The association between obstructive sleep apnea syndrome (OSAS) and mortality has not been extensively researched among individuals with varying diabetic status. This study aimed to compare the relationship of OSAS with all-cause and cause-specific mortality in US individuals with or without diabetes based on data from the National Health and Nutrition Examination Survey (NHANES).
The study included participants from the NHANES 2005–2008 and 2015–2018 cycles with follow-up information. OSAS data (OSAS.MAP10) was estimated from the questionnaire. Hazard ratios (HRs) and the 95% confidence interval (CI) of OSAS for mortality were calculated by Cox regression analysis in populations with different diabetes status. The relationships between OSAS and mortality risk were examined using survival curves and restricted cubic spline curves.
A total of 13 761 participants with 7.68 ± 0.042 follow-up years were included. In the nondiabetic group, OSAS.MAP10 was positively associated with all-cause, cardiovascular, and cancer mortality. In individuals with prediabetes, OSAS.MAP10 was positively related to all-cause mortality (HR 1.11 [95% CI: 1.03–1.20]) and cardiovascular mortality (HR 1.17 [95% CI: 1.03–1.33]). The relationship between OSAS.MAP10 and the risk of all-cause mortality and cancer mortality exhibited L-shaped curves in diabetes patients (both with nonlinear p values <.01). Further threshold effect analysis revealed that OSAS was positively related to death risk when OSAS.MAP10 exceeded the threshold scores.
The relationship between OSAS and mortality differed among participants with or without diabetes. Individualized clinical treatment plans should be developed in clinical practice to reduce the risk of death for patients with different metabolic conditions.
It is not clear whether there are differences in glycemic control between the Equil patch and the MMT-712 insulin pump. Our objective was to compare two types of insulin pumps in the treatment of type 2 diabetes mellitus (T2DM), using continuous glucose monitoring (CGM) metrics and profiles.
This was a randomized case-crossover clinical trial. Participants were hospitalized and randomly allocated to two groups and underwent two types of insulin pump treatments (group A: Equil patch—Medtronic MMT-712 insulin pump; group B: Medtronic MMT-712—Equil patch insulin pump) separated by a 1-day washout period. Glycemic control was achieved after 7–8 days of insulin pump therapy. Each patient received CGM for 5 consecutive days (from day 1 to day 5). On day 3 of CGM performance, the Equil patch insulin pump treatment was switched to Medtronic MMT-712 insulin pump treatment at the same basal and bolus insulin doses or vice versa. CGM metrics and profiles including glycemic variability (GV), time in range (TIR, 3.9–10.0 mmol/L), time below range (TBR, <3.9 mmol/L), time above range (TAR, >10.0 mmol/L), and postprandial glucose excursions, as well as incidence of hypoglycemia.
Forty-six T2DM patients completed the study. There was no significant difference in parameters of daily GV and postprandial glucose excursions between the Equil patch insulin pump treatment and the Medtronic insulin pump treatment. Similarly, there was no between-treatment difference in TIR, TBR, and TAR, as well as the incidence of hypoglycemia.
The Equil patch insulin pump was similar to the traditional MMT-712 insulin pump in terms of glycemic control. Equil patch insulin pump is a reliable tool for glycemic management of diabetes mellitus.
We investigated the association between post-hospital discharge use of sodium glucose cotransporter-2 inhibitors (SGLT-2is) compared to dipeptidyl peptidase-4 inhibitors (DPP-4is) and the incidence of hospitalization for acute renal failure (ARF) and chronic kidney disease (CKD) in people with type 2 diabetes.
We conducted a retrospective cohort study using linked hospital and prescription data. Our cohort included people aged ≥30 years with type 2 diabetes discharged from a hospital in Victoria, Australia, from December 2013 to June 2018. We compared new users of SGLT-2is with new users of DPP-4is following discharge. People were followed from first dispensing of a SGLT-2i or DPP-4i to a subsequent hospital admission for ARF or CKD. We used competing risk models with inverse probability of treatment weighting (IPTW) to estimate subhazard ratios.
In total, 9620 people initiated SGLT-2is and 9962 initiated DPP-4is. The incidence rate of ARF was 12.3 per 1000 person-years (median years of follow-up [interquartile range [IQR] 1.4 [0.7–2.2]) among SGLT-2i initiators and 18.9 per 1000 person-years (median years of follow-up [IQR] 1.7 [0.8–2.6]) among DPP-4i initiators (adjusted subhazard ratio with IPTW 0.78; 95% confidence interval [CI] 0.70–0.86). The incidence rate of CKD was 6.0 per 1000 person-years (median years of follow-up [IQR] 1.4 [0.7–2.2]) among SGLT-2i initiators and 8.9 per 1000 person-years (median years of follow-up [IQR] 1.7 [0.8–2.6]) among DPP-4i initiators (adjusted subhazard ratio with IPTW 0.83; 95% CI 0.73–0.94).
Real-world data support using SGLT-2is over DPP-4is for preventing acute and chronic renal events in people with type 2 diabetes.
Kisspeptins (KPs) are proteins that were first recognized to have antimetastatic action. Later, the critical role of this peptide in the regulation of reproduction was proved. In recent years, evidence has been accumulated supporting a role for KPs in regulating metabolic processes in a sexual dimorphic manner. It has been proposed that KPs regulate metabolism both indirectly via gonadal hormones and/or directly via the kisspeptin receptor in the brain, brown adipose tissue, and pancreas. The aim of the review is to provide both experimental and clinical evidence indicating that KPs are peptides linking metabolism and reproduction. We propose that KPs could be used as a potential target to treat both metabolic and reproductive abnormalities. Thus, we focus on the consequences of disruptions in KPs and their receptors in metabolic conditions such as diabetes, undernutrition, obesity, and reproductive disorders (hypogonadotropic hypogonadism and polycystic ovary syndrome). Data from both animal models and human subjects indicate that alterations in KPs in the case of metabolic imbalance lead also to disruptions in reproductive functions. Changes both in the hypothalamic and peripheral KP systems in animal models of the aforementioned disorders are discussed. Finally, an overview of current clinical studies involving KP in fertility and metabolism show fewer studies on metabolism (15%) and only one to date on both. Presented data indicate a dynamic and emerging field of KP studies as possible therapeutic targets in treatments of both reproductive and metabolic dysfunctions.
Depression is the most common psychological disorder in patients with type 1 diabetes (T1D). However, the characteristics of microbiota and metabolites in these patients remain unclear. This study aimed to investigate microbial and metabolomic profiles and identify novel biomarkers for T1D with depression.
A case–control study was conducted in a total of 37 T1D patients with depression (TD+), 35 T1D patients without depression (TD−), and 29 healthy controls (HCs). 16S rRNA gene sequencing and liquid chromatography–mass spectrometry (LC–MS) metabolomics analysis were conducted to investigate the characteristics of microbiota and metabolites. The association between altered microbiota and metabolites was explored by Spearman's rank correlation and visualized by a heatmap. The microbial signatures to discriminate TD+ from TD− were identified by a random forest (RF) classifying model.
In microbiota, 15 genera enriched in TD− and 2 genera enriched in TD+, and in metabolites, 14 differential metabolites (11 upregulated and 3 downregulated) in TD+ versus TD− were identified. Additionally, 5 genera (including Phascolarctobacterium, Butyricimonas, and Alistipes from altered microbiota) demonstrated good diagnostic power (area under the curve [AUC] = 0.73; 95% CI, 0.58–0.87). In the correlation analysis, Butyricimonas was negatively correlated with glutaric acid (r = −0.28, p = 0.015) and malondialdehyde (r = −0.30, p = 0.012). Both Phascolarctobacterium (r = 0.27, p = 0.022) and Alistipes (r = 0.31, p = 0.009) were positively correlated with allopregnanolone.
T1D patients with depression were characterized by unique profiles of gut microbiota and serum metabolites. Phascolarctobacterium, Butyricimonas, and Alistipes could predict the risk of T1D with depression. These findings provide further evidence that the microbiota–gut–brain axis is involved in T1D with depression.
Gestational diabetes mellitus increases the risk of developing type 2 diabetes. The aim of this study is to compare cardiometabolic and renal outcomes for all women in New Zealand with gestational diabetes (2001–2010) with women without diabetes, 10–20 years following delivery.
A retrospective cohort study, utilizing a national dataset providing information for all women who gave birth between 1 January 2001 and 31 December 2010 (n = 604 398). Adolescent girls <15 years, women ≥50 years and women with prepregnancy diabetes were excluded. In total 11 459 women were diagnosed with gestational diabetes and 11 447 were matched (for age and year of delivery) with 57 235 unexposed (control) women. A national hospital dataset was used to compare primary outcomes until 31 May 2021.
After controlling for ethnicity, women with gestational diabetes were significantly more likely than control women to develop diabetes—adjusted hazard ratio (HR) 20.06 and 95% confidence interval (CI) 18.46–21.79; a first cardiovascular event 2.19 (1.86–2.58); renal disease 6.34 (5.35–7.51) and all-cause mortality 1.55 (1.31–1.83), all p values <.0001. The HR and 95% CI remained similar after controlling for significant covariates: diabetes 18.89 (17.36–20.56), cardiovascular events 1.79 (1.52–2.12), renal disease 5.42 (4.55–6.45), and all-cause mortality 1.44 (1.21–1.70). When time-dependent diabetes was added to the model, significance remained for cardiovascular events 1.33 (1.10–1.61), p = .003 and renal disease 2.33 (1.88–2.88), p < .0001 but not all-cause mortality.
Women diagnosed with gestational diabetes have an increased risk of adverse cardiometabolic and renal outcomes. Findings highlight the importance of follow-up screening for diabetes, cardiovascular risk factors, and renal disease.
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