The Repercussion of SARS-CoV-2 on the Blood Glucose Level of Diabetes Patients Prior and During the Lockdown in Bangladesh
Abrar, S. M.
Show abstract
PurposeDiabetes Mellitus (DM) patients were exposed to subacute risk as a result of the unanticipated lockdown. Furthermore, most DM patients were unable to engage in physical activity during that period. This impediment to proper healthcare management had increased Blood Glucose Levels (BGL). Therefore, initiatives must be adopted to prevent the same result in the second lockdown in 2021 for the well-being of patients. MethodThis statistical analysis aimed to assess the rise in BGL of diabetic patients before and during the lockdown. A survey was conducted among the DM patients in the Bangladeshi cohort, who came from various socioeconomic backgrounds and included both men and women. The statistical modeling, performed with the help of stat-ease software, was conducted by applying the Analysis of Variance (ANOVA) method to Response Surface Methodology (RSM). ResultOut of the 3 models applied (quadratic, main effect and sequential sum of squares for 2 factor interaction (2FI)) in 2 different response vectors the 2FI model was the best suited (p value - 0.0441 and 0.0015). The results yielded by the 2FI model were used to evaluate RSM. ConclusionThe analysis had shown a significant rise in the BGL among the DM patients during the lockdown, and the patients with the higher BMI tend to have a more significant increment in the BGL. Male patients experienced a greater rise in BGL. Furthermore, elderly patients with high Random Blood Glucose (RBG) levels before lockdown were more likely to have high RBG levels during the lockdown.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Multi- Stage Feature Selection (MSFS) Algorithm for UWB- Based Early Breast Cancer Size Prediction 96%
- Enhancing pigment production by a chromogenic bacterium (Exiguobacterium aurantiacum) using tomato waste extract: A Statistical approach 95%
- Heterologous expression and characterization of mutant cellulase from indigenous strain of Aspergillus niger 95%
Similar papers in this journal
- Patterns of physical activity among the students of an Indian university and their perceptions about the curricular content concerned with health 93%
- In-silico development of a method for the selection of optimal enzymes using L-asparaginase II against Acute Lymphoblastic Leukemia as an example. 92%
- The Impact of SARS-CoV-2 Lineages (Variants) on the COVID-19 Epidemic in South Africa 92%
Similar papers in this journal
- Clustering of Countries for COVID-19 Cases based on Disease Prevalence, Health Systems and Environmental Indicators 95%
- Detection of Static, Dynamic, and No Tactile Friction Based on Non-linear dynamics of EEG Signals: A Preliminary Study 94%
- A first study on the impact of containment measure on COVID-19 spread in Morocco 92%
Similar papers in this journal
- Classification models for Invasive Ductal Carcinoma Progression, based on gene expression data-trained supervised machine learning 94%
- Comparing protein-protein interaction networks of SARS-CoV-2 and (H1N1) influenza using topological features 94%
- Discovering Key Transcriptomic Regulators in Pancreatic Ductal Adenocarcinoma using Dirichlet Process Gaussian Mixture Model 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.