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Background There are several observations that the onset of coronavirus 19 (COVID‐19) pandemic was associated with an increase in the incidence of diabetic ketoacidosis (DKA). However, due to heterogeneity in study designs and country‐specific healthcare policies, more national‐level evidence is needed to provide generalizable conclusions. Objective To compare the rate of DKA in Polish children diagnosed with type 1 diabetes (T1D) between the first year of COVID‐19 pandemic (15 March 2020 to 15 March 2021) and the preceding year (15 March 2019 to 15 March 2020). Methods Reference centers in 13 regions (covering ~88% of Polish children) retrospectively reported all new‐onset T1D cases in children from assessed periods, including DKA status at admission, administered procedures and outcomes. Secondly, we collected regions' demographic characteristics and the daily‐reported number of COVID‐19‐related deaths in each region. Results We recorded 3062 cases of new‐onset T1D (53.3% boys, mean age 9.5 ± 4.3 years old) of which 1347 (44%) had DKA. Comparing pre‐ and post‐COVID‐19 period, we observed a significant increase in the rate of DKA (37.5%–49.4%, p < .0001). The fraction of moderate (+5.4%) and severe (+3.4%) DKA cases increased significantly (p = .0089), and more episodes required assisted ventilation (+2.1%, p = .0337). Two episodes of DKA during 2020/2021 period were fatal. By region, change in DKA frequency correlated with initial COVID‐19 death toll (March/April 2020) (R = .6, p = .0287) and change in T1D incidence (R = .7, p = .0080). Conclusions The clinical picture of new‐onset children T1D in Poland deteriorated over a 2‐year period. The observed increase in the frequency of DKA and its severity were significantly associated with the overlapping timing of the COVID‐19 epidemic.

Background New‐Onset Diabetes Mellitus (NODM) is often an early manifestation of pancreatic cancer (Pancreatic Ductal Adenocarcinoma, PDAC). However, there is limited information about (1) the duration prior to PDAC diagnosis when the annual incidence of NODM starts significantly exceeding that in age‐matched controls, (2) the percentage of PDAC patients diagnosed with NODM in the years preceding, and (3) the risk of PDAC following NODM in time when the PDAC risk is significantly higher than in controls. Methods Using the nationwide VA database, we evaluated the annual incidence of NODM for 15 years preceding the PDAC diagnosis and in the age‐ and sex‐matched controls (1:5 matching). In the second part, we evaluated the long‐term risk and predictors of PDAC in NODM patients and controls. Results The case–control study comprised 8198 PDAC patients and 40,992 matched controls. The higher annual incidence of NODM in PDAC patients was statistically significant up to 15 years before PDAC diagnosis. 69.2% of PDAC patients had NODM in the preceding 15 years versus 38.0% of controls. PDAC risk in the 15 years following NODM was 0.60% compared to 0.13% in the controls (aHR 3.83, 95% CI 3.68–3.98, p < 0.001). The risk of PDAC is more pronounced in the 1 year following NODM (aHR 9.07, 95% CI 8.33–9.87) than the subsequent 5 years (aHR 2.98, 95% CI 2.82–3.15). Conclusion NODM pre‐dates PDAC diagnosis in most patients with PDAC. Further evaluation of NODM patients for PDAC has the potential to become a feasible strategy for diagnosing more early‐stage resectable PDACs. Evaluation of New‐Onset Diabetes Mellitus (NODM) for Pancreatic Ductal Adenocarcinoma at the onset of NODM and subsequent surveillance for 3–12 years would be a potential strategy for early diagnosis and improved outcomes in patients with pancreatic cancer.

Aim New‐onset diabetes mellitus is a frequent and severe complication arising after liver transplantation (LT). We aimed to identify the risk factors for new‐onset diabetes mellitus after liver transplantation (NODALT) and to develop a risk prediction score system for relevant risks. Methods We collected and analyzed data from all recipients who underwent liver transplantation at the First Affiliated Hospital of Xi'an Jiaotong University. The OR derived from a multiple logistic regression predicting the presence of NODALT was used to calculate the risk prediction score. The performance of the risk prediction score was externally validated in patients who were from the CLTR (China Liver Transplant Registry) database. Results A total of 468 patients met the outlined criteria and finished the follow‐up. Overall, NODALT was diagnosed in 115 (24.6%) patients. Age, preoperative impaired fasting glucose (IFG), postoperative fasting plasma glucose (FPG), and the length of hospital stay were significantly associated with the presence of NODALT. The risk prediction score includes age, preoperative IFG, postoperative FPG, and the length of hospital stay. The risk prediction score of the area under the receiver operating curve was 0.785 (95% CI: 0.724–0.846) in the experimental population and 0.782 (95% CI: 0.708–0.856) in the validation population. Conclusions Age at the time of transplantation, preoperative IFG, postoperative FPG, and length of hospital stay were independent predictive factors of NODALT. The use of a simple risk prediction score can identify the patients who have the highest risk of NODALT and interventions may start early. Although the survival rate of liver transplantation has improved greatly in recent years, there are still many complications that affect prognosis and life span. New‐onset diabetes mellitus after liver transplantation (NODALT) is a frequent and severe complication arising after liver transplantation, but the pathogenesis of NODALT is still incompletely understood. We found that age, preoperative impaired fasting glucose (IFG), postoperative fasting plasma glucose (FPG), and the length of hospital stay were significantly associated with the presence of NODALT. In addition, the established risk prediction score can identify the patients who have the highest risk of NODALT.

Aims/Introduction To systematically review the risk factors for new‐onset diabetes mellitus after kidney transplantation, and to provide a theoretical basis for the prevention and management of new‐onset diabetes mellitus after kidney transplantation. Materials and Methods We searched PubMed, Web of Science, Embase, the Cochrane Library databases and other databases for case–control studies related to risk factors for new‐onset diabetes mellitus after kidney transplantation published between January 2005 and July 2019. A meta‐analysis of data on risk factors for new‐onset diabetes mellitus after kidney transplantation from the included studies was carried out. A narrative review of risk factors for new‐onset diabetes mellitus after kidney transplantation was also carried out. Results A total of 24 case–control studies were included in the meta‐analysis, with a total of 7,140 patients. There were 1,598 patients with new‐onset diabetes mellitus after kidney transplantation, and 5,542 patients without new‐onset diabetes mellitus after kidney transplantation. The meta‐analysis results showed that age, polycystic kidney disease, family history of diabetes, body mass index, acute rejection, tacrolimus use, hepatitis B virus infection, hepatitis C virus infection and hypertension were associated with new‐onset diabetes mellitus after kidney transplantation, whereas sex, sirolimus use, cyclosporin A use, steroid use and cytomegalovirus infection were not associated with new‐onset diabetes mellitus after kidney transplantation. Conclusions Older age, body mass index, family history of diabetes, tacrolimus use, history of hypertension, polycystic kidney disease, acute rejection, hepatitis B virus infection and hepatitis C virus infection are risk factors for new‐onset diabetes mellitus after kidney transplantation. Therefore, the clinical implications of these factors warrant attention. Older age, body mass index, family history of diabetes, tacrolimus use, history of hypertension, polycystic kidney disease, acute rejection, hepatitis B virus infection and hepatitis C virus infection are risk factors for new‐onset diabetes mellitus after kidney transplantation. Therefore, the clinical implications of these factors warrant attention.

Elevated blood glucose levels may serve as an early indicator of underlying pancreatic cancer. Discriminating between pancreatic cancer‐associated new‐onset diabetes (PCAND) and new‐onset type 2 diabetes mellitus (T2DM) holds promise for enabling an earlier diagnosis of pancreatic cancer. Nevertheless, the absence of effective biomarkers for distinguishing PCAND from the more prevalent new‐onset T2DM persists, primarily because of the elusive pathogenesis of PCAND. In this study, the intricate intercellular communication is comprehensively elucidated through single‐cell RNA sequencing. The findings identified Midkine (MDK) as a potential mediator of the interaction between tumor and beta cells. MDK, which originated from pancreatic ductal adenocarcinoma cells, exerted deleterious effects on paraneoplastic beta cells by binding to the SDC4 receptor on the beta cell surface and subsequently downregulating the Ras signaling pathway, thereby impairing insulin production and secretion. Notably, the plasma levels of MDK are higher in patients with PCAND than in those with T2DM. In conclusion, MDK has emerged as a pivotal driver of PCAND pathogenesis and may function as a blood‐based biomarker for discriminating between PCAND and T2DM in populations with new‐onset diabetes, thereby facilitating the advancement of early detection strategies for pancreatic cancer. Midkine (MDK) is a mediator of the interaction between pancreatic cancer and beta cells. MDK, which originated from pancreatic ductal adenocarcinoma cells, exerted deleterious effects on paraneoplastic beta cells by binding to the SDC4 receptor on the beta cell surface and subsequently downregulating the Ras signaling pathway, thereby impairing insulin production and secretion.

The purpose of this study was to investigate the impact of income and industry type on the risk of developing diabetes among Japanese workers, including how this impact is affected by sex. A total of 24,516 employees at small- and medium-sized enterprises in Japan aged 40–74 years who underwent health examinations in fiscal years 2010–2015 were included in this retrospective cohort study. Generalized linear regression models were used to assess the association between new-onset diabetes and income and industry. In men, the cumulative incidence rate was significantly higher in the low-income group; it was highest in the transportation and postal service industries. Although income and industry were independent risk factors for developing diabetes in men, an interaction was found between income and industry, which was affected by participants’ sex: in specific industries (i.e., lifestyle-related, personal services, and entertainment services), men had a significantly higher risk of developing diabetes in the high-income group, and women had a significantly higher risk of developing diabetes in the low-income group. These findings highlight important factors to consider in assessing diabetes risk and suggest that efficient primary and secondary prevention should be encouraged in industries where workers have a high risk of diabetes.

Background The association between macronutrient intake and diabetes is unclear. We used data from the China Health and Nutrition Survey to explore the association between macronutrient intake trajectories and diabetes risk in this study. Methods We included 6755 participants who did not have diabetes at baseline and participated in at least three surveys. The energy supply ratio of carbohydrate, protein, and fat was further calculated from dietary data; different macronutrient trajectories were determined using multitrajectory models; and multiple Cox regression models were used to evaluate the association between these trajectories and diabetes. Results We found three multitrajectories: decreased low carbohydrate‐increased moderate protein‐increased high fat (DLC‐IMP‐IHF), decreased high carbohydrate‐moderate protein‐increased low fat (DHC‐MP‐ILF), and balanced‐macronutrients (BM). Compared to the BM trajectory, DHC‐MP‐ILF trajectories were significantly associated with increased risk of diabetes (hazard ratio [HR]: 3.228, 95% confidence interval [CI]: 1.571–6.632), whereas no association between DLC‐IMP‐IHF trajectories and diabetes was found in our study (HR: 0.699, 95% CI: 0.351–1.392). Conclusions The downward trend of high carbohydrate and the increasing trend of low fat increased the risk of diabetes in Chinese adults. Highlights This study explored the multitrajectories of macronutrients in the Chinese adult population over a period of 26 years. The impact of each macronutrient ratio on diabetes was comprehensively considered. More ideas are provided for the prevention of diabetes.

Hypertensive patients usually have a higher risk of new‐onset diabetes mellitus (NOD) which may trigger cardiovascular diseases. In this study, the effectiveness of six antihypertensive agents with respect to NOD prevention in hypertensive patients was assessed. A network meta‐analysis was conducted to compare the efficacy of specific drug classes. PubMed and Embase databases were searched for relevant articles. Results of the pairwised meta‐analysis were illustrated by odd ratios (OR) and a corresponding 95% confidence interval (CI). The probabilities and outcome of each treatment were ranked and summarized using the surface under the cumulative ranking curve (SUCRA).Twenty‐three trials were identified, including 224,832 patients with an average follow‐up period of 3.9 ± 1.0 years. The network meta‐analysis showed that patients treated by angiotensin II receptor blockers (ARBs) were associated with a lower risk of NOD compared to placebo (PCB), calcium channel blockers (CCBs) and β‐blockers, while diuretic appeared to be ineffective for NOD prevention. Network meta‐analysis results of specific drugs showed that enalapril exhibited distinct advantages and hydrochlorothiazide also exhibited a reliable performance. Our results suggested that both ARBs and angiotensin converse enzyme inhibitors (ACEIs), especially candesartan and enalapril, were preferable for NOD prevention in hypertensive patients. Hydrochlorothiazide also exhibited a reliable performance in comparison with other agents.

Background Serum sodium level is associated with cardiovascular and endocrine health. Though decreased serum sodium is considered to be associated with reduced hypertension risk, some studies also found that it may increase the risk of diabetes. This study aimed to investigate the association of serum sodium with new‐onset diabetes in hypertensive patients. Methods Based on the annual health examinations from 2011 to 2016 in Dongguan City, Guangdong, China, hypertensive patients without diabetes at baseline were selected. Logistic regression and restricted cubic spline were used to evaluate the association between serum sodium level and new‐onset diabetes. Subgroup analysis was also conducted. Results A total of 4438 hypertensive patients with a mean age of 58.65 years were included, of whom 48.9% were male. During a median follow‐up of 35.1 months, 617 (13.9%) of the subjects developed new‐onset diabetes. Per 1‐SD (3.39 mmol/L) increment of serum sodium was associated with a 14% lower risk of new‐onset diabetes (odds ratio = 0.86; 95% CI: 0.78, 0.97; p = 0.01). The lowest quartile of serum sodium was associated with the lowest diabetes risk. The restricted cubic spline showed a linear inverse relationship (nonlinear p = 0.72). Across all the subgroups, the inverse association was consistent (p for interaction >0.05). Conclusion An inverse association of serum sodium with new‐onset diabetes in hypertensive patients was observed. 摘要 背景:血清钠水平与心血管和内分泌健康相关。虽然降低血钠被认为与降低高血压风险相关, 但也有研究发现其可能增加糖尿病风险。本研究旨在探究血清钠与高血压患者新发糖尿病的关系。 方法:基于2011‐2016年广东省东莞市年度健康体检人群, 选取基线时无糖尿病的高血压患者。采用Logistic回归和限制性立方样条分析血钠水平与新发糖尿病的关系, 并进行亚组分析。 结果:研究共纳入4438例高血压患者, 平均年龄58.65岁, 男性占48.9%。中位随访35.1个月, 617例(13.9%)研究对象新发糖尿病。血钠每增加1SD (3.39 mmol/L), 新发糖尿病风险降低14%。(or = 0.86;95% ci: 0.78, 0.97;p值= 0.01)。血清钠的最低四分位数与最低的糖尿病风险相关。限制性立方样条呈线性反比关系(非线性p值= 0.72)。在所有亚组中, 负相关是一致的(交互作用的p值>0.05)。 结论:血清钠与高血压患者新发糖尿病呈负相关。 Highlights There is an inverse association between serum sodium and new‐onset diabetes in a Chinese community‐based hypertensive population. Sodium control may need to be further refined to provide comprehensive cardiovascular and diabetes risk management for hypertensive patients.

Background This study investigated the association between the preoperative lipid profiles and new‐onset diabetes after transplantation (NODAT) in Chinese kidney transplant recipients (KTRs). Methods In this study, of 1140 KTRs registered between January 1993 and March 2018 in Zhongshan Hospital, Fudan University, 449 were enrolled. Clinical data, obtained through a chart review of the patient records in the medical record system, were evaluated, and NODAT was diagnosed based on the American Diabetes Association guidelines. Multivariate Cox regression analysis was conducted to determine whether the preoperative lipid profiles in KTRs were independently associated with NODAT incidence. The preoperative lipid profiles were analyzed as continuous variables and grouped into tertiles. Smooth curve fitting was used to confirm the linear associations. Results During a median follow‐up of 28.03 (interquartile range 12.00–84.23) months, 104 of the 449 (23.16%) participants developed NODAT. The multivariate model analysis, adjusted for all potential covariates, showed that increased values of the following parameters were associated with NODAT (hazard ratio, 95% confidence interval): preoperative total cholesterol (TC; 1.25, 1.09–1.58, p = 0.0495), low‐density lipoprotein cholesterol (LDL‐C; 1.33, 1.02–1.75, p = 0.0352), non‐high‐density lipoprotein cholesterol (non‐HDL‐C; 1.41, 1.09–1.82, p = 0.0084), TC/HDL‐C (1.28, 1.06–1.54, p = 0.0109), and non‐HDL‐C/HDL‐C (1.26, 1.05–1.52, p = 0.0138). However, the association between the preoperative triglyceride, HDL‐C, or TG/HDL‐C and NODAT was not significant. Conclusions Preoperative TC, LDL‐C, non‐HDL‐C, TC/HDL‐C, and non‐HDL‐C/HDL‐C were independent risk factors for NODAT. The relationship between preoperative lipid profiles and NODAT. The area between two dotted lines is expressed as a 95% confidence interval. Each point shows the preoperative lipid level and is connected to form a continuous line. Preoperative TC, LDL‐C, non‐HDL‐C, TC/HDL‐C, and non‐HDL‐C/HDL‐C are independent risk factors for NODAT. However, the association between preoperative TG, HDL‐C, or TG/HDL‐C and NODAT was not significant.