Introduction: Obstructive sleep apnea (OSA) is characterized by a complete or partial obstruction of the upper airway, along with hypoxemia, microarousals, and sleep fragmentation. Compelling evidence has clarified a bidirectional correlation between OSA and diabetes mellitus (DM). This paper was to assess the link between OSA and DM via meta-analysis, consisting of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM).
Materials And Methods: Four databases (PubMed, Cochrane Library, Embase, and CNKI) were screened from inception to March 2024 for observational studies of OSA and DM, including case-control studies and cohort studies. Bidirectional associations between OSA and DM were analyzed, consisting of T1DM and T2DM. Random-effect models were employed to determine the pooled odds ratio (OR) and 95% confidence intervals (CIs) to compare prevalence. Traditional subgroup analyses were implemented. Review Manager 5.3 and Stata 16.0 were utilized for data analyses.
Results: Thirty-five studies were enrolled, including 12 prospective cohort studies, 4 retrospective cohort studies, and 19 case-control studies. DM prevalence was notably higher in OSA patients than in non-OSA patients (OR: 2.29, 95% CI: 1.93-2.72), and OSA prevalence was notably higher in DM patients than in non-DM patients (OR: 2.12, 95% CI: 1.73-2.60). Subgroup analysis uncovered that DM prevalence in the OSA population was more significant in the group <50 years (OR: 3.28, 95% CI: 2.20-4.89) and slightly decreased in the group >50 years (OR: 1.82, 95% CI: 1.38-2.40).
Conclusions: The meta-analysis reveals a bidirectional link between OSA and DM.
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http://dx.doi.org/10.1111/jdi.14354 | DOI Listing |
Scand J Gastroenterol
December 2024
Norwegian Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Objectives: Concurrent type 1 diabetes (T1D) and celiac disease (CeD) pose challenges in insulin dosage adjustments and gluten-free dietary adherence. Urine testing for gluten immunogenic peptides (GIP) is a new method to detect gluten exposure within the last 3-12 h. Our aims were to compare gluten-free dietary adherence between T1D + CeD and CeD individuals and evaluate urinary GIP testing in an outpatient setting.
View Article and Find Full Text PDFMed Sci Monit
December 2024
Independent Laboratory of Minimally Invasive Gynecology and Gynecological Endocrinology, Medical University of Lublin, Lublin, Poland.
Polycystic ovary syndrome (PCOS) is associated with several mild metabolic disorders, including insulin resistance (IR), obesity, and dyslipidemia, as well as with some more severe ones, including type 2 diabetes mellitus, non-alcoholic fatty liver disease (NAFLD), and cardiovascular disease. Clinically, mild metabolic complications of PCOS such as IR or lipid metabolism disorders are the predictors of these more severe ones. So far, there is no reliable single marker that enables defining metabolic risk in patients with PCOS.
View Article and Find Full Text PDFCardiovasc Diabetol
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INSERMU1138-Centre de Recherche Des Cordeliers, Paris Cite University, Sorbonne University, 75006, Paris, France.
Hypertension, cardiovascular disease and kidney failure are associated with persistent hyperglycaemia and the subsequent development of nephropathy in people with diabetes. Diabetic nephropathy is associated with widespread vascular disease affecting both the kidney and the heart from an early stage. However, the risk of diabetic nephropathy in people with type 1 diabetes is strongly genetically determined, as documented in familial transmission studies.
View Article and Find Full Text PDFCardiovasc Diabetol
December 2024
Saw Swee Hock School of Public Heath, National University of Singapore, Singapore, 117549, Republic of Singapore.
Background: Data on the relationship between potassium intake and major cardiovascular events (MACE) in patients with diabetes are scarce. We aim to study the association between estimated potassium intake and risk of MACE in individuals with type 2 diabetes.
Methods: The discovery cohort consisted of 1572 participants with type 2 diabetes from a secondary hospital.
BMC Med Inform Decis Mak
December 2024
Hellenic Complex Systems Laboratory, Kostis Palamas 21, 66131, Drama, Greece.
Background: In medical diagnostics, estimating post-test or posterior probabilities for disease, positive and negative predictive values, and their associated uncertainty is essential for patient care.
Objective: The aim of this work is to introduce a software tool developed in the Wolfram Language for the parametric estimation, visualization, and comparison of Bayesian diagnostic measures and their uncertainty.
Methods: This tool employs Bayes' theorem to estimate positive and negative predictive values and posterior probabilities for the presence and absence of a disease.
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