Predictors Of New-onset Diabetes Mellitus Research Articles

Myosteatosis as a novel predictor of new-onset diabetes mellitus after kidney transplantation.

We evaluate the effect of myosteatosis on new-onset diabetes mellitus after kidney transplantation. Consecutive patients who had renal transplant between 2006 and 2021 were reviewed, and 219 patients were finally included. Psoas muscle index was used to evaluate sarcopenia and average total psoas density (calculated by computed tomography before surgery) for myosteatosis. We used Cox proportional regression analyses in investigation of whether skeletal muscle depletion before surgery inclusive of sarcopenia and myosteatosis is a new additional predictor of new-onset diabetes mellitus. Median recipient age and body mass index were 45 years and 21.1 kg/m2 , respectively, and 123 patients (56%) were male. Preoperative impaired glucose tolerance was present in 58 patients (27%) and new-onset diabetes mellitus in 30 patients (14%), with median psoas muscle index of 6 cm2 /m2 and average total psoas density of 41 Hounsfield Unit. In multivariate analysis, significant risk factors were body mass index ≥25 kg/m2 (p < 0.01), impaired glucose tolerance (p < 0.01), and average total psoas density < 41.9 Hounsfield Unit (p = 0.03). New-onset diabetes mellitus had incidence rates of 3.7% without risk factors, 10% with a single risk factor, 33% with two, and 60% with three. Patients with new-onset diabetes mellitus were effectively stratified by the number of risk factors (p < 0.01). Myosteatosis could be a new risk factor used to predict new-onset diabetes mellitus.

Prediction of New-Onset Diabetes Mellitus within 12 Months after Liver Transplantation-A Machine Learning Approach.

Liver transplantation (LT) is a routine therapeutic approach for patients with acute liver failure, end-stage liver disease and/or early-stage liver cancer. While 5-year survival rates have increased to over 80%, long-term outcomes are critically influenced by extrahepatic sequelae of LT and immunosuppressive therapy, including diabetes mellitus (DM). In this study, we used machine learning (ML) to predict the probability of new-onset DM following LT. A cohort of 216 LT patients was identified from the Disease Analyzer (DA) database (IQVIA) between 2005 and 2020. Three ML models comprising random forest (RF), logistic regression (LR), and eXtreme Gradient Boosting (XGBoost) were tested as predictors of new-onset DM within 12 months after LT. 18 out of 216 LT patients (8.3%) were diagnosed with DM within 12 months after the index date. The performance of the RF model in predicting the development of DM was the highest (accuracy = 79.5%, AUC 77.5%). It correctly identified 75.0% of the DM patients and 80.0% of the non-DM patients in the testing dataset. In terms of predictive variables, patients' age, frequency and time of proton pump inhibitor prescription as well as prescriptions of analgesics, immunosuppressants, vitamin D, and two antibiotic drugs (broad spectrum penicillins, fluocinolone) were identified. Pending external validation, our data suggest that ML models can be used to predict the occurrence of new-onset DM following LT. Such tools could help to identify LT patients at risk of unfavorable outcomes and to implement respective clinical strategies of prevention.

Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis With Liver Fibrosis as Predictors of New-Onset Diabetes Mellitus in People With HIV: A Longitudinal Cohort Study.

We investigated the association between nonalcoholic fatty liver disease (NAFLD) plus or minus a concurrent diagnosis of nonalcoholic steatohepatitis (NASH) and incident diabetes mellitus (DM) and the risk factors associated with NAFLD or NASH development. In this prospective study, we analyzed people with human immunodeficiency virus (HIV; PWH) aged ≥18 years without excessive alcohol consumption or hepatitis coinfections. NAFLD was defined as controlled attenuation parameter ≥248 dB/m, whereas NASH with significant disease activity and liver fibrosis was defined as a FibroScan-AST score ≥0.67. Cox proportional hazard regression was used to investigate the association between NAFLD with or without NASH and new-onset DM. Of 847 PWH, the median age at baseline was 45 years (interquartile range, 38-51; 43% female). Baseline NAFLD was associated with 2.8-fold higher risk of new-onset DM after adjusting for age, sex, family history of DM, antiretroviral therapy duration, smoking, statin use, stavudine/didanosine/zidovudine exposure, time-updated body mass index, hypertension, and dyslipidemia. Combined NAFLD and NASH at baseline had 3.1-fold higher new-onset DM risk. In separate analyses, baseline DM did not predict progression to NAFLD or NASH, but tenofovir alafenamide use was associated with an increased risk of NAFLD (hazard ratio [HR], 2.01; 95% confidence interval [CI], 1.02-4.02) or NASH development (2.31; 95% CI, 1.12-5.11). NAFLD alone or combined with NASH strongly predicts new-onset DM. This highlights the need for systematic risk assessments and management of NAFLD/NASH, as it may contribute to metabolic complications such as DM and subsequent cardiovascular diseases in PWH.

Myosteatosis as a novel predictor of new-onset diabetes mellitus after kidney transplantation

Myosteatosis as a novel predictor of new-onset diabetes mellitus after kidney transplantation

PS-P08-9: DEPRESSION IS ASSOCIATED WITH NEW-ONSET DIABETES MELLITUS, BUT NOT HYPERTENSION, IN THE GENERAL POPULATION

Objective: Epidemiological studies have shown that depression is a risk factor for cardiovascular disease, however, the mechanism underlying this association is yet unclear especially in the general populations. The aim of this study was to evaluate the relationship between depression and new-onset hypertension/diabetes mellitus in the general population. Design and Method: Individuals from the general population who participated in a medical check-up both in 2019 and 2020 were enrolled in this study. Fasting blood and urinary samples were taken for biochemical analysis, and depression was assessed by using Self-rating Depression Scale (SDS). Hypertension was defined as blood pressure of more than or equal to 140/90 mmHg or use of anti-hypertensive drugs. Diabetes mellitus was defined as fasting blood glucose of more than or equal to 126 mg/dL or HbA1c of 6.5% or use of anti-diabetic drugs. Multivariate logistic regression models were used to calculate odds ratios for new-onset hypertension and diabetes mellitus in 2020 after adjustment for possible confounding factors. Results: Among 550 participants without present hypertension in 2019, 124 developed hypertension in 2020. Similarly, among 890 participants without diabetes mellitus in 2019, 39 developed diabetes in 2020. Multivariate logistic regression analysis showed that severe depression (SDS score of more than or equal to 48) was significantly associated with new-onset diabetes mellitus (odds ratio: 2.558, 95%CI: 1.009–6.487, p = 0.048), but not with new-onset hypertension (odds ratio: 0.943, 95%CI: 0.434–2.051, p = 0.883) after adjustment for potential risk factors. Conclusions: In conclusion, severe depression may be a possible predictor of new-onset diabetes mellitus in the general population.

Identification of a Risk Profile for New-Onset Diabetes After Acute Pancreatitis.

There is a paucity of studies evaluating predictors of new-onset diabetes mellitus (DM) after acute pancreatitis (AP-related DM). We used a population-based database to evaluate predictors of AP-related DM. The Nationwide Readmissions Database (2010-2014) was used to identify all nondiabetic adults with an index primary diagnosis of AP. Multiple exclusions were applied to identify cohorts with and without AP-related DM. A case-control study was conducted to identify risk factors for developing AP-related DM within the calendar year. We identified 2510 subjects with AP-related DM and 40,308 controls with AP who did not develop DM. Multivariable analysis revealed that increasing age (50-64 years; adjusted odds ratio [aOR], 1.35; 95% confidence interval [CI], 1.14-1.60), male sex (aOR, 1.2; 95% CI, 1.03-1.40), lowest income quartile (aOR, 1.48; 95% CI, 1.18-1.84), Elixhauser comorbidity index of 3 or higher (aOR, 1.47; 95% CI, 1.23-1.75), components of metabolic syndrome (aOR, 2.12; 95% CI, 1.21-3.70), severe AP (aOR, 1.60; 95% CI, 1.34-1.90), and recurrent AP (aOR, 1.46; 95% CI, 1.24-1.72) were independently associated with increased risk of AP-related DM. These population-level variables predictive of developing AP-related DM can potentially identify patients who may benefit from closer follow-up, intensive education, and implementation of preventative strategies.

Low fasting plasma glucose level as a predictor of new-onset diabetes mellitus on a large cohort from a Japanese general population

Although fasting plasma glucose levels <70 mg/dL are associated with a high incidence of cardiovascular disease (CVD), whether there is any risk of new-onset diabetes mellitus owing to fasting plasma glucose at this range has not been clarified. We measured the odds ratio (OR) of new-onset diabetes mellitus relative to fasting plasma glucose levels at various ranges in a nation-wide Japanese population with and without CVD history. Of 186,749 participants without diabetes in 2008, 171,408 had no history of CVD, while 15,341 did. Participants were classified into 8 categories according to their fasting plasma glucose levels. Unadjusted and multivariable-adjusted logistic regression models were used to measure the OR of new-onset diabetes mellitus in the 3-year follow up. In all participants, multivariable-adjusted OR increased when fasting plasma glucose levels were <70 mg/dL or 90–125 mg/dL. Participants without CVD showed increased OR when glucose levels were <70 mg/dL or 90–125 mg/dL. Participants with a history of CVD showed increased OR with glucose levels of 95–125 mg/dL. The risk of new-onset diabetes mellitus is higher when fasting glucose levels are <70 mg/dL, indicating that the paradox of fasting glucose seeks a new risk stratification for new-onset diabetes mellitus.

Increased epicardial adipose tissue thickness is a predictor of new-onset diabetes mellitus in patients with coronary artery disease treated with high-intensity statins

BackgroundStatins are widely used for lipid lowering in patients with coronary artery disease (CAD), but increasing evidence indicates an association between statin use and new-onset of diabetes mellitus (NODM). Epicardial adipose tissue (EAT) refers to the visceral fat surrounding the heart, which is associated with metabolic diseases. We sought to determine the association between EAT thickness and NODM in CAD patients treated with high-intensity statins.MethodsWe conducted a retrospective medical record review of CAD patients treated with high-intensity statins for at least 6 months after percutaneous coronary intervention performed between January 2009 and June 2013 at Seoul National University Bundang Hospital. EAT thickness was measured by echocardiography using standardized methods.ResultsA total of 321 patients were enrolled, who received high-intensity statins for a mean of 952 days; atorvastatin 40 mg in 204 patients (63.6%), atorvastatin 80 mg in 57 patients (17.8%), and rosuvastatin 20 mg in 60 patients (18.7%). During the follow-up period of 3.9 ± 1.7 years, NODM occurred in 40 patients (12.5%). On Cox proportional-hazard regression analysis, EAT thickness at systole [for each 1 mm: hazard ratio (HR) 1.580; 95% confidence interval (CI) 1.346–1.854; P < 0.001] and prediabetes at baseline (HR 4.321; 95% CI 1.998–9.349; P < 0.001) were the only independent predictors of NODM. Using binary cutoff values derived from the receiver operating characteristic curve analysis, EAT thickness at systole larger than 5.0 mm had an HR of 3.402 (95% CI 1.751–6.611, P < 0.001), sensitivity of 52.5%, and specificity of 80.8% for predicting NODM. Also, patients with EAT thickness ≥ 5 mm and prediabetes at baseline had a 12.0-times higher risk of developing NODM compared to the risk noted in patients with EAT thickness < 5 mm and normal glucose tolerance at baseline.ConclusionEpicardial adipose tissue thickness at systole is a consistent independent predictor of NODM in patients with CAD treated with high-intensity statins. Such predictors may help physicians plan adequate surveillance for early detection of NODM.

P4450Isolated systolic hypertension versus combined systolic-diastolic hypertension as predictors of new-onset diabetes mellitus: Data from a Greek 8-year-follow-up study

P4450Isolated systolic hypertension versus combined systolic-diastolic hypertension as predictors of new-onset diabetes mellitus: Data from a Greek 8-year-follow-up study

Does the pancreatic volume reduction rate using serial computed tomographic volumetry predict new onset diabetes after pancreaticoduodenectomy?

Volume reduction of the pancreatic tissues following a pancreatectomy can lead to the deterioration of glucose homeostasis. This is defined as pancreatogenic diabetes mellitus (DM). The objective of this study was to investigate the occurrence of new-onset DM (NODM) and evaluate the risk factors, including the pancreas volume reduction rate in patients undergoing pancreaticoduodenectomy (PD).Sixty-six patients without preoperative DM underwent PD for periampullary tumors between August 2007 and December 2012 and were included in this analysis. These patients underwent follow-up tests and abdominal computed tomography (CT) scan 7 days, 6 months, 12 months, 24 months, and 36 months after the operation. The pancreas volume reduction rate was calculated by CT volumetry. The patients were divided into 2 groups according to the postoperative development of DM.After PD, newly diagnosed DM occurred in 16 patients (24.2%). The incidence of DM was highest among patients with carcinomas with an advanced T stage. The pancreatic volume reduction rate after 6 and 12 months in the NODM group was significantly higher than the normal glucose group in the univariate analysis. In the multivariate analysis, the pancreatic volume reduction rate 6 months after PD was the only significant predictive factor for the development of NODM (P = 0.002).This study suggests that the pancreatic volume reduction rate 6 months after PD was the only significant predictive factor for the development of NODM. CT volumetry of the pancreas may be useful as a predictor of NODM after PD.

Epidemiology and Mortality of New-Onset Diabetes After Dialysis

OBJECTIVEWe examined the predictors and risks associated with pre-existing versus new-onset diabetes mellitus (DM) after initiation of chronic dialysis therapy in end-stage renal disease (ESRD) patients.RESEARCH DESIGN AND METHODSIn the Taiwan National Health Insurance Research Database, we examined records of ESRD patients who initiated dialysis between 1999 and 2005. Patients were followed until death, transplant, dialysis withdrawal, or 31 December 2008. Predictors of new-onset DM and mortality were calculated using Cox models.RESULTSA total of 51,487 incident dialysis patients were examined in this study, including 25,321 patients with pre-existing DM, 3,346 with new-onset DM, and 22,820 without DM at any time. Patients’ age (mean ± SD) was 61.8 ± 11.5, 61.6 ± 13.7, and 56.5 ± 16.6 years in pre-existing, new-onset DM, and without DM groups, respectively. The cumulative incidence rate of new-onset DM was 4% at 1 year and 21% at 9 years. Dialysis modality was not a risk factor for new-onset DM (peritoneal dialysis to hemodialysis hazard ratio [HR] of new-onset DM, 0.94 [95% CI 0.83–1.06]). Pre-existing DM was associated with 80% higher death risk (HR 1.81 [95% CI 1.75–1.87]), whereas the new-onset DM was associated with 10% increased death risk (HR 1.10 [95% CI 1.03–1.17]).CONCLUSIONSWhereas dialysis modality does not appear to associate with new-onset DM, both pre-existing and new-onset DM are related to higher long-term mortality in maintenance dialysis patients.

English

Introduction Diabetic nephropathy is the leading cause of end-stage renal disease in patients undergoing dialysis. Most studies evaluate the association between pre-existing diabetes mellitus, but very few focus on newonset diabetes mellitus after dialysis. Chronic dialysis patients are often older and have multiple comorbidities, including cardiovascular diseases and pancreatic disorder. In addition, these patients have been found to be in a state of chronic inflammation. These characteristics have been associated with the development of insulin resistance and diabetes. Herein, we critically review the epidemiology, risk factors and mortality of new-onset diabetes mellitus after dialysis. Conclusion The dialysis population has a higher incidence of new-onset diabetes mellitus and a greater risk of mortality than the general population. In addition, the post-transplant incidence of diabetes mellitus, which always occurs the first year after transplant, is much higher than the pre- transplant incidence. However, dialysis modality does not appear to be associated with new-onset diabetes mellitus after dialysis and post- transplant. The independent predictors of newonset diabetes mellitus are old age, cardiovascular comorbidity and dyslipidemia. Other possible contributing factors are inflammation and use of some commonly prescribed drugs for cardiovascular disease, such as statin. Physicians may need to pay more attention to the possibility of new-onset diabetes mellitus when treating high-risk patients undergoing dialysis.

Predictors of new-onset diabetes mellitus in hypertensive patients: the VALUE trial

Diabetes mellitus often develops in patients with hypertension. We investigated predictors of diabetes mellitus development in hypertensives at risk of developing the disease in the VALUE trial population. Among the 9995 non-diabetic hypertensive patients at baseline, 1298 patients developed diabetes mellitus during the average follow-up of 4.2 years. New-onset diabetes mellitus was defined from adverse event reports, information about new antidiabetic medication and/or a fasting glucose >or=7.0 mmol l(-1) at the end of trial. Twenty-five potential baseline predictors of new-onset diabetes mellitus were analysed by univariate logistic regression and 14 of 25 predictors were found to be statistically significant with a P-value <0.05. The predictors were in order of decreasing significance; glucose, body mass index (BMI), age, uric acid, non-Caucasian race, haemoglobin, heart rate, randomized study treatment, history of coronary heart disease (CHD), gender, total cholesterol, proteinuria, potassium and creatinine. Multivariate stepwise logistic regression analyses were used and potential baseline predictors of new-onset diabetes mellitus were considered significant by four different models (P-value <0.001). The final multivariate model selected included all patients, but not treatment group as a potential predictor, and the six significant predictors identified from this model were glucose, BMI, non-Caucasian race, age, heart rate and history of CHD. In conclusion, glucose and BMI were the most important predictors of new-onset diabetes mellitus in hypertensive patients at high cardiovascular risk, and easily accessible clinical characteristics strongly predict patients at risk of developing diabetes mellitus.

The Effect of Body Mass Index on Fasting Blood Glucose After Initiation of Thiazide Therapy in Hypertensive Patients

The prevalence of obesity, hypertension, and type 2 diabetes mellitus is increasing in the United States. In this setting, it is important to understand the effects of antihypertensives on glucose metabolism. We therefore examined the association between body mass index (BMI) (kg/m(2)) and fasting blood glucose (FBG) in subjects in whom thiazide antihypertensive therapy had been initiated. A retrospective observational study was carried out on individuals with hypertension who had been started on thiazide therapy. The subjects' age, thiazide dose, BMI, serum potassium, FBG, new onset of diabetes mellitus, and concurrent use of other antihypertensives were included in the analysis. Predictors of change in FBG were analyzed using multiple linear regression analysis, while predictors of new-onset diabetes mellitus were determined using multiple logistic regression. A total of 2,624 individuals who had been started on thiazide therapy for hypertension were divided into quartiles of increasing BMI. FBG was found to be associated with baseline BMI and, after thiazide initiation, there was a step-wise increase in the magnitude of change in FBG with increasing BMI (P < 0.001 for both). Analysis using multiple linear regression found that BMI and baseline FBG predicted the magnitude of FBG change in subjects initiated on thiazide treatment (P < 0.001 for both). Analysis with logistic regression found that, after thiazide initiation, BMI, serum potassium baseline (P < 0.05 for both), and baseline FBG (P < 0.001) predicted the development of diabetes mellitus. There is an overall increase in FBG in individuals who are started on treatment with thiazides for hypertension. The magnitude of change in FBG and the development of new-onset diabetes mellitus after thiazide initiation were associated with increases in BMI and baseline FBG. American Journal of Hypertension (2008) doi:10.1038/ajh.2007.75American Journal of Hypertension (2008); 21 4. 438-442 doi:10.1038/ajh.2007.75.

Obesity, Adiponectin and Inflammation as Predictors of New-Onset Diabetes Mellitus After Kidney Transplantation

The high incidence of new-onset diabetes mellitus after transplantation (NODAT) suggests the need to find new factors to explain the pathogenesis. Our objectives were (1) to confirm that low levels of pre-transplant adiponectin are an independent risk factor for the development of NODAT in a larger transplanted population; (2) to analyze whether adiponectin is a better predictor of NODAT than other inflammatory markers (C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-alpha) and pregnancy-associated plasma protein A (PAPP-A)) and (3) to assess the relationship between obesity, inflammatory markers and NODAT. One hundred ninety-nine non-diabetic patients (128 men; age: 53 +/- 11 years; body mass index (BMI) 24.98 +/- 3.76 kg/m2) were included. Pre-transplant plasma glucose, insulin, adiponectin, CRP, TNF-alpha, IL-6 and PAPP-A were measured. Forty-five patients developed NODAT. Patients with NODAT had a greater BMI (p = 0.005). Adiponectin was lower (p < 0.001) and CRP higher (p = 0.032) in patients with NODAT. Multivariate logistic regression and Cox analysis showed that the calcineurin inhibitor used, pre-transplant BMI and adiponectin were predictors of NODAT. ROC analysis showed that an adiponectin concentration of 11.4 microg/mL had a significant negative prediction for NODAT risk (sensitivity: 81% and specificity: 70%). Of the inflammatory markers studied, adiponectin proved to be an independent predictor of NODAT.