Clinicopathological analysis of BRAF and non-BRAF MAPK pathway-altered gliomas in paediatric and adult patients: a single-institution study of 40 patients.

AIMS: Mitogen-activated protein kinase (MAPK) pathway alteration is a major oncogenic driver in paediatric low-grade gliomas (LGG) and some adult gliomas, encompassing BRAF (most common) and non-BRAF alterations. The aim was to determine the frequency, molecular spectrum and clinicopathological features of MAPK-altered gliomas in paediatric and adult patients at our neuropathology site in Kuwait. METHODS: We retrospectively searched the data of molecularly sequenced gliomas between 2018 and 2023 for MAPK alterations, revised the pathology in view of the 2021 WHO classification and evaluated the clinicopathological data for possible correlations. RESULTS: Of 272 gliomas, 40 (15%) harboured a MAPK pathway alteration in 19 paediatric (median 9.6 years; 1.2-17.6) and 21 adult patients (median 37 years; 18.9-89.2), comprising 42% and 9% of paediatric and adult cases, respectively. Pilocytic astrocytoma and glioblastoma were the most frequent diagnoses in children (47%) and adults (43%), respectively. BRAF V600E (n=17, 43%) showed a wide distribution across age groups, locations and pathological diagnoses while KIAA1549::BRAF fusion (n=8, 20%) was spatially and histologically restricted to cerebellar paediatric LGGs. Non-V600E variants and BRAF amplifications accompanied other molecular aberrations in high-grade tumours. Non-BRAF MAPK alterations (n=8) included mutations and gene fusions involving FGFR1, NTRK2, NF1, ROS1 and MYB. Fusions included KANK1::NTRK2, GOPC::ROS1 (both infant hemispheric gliomas), FGFR1::TACC1 (diffuse LGG), MYB::QKI (angiocentric glioma) and BCR::NTRK2 (glioblastoma). Paradoxical H3 K27M/MAPK co-mutations were observed in two LGGs. CONCLUSION: The study provided insights into MAPK-altered gliomas in Kuwait highlighting the differences among paediatric and adult patients and providing a framework for planning therapeutic polices.

Prevalence of Latent Tuberculosis Infection Among Rheumatology Patients and Management Practices in the United Arab Emirates: A Single-Center Retrospective Cohort Study.

Introduction Prior to immunosuppression, rheumatology patients are routinely screened for latent tuberculosis (TB) infection using interferon-gamma release assays (IGRAs). Variability in the management of latent and indeterminate IGRA results across institutions limited long-term outcome data. A retrospective study was conducted at Tawam Hospital, United Arab Emirates, to investigate the incidence and management protocols associated with positive and indeterminate IGRA results, as well as TB infection, among patients with rheumatic conditions. Methods A single-center retrospective observational study was performed at Tawam Hospital, Abu Dhabi, UAE. Ethical approval for this study was obtained from the Tawam Human Research Ethics Committee. Laboratory records and the hospital's electronic medical system were used to obtain information about IGRA results over a 12-year period (April 2010-April 2022). The hospital's electronic medical system was used to obtain patient information and subsequent management approaches of positive and indeterminate IGRAs. Moreover, long-term follow-up data were collected to determine the risk of TB reactivation in the cohort. Results We found a total of 1,012 positive and 223 indeterminate IGRA test results within the 12-year period. Within the rheumatology department, 123 positive and 39 indeterminate IGRA results were identified. In the indeterminate IGRA group, the majority were women (n = 24, 61.5%) and UAE nationals (n = 22, 56.4%), and their mean age was 38.6 years. Systemic lupus erythematosus was the most prevalent rheumatologic condition (n = 21, 53.8%). Thirteen (33.3%) were on disease-modifying anti-rheumatic drugs (DMARDs) and 26 (66.7%) were on corticosteroids during IGRA testing. A total of eight patients (20.5%) received anti-TB medications. In the positive IGRA group, the mean age was 55.7 years and the female-to-male ratio was 3:1. The most common rheumatologic condition was rheumatoid arthritis (n = 69, 56%). Sixty-five (52.8%) patients were on conventional DMARDs, 43 (34.9%) were on corticosteroids during IGRA testing, and 74 (60%) received anti-TB medications. Two cases (1.6%) of active TB infections were detected among patients with positive IGRA tests, both of whom were receiving anti-tumor necrosis factor alpha inhibitor treatment in combination with methotrexate. No cases of active TB infection were observed in the indeterminate IGRA group. Conclusion Long-term data on the risk of TB activation in positive and indeterminate IGRA results for rheumatological conditions are low. It is recommended to reassess the choice of using anti-TNF-α, with a positive IGRA result if no other feasible alternatives can be offered. Our findings stress the importance of age, underlying diseases, and immunosuppressive treatments in interpreting IGRA results and guiding patient management. A large multicenter study is needed to understand the differences and outcomes of such patients in TB endemic and nonendemic geographical areas.

Correction to: Exploring the impact of air pollution on COVID-19 admitted cases: Evidence from vector error correction model (VECM) approach in explaining the relationship between air pollutants towards COVID-19 cases in Kuwait.

[This corrects the article DOI: 10.1007/s42081-022-00165-z.].

Exploring the impact of air pollution on COVID-19 admitted cases: Evidence from vector error correction model (VECM) approach in explaining the relationship between air pollutants towards COVID-19 cases in Kuwait.

In urban areas, air pollution is one of the most serious global environmental issues. Using time-series approaches, this study looked into the validity of the relationship between air pollution and COVID-19 hospitalization. This time series research was carried out in the state of Kuwait; stationarity test, cointegration test, Granger causality and stability test, and test on multivariate time-series using the Vector Error Correction Model (VECM) technique. The findings reveal that the concentration rate of air pollutants ( O 3 , SO 2 , NO 2 , CO , and PM 10 ) has an effect on COVID-19 admitted cases via Granger-cause. The Granger causation test shows that the concentration rate of air pollutants ( O 3 , PM 10 , NO 2 , temperature and wind speed) influences and predicts the COVID-19 admitted cases. The findings suggest that sulfur dioxide ( SO 2 ), NO 2 , temperature, and wind speed induce an increase in COVID-19 admitted cases in the short term according to VECM analysis. The evidence of a positive long-run association between COVID-19 admitted cases and environmental air pollution might be shown in the cointegration test and the VECM. There is an affirmation that the usage of air pollutants ( O 3 , SO 2 , NO 2 , CO , and PM 10 ) has a significant impact on COVID-19-admitted cases' prediction and its explained about 24% of increasing COVID-19 admitted cases in Kuwait.

Outcomes of tocilizumab therapy in severe or critical COVID-19 patients: A retrospective cohort, single-centre study.

OBJECTIVES: To assess the effectiveness and safety of tocilizumab, a humanised anti-interleukin-6 receptor antibody, in the treatment of critical or severe coronavirus disease 2019 (COVID-19) patients. METHODS: This was a retrospective cohort study of severe or critical COVID-19 patients (≥18 years) admitted to one hospital in Kuwait. Fifty-one patients received intravenous tocilizumab, while 78 patients received the standard of care at the same hospital. Both groups were compared for clinical improvement and in-hospital mortality. RESULTS: The tocilizumab (TCZ) group had a significantly lower 28-day in-hospital mortality rate than the standard-of care-group (21.6% vs. 42.3% respectively; p = 0.015). Fifty-five per cent of patients in the TCZ group clinically improved vs. 11.5% in the standard-of-care group (p < 0.001). Using Cox-proportional regression analysis, TCZ treatment was associated with a reduced risk of mortality (adjusted hazard ratio 0.25; 95% CI: 0.11-0.61) and increased likelihood of clinical improvement (adjusted hazard ratio 4.94; 95% CI: 2.03-12.0), compared to the standard of care. The median C-reactive protein, D-dimer, procalcitonin, lactate dehydrogenase and ferritin levels in the tocilizumab group decreased significantly over the 14 days of follow-up. Secondary infections occurred in 19.6% of the TCZ group, and in 20.5% of the standard-of-care group, with no statistical significance (p = 0.900). CONCLUSION: Tocilizumab was significantly associated with better survival and greater clinical improvement in severe or critical COVID-19 patients.

Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018).

In environmental research, missing data are often a challenge for statistical modeling. This paper addressed some advanced techniques to deal with missing values in a data set measuring air quality using a multiple imputation (MI) approach. MCAR, MAR, and NMAR missing data techniques are applied to the data set. Five missing data levels are considered: 5%, 10%, 20%, 30%, and 40%. The imputation method used in this paper is an iterative imputation method, missForest, which is related to the random forest approach. Air quality data sets were gathered from five monitoring stations in Kuwait, aggregated to a daily basis. Logarithm transformation was carried out for all pollutant data, in order to normalize their distributions and to minimize skewness. We found high levels of missing values for NO2 (18.4%), CO (18.5%), PM10 (57.4%), SO2 (19.0%), and O3 (18.2%) data. Climatological data (i.e., air temperature, relative humidity, wind direction, and wind speed) were used as control variables for better estimation. The results show that the MAR technique had the lowest RMSE and MAE. We conclude that MI using the missForest approach has a high level of accuracy in estimating missing values. MissForest had the lowest imputation error (RMSE and MAE) among the other imputation methods and, thus, can be considered to be appropriate for analyzing air quality data.