The Mental Status in Patients with Diabetes Mellitus Admitted to a Diabetes Clinic After Presenting in the Emergency Room: The Application of the SCL-90 Scale

Predictive Factors of Anxiety and Depression in Patients with Type 2 Diabetes Mellitus

Background: Diabetes mellitus (DM) is a chronic condition associated with multiple complications and comorbidities. Some of these comorbidities are anxiety and depression, with a negative impact on the quality of life, non-adherence to treatment, and poor prognosis. The main aim of this study was to evaluate depression and anxiety in a group of patients with DM and their impact on quality of life and identify factors that improve the prognosis and increase the life expectancy and quality of life of patients with DM. Methods: A total of 209 patients with type 2 DM (T2DM) were enrolled cross-sectionally. Patients were screened for psychiatric disorders, cognitive impairment, and metabolic parameters. Results: Included patients had a median age of 66.0 (58; 70) years, a median DM duration of 9 (6; 15) years, and a suboptimal glycemic control reflected by a median HbA1c of 7.8 (7; 9.2) mg/dL. Patients presented anxiety at different stages in 51.5% of cases, and similarly, depression in 37.5% of cases. Age, duration of DM, HbA1c, and postprandial hyperglycemia (PPG) were predictive factors for anxiety and depression in patients with T2DM. An age > 57 years (sensitivity 84.3, specificity 33.7, AUROC 0.621, p = 0.002) and an HbA1c > 8.5% (sensitivity 45.8, specificity 83.1, AUROC = 0.635, p < 0.0001) predict a higher rate of anxiety, respectively, of depression in these patients. Conclusions: Patients with T2DM have an increased rate of anxiety and depression due to persistent hyperglycemia and aging, which is expressed in a lower quality of life.

Potential biomarkers and therapeutic targets for obsessive compulsive disorder: Evidences from clinical studies

Obsessive compulsive disorder (OCD) is a prevalent behavioral disorder with a complex etiology. However, the underlying pathogenic molecular pathways and the associated risk factors are largely obscure. This has hindered both the identification of relevant prognostic biomarkers and the development of effective treatment strategies. Because of the diverse range of clinical manifestations, not all patients benefit from therapies currently practiced in the clinical setting. Nevertheless, several lines of evidence indicate that neurotrophic, neurotransmitter, and oxidative signaling are involved in the pathophysiology of OCD. Based upon evidences from clinical (and pre-clinical studies), the present review paper sets out to decipher the utilities of three parameters (i.e. brain-derived neurotrophic factor; BDNF, noradrenalin-synthesizing enzyme dopamine beta-hydroxylase; DBH; and oxidative damage marker malondialdehyde; MDA) as diagnostic peripheral biomarkers as well as bio-targets for therapeutic strategies. While the data indicates promising results, there is necessitation for future studies to further confirm and establish these. Further, based again on the available clinical data, we investigated the possibilities of exploiting the etiological links between disruptions in the sleep-wake cycle and insulin signaling, and OCD for the identification of potential anti-OCD ameliorative agents with the ability to elicit multimodal effects, including attenuation of the alterations in BDNF, noradrenergic and redox pathways. In this respect, agomelatine and metformin may represent particularly interesting candidates; however, further clinical studies are warranted to establish these as singular or complementary medications in OCD subjects.

Salivary Biomarkers Associated with Psychological Alterations in Patients with Diabetes: A Systematic Review

The care of individuals with diabetes needs a holistic perspective, taking into account both the physical disease and the mental health problems that may be associated. Different studies show a higher prevalence of depression or anxiety issues in diabetes patients than in the general population, which is why diabetes can be considered one of the chronic diseases in which psychological care is crucial to maintain quality of life. The objective of this review is to examine the published articles that relate the bidirectional associations between objective and subjective measures of anxiety, depressive symptomatology, stress, sleep quality, and salivary biomarkers in patients with diabetes. For this, a search was carried out in the electronic databases PubMed, Cochrane, and SCOPUS using the keywords "diabetes", "saliva", "sleep", "anxiety", "depression", and "stress" for works published up until May 2022 and limited to the English and Spanish languages. The sample comprised 14 articles, 5 of which analysed the associations between depressive symptomatology and salivary biomarkers in people with diabetes. Among the salivary biomarkers most frequently used to evaluate psychological alterations in persons with diabetes are cortisol and melatonin. Thus, significant changes in the levels of these biomarkers were observed in most studies. Four out of five studies reported a statistically significant relationship between increased salivary cortisol in the evening/midnight or the cortisol awakening response and depressive symptoms. In contrast, lower cortisol levels upon waking in the morning were observed when there was no depression or anxiety. Regarding the association between salivary cortisol values and sleep quality in patients with diabetes, lower morning cortisol values related to prolonged nighttime sleep were common in the analysed studies. Low melatonin concentrations showed a negative correlation with sleep quality. As it is an easy-to-apply and non-invasive method, the measurement of salivary biomarkers can be very useful for predicting psychological alterations in patients with diabetes. Further scientific studies are required to determine the sensitivity of these biological substances acting as biomarkers for detecting sleep disorders and psychological alterations.

Impairment of Mitochondrial Respiration in Metabolic Diseases: An Overview

Mitochondrial dysfunction has emerged as a central pathomechanism in the setting of obesity and diabetes mellitus, linking these intertwined pathologies that share insulin resistance as a common denominator. High-resolution respirometry (HRR) is a state-of-the-art research method currently used to study mitochondrial respiration and its impairment in health and disease. Tissue samples, cells or isolated mitochondria are exposed to various substrate-uncoupler-inhibitor-titration protocols, which allows the measurement and calculation of several parameters of mitochondrial respiration. In this review, we discuss the alterations of mitochondrial bioenergetics in the main dysfunctional organs that contribute to the development of the obese and diabetic phenotypes in both animal models and human subjects. Herein we review data regarding the impairment of oxidative phosphorylation as integrated mitochondrial function assessed by means of HRR. We acknowledge the critical role of this method in determining the alterations in oxidative phosphorylation occurring in the early stages of metabolic pathologies. We conclude that there is a mutual two-way relationship between mitochondrial dysfunction and insulin insensitivity that characterizes these diseases.

Practical Applicability of the ISARIC-4C Score on Severity and Mortality due to SARS-CoV-2 Infection in Patients with Type 2 Diabetes

Background and objectives. There is a bidirectional relationship between SARS-CoV-2 infection and diabetes mellitus (DM), as people with DM are more vulnerable, and SARS-CoV-2 infections worsen the prognosis in these patients. The main purpose of the study was to evaluate the application validity of the ISARIC-4C score in patients confirmed with SARS-CoV-2 infection. Materials and Methods. The study included 159 patients previously known to have type 2 DM and confirmed positive for SARS-CoV-2 infection. We analyzed the concordance between the clinical evaluation of the patients and the ISARIC-4C score. Results. The mortality rate in hospitalized patients was 25.15%. The mortality risk was higher for ISARIC-4C values >14 than in the opposite group (63.93% vs. 31.24%; p < 0.001). The area under the curve (AUC) of the mortality score was 0.875 (95% CI: 0.820−0.930; p < 0.001), correctly classifying 77.36% of the cohort. A cut-off value of >14 had a sensitivity of 87.80% (95% CI: 87.66−87.93), specificity 73.72% (95% CI: 73.48−73.96), positive predictive value 53.73% (95% CI: 53.41−54.04), and negative predictive value 94.56% (95% CI: 94.5−94.62). The Cox regression model showed that the length of hospitalization (LH) was significantly influenced by body mass index, lung impairment, and aspartate aminotransferase, increasing the hazards, while lower HbA1c and lower SatO2 significantly decreased the hazards. Conclusions. ISARIC-4C score estimates the likelihood of clinical deterioration and the mortality risk in patients hospitalized with type 2 DM and positive for SARS-CoV-2, being useful in assessing the prognosis from the onset, as well as in developing therapeutic strategies.