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5. Factors Influencing Poor Academic Performance among Urban University Students in Bangladesh

Author

Shahjahan, M., Ahmed, Kazi Rumana, Al Hadrami, Ahm, Islam, Md. Rabiul, Hossain, Sharmin, and Khan, Md. Sabur

Abstract

Poor academic performance is challenging for students, parents, and teachers. This cross-sectional study aimed to determine the factors associated with the poor academic performance of 661 undergraduate students who scored CGPA [less than or equal to]2.5 from a selected private university of Dhaka City, Bangladesh, using a simple random sampling technique. Data were collected using a pretested and self-administered questionnaire. Of the study participants, male preponderance (88.4%) was found, and 77.9% of them selected the study programs by themselves. Poor academic performance was found significantly correlated with irregular class attendance (p=0.003), father's low education level (p<0.003), partial family cooperation (p=0.020), use of social media (p=0.006), and excessive time spent for gossiping (p=0.030). There is a need for implementing an appropriate counseling strategy to follow up the academic performance of the poor performing students.

Published
2021

6. Arsenic and other geogenic contaminants in global groundwater

Author

Mukherjee, Abhijit, Coomar, Poulomee, Sarkar, Soumyajit, Johannesson, Karen H., Fryar, Alan E., Schreiber, Madeline E., Ahmed, Kazi Matin, Alam, Mohammad Ayaz, Bhattacharya, Prosun, Bundschuh, Jochen, Burgess, William, Chakraborty, Madhumita, Coyte, Rachel, Farooqi, Abida, Guo, Huaming, Ijumulana, Julian, Jeelani, Gh, Mondal, Debapriya, Nordstrom, D. Kirk, Podgorski, Joel, Polya, David A., Scanlon, Bridget R., Shamsudduha, Mohammad, Tapia, Joseline, and Vengosh, Avner

Published
2024
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11. A mechanistic study on the tolerance of PAM distal end mismatch by SpCas9

Author

Dey, Dhritiman, Chakravarti, Rudra, Bhattacharjee, Oindrila, Majumder, Satyabrata, Chaudhuri, Dwaipayan, Ahmed, Kazi Tawsif, Roy, Dipanjan, Bhattacharya, Bireswar, Arya, Mansi, Gautam, Anupam, Singh, Rajveer, Gupta, Rahul, Ravichandiran, Velayutham, Chattopadhyay, Dhrubajyoti, Ghosh, Abhrajyoti, Giri, Kalyan, Roy, Syamal, and Ghosh, Dipanjan

Published
2024
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15. Evolution of cisplatin resistance through coordinated metabolic reprogramming of the cellular reductive state

Author

Yu, Wangie, Chen, Yunyun, Putluri, Nagireddy, Osman, Abdullah, Coarfa, Cristian, Putluri, Vasanta, Kamal, Abu H. M., Asmussen, Jennifer Kay, Katsonis, Panagiotis, Myers, Jeffrey N., Lai, Stephen Y., Lu, Wuhao, Stephan, Clifford C., Powell, Reid T., Johnson, Faye M., Skinner, Heath D., Kazi, Jawad, Ahmed, Kazi Mokim, Hu, Linghao, Threet, Addison, Meyer, Matthew D., Bankson, James A., Wang, Tony, Davis, Jack, Parker, Kirby R., Harris, Madison A., Baek, Mokryun L., Echeverria, Gloria V., Qi, Xiaoli, Wang, Jin, Frederick, Andy I., Walsh, Alex J., Lichtarge, Olivier, Frederick, Mitchell J., and Sandulache, Vlad C.

Published
2023
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16. Sediment delivery to sustain the Ganges-Brahmaputra delta under climate change and anthropogenic impacts

Author

Raff, Jessica L., Goodbred, Jr., Steven L., Pickering, Jennifer L., Sincavage, Ryan S., Ayers, John C., Hossain, Md. Saddam, Wilson, Carol A., Paola, Chris, Steckler, Michael S., Mondal, Dhiman R., Grimaud, Jean-Louis, Grall, Celine Jo, Rogers, Kimberly G., Ahmed, Kazi Matin, Akhter, Syed Humayun, Carlson, Brandee N., Chamberlain, Elizabeth L., Dejter, Meagan, Gilligan, Jonathan M., Hale, Richard P., Khan, Mahfuzur R., Muktadir, Md. Golam, Rahman, Md. Munsur, and Williams, Lauren A.

Published
2023
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18. Consequences of access to water from managed aquifer recharge systems for blood pressure and proteinuria in south-west coastal Bangladesh: a stepped-wedge cluster-randomized trial.

Author

Naser, Abu, Doza, Solaiman, Rahman, Mahbubur, Unicomb, Leanne, Ahmed, Kazi, Anand, Shuchi, Selim, Shahjada, Shamsudduha, Mohammad, Narayan, Km, Chang, Howard, Clasen, Thomas, Luby, Stephen, and Gribble, Matthew

Subjects
Managed aquifer recharge, blood pressure, drinking-water salinity, stepped-wedge cluster-randomized trial, Bangladesh, Blood Pressure, Groundwater, Humans, Proteinuria, Water
Abstract

BACKGROUND: Drinking-water salinity has been associated with high blood pressure (BP) among communities in south-west coastal Bangladesh. We evaluated whether access to water from managed aquifer recharge (MAR)-a hydrogeological intervention to lower groundwater salinity by infiltrating rainwater into the aquifers-can reduce community BP. METHODS: We conducted a stepped-wedge cluster-randomized trial with five monthly visits between December 2016 and April 2017 in 16 communities. At each visit following baseline, four communities were randomized to access MAR water. Systolic BP was the primary outcome, measured during each visit using Omron® HEM-907 devices. We also measured participants 24-hour urinary sodium and households drinking- and cooking-water salinity each visit. We used multilevel regression models to estimate the effects of MAR-water access on participants BP. The primary analysis was intention-to-treat. RESULTS: In total, 2911 person-visits were conducted in communities randomized to have MAR-water access and 2834 in communities without MAR-water access. Households without MAR-water access predominantly used low-salinity pond water and 42% (range: 26-50% across visits) of households exclusively consumed MAR water when access was provided. Communities randomized to MAR-water access had 10.34 [95% confidence interval (CI): 1.11, 19.58] mmol/day higher mean urinary sodium, 1.96 (95% CI: 0.66, 3.26; p = 0.004) mmHg higher mean systolic BP and 1.44 (95% CI: 0.40, 2.48; p = 0.007) mmHg higher mean diastolic BP than communities without MAR-water access. CONCLUSIONS: Our findings do not support the scale-up of MAR systems as a routine drinking-water source, since communities that shifted to MAR water from the lower-salinity pond-water source had higher urinary sodium and BP.

Published
2021

25. Augmenting Radiological Diagnostics with AI for Tuberculosis and COVID-19 Disease Detection: Deep Learning Detection of Chest Radiographs

Author

Manjur Kolhar, Ahmed M. Al Rajeh, and Raisa Nazir Ahmed Kazi

Subjects
ResNet50, VGG16. augmenting, lung, disease, deep learning, Medicine (General), R5-920
Abstract

In this research, we introduce a network that can identify pneumonia, COVID-19, and tuberculosis using X-ray images of patients’ chests. The study emphasizes tuberculosis, COVID-19, and healthy lung conditions, discussing how advanced neural networks, like VGG16 and ResNet50, can improve the detection of lung issues from images. To prepare the images for the model’s input requirements, we enhanced them through data augmentation techniques for training purposes. We evaluated the model’s performance by analyzing the precision, recall, and F1 scores across training, validation, and testing datasets. The results show that the ResNet50 model outperformed VGG16 with accuracy and resilience. It displayed superior ROC AUC values in both validation and test scenarios. Particularly impressive were ResNet50’s precision and recall rates, nearing 0.99 for all conditions in the test set. On the hand, VGG16 also performed well during testing—detecting tuberculosis with a precision of 0.99 and a recall of 0.93. Our study highlights the performance of our deep learning method by showcasing the effectiveness of ResNet50 over traditional approaches like VGG16. This progress utilizes methods to enhance classification accuracy by augmenting data and balancing them. This positions our approach as an advancement in using state-of-the-art deep learning applications in imaging. By enhancing the accuracy and reliability of diagnosing ailments such as COVID-19 and tuberculosis, our models have the potential to transform care and treatment strategies, highlighting their role in clinical diagnostics.

Published
2024
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26. AI-Driven Real-Time Classification of ECG Signals for Cardiac Monitoring Using i-AlexNet Architecture

Author

Manjur Kolhar, Raisa Nazir Ahmed Kazi, Hitesh Mohapatra, and Ahmed M Al Rajeh

Subjects
artificial intelligence, ECG signals, optimization, AlexNet, performance, Medicine (General), R5-920
Abstract

The healthcare industry has evolved with the advent of artificial intelligence (AI), which uses advanced computational methods and algorithms, leading to quicker inspection, forecasting, evaluation and treatment. In the context of healthcare, artificial intelligence (AI) uses sophisticated computational methods to evaluate, decipher and draw conclusions from patient data. AI has the potential to revolutionize the healthcare industry in several ways, including better managerial effectiveness, individualized treatment regimens and diagnostic improvements. In this research, the ECG signals are preprocessed for noise elimination and heartbeat segmentation. Multi-feature extraction is employed to extract features from preprocessed data, and an optimization technique is used to choose the most feasible features. The i-AlexNet classifier, which is an improved version of the AlexNet model, is used to classify between normal and anomalous signals. For experimental evaluation, the proposed approach is applied to PTB and MIT_BIH databases, and it is observed that the suggested method achieves a higher accuracy of 98.8% compared to other works in the literature.

Published
2024
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28. A Deep Q-Learning Method for Downlink Power Allocation in Multi-Cell Networks

Author

Ahmed, Kazi Ishfaq and Hossain, Ekram

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing, Statistics - Machine Learning
Abstract

Optimal resource allocation is a fundamental challenge for dense and heterogeneous wireless networks with massive wireless connections. Because of the non-convex nature of the optimization problem, it is computationally demanding to obtain the optimal resource allocation. Recently, deep reinforcement learning (DRL) has emerged as a promising technique in solving non-convex optimization problems. Unlike deep learning (DL), DRL does not require any optimal/ near-optimal training dataset which is either unavailable or computationally expensive in generating synthetic data. In this paper, we propose a novel centralized DRL based downlink power allocation scheme for a multi-cell system intending to maximize the total network throughput. Specifically, we apply a deep Q-learning (DQL) approach to achieve near-optimal power allocation policy. For benchmarking the proposed approach, we use a Genetic Algorithm (GA) to obtain near-optimal power allocation solution. Simulation results show that the proposed DRL-based power allocation scheme performs better compared to the conventional power allocation schemes in a multi-cell scenario.

Published
2019

29. Associations of drinking rainwater with macro-mineral intake and cardiometabolic health: a pooled cohort analysis in Bangladesh, 2016-2019.

Author

Naser, Abu, Rahman, Mahbubur, Unicomb, Leanne, Parvez, Sarker, Islam, Shariful, Doza, Solaiman, Khan, Golam, Ahmed, Kazi, Anand, Shuchi, Luby, Stephen, Shamsudduha, Mohammad, Narayan, K, Clasen, Thomas, and Gribble, Matthew

Abstract

This study explores the associations of drinking rainwater with mineral intake and cardiometabolic health in the Bangladeshi population. We pooled 10030 person-visit data on drinking water sources, blood pressure (BP) and 24-h urine minerals. Fasting blood glucose (FBG) was measured in 3724 person-visits, and lipids in 1118 person-visits. We measured concentrations of sodium (Na), potassium (K), calcium (Ca) and magnesium (Mg) in 253 rainwater, 935 groundwater and 130 pond water samples. We used multilevel linear or gamma regression models with participant-, household- and community-level random intercepts to estimate the associations of rainwater consumption with urine minerals and cardiometabolic biomarkers. Rainwater samples had the lowest concentrations of Na, K, Ca and Mg. Rainwater drinkers had lower urine minerals than coastal groundwater drinkers: -13.42 (95% CI: -18.27, -8.57) mmol Na/24 h, -2.00 (95% CI: -3.16, -0.85) mmol K/24 h and -0.57 (95% CI: -1.02, -0.16) mmol Mg/24 h. The ratio of median 24-hour urinary Ca for rainwater versus coastal groundwater drinkers was 0.72 (95% CI: 0.64, 0.80). Rainwater drinkers had 2.15 (95% CI: 1.02, 3.27) mm Hg higher systolic BP, 1.82 (95% CI: 1.19, 2.54) mm Hg higher diastolic BP, 0.59 (95% CI: 0.17, 1.01) mmol/L higher FBG and -2.02 (95% CI: -5.85, 0.81) mg/dl change in high-density lipoprotein cholesterol compared with the coastal groundwater drinkers. Drinking rainwater was associated with worse cardiometabolic health measures, which may be due to the lower intake of salubrious Ca, Mg and K.

Published
2020

35. Global Undergraduate Research Landscape Analysis and Its Effect on 4th Industrial Revolution

Author

Mostafa, Javed, Ashrafi, Shamim, Ahmed, Kazi Sadman, Islam, Md. Imranul, Chowdhury, Shadman Islam, Khaleque, Muntasir, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Hossain, Sazzad, editor, Hossain, Md. Shahadat, editor, Kaiser, M. Shamim, editor, Majumder, Satya Prasad, editor, and Ray, Kanad, editor

Published
2022
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36. A Comprehensive Analysis of Machine Learning-Based Intrusion Detection System for IoT-23 Dataset

Author

Kim, Yang G., Ahmed, Kazi J., Lee, Myung J., Tsukamoto, Kazuya, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, and Miwa, Hiroyoshi, editor

Published
2022
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37. Stochastic Computing-Based Baseband Processing for Resource Constraint IoT Devices

Author

Ahmed, Kazi J., Kim, Yang G., Yuan, Bo, Lee, Myung J., Tsukamoto, Kazuya, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, and Miwa, Hiroyoshi, editor

Published
2022
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38. Temporal Variation of Land Surface Temperature in Response to Changes in Vegetation Index of Bhawal National Park, Bangladesh

Author

Alam, Ha-mim Ebne, Arafat, Md. Yeasir, Ahmed, Kazi Tawkir, Uddin, Md. Nizam, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Pal, Indrajit, editor, and Kolathayar, Sreevalsa, editor

Published
2022
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39. Groundwater Chemistry and Blood Pressure: A Cross-Sectional Study in Bangladesh.

Author

Naser, Abu, Clasen, Thomas, Luby, Stephen, Rahman, Mahbubur, Unicomb, Leanne, Ahmed, Kazi, Doza, Solaiman, Ourshalimian, Shadassa, Chang, Howard, Stowell, Jennifer, Narayan, K, Shamsudduha, Mohammad, Patel, Shivani, OShea, Bethany, and Gribble, Matthew

Subjects
blood pressure, chemical mixtures, exposure combinations, exposure mixtures, groundwater, medical geology, Adult, Bangladesh, Blood Pressure, Body Mass Index, Cross-Sectional Studies, Female, Groundwater, Humans, Hypertension, Male
Abstract

Background: We assessed the association of groundwater chemicals with systolic blood pressure (SBP) and diastolic blood pressure (DBP). Methods: Blood pressure data for ≥35-year-olds were from the Bangladesh Demographic and Health Survey in 2011. Groundwater chemicals in 3534 well water samples from Bangladesh were measured by the British Geological Survey (BGS) in 1998-1999. Participants who reported groundwater as their primary source of drinking water were assigned chemical measures from the nearest BGS well. Survey-adjusted linear regression methods were used to assess the association of each groundwater chemical with the log-transformed blood pressure of the participants. Models were adjusted for age, sex, body mass index, smoking status, geographical region, household wealth, rural or urban residence, and educational attainment, and further adjusted for all other groundwater chemicals. Results: One standard deviation (SD) increase in groundwater magnesium was associated with a 0.992 (95% confidence interval (CI): 0.986, 0.998) geometric mean ratio (GMR) of SBP and a 0.991 (95% CI: 0.985, 0.996) GMR of DBP when adjusted for covariates except groundwater chemicals. When additionally adjusted for groundwater chemicals, one SD increase in groundwater magnesium was associated with a 0.984 (95% CI: 0.972, 0.997) GMR of SBP and a 0.990 (95% CI: 0.979, 1.000) GMR of DBP. However, associations were attenuated following Bonferroni-correction for multiple chemical comparisons in the full-adjusted model. Groundwater concentrations of calcium, potassium, silicon, sulfate, barium, zinc, manganese, and iron were not associated with SBP or DBP in the full-adjusted models. Conclusions: Groundwater magnesium had a weak association with lower SBP and DBP of the participants.

Published
2019

40. Drinking Water Salinity, Urinary Macro-Mineral Excretions, and Blood Pressure in the Southwest Coastal Population of Bangladesh.

Author

Naser, Abu, Rahman, Mahbubur, Unicomb, Leanne, Doza, Solaiman, Gazi, Mohammed, Alam, Gazi, Karim, Mohammed, Uddin, Mohammad, Khan, Golam, Ahmed, Kazi, Shamsudduha, Mohammad, Anand, Shuchi, Narayan, K, Chang, Howard, Luby, Stephen, Clasen, Thomas, and Gribble, Matthew

Subjects
blood pressure, calcium, drinking water salinity, magnesium, potassium, sodium, water salinity, Adult, Aged, Bangladesh, Blood Pressure, Calcium, Drinking Water, Electric Conductivity, Female, Humans, Hypertension, Magnesium, Male, Middle Aged, Protective Factors, Renal Elimination, Risk Factors, Salinity, Sodium, Young Adult
Abstract

Background Sodium (Na+) in saline water may increase blood pressure ( BP ), but potassium (K+), calcium (Ca2+), and magnesium (Mg2+) may lower BP . We assessed the association between drinking water salinity and population BP . Methods and Results We pooled 6487 BP measurements from 2 cohorts in coastal Bangladesh. We used multilevel linear models to estimate BP differences across water salinity categories: fresh water (electrical conductivity,

Published
2019

45. Effects of a School-Based Physical Activity Intervention on Adolescents' Mental Health: A Cluster Randomized Controlled Trial.

Author

Ahmed, Kazi Rumana, Horwood, Sharon, and Khan, Asaduzzaman

Subjects
CLUSTER randomized controlled trials, CENTER for Epidemiologic Studies Depression Scale, PHYSICAL activity, MENTAL health, PSYCHOEDUCATION, LIFE satisfaction
Abstract

Background: The aim of this study was to evaluate the effectiveness of a school-based multicomponent physical activity intervention on mental health of adolescents. Methods: A clustered, randomized, controlled trial was employed in 8 high schools in Dhaka, Bangladesh, which were randomly assigned to either an intervention or control group; 40 students in grades 8 and 9 from each school took part in the trial (n = 160/group). Students in the intervention schools participated in a 12-week physical activity intervention with multiple components (eg, supervised circuits, lunchtime sports, health education, infographics), while control schools received no intervention. Participants completed baseline and postintervention surveys measuring depressive symptoms (Center for Epidemiologic Studies Depression Scale) and life satisfaction (Cantril Ladder), along with other sociodemographic and behavioral characteristics. Linear mixed-effects modeling was used to evaluate the intervention effects. Results: Depressive symptoms in the intervention group decreased at postintervention, but remained stable in the control group. There was an increase in life satisfaction in the intervention group and a decrease in the control group. Multivariable modeling showed that students in the intervention group had a significantly lower level of depressive symptoms (β = −4.60; 95% confidence interval, −5.76 to −3.46) and higher level of life satisfaction (β = 1.43; 95% confidence interval, 0.77 to 2.10) compared with their counterparts in the control group. Sensitivity analyses supported the positive effects of the intervention. Conclusions: Our school-based, multicomponent physical activity intervention is effective in improving mental health indicators in adolescents. Future trials should be ramped up to include schools in rural and regional settings, using robust measures of mental well-being. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Significant 13C NMR signal enhancements in amino acids via adiabatic demagnetization and remagnetization cross polarization.

Author

Ahmed, Kazi S. and Harris, Kristopher J.

Subjects
*AMINO acids, *DEMAGNETIZATION, *SPECTROMETRY
Abstract

Herein, we report an improvement over Hartmann–Hahn cross polarization for NMR signal enhancement: adiabatic demagnetization/remagnetization transfers that provide up to a 9-fold experimental speedup for 13C NMR signals in amino acids over conventional means. The experiment proved insensitive to site type, and we also demonstrate a means for making it compatible with high-resolution spectroscopy. [ABSTRACT FROM AUTHOR]

Published
2024
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48. Association of Psychotropic Prescriptions With Non‐Registered Indications and the Risk of Mortality in Older Adults: A Danish Nationwide Cohort Study.

Author

Ishtiak‐Ahmed, Kazi, Jensen‐Dahm, Christina, Christensen, Kaj Sparle, Waldemar, Gunhild, and Gasse, Christiane

Subjects
*OFF-label use (Drugs), *RISK assessment, *POISSON distribution, *BENZODIAZEPINES, *MEDICAL prescriptions, *RESEARCH funding, *SEX distribution, *ANTIPSYCHOTIC agents, *TRANQUILIZING drugs, *LONGITUDINAL method, *ANTIDEPRESSANTS, *PEOPLE with mental illness, *CONFIDENCE intervals, *DEMENTIA, *PSYCHIATRIC drugs, *MENTAL depression, *TIME, *OLD age, MORTALITY risk factors
Abstract

Background and Objective: Psychotropic drug use is common in older adults, with off‐label use reported despite limited understanding of the safety outcomes compared to on‐label use. Incomplete recordings of treatment indications in the Danish National Prescription Register (DNPR) raise concerns about potential off‐label medication use, particularly among older adults. We, therefore, investigated the association between psychotropic prescriptions with non‐registered indications in DNPR and the 1‐year all‐cause mortality in older adults, including subgroups with any psychiatric disorders, depression, or dementia. Methods: Register‐based cohort study following all older adults (≥ 65) who redeemed a first‐time (since 1995) prescription of either antidepressants, antipsychotics, or benzodiazepine during 2006–2017. Redemption of a prescription with non‐registered indications in the DNPR was the exposure. The outcome, 1‐year all‐cause mortality was analyzed using Poisson regression, estimating incidence rate ratios with 95% confidence intervals, adjusting for socio‐demographics and clinical factors. Results: 32% of prescriptions filled by 202,067 individuals for antidepressants, 37% of 97,387 for antipsychotics, and 22% of 130,471 for benzodiazepines had non‐registered indications. No significant differences in mortality rates were found for antidepressants and antipsychotics with non‐registered indications, while higher mortality rates were associated with benzodiazepines, mitigated when excluding individuals receiving intravenous administrations representing end‐of‐life treatment. The results remained consistent in subgroup analyses in patients with any psychiatric disorders, depression, or dementia and further stratified analyses by sex and age. Conclusions: We found that while psychotropic prescriptions with non‐registered indications in DNPR were prevalent in older adults, they were not associated with excess mortality. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Depression Treatment Trajectories and Associated Social Determinants: A Three‐Year Follow‐Up Study in 66,540 Older Adults Undergoing First‐Time Depression Treatment in Denmark.

Author

Ishtiak‐Ahmed, Kazi, Rohde, Christopher, Köhler‐Forsberg, Ole, Christensen, Kaj Sparle, and Gasse, Christiane

Subjects
*SOCIAL determinants of health, *RESEARCH funding, *HOSPITAL care, *MULTIPLE regression analysis, *TERMINATION of treatment, *SEX distribution, *RESIDENTIAL patterns, *REPORTING of diseases, *DESCRIPTIVE statistics, *MEMBERSHIP, *LONGITUDINAL method, *ANTIDEPRESSANTS, *ODDS ratio, *RURAL conditions, *MARITAL status, *DRUGS, *MENTAL depression, *GROUP process, *OLD age
Abstract

Objective: This study aimed to describe depression treatment patterns, identify unique trajectory groups using a group‐based trajectory approach, and explore associated social determinants in older adults undergoing first‐time depression treatment during a 3‐year follow‐up. Methods: This Danish register‐based cohort study included all adults aged ≥ 65 who initiated depression treatment by redeeming first‐time antidepressant prescriptions (no prescriptions in the last 10 years) between 2006 and 2015. The outcome of interest during the 2‐year follow‐up was depression treatment, assessed as antidepressant prescriptions redemptions and psychiatric hospital contacts for depression. Latent class growth analyses were applied to model treatment trajectories during 3 years. Multinomial logistic regression analyses were used to analyze adjusted associations between social determinates and trajectory group membership. Results: Among the 66,540 older adults (55.2% females, mean age: 77.3 years), we identified three distinct groups with unique patterns of depression treatment trajectories: 'brief‐treatment' where individuals stopped depression treatment within 6 months (33.7%); 'gradual‐withdrawal' (26.5%) where treatment was gradually stopped over 2 years; and 'persistent‐treatment' where individuals continued depression treatment for the entire 3 years (39.8%). Females, single‐person households, and residents of less‐urbanized regions were associated with higher odds of membership in the 'persistent‐treatment' group, while older age, widowhood or separation, and non‐Danish ethnicities were associated with lower odds. Conclusions: Three distinct patterns of depression treatment trajectories were identified in older adults, indicating differential clinical courses of depression—potentially influenced by social determinants, including sex, marital status, urban residence, and ethnicity. Early patient stratification and targeted interventions are crucial in depression care for older adults. [ABSTRACT FROM AUTHOR]

Published
2024
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50. 30-day Morbidity and Mortality After Cholecystectomy for Benign Gallbladder Disease (AMBROSE)

Author

Wong, Geoffrey Yuet Mun, Wadhawan, Himanshu, Roth Cardoso, Victor, Bravo Merodio, Laura, Rajeev, Yashasvi, Maldonado, Ricardo David, Martinino, Alessandro, Balasubaramaniam, Vignesh, Ashraf, Aabid, Siddiqui, Adeela, Al-Shkirat, Ahmad Ghassan, Mohammed Abu-Elfatth, Ahmed, Gupta, Ajay, Alkaseek, Akram, Ouyahia, Amel, Said, Amira, Pandey, Anshuman, Kumar, Ashwani, Maqbool, Baila, Millán, Carlos Alberto, Singh, Cheena, Pantoja Pachajoa, Diana Alejandra, Adamovich, Dmitry Mikhailovich, Petracchi, Enrique, Ashraf, Fariha, Clementi, Marco, Mulita, Francesk, Marom, Gad Amram, Abdulaal, Gamaleldeen, Verras, Georgios-Ioannis, Calini, Giacomo, Moretto, Gianluigi, Elfeki, Hossam, Liang, Hui, Jalaawiy, Humam, Elzayat, Ibrahim, Das, Jayanta Kumar, Aceves-Ayala, Jose Miguel, Ahmed, Kazi T., Degrate, Luca, Aggarwal, Manisha, Omar, Mohammed Ahmed, Rais, Mounira, Elhadi, Muhammed, Sakran, Nasser, Bhojwani, Rajesh, Agarwalla, Ramesh, Kanaan, Samir, Erdene, Sarnai, Chooklin, Serge, Khuroo, Suhail, Dawani, Surrendar, Asghar, Syed Tanseer, Fung, Tak Kwan James, Omarov, Taryel, Grigorean, Valentin Titus, Boras, Zdenko, Gkoutos, Georgios V., Singhal, Rishi, Mahawar, Kamal, Group:, TUGSS Multinational Audit Steering, Madhok, Brij, Graham, Yitka, Donohoe, Claire, Reira, Manel, Wadhawan, Himanshu, Vish, YKS, Jain, Rajesh, Elhadi, Muhammed, Popat, Sunil, Boddy, Alex, Jain, Vikas, Singhal, Rishi, Mahawar, Kamal, Coordinators:, TUGSS Multinational Audit Study, Martinino, Alessandro, Said, Amira, Marques, Cláudia Neves, Wazir, Ishaan, Pereira, Juan Pablo Scarano, Abouelazayem, Mohamed, Viswanath, Nakul, Sarodaya, Varun, Bala, Vignesh, Coordinators:, TUGSS Multinational Audit National, Homayoon, Roshan, Dogjani, Agron, Tidjane, Anisse, Antozzi, Luciano, Hong, Joshua, Omarov, Taryel, Dash, Anuj Kanti, Chokshi, Aishwarya, Wietzycoski, Cacio Ricardo, Petkov, Plamen, Mbonicura, Jean Claude, Yang, Wah, Zuluaga, Mauricio, Kraljik, Darko, Lincango Naranjo, Eddy P., Elghadban, Hosam Mohamed, Diaz, Angel, Gerogiannis, Ioannis, Mohammed, Adnan, Lazaros, Lazarou, Mulita, Francesk, Bhasker, Aparna Govil, Kermansaravi, Mohammad, Mahdi, Ahmed Salah, Kayyal, Mohd Yasser, Sakran, Nasser, Frattini, Francesco, Alabdallah, Nadeem Bilal, Sylvester, Kimutai Ronoh, Abdelhamid, Ibrahim, EL Fawal, Mohamad Hayssam, Allawgalli, Aiman Nuri, Dulskas, Audrius, Voon, Kelvin, Caruana, Clifford, Ballesteros, Guillermo Ponce De Leon, Erdene, Sarnai, Ouadii, Mouaqit, Nashidengo, Pueya Abdulrashid, Hazebroek, Eric, Gunawardene, Ashok, Adeyeye, Ademola, Shariff, Amir H., Liakopulos, Nicolas Juan, Toro-Huamanchumo, Carlos J., Waledziak, Maciej, Borges, Nuno, Shabbir, Azhar, Negoi, Ionut, Neimark, Aleksandr, Abouleid, Ayman, Kim, Guowei, Košir, Jurij Aleš, Ruiz Úcar, Elena, Hamid, Hytham K. S., Masri, Ruqaya, Ozmen, Mahir, Taha, Safwan, Goodman, Elliot, AL-Naggar, Hamza, Authors:, AMBROSE Audit Collaborative, Ghouali, Amin Khayreddine, Wafa, Benbrahmin, Allel, Sahli, Elkacem, Bouzenita Mohamed, Ibagherache, Razika, Ouyahia, Amel, Rais, Mounira, Seddik, El Hachemi, Kouicem, Aya Tinhinane, Abdoun, Meriem, Bouaoud, Souad, Boucenak, Kamel, Khalfa, Safia, Brahim, Bouflih, Tidjane, Anisse, Tabeti, Benali, Meharzi, Sif-El-Islem, Larbi, Hakim, Derdous, Reda, Abderaouf, Bettahar, Bouregba, Nadjette, Boukaaabeche, Fouad, Djeroua, Kamel, Sabrin, Naît Ali, Khennaf, Leila, Mesli, Smain Nabil, Ghouali, Amin Khayreddine, Aissat, Abdelnour, Pantoja Pachajoa, Diana Alejandra, Alvarez, Fernando Andrés, Milagros, Nicole Benitez, Medrano Ortiz Palombarini, Valentina Cecilia, Petracchi, Enrique, Quesada, Matias, Canullan, Carlos, Varela, Jose, Posada, Hector, Du Plessis, Cristina, Valenzuela, José Ignacio, Zurita, Melissa Andrea Fernandez, Nasim, Sana, Bowles, Thomas Alexander, Yeboah, Edward, Nair, Roshan, Felsenreich, Daniel Moritz, Omarov, Taryel, Allahverdiyeva, Nigar, Abizade, Rashad, Adamovich, Dmitry Mikhailovich, Barreiro, Thiago Alvim, Cunha, Hercio Azevedo de Vasconcelos, Castilho, Michel Victor, Ferreira, Rafael Meneguzzi Alves, Legati Junior, Ronaldo, Dias, Lorenzo, Wietzycoski, Cacio, Jacobi, Everton Walter, Julianov, Alexander, Saroglu, Azize, Yuruk, Shaban, Dimov, Rosen, Ivanov, Valentin, Dardanov, Dragomir, Yang, Wah, Wei, Zhuoqi, Liang, Hui, Millán, Carlos A., Urbina, Mónica, Cubieros, Jorge, Acosta, Shary, Jiménez, Julián, Boras, Zdenko, Vlahović, Ivan, Koronakis, Nikolaos, González, Ricardo Andrés Buenaño, Ojeda, Cintya Anabel Llerena, Aspiazu-Briones, Cristhian Gonzalo, Martinez-Espinoza, Dario Javier, Rivas-Torres, Eduardo Antonio, Lincango Naranjo, Eddy P., Aldabash, Lama, Shaat, Iman, Alsayed, Mohamed Moneer Abulfotooh, Bali, Eslam, Ayoub, Mohamed Abdel Maksoud, Mohamed, Mohamed, AL Sayed, Mohamed, Elshinnawy, Azza Mohamed Gaber, Tayiawi, Mosaab, Abu-Elfatth, Ahmed Mohammed, Mohamed, Ahmed Emadelden, Elzayat, Ibrahim, Hassan, Ahmed Abdelmotaleb Mohamed, Madany, Mohie El-Din Mostafa, EL-Kassas, Mohamed, Omar, Wael, Tawheed, Ahmed, Elfeki, Hossam, Shalaby, Mostafa, Sakr, Ahmad, Elghrieb, Ahmed Ezzat, Warda, Hisham Hazem, Sadek, Mirna, Mostafa, Mohamed, Elghadban, Hosam, Awad, Selmy, Madany, Mohie El-Din Mostafa, Maghraby, Ahmed Mostafa, Saleem, Abd-El-Aal Ali, Mahmoud, Ahmed Gaber, Madany, Mohie El-Din Mostafa, Maghraby, Ahmed Mostafa, Saleem, Abd-El-Aal Ali, Mahmoud, Ahmed Gaber, Gebril, Mahmoud, Omar, Mohammed Ahmed, Safy, Ahmed Mohamed, Saada, Ahmed, Mohamed Ads, Alaa, Diaz, Angel, Gutiérrez, Emmanuel, Salinas, Hanton, Zimmermann, Perrine, Rhaiem, Rami, Kianmanesh, Reza, Efthymiou, Evripidis, Konstantinidis, Sergios, Drogouti, Maria, Katsourakis, Anastasios, Papadoliopoulou, Maria, Michalopoulos, Nikolaos V., Sidiropoulos, Theodoros A., Kokoropoulos, Panagiotis, Ioannidis, Argyrios, Konstantinidis, Michael, Charalampakis, Vasileios, Sotiropoulou, Maria, Pantelis, Athanasios G., Kapiris, Stylianos, Tsiampas, Ioannis, Tseliou, Vasiliki, Paspala, Anna, Nastos, Constantinos, Ioannidis, Orestis, Symeonidis, Savvas, Anestiadou, Elissavet, Zapsalis, Konstantinos, Machairas, Nikolaos, Keramida, Myrto D., Dorovinis, Panagiotis, Kyakalos, Stylianos, Stavratis, Fotios, Papadopoulos, Aristeidis, Manioti, Eleni, Mouzakis, Odysseas, Nikolaou, Vassiliki, Barkolias, Evangelos, Mulita, Francesk, Verras, Georgios-Ioannis, Vasileios, Mousafeiris, Triantafyllou, Alexandra, Triantafyllou, Tania, Matthaiou, Georgia, Frountzas, Maximos, Toutouzas, Konstantinos G., Tampaki, Ekaterini Christina, Bellou, Olga, Papazacharias, Christos, Moris, Dimitrios, Felekouras, Evangelos, Stamou, Konstantinos, Tsiotos, Gregory, Fanidou, Domna, Drakos, Panagiotis Alexandros, Schizas, Dimitrios, Syllaios, Athanasios, Vailas, Michail, Georgiadou, Despoina, Zampitis, Nikolaos, Marinis, Athanasios, Stefou, Fotini, Melachroinopoulos, Nikolaos, Papaconstantinou, Dimitrios, Dellaportas, Dionysios, Lykoudis, Panagis, Lasithiotakis, Konstantinos, Magouliotis, Dimitrios, Zacharoulis, Dimitris, Laliotis, Aggelos, Gkionis, Ioannis, Baksi, Aditya, Lodha, Mahendra, Kaur, Supreet, Guha, Shanto Shila, Gupta, Amit, Rajput, Deepak, Sharma, Oshin, Huda, Farhanul, Hassan, Mohsin, Singh, Sudhir Kumar, Basu, Somprakas, Kumar, Navin, Mallik, Dhiraj, David, Lena Elizabath, Agrawal, Aditi, Pillai, Vinod G., Muralee, Meera, Haque, Parvez David, Veetil, Sreejith Kannumal, Mahajan, Amit, Jain, Deepak, Annareddy, Dinakar Reddy, Bahadur, Akshay, Bisht, Shankar Dutt, Kashmira, Mayank, Shukla, Ashish, Pandey, Anshuman, Sarda, Hitesh, Agarwalla, Ramesh, Kumar, Ashwani, Aggarwal, Manisha, Sharma, Akanksha, Paras, Alagarsamy, Raghuraman, Chokkalingam, Gangalakshmi, Bhalla, Bhavneet Singh, Ahamad, Mohammad Nafees, Ahmad, Nabeel, Oommen, Ashok Ninan, Subbarayan, Shankar, Mohan, Karthikeyan, Ashraf, Aabid, Singh, Cheena, Jaswal, Kamaljeet S., Minhas, S. S., Bains, Lovenish, Lal, Pawanindra, Das, Jayanta K., Rangad, Gordon M., Lepcha, Alfred, Kynjing, Hampher, Islam, Md Samsul, Shangpliang, Virginia, Thota, Anuroop, Pinnamraju, Karthikeya, Surapaneni, Sushama, Gurram, Ram Prakash, Reddy, Mandapati Mallikarjuna, Inteti, Kamalesh, Srikanth, V., Reddy, V. Jayapala, Parikh, Chirag, Shah, Shakshi, Chaudhary, Priya, Bhojwani, Rajesh, Gupt, Pranoy, Srimal, Ankur, Sharma, Abadhesh, Tayal, Nikhil, Ramu, Gopi, Paul, Ratnadeep, Khuroo, Suhail, Wani, Ajaz, Gusani, Rajat, Gupta, Rahul, Khanduri, Archana, Singh, Arvind, Singh, Sudhir, Pokharia, Pradip, Sharma, Ankur, Venkatappa, Sunil Kumar, Soni, Vishal, Suprapto, Bambang, Tobroni, Ahmad, Kermansaravi, Mohammad, Mousavimaleki, Ali, Eghbali, Foolad, Eghbali, Foodlad, Mashkouri, Nazanin, Jasim, Ali, Kadhim, Nammer, Jalaawiy, Humam, Sakran, Nasser, Haj, Bassel, Asadi, Ahmad, Marom, Gad Amram, Szydlo, Gabriel Shein, Demma, Jonathan Abraham, Pikarasy, Alon J., Targa, Simone, Buzzi, Gianluca, Sanna, Andrea, Currò, Giuseppe, Ammendola, Michele, Palomba, Giuseppe, Aprea, Giovanni, Capuano, Marianna, Basile, Raffaele, Argenio, Giulio, Annecchiarico, Mario, Ferraro, Daniele, Cacciatore, Chiara, Vennarecci, Giovanni, Granieri, Stefano, Bonomi, Alessandro, Frontali, Alice, Cotsoglou, Christian, Centonze, Danilo, Licciardello, Alessio, Martines, Gennaro, Tomasicchio, Giovanni, Veroux, Massimiliano, Gioco, Rossella, Distefano, Costanza, calabrò, Marcello, Caputo, Damiano, LA Vaccara, Vincenzo, Cammarata, Roberto, Farolfi, Tommaso, Degrate, Luca, adjei antwi, Stella Konadu, Brisinda, Giuseppe, Fico, Valeria, Mirco, Paolo, Biondi, Alberto, Persiani, Roberto, Giovinazzo, Francesco, Frongillo, Francesco, Evola, Giuseppe, Ferrara, Francesco, Altomare, Michele, Benuzzi, Laura, Pezzoli, Isabella, Borghi, Alessandra, Cimbanassi, Stefania, Dapri, Giovanni, Nessi, Chiara, Bianco, Federica, Uccelli, Fara Margherita Letizia, Viganò, Luca, Cordaro, Giuseppe, Dionigi, Gianlorenzo, Pino, Antonella, Morezzi, Daniele, Rizzo, Roberta, Convertini, Girolamo, Vallicelli, Carlo, Catena, Fausto, Verdi, Daunia, Mondi, Isabella, Da Lio, Corrado, Loss, Greta, D'acapito, Fabrizio, Di Pietrantonio, Daniela, Tauceri, Francesca, Ercolani, Giorgio, Bottino, Vincenzo, Bosco, Alfonso, Canfora, Alfonso, Chiappetta, Sonja, Frattini, Francesco, Rizzi, Andrea, Breda, Marta, Quaglino, Francesco, Festa, Federico, Savasta, Francesca Maria Chiara, Fiore, Alessia, Soncini, Stefania, Giordano, Alessio, Carganico, Giacomo, Cocchi, Lorenzo, Epis, Lorenzo, Moretto, Gianluigi, Casaril, Andrea, Inama, Marco, Harmony, Impellizzeri, Michail, Creciun, Alessandro, Vitali, Piazza, Martina, Basile, Guido, Pinotti, Enrico, Lapolla, Pierfrancesco, Mingoli, Andrea, Brachini, Gioia, Cirillo, Bruno, Campanelli, Michela, Gentileschi, Paolo, Rossi, Stefano, Picardi, Biagio, Savia, Eleonora, Olmi, Stefano, Uccelli, Matteo, Balla, Andrea, Lepiane, Pasquale, Saraceno, Federica, Coppola, Alessandro, Clementi, Marco, Paniccia, Federico, Grasso, Antonella, Tartaglia, Nicola, Pavone, Giovanna, Ambrosi, Antonio, Angelico, Roberta, Manzia, Tommaso Maria, Materazzo, Marco, Tisone, Giuseppe, Calini, Giacomo, Bresadola, Vittorio, Morinelli, Vittoria, Matucci-Cerinic, Pietro, Michelutti, Luca, Luzzi, Andrea-Pierre, Romairone, Emanuele, Carrabetta, Salvatore, Marzorati, Sara, Khamees, Almu'atasim, Mohammad, Alyaman Meizer, Alananzeh, Samah, AL Momani, Salam, Hijazin, Nadeen, Tarawneh, Shahd Abdulhadi, Alheji, Hazim, Alhajji, Amer, AL-Shkirat, Ahmad Ghassan, Alzoubi, Mohammad N., AL Manasra, Abdel Rahman Abdullah, Elayyan, Rasheed, Jamous, Hussam, Dardour, Mohammad, Mahafdah, Mahmoud Rawhi, AL Hammoud, Amr Ahmad, AL Quran, Mahmoud, Bosire, Friday, Zakaria, Ramy Magdy, Abdullah, Hawraa Reda, Tarboush, Abdullah, Hasan, Wisam Abraheem, Kredan, Ali Abdulnasir, Zreeg, Dafer, Muftah, Aiman, Koshlaf, Abdulmajeed, Albadi, Doaa, Abunaaja, Hayat Omar, Otman, Rema, Ben Hamida, Bahaeddin, Amnaina, Mohamed Gamal, Alhaddad, Hayfa Faraj, Shuaip, Nouran Musbah, Buderbala, Yasmeen, Hamad, Ahmad Faraj, Shames, Haitam, Bakeer, Hiba Bileid, Alkaseek, Akram, Shalabi, Laila Esnoussi, Alhadi, Aliya Salih, Ahjaaz, Mabroukah A. A., Zgheel, Usama, Abdulmoula, Zenab, Younis, Hoda, Aboubeirah, Mohammed Khayri, Binnawara, Muhannud Hassan, Arebi, Jaber Abdusslam, Alboueishi, Asraa Ali, Mohammed Ammar, Sara, Abdedalmajed Rhuma, Heba, Alsori Alharari, Mohamed, Endisha, Salahaldin Emhemmed, Ng, Chin E'ng, Lee, Yu Wei, Tay, Yen Zhir, Abdul Manan, Nurhidayah, Tajul Arifin, Mohd Syazwan, Khairul Anuar, Ariff Solihin, Kumar, Neeraj, Maiyauen, Thanesh Kumar, Zakari, Andee Dzulkarnaen, Fathi, Mohd Azem, Izhar, Mas Izzati, Awang Dahlan, Dayang Azzyati, Mokhtar, Suryati, Samsudin, Syakirah, Jaktaram Singh, Balraj Singh, Arumugam, Mohanasundram Pillai, Theevashini, Krishnasamy, Manap, Shaiful Amir, Yong, Chon Woon, Mohamed Nabil, Mohamed Nazri, Lim, Jolene Sze Huey, Voon, Kelvin, Cheng, Shi Yu, Amanullah, Muhammad Mubarak, Ahmed, Nurzarina, Lim, I. Vern, Mazlan, Mohd Rashid, Sivananthan, Asokumar, Yussra, Yusoff, Puvisny, Shanmugam Nathan, Chua, Ian Bin, Sharman, Matthew, Siow, Sze Li, Axiak, Jessica, Dowling, Jessica, Portelli, Mark, Caruana, Clifford, Beristain-Hernandez, Jose-Luis, Vazquez-Romero, Odette-Desiree, Jaime-Silva, Jessica, Cadena-Guzman, Joaquin-Homar, Aceves-Ayala, Jose Miguel, Treviño -Meza, Jasmin Marielena, Erik, Efrain-Sosa-Duran, Guzman-Águilar, Rafael, María, Zuñiga, Jose Edusrdo, Pinto Angulo, Victor Manuel, Trejo-Avila, Mario, Bozada-Gutierrez, Katya, Carrion, Christian, Gómez-Herrera, María Norma, García-Gómez, Aurora, Pimentel Melendez, Samuel Arnulfo, Bautista Martinez, Abelardo Olaf, Nuñez DE LA Rosa, Sofia, Inchaustegui Tinajero, Jose, Sordo Lima, Diego Ervey, Pérez-Soto, Rafael Humberto, Hernández-Acevedo, Juan David, Domínguez-Rosado, Ismael, Mercado-Díaz, Miguel Ángel, Sierra-Salazar, Mauricio, Pimienta, Ana, Erdene, Sarnai, Sandag, Erdene, Orgoi, Sergelen, Ochir, Chimedsuren, Batmunkh, Munkhbat, Ouazzani, Et-tayab, EL Fdili, Mostafa, Hassani Ibn Majdoub, Karim, Mazaz, Khalid, Errachidy, Meriem, Mekondjo Nashidengo, Pueya, William Quayson, Francis, Tabiri Abebrese, John, Sushmita Seibes, Sharifa, Tjipetekera, Rejoice, Lim, Yukai, Haimona, Mairarangi, Mcclean, Sophie F., Rodriguez, Shaymar Eddylena Gutierrez Rodriguez, Lopez, Acris Arnoldo Arauz Lopez, Adetoyese Adeyeye, Ademola, Nwabuoku, Emeka Stanley, Mohammed Bello, Usman, Musa Umar, Bashir, Makama, Jerry Godfrey, Aminu, Bashir, Oriakhi, Steve-nation Nehiweze, Mosanya, Arinzechukwu Obi, Omon, Henry Ehidiamen, Wuraola, Funmilola Olanike, Ishola, Adegoke, Ulasi, Ikechukwu, Irowa, Omorodion O., Agbonrofo, Peter I., Irmiya, Solomon, Ammar, Ahmed Siddique, Khattak, Shehrbano, Qureshi, Sajid, Bashir, Nida Wahid, Jalal, Hira, Kamran, Ali, Sultan, Rizwan, Fatima, Mishal, Ali, Muhammad, Farooq, Omama, Khan, Muhammad Taha Junaid, Soomro, Umar, Saleem, Amna, Khawaja, Uzzam Ahmed, Martins, Russell Seth, Dawani, Surrendar, Siddiqui, Adeela, Khan, Madiha Masood, Jafferi, Salman, Faizi, Tashaba Qaiser, Talib, Vikash, Ali, Danish, Javed, Mahad Hassan, Rasheed, M. Ahsan, Mughal, Javeed, Ijaz, Nadeem, Rehman, Imtiaz ur, Aurangzeb, Mahmud, Ahmed, Nisar, Jan, Zaka Ullah, Khan, Shahzeb, Aziz, Sarmad Saeed, Shamim Afridi, Shehzadi Ghazala, Maroof, Syed Asad, Khan, Muhammad Imaran, Zarin, Muhammad, Naz, Farah, Jan, Zakaullah, Asghar, Syed Tanseer, Ali, Sana, Azam, Saim, Jalil, Hira, Naqvi, Hasham, Ashraf, Fariha, Siddiqui, Tayyab, Murataza, Ghulam, Bari, Hassaan, Ahmed, Hassan, Jayyab, Mustafa Abu, AL-Dahdouh, Mosheer, Echeverria, R. Rainer, Mendoza, Mario Ynoue, Kisielewski, Michal, Stefura, Tomasz, Richter, Karolina, Klos, Nikola, Walędziak, Maciej, Bartosiak, Katarzyna, Komorowska, Katarzyna, Silvestre, Miguel Trigo, Santos, Cláudia, Gil, Isabela, Cardoso, Vasco Silva, Melo, Miguel Rocha, Lima, Rita, Bolota, Joana, Cotovio, Manuel, Grigorean, Valentin Titus, Stoian, Alexandru Rares, Diana Andreea, Draghici, Toma, Elena A., Lunca, Sorinel, Zarnescu, Narcis, Costea, Radu Virgil, Litvin, Andrey, Aljohani, Emad, Zaid, AbdelNasser, Shaar, Khalid, Awaf, Khalid, Zakarneh, Eman, Alowayrdi, Tumadher, Alyami, Fatimah, Alamer, Adam, Taha, Mohamed Y., Chowdhury, Sharfuddin, Alshahrani, Salem, Panyko, Arpád, Košir, Jurij Aleš, Grosek, Jan, Tomažič, Aleš, Pintar, Tadeja, Ruiz Úcar, Elena, Castro, Ernest, Sambrano, David, Garcia-Dominguez, Rafael, Tusa, Claudio, Landaluce-Olavarria, Aitor, Estraviz-Mateos, Begoña, González, Jaime, Roca, Begoña, Jayarajah, Umesh, Subasinghe, Duminda, Sivaganesh, Sivasuriya, Hamid, Hytham K. S., Galal-Eldin, Sami, Eldirdiri, Sami, Elnour, Moheyaldien, Asaad, Nada, Mohammed, Musab, Hassan, Luden Saifaldawla, Mohamed, Khalid Osman, Abdelrahman, Salma Ahmed, Alsadeg, Hajer, Ali, Ahmed Altigani Elhadi, Elsiddig Musa, Reem Abdalla, Sarih, Monira, Ismail, Samir, Ahmed, Omer Albasher Almaki, Taj Eldeen, Samaher Taj Eldeen Hassan, Elsiddig, Kamal Elzaki, Elhasan, Mohamed Elghazali Ahmed Basheer, Karamelghani, Mohammed A. F., Mohammed, Ozaz, Adam, Albushra Altayeb, Barakat, Habab Osman, Elhadi, Rawan Elnoman, Alnaji, Abdallh Abdalmajid, Mohamed, Esraa Hamza Abdel Ghani, AL Houri, Hasan, Alhouri, Ahmad, Soliman, Alnour Khmeis, AL Ahmad, Mohamad, Kayali, Ahmad Amir, Nasani, Mohannad, Nerabani, Yaman, Ashkar, Eman, Sawas, Mohamad Nabhan, Aldirani, Alaa N., Zahreddin, Amnah, Alasmar, Ammar M., Hasan, Lilav, Alhosen, Mohammed Alahmed, Klib, Mohamad, Rahman Hammadieh, Abdul, Chikh Salem, Mhd Tarek, Ghandour, Munir, Sara, Samer, Kara Tahhan, Nour, Albani, Nour, Alsaid, Bayan, Ahmad, Basel, Almaydaani, Mohamad, Abbas, Morhaf, Nanaa, Mohamad, Aloulou, Mohammad, Kudra Danial, Aghyad, Khaled, Ahmad, Latouf, Rama, Saeed, Diyala, Ghazal, Ahmad, Masri, Ruqaya, Hamdan, Ola, Ayoub, Kusay, Kadoura, Lama, Atli, Abd Alazeez, Zayat, Hussein, Niazi, Ammar, Dabbit, Abdallah, Dahrouj, Wissam, Alhaj, Ahmad, Dabbagh, Ezeddin, Aldaher, Mohammad, Bsata, Adel, Shahrour, Mohamad Zaher, Khusruf, M. Akram, Wali, Tayssier, Aldroubi, Mohammad Tayeb, Almoshantaf, Mohammad Badr, Alahmad, Mohammad Abdullah, Leen, Jamil, AL-Nokta, Aya, Bakri, Ashraf, Arnaout, Ahmad Yamen, Ibrahim, Hamza, Nastah, Samer, Kanaan, Samir, Rasheed, Omeed, Mohammad, Alttaher, Bokal, Zied, Gafsi, Besma, Baccar, Marwen, AMMAR, Houssem, Ermis, Ilker, Tokocin, Merve, Kabuli, Hamit Ahmet, Tokocin, Onur, Ergenç, Muhammer, Gülşen, Taygun, Erginöz, Ergin, Uludağ, Server Sezgin, Bozkir, Haktan Övül, Zengin, Kağan, Özçelik, Mehmet Faik, Zarbaliyev, Elbrus, Çağlikülekçi, Mehmet, Böler, Deniz, Aktokmakyan, Talar Vartanoglu, Peksen, Caghan, Savas, Osman Anil, Sumer, Aziz, Guldogan, Cem Emir, Ozmen, Mahir, Kaplan, Mehmet, Colak, Elif, Şanli, Ahmet Necati, Kilani, Ayoub Ibrahim, Kamer, Erdinc, Namdaroglu, Ozan, Ahmed, Fuad, Marzouk, Ahmed, Harbinson, Daniel, Abdulrahman, Hassal, Ali, Heba, Abousamra, Mohamed, Di Maggio, Francesco, Abushawaly, Amr, Badawi, Marwa, Rahman, Atiqur, Jenner, Deborah, Said, Amira, Ahmed, Kazi, Watali, Yawar, Soggiu, Fiammetta, Sheth, Hemant, Drymousis, Panagiotis, Caterson, Jessica, Mehmood, Saqib, Wadhawan, Himanshu, Strachan, David, Mcelroy, Luke, Chauhan, Munish, Morgan, Richard, Mamun, Muhammad, Tora, Mir, Shamali, Awad, ML Williamson, James, Slim, Naim, Mark, Safiya, Huppler, Lucy, Crane, Sophie, Mcgrath, Polly, Fung, James Tak Kwan, Kok, Siu Yan, Bond-Smith, Giles, Dawani, Aruna, Shamardal, Aliaa, Ahmed, Mohammed M. Madi, Obasi, Chekwas, Gala, Tanzeela, Elshaer, Ahmed Mohammed, Warner, Sian, Nathadwarawala, Pooja, Askari, Alan, Pandanaboyana, Sanjay, Thakkar, Rohan, Barbour, Fraser, Finch, Jonathan Guy, Habib, Helai, Ansong, Eric, Attard, Joseph, Aujayeb, Avinash, Gupta, Ajay, Fale, Madeleine, Gupta, Anuj, Gajdhar, Aniq, Fareed, Khaleel, Elfeky, Mohamed Abdelfattah, Ashry, Mohamed, Kaur, Mandeep, Faycal Mirghani, Shaza, Tanveer, Yousaf, Albendary, Mohamed, Bhattacharya, Pratik, Abdulaal, Gamaleldeen, Ghufran, Muhammad Ali, Ghanem, Ahmed, Leong, Darren, Mamidanna, Ravikrishna, Aamery, Amaar, Tewari, Nilanjana, Williams, Greg, Tariq, Hamza, Klair, Anjeevan Kaur, Jones, Katie, Selvachandran, Haran, Day, Arthur, Ajmani, Adesh, Parmar, Chetan, Bosch, Karen, Young, Richard, Chan, Alvina, Silva, Yashodha, Kureci, Abdulrahman, Paranyak, Mykola, Shepetko-Dombrovskii, Oleksii, Chooklin, Serge, Chuklin, Serhii, Dutka, Yaromyr, Maqbool, Baila, Gill, Ali Abdullah, Jan, Azalea, Murali, Tharani, Alhajami, Faris, Atiah, Nora, Nadeesh, Areej, and Almaqdi, Sarah

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2025
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