treatment adherence of patients treated for IBD is quite low, around 50% according to literature. Patients are often suspicious of the infectious risks vis-à-vis immunosuppressants and in particular biotherapies. Methods Analysis of the treatment adherence and the level of anxiety of IBD patients treated by immunosuppressants during the first French COVID-19 lockdown. Monocentric prospective observational study. Teleconsultations were made by the same gastroenterologist not usually involved in patient care, using randomly an active file of 96 IBD patients monitored in a database (Focus MICI®). Treatments: Corticosteroids n = 0; Azathioprine n = 2; Adalimumab n = 9; Infliximab n= 44 (53%); Golimumab n = 1; Vedolizumab n = 11; Tofacitinib n = 0; Methotrexate n = 3; Ustekinumab n = 5; Combotherapy n = 20. Results Calls from 09/4 to 07/5 2020. 13/96 (13.5%) unreachable patients (answering machine, wrong number, no answer, working, etc.). No call was refused when patients were reached. Analysis on 83 patients. Average age: 41.7 years; M / F (55/41) [20-80]. Crohn / RCH: 72/24. Call duration: 5 to 22 minutes. Clinical remission estimated by the patient: Yes / No: 73/10 (88%). Clinical signs possibly linked to Covid: 9/86 (10.4%); discontinuation of treatment: 2/9 (22%). Finally, the treatment was stopped for 11/83 (13%) patients in this IBD population, most of them were in remission. Only 2/9 (22%) with potential Covid symptoms had stopped their treatment. On an anxiety scale from 1 to 10, 41% of patients were moderately to very worried. Among the main fears: increased risk of Covid-19 infection during treatment and fear of coming to the hospital during the epidemic (nosocomial risk). None of the patients spontaneously took the initiative to call first their referent gastroenterologist to discuss the situation. For the others (87%), continuation of treatment with an adherence estimated between 8 and 10 on a scale from 1 to 10. Results of the call the phone call was generally much appreciated by IBD patients. Most of the patients were reassured and convinced to continue their treatment and to contact their referent gastroenterologist. Conclusion Our results show that the first Covid-19 lockdown was responsible for a high level of anxiety among patients (41%) and a negative effect on patient compliance (not necessarily potential Covid + patients). Advantages of teleconsultation: good acceptability, excellent effectiveness in terms of reassurance and treatment adherence. The cessation of the treatment was in most cases hidden to the doctor. We think that there is a subsequent interest in maintaining tele/visio consultations in addition to face-to-face consultations.

A Monte Carlo evaluation of growth mixture modeling

Growth mixture modeling (GMM) and its variants, which group individuals based on similar longitudinal growth trajectories, are quite popular in developmental and clinical science. However, research addressing the validity of GMM-identified latent subgroupings is limited. This Monte Carlo simulation tests the efficiency of GMM in identifying known subgroups (k = 1–4) across various combinations of distributional characteristics, including skew, kurtosis, sample size, intercept effect size, patterns of growth (none, linear, quadratic, exponential), and proportions of observations within each group. In total, 1,955 combinations of distributional parameters were examined, each with 1,000 replications (1,955,000 simulations). Using standard fit indices, GMM often identified the wrong number of groups. When one group was simulated with varying skew and kurtosis, GMM often identified multiple groups. When two groups were simulated, GMM performed well only when one group had steep growth (whether linear, quadratic, or exponential). When three to four groups were simulated, GMM was effective primarily when intercept effect sizes and sample sizes were large, an uncommon state of affairs in real-world applications. When conditions were less ideal, GMM often underestimated the correct number of groups when the true number was between two and four. Results suggest caution in interpreting GMM results, which sometimes get reified in the literature.

Advances and surprises in a decade of oocyte meiosis research

Eggs are produced from progenitor oocytes through meiotic cell division. Fidelity of meiosis is critical for healthy embryogenesis – fertilisation of aneuploid eggs that contain the wrong number of chromosomes is a leading cause of genetic disorders including Down’s syndrome, human embryo deaths and infertility. Incidence of meiosis-related oocyte and egg aneuploidies increases dramatically with advancing maternal age, which further complicates the ‘meiosis problem’. We have just emerged from a decade of meiosis research that was packed with exciting and transformative research. This minireview will focus primarily on studies of mechanisms that directly influence chromosome segregation.

Current Projection Methods-Induced Biases at Subgroup Detection for Machine-Learning Based Data-Analysis of Biomedical Data

Advances in flow cytometry enable the acquisition of large and high-dimensional data sets per patient. Novel computational techniques allow the visualization of structures in these data and, finally, the identification of relevant subgroups. Correct data visualizations and projections from the high-dimensional space to the visualization plane require the correct representation of the structures in the data. This work shows that frequently used techniques are unreliable in this respect. One of the most important methods for data projection in this area is the t-distributed stochastic neighbor embedding (t-SNE). We analyzed its performance on artificial and real biomedical data sets. t-SNE introduced a cluster structure for homogeneously distributed data that did not contain any subgroup structure. In other data sets, t-SNE occasionally suggested the wrong number of subgroups or projected data points belonging to different subgroups, as if belonging to the same subgroup. As an alternative approach, emergent self-organizing maps (ESOM) were used in combination with U-matrix methods. This approach allowed the correct identification of homogeneous data while in sets containing distance or density-based subgroups structures; the number of subgroups and data point assignments were correctly displayed. The results highlight possible pitfalls in the use of a currently widely applied algorithmic technique for the detection of subgroups in high dimensional cytometric data and suggest a robust alternative.

A SEMANTIC ANALYSIS OF DEIXIS IN DRAMA WRITTEN BY LUCILLE FLETCHER

This study purposes to describe the forms of deixis in the drama written by Lucille Fletcher. This is descriptive qualitative study. The sources of the data are in the form of word and phrase in the drama script written by Lucille Fletcherentitled Sorry, Wrong Number. Based on the data findings, the form of deixis in the drama script Lucille Fletcher’s Sorry, Wrong Number are the person deixis, place deixis, time deixis, and social deixis. The highest occurrence on the forms of deixis in Lucille Fletcher’s Sorry, Wrong Number is person deixis. It means that person deixis is the most common type used by the characters in Lucille Fletcher’s Sorry, Wrong Number to communicate between each character in order to deliver their message due to the plot of the drama.