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  • Author: Simona Cernea x
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Complex hemodynamic, neurohormonal and biochemical changes occur in heart failure and chronic kidney disease, and hyperglycemia/diabetes further accentuate the multifactorial pathogenetic mechanisms. The acknowledgement of concomitant heart and kidney dysfunction in patients with type 2 diabetes has major clinical implications with regards to prognosis, as they significantly increase the risk of mortality, and to therapeutical strategy of both conditions, as well as of hyperglycemia. A comprehensive interdisciplinary approach is needed in these cases in order to improve the outcomes.


Our current clinical doctrine and practice is based upon a classification of diabetes which relies mainly on some clinical manifestations/criteria, rather than markers of the pathophysiological mechanisms of the disease. An improved classification based on such biological markers (i.e. of insulin resistance, beta cell dysfunction, autoimmunity) may assist in clinical decision and may offer the opportunity of an optimized therapeutic strategy. We address here some important questions that have not yet been clarified, e.g. which markers/indicators best define the main pathogenic mechanisms of the disease in a patient with diabetes and what threshold values are relevant for this purpose.


Background/Aim: In patients with type 2 diabetes (T2D), malnutrition has been recognized as a serious health problem mainly in hospitalized conditions, but there is little data regarding malnutrition outside hospital settings. The aim of this study was to evaluate the risk of malnutrition and associated metabolic changes in ambulatory patients with T2D.

Material and methods: This analysis used data collected from 161 patients with T2D enrolled in a larger cross-sectional study. Several anthropometric and metabolic parameters were obtained. Nutritional status was evaluated using the Controlling Nutritional Status (CONUT) score. Correlations between nutritional status and metabolic and anthropometric parameters of interest were examined.

Results: Of all T2D patients, 29.8% had mild malnutrition (CONUT score 2–4). These patients presented lower triglyceride (124.8 ± 42.3 mg/dL vs. 165.7 ± 84.3 mg/dL, p <0.01) and LDL cholesterol concentrations (62.7 ± 20.0 mg/dL vs. 104.9 ± 30.6 mg/dL, p <0.0001), higher leptin levels (10.2 [1.6–44.9] ng/mL vs. 7.3 [0.9–49.8] ng/mL, p <0.05) and free leptin index (0.65 [0.04–2.88] vs. 0.36 [0.01–3.98], p <0.05) compared with patients with normal nutritional status. They also had higher total body adiposity. In patients with obesity, triglycerides levels were lower in those with mild malnutrition vs. those without malnutrition (mean difference: 27.26 mg/dL, p <0.05). Serum C peptide/leptin ratio was higher in T2D patients with normal nutritional status without obesity, the differences being significant vs. the two groups with obesity (with or without malnutrition, 0.71 ± 0.53, 0.42 ± 0.33, and 0.49 ± 0.68, respectively). HOMA-IR was lower in patients with normal nutritional status without obesity vs. those with obesity (mean difference: −0.7126, p <0.05), while in patients with mild malnutrition, HOMA-IR values were higher, but no differences were noted between the groups with or without obesity.

Conclusion: In patients with T2D, malnutrition associated with lower triglycerides concentrations, even in the presence of obesity. Malnutrition and/or obesity associated with higher HOMA-IR, serum leptin levels and lower C peptide/leptin ratio.


Aim: The aim of the study was to evaluate the correlation between renal function and heart function/echocardiographic parameters and epicardial adipose tissue thickness (EATT), respectively.

Material and methods: Fifty patients with type 2 diabetes (T2D) were included in this study. Several laboratory parameters were obtained (HbA1c, fasting blood glucose, LDL-cholesterol, creatinine) and eGFR was calculated. Anthropometric measurements were performed (weight, waist and hip circumferences, 4 skinfolds, based on which % body fat was calculated). Patients underwent echocardiographic assessment to evaluate structural and functional parameters, including EATT. Left ventricular mass (LVM) was calculated and the geometric changes of the left ventricle were evaluated.

Results: Forty-six per cent of the patients had a LV ejection fraction (EF) <55% and 34% had diastolic dysfunction. There were no significant differences between the three eGFR groups with regards to metabolic parameters, but LVEF was lower (53.0 ± 0.8%, 54.4 ± 2.4%, and 55.2 ± 1.5%, respectively) and EATT was higher (11.0 ± 1.0 mm, 8.58 ± 2.2 mm, and 7.63 ± 2.6 mm, respectively) with a lower eGFR (p = 0.04). More patients with eGFR <90 mL/min/1.73 m2 had cardiac hypertrophy compared with those with eGFR ≥90 mL/min/1.73 m2 (p = 0.04). EATT correlated positively with several anthropometric parameters, e.g. weight (r = 0.309, 95% CI: 0.022 to 0.549, p = 0.03), BMI (r = 0.398, 95% CI: 0.123 to 0.616, p = 0.004), and negatively with LVEF (r = −0.496, 95% CI: −0.687 to −0.242, p = 0.0003) and eGFR (r = −0.293, 95% CI: −0.531 to −0.013, p = 0.04). In patients with LVEF <55% vs. ≥55%, the EATT was significantly higher (9.5 ± 1.99 mm vs. 7.33 ± 2.37 mm, p = 0.013).

Conclusion: In patients with T2D decreased renal function was associated with lower LVEF and higher EATT. EATT was also higher in patients with reduced LVEF.


Background. The study aimed to evaluate the correlations of cognitive function with metabolic, nutritional, hormonal and immunologic parameters in patients with type 2 diabetes (T2D), in order to identify markers of cognitive impairment.

Material and methods. This cross-sectional study included 216 T2D patients and 23 healthy individuals (HC). The cognitive status was evaluated by the MoCA test. From HC and 145 T2D patients several parameters were also determined: C-peptide, vitamin B12, high-sensitivity CRP (by chemiluminescent immunometric assay), HbA1c, lipids, cortisol, TSH, Mg (by a Cobas 6000 analyzer), glucose (by glucose-oxidase method) and leptin and adiponectin (by ELISA method). Statistical significance was set at p < 0.05.

Results. There was a significant difference in the MoCA scores between HC and T2D groups (26.0(17.0-29.0) vs. 23.0(13.0- 31.0) points; p: 0.004). T2D patients with cognitive dysfunction were significantly older and less formally educated (p < 0.0001). Age negatively correlated with MoCA scores (-0.31; 95%CI:-0.42,-0.18; p < 0.0001). T2D patients had significantly lower visuospatial/executive (4.0(0.0-5.0) vs. 5.0(2.0-5.0) points; p: 0.04) and delayed recall scores (2.0(0.0- 5.0) vs. 3.0(1.0-5.0) points; p: 0.03) and lower serum Mg concentrations (0.81(0.12-0.99) vs. 0.92(0.41-1.35) mmol/l, p < 0.0001). Serum Mg levels positively correlated with MoCA scores (0.24, 95%CI: 0.07, 0.39; p: 0.003) and with visuospatial/ executive (0.30; 95%CI: 0.14, 0.45; p: 0.0002) and naming functions (0.18; 95%CI: 0.01, 0.34; p: 0.02).

Conclusions. Patients with T2D had significant cognitive impairment, with decrements in the visuospatial/executive and delayed recall domains. Younger age and higher education correlated with better cognitive function. Serum Mg levels correlated positively with overall cognitive function and with visuospatial/executive and naming domains.


Aim: We evaluated the association between anthropometric parameters and markers of insulin and leptin secretion/resistance in patients with type 2 diabetes mellitus (T2DM).

Material and methods: This post-hoc data analysis from a cross-sectional study included 176 T2DM patients. Laboratory tests (serum leptin, soluble form of leptin receptor (sObR), C peptide, glycemic and lipid parameters) and anthropometric parameters were obtained, adiposity indexes (including body adiposity index (BAI), visceral adiposity index (VAI)), indicators of insulin resistance, β-cell function, and leptin resistance (Free Leptin Index, FLI) were calculated.

Results: The body mass index (BMI), diabetes duration, VAI and leptin correlated independently with HOMA-IR, while BMI, diabetes duration and HbA1c with HOMA-B. The total body fat mass (TBFM), C peptide, diabetes duration, BMI and BAI correlated with leptin concentrations, while the first three with FLI. VAI was an indicator of insulin resistance (β=0.166, p=0.003), while BAI of leptin secretion (β=0.260, p=0.010). TBFM strongly associated with leptin resistance and secretion (β=0.037, r=0.688, p<0.0001, and β=0.521, r=0.667, p<0.0001), and BMI correlated weakly with insulin secretion and resistance. While insulin and leptin secretion increased progressively with BMI, leptin and insulin resistance became significant only in case of obesity. The sObR was significantly associated with C peptide concentrations (β=-0.032; p=0.044), but not with HOMA-B or -IR. A strong positive correlation between the C peptide/leptin ratio and non-fat mass /TBFM ratio was noted (r=0.62 [0.52, 0.71], p<0.0001).

Conclusions: Parameters of peripheral adiposity correlated better with markers of leptin system, and those of visceral adiposity with markers of insulin secretion/resistance. The sObR correlated independently and negatively with C peptide.


Objectives: The primary aim of this study was to assess residual beta cell function at diagnosis of type 2 diabetes and identify accessible laboratory markers that best estimate it. The secondary objective was to evaluate the change in beta cell function 6 months after starting different therapeutical regimens. Materials and methods: Forty seven subjects were included in the study and each performed a 75-g oral glucose tolerance test (OGTT) at baseline and after 6 months. Metabolic and immunologic parameters were determined from fasting samples. According to the degree of metabolic decompensation, specific therapy was started: metformin, metformin plus gliclazide or insulin therapy (with/out metformin). Early and total beta cell function was evaluated by the disposition index (DI) calculated for 30 minutes and 120 minutes, respectively. Results: At diagnosis, fasting blood glucose (BG) and HbA1c varied largely (129-521 mg/dl and 5.5-14%, respectively). The DI30 and DI120 decreased with more severe glycemic decompensation. For both DI30 and DI120 significant negative correlations were found for glycemic markers (HbA1c, 2-hour BG and maximal BG amplitude) and positive correlation for 2- hour C peptide (p<0.0001 for all). HbA1c value of 7% discriminated an important decrease of DI30 and DI120. Insulin and combined therapy significantly improved DI120 at 6 months (p: 0.0062 and 0.01, respectively), while DI30 was improved only with insulin therapy (p: 0.0326). Conclusions: Beta cell function at onset correlated with HbA1c, 2-hour BG and C peptide during OGTT. Thus OGTT and HbA1c are pivotal for evaluation of beta cell function. Insulin therapy improved early and total insulin secretion at 6 months.


Objective: The aim of this study was to assess the prevalence of depression, anxiety and cognitive impairment in patients with type 2 diabetes (T2D).

Material and methods: We conducted a cross-sectional study in patients with T2D. Depression and anxiety were assessed by questionnaires (PHQ-9, CES-D and GAD-7 respectively), cognitive function by the MoCA test. Additionally, 503 patients’ clinic charts were separately analyzed in order to compare the data recorded in the charts with that resulted from the active assessment.

Results: In the screening study 216 subjects with T2D were included (62.2 ± 7.8 years old). 34.3% of them had depression and 7.4% presented major depression. 44.9% of patients with T2D had anxiety (9.2% major anxiety) and this was highly correlated with depression (OR: 21.139, 95%CI: 9.767-45.751; p<0.0001). Women had significantly higher prevalence of depression and anxiety compared to men (42.1% vs. 21.7%; p: 0.0021 and 51.1% vs. 34.9%; p: 0.02), but severe depression was similar between genders (9.0% vs. 4.8%; p: 0.29). Significantly more patients had depression and anxiety than recorded in their charts (34.3% vs. 13.9% and 44.9% vs. 9.3%, respectively; p<0.0001 for both). 69.0% of T2D patients had mild, 6.0% had moderate and none had severe cognitive dysfunction, respectively. Significantly more patients with depression and anxiety had mild and moderate cognitive impairment (p: 0.03 and p: 0.04, respectively).

Conclusions: Patients with T2D had a high prevalence of comorbid depression, anxiety and cognitive impairment. Depression and anxiety were significantly more frequent in women. These conditions were under-evaluated and/or under-reported.


Aim: This study evaluated the correlations between metabolic parameters and reproductive health data in women with type 2 diabetes mellitus (T2DM).

Material and methods: In this observational retrospective study, data from the medical records of 324 adult women with T2DM attending their regular diabetes check-ups were collected and analyzed (i.e., anthropometric parameters at first outpatient visit and yearly thereafter, first recorded HbA1c and all HbA1c for the entire follow-up duration, as well as obstetrical/gynecological information).

Results: Age at the diagnosis of T2DM correlated positively with age at menarche (r = 0.21, [95% CI: 0.09, 0.31], p = 0.0002) and age at menopause (r = 0.18 [95% CI: 0.07, 0.29], p <0.01). Age at menarche correlated negatively with mean weight (r = –0.21 [95% CI: –0.31, –0.10], p: 0.0002) and mean BMI (–0.22 [–0.32, –0.11], p <0.0001) over the follow-up time. Patients with shorter time difference between age at menarche and age at onset of T2DM (≤45 years) had higher mean weight (83.8 ± 14.5 kg vs. 78.4 ± 16.0 kg, p = 0.0001), BMI (33.2 ± 5.6 kg/m2 vs. 31.8 ± 5.7 kg/m2, p <0.05), and HbA1c over time (6.9 ± 0.8% vs. 6.6 ± 0.9%, p <0.0001). Women with T2DM with earlier menarche (<12 years old), with irregular menses during their reproductive life, and ≥3 pregnancies had higher overall BMI, but mean HbA1c were not significantly different. However, women diagnosed with T2DM before menopause had a higher mean HbA1c over time (7.1 ± 0.8% vs. 6.7 ± 0.9%, p <0.01).

Conclusion: The BMI correlated with several indicators of reproductive health (earlier menarche, irregular menses, and higher number of pregnancies), while earlier onset of T2DM influenced metabolic control in women with T2DM.