Background/Objectives: Thyroid function tests (TFTs) changes in obese people have been studied with increasing interest, however, studies have been inconsistent hence it remains poorly understood. We compared the TFTs of morbidly obese euthyroid Saudi subjects with non-obese controls and then we examined the influence of leptin, adiponectin, and insulin resistance on TFTs. Subjects/Methods: Fifty-five euthyroid obese subjects attending bariatric surgery clinic and 52 non-obese age-and gender-matched controls were recruited. We measured body weight, BMI, body composition, thyroid-stimulating hormone (TSH), Free T4 (FT4), Free T3(FT3), thyroid antibodies, fasting leptin, adiponectin, and lipid profile. Insulin resistance was quantified by HOMA-IR. Data are presented as mean ± SEM. Results: Mean BMI was 45.6 ± 1.5 and 23.2 ± 0.5 kg/m², for the obese and non-obese controls, respectively, P value < 0.001. Mean TSH was 2.7 ± 0.18 mIU/L in obese subjects and 1.7 ± 0.13 mIU/L (0.27-4.2) in the non-obese controls, respectively, P value .014. Mean FT3 was 3.9 ± 0.1 pmol/L (3.1-6.8) in obese subjects compared to 5.0 ± 0.1 pmol/L in non-obese controls, respectively, P value 0.001, however, FT4 was similar in the 2 groups. In the whole group ( N = 107), BMI correlated positively with TSH and negatively with FT3. Leptin correlated negatively with both FT4 and FT3 in the non-obese group only while none of the TFTs correlated with HOMA-IR or adiponectin in either group. Binary logistic regression showed that each 1 unit increase in TSH increased the odds of becoming obese by 12.7, P value 0.009, 95 C.I. (1.9-85.0). Conversely, each - unit increase in FT3 decreased the odds of becoming obese by 0.2, P value 0.023, 95% C.I. (0.05-0.80). Conclusions: We report a small increase in TSH and a small decrease in FT3 within the normal range in obese subjects compared to non-obese controls. We also report a positive correlation between TSH and BMI with increased odds ratio of becoming obese with the increase in TSH and decrease in FT3. These changes may be either causally related or adaptive to the obesity state. FT4 and FT3 seem to correlate with leptin (but not with adiponectin or HOMA-IR) in the non-obese controls only. Larger mechanistic studies are needed to further elucidate the interesting association between obesity and TFTs.

Introduction: Type 1 diabetes mellitus (T1DM) is characterized by autoimmune destruction of insulin-producing pancreatic beta (β-) cells. Previous studies suggested an imbalance between and pro- and anti-inflammatory cytokines exacerbates T1DM development. Objectives: We aimed to test the hypothesis that patients with T1DM carry a higher frequency of regulatory genes associated with low levels of the anti-inflammatory cytokines interleukin-4 (IL-4), its receptor (IL-4R), and interleukin-10 (IL-10). Methods: Accordingly, we compared frequencies of five different single nucleotide polymorphisms (SNPs) in T1DM patients and healthy controls who had been typed for HLA-DRB1, HLA-DQA1, and HLA-DQB1 genes. Results: The frequencies of rs2070874 (IL-4) alleles C and T differed between T1DM patients and controls (^cp = 0.0065), as did their codominant (^cp = 0.026) and recessive (^cp = 0.015) models. Increased frequencies were observed in T1DM patients for HLA alleles: DRB1*03 (pc < 0.0013), DRB1*04 (^cp = 0.0169), DQA1*03 (^cp = 0.0222), DQA1*05 (^cp < 0.0006), DQB1*02 (^cp = 0.0005), and DQB1*06 (^cp < 0.0005). And lower frequencies were observed for: DRB1*07 (^cp = 0.0078), DRB1*11 (^cp = 0.0013), DRB1*13 (^cp < 0.0364), DRB1*15 (^cp < 0.0013), DQA1*01 (^cp < 0.0006), and DQA1*02 (^cp = 0.0348). Certain DRB1: DQA1: DQB1 haplotypes showed greater frequencies, including, 03:05:02 (p < 0.0001) and 04:03:03 (p = 0.0017), whereas others showed lower frequencies, including, 07:02:02 (p = 0.0032), 11:05:03 (p = 0.0007), and 15:01:06 (p = 0.0002). Stratification for the above HLA haplotypes with rs2070874 C/C exhibited no significant differences between T1DM patients overall and controls. However, when stratified for the vulnerable HLA haplotype (03:05:02/04:03:03), young patients in whom T1DM began at ≤13 years had a higher frequency of the SNP (rs2070874 C/C); a gene associated with low IL-4 production (p < 0.024). Conclusion: This study suggests that possession of the rs2070874 C/C genotype, which is associated with low production of IL-4, increases the risk of T1DM in young individuals carrying vulnerable HLA alleles/haplotypes.

Objectives: This study aimed to assess the correlation between glycated hemoglobin A1 (HbA1c), time in range (TIR), and glycemic management indicator (GMI) in patients with both type 1 diabetes (T1D) and type 2 diabetes (T2D) who were using a flash glucose monitoring (FGM) device (FreeStyle Libre; Abbott Diabetic Care, Witney, UK). Methods: This was a retrospective study that looked at T1D and T2D FreeStyle Libre users' LibreView database in the period between lanuary 2020 to lune 2022. The study was conducted at the diabetes department at the King Fahad Medical City (KFMC) in Riyadh, Saudi Arabia, following Institutional Review Board (IRB) approval. Data were collected from the LibreView website, as well as from the electronic privacy information center (EPIC) hospital records. Results: Data were available for 327 patients, mean age of 33.08(+/- 17.1) years old, and 55.7% were females. HbA1c had a statistically significant correlation with both TIR and GMI with coefficient of correlation (r) values of 0.78 (p<0.001) and 0.82 (p<0.001), respectively. A linear regression model between TIR and Hb1Ac was also developed and found to be statistically significant (p<0.001) with an acceptable R 2 value (0.60). Conclusion: Study findings revealed that the %TIR could be a reliable predictor of Hb1Ac. Thus, Freestyle Libre was able to determine Hb1Ac as close to the lab results as possible. Therefore, it is necessary to encourage diabetes patients to achieve at least 70% TIR in order to keep Hb1Ac within the desired range.

Background: Artificial intelligence (AI) is revolutionizing medical practice and the healthcare industry. The World Health Organization expects AI to help developing countries and rural communities bridge the gaps in healthcare access. The ongoing conflict in Sudan has exposed shortcomings in the country’s healthcare system, underscoring a pressing need for improvement and the adoption of innovative technologies. We have conducted this research to assess the knowledge, attitudes, and concerns of Sudanese doctors regarding the use of AI in Sudan. Methods: This research is an online questionnaire-based study aimed at assessing Sudanese doctors’ perceptions of the use and application of AI. A 34-question Google Form survey was created and distributed via social media platforms, primarily WhatsApp, Facebook, LinkedIn, and personal emails, to Sudanese doctors, both within and outside Sudan, from July to December 2024. Data were analyzed using SPSS software. Results: One hundred ninety-five participants responded to the questionnaire. The results reflected poor knowledge about AI and its applications, but showed a good level of acceptance after training prior to its adoption in Sudan. Participants’ main concerns were related to training and legal matters, mainly accountability and consent. Conclusion: The research revealed significant deficiencies in the knowledge of AI applications among Sudanese doctors. However, it also demonstrated the doctors’ readiness to adopt AI in practice. We recommend incorporating AI education into the curricula of medical schools and postgraduate programs.