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1.
Rev. invest. clín ; 74(4): 193-201, Jul.-Aug. 2022. tab, graf
Article in English | LILACS-Express | LILACS | ID: biblio-1409581

ABSTRACT

ABSTRACT Background: Insulin resistance is key in the pathogenesis of the metabolic syndrome and cardiovascular disease. Objective: We aimed to identify glucose and insulin patterns after a 5-h oral glucose tolerance test (OGTT) in individuals without diabetes and to explore cardiometabolic risk factors, beta-cell function, and insulin sensitivity in each pattern. Methods: We analyzed the 5-h OGTT in a tertiary healthcare center. We identified classes using latent class trajectory analysis and evaluated their association with cardiometabolic risk factors, beta-cell function, and insulin sensitivity surrogates by multinomial logistic regression analysis. Results: We included 1088 5-h OGTT performed between 2013 and 2020 and identified four classes. Class one was associated with normal insulin sensitivity and secretion. Class two showed hyperglycemia, dysinsulinism, and a high-risk cardiometabolic profile (obesity, hypertriglyceridemia, and low high-density lipoprotein [HDL] cholesterol). Class three included older individuals, a higher proportion of males, and a greater prevalence of hypertension, hyperglycemia, hyperinsulinemia, and postprandial hypoglycemia. Finally, class four showed hyperglycemia, dysinsulinism, and hyperinsulinemia; this class had the worst cardiometabolic profile (a high proportion of males, greater age, hypertension, obesity, hypertriglyceridemia, and low HDL cholesterol, p < 0.001 vs. other classes). Conclusions: The latent class analysis approach allows the identification of groups with an adverse cardiometabolic risk factor, and who might benefit from frequent follow-ups and timely multidisciplinary interventions.

2.
Rev Invest Clin ; 74(4): 193-201, 2022 07 01.
Article in English | MEDLINE | ID: mdl-35797731

ABSTRACT

Background: Insulin resistance is key in the pathogenesis of the metabolic syndrome and cardiovascular disease. Objective: We aimed to identify glucose and insulin patterns after a 5-h oral glucose tolerance test (OGTT) in individuals without diabetes and to explore cardiometabolic risk factors, beta-cell function, and insulin sensitivity in each pattern. Methods: We analyzed the 5-h OGTT in a tertiary healthcare center. We identified classes using latent class trajectory analysis and evaluated their association with cardiometabolic risk factors, beta-cell function, and insulin sensitivity surrogates by multinomial logistic regression analysis. Results: We included 1088 5-h OGTT performed between 2013 and 2020 and identified four classes. Class one was associated with normal insulin sensitivity and secretion. Class two showed hyperglycemia, dysinsulinism, and a high-risk cardiometabolic profile (obesity, hypertriglyceridemia, and low high-density lipoprotein [HDL] cholesterol). Class three included older individuals, a higher proportion of males, and a greater prevalence of hypertension, hyperglycemia, hyperinsulinemia, and postprandial hypoglycemia. Finally, class four showed hyperglycemia, dysinsulinism, and hyperinsulinemia; this class had the worst cardiometabolic profile (a high proportion of males, greater age, hypertension, obesity, hypertriglyceridemia, and low HDL cholesterol, p < 0.001 vs. other classes). Conclusions: The latent class analysis approach allows the identification of groups with an adverse cardiometabolic risk factor, and who might benefit from frequent follow-ups and timely multidisciplinary interventions.


Subject(s)
Cardiovascular Diseases , Diabetes Mellitus, Type 2 , Hyperglycemia , Hypertension , Hypertriglyceridemia , Insulin Resistance , Blood Glucose/metabolism , Cardiometabolic Risk Factors , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/etiology , Diabetes Mellitus, Type 2/complications , Glucose , Glucose Tolerance Test , Humans , Hyperglycemia/complications , Hyperglycemia/epidemiology , Hypertension/complications , Hypertriglyceridemia/complications , Insulin/metabolism , Insulin Resistance/physiology , Male , Obesity/complications , Risk Factors
3.
Parkinsonism Relat Disord ; 44: 147-150, 2017 Nov.
Article in English | MEDLINE | ID: mdl-28941829

ABSTRACT

BACKGROUND: Tremor is a known side-effect of anticonvulsants, particularly of valproate. However, there is a dearth of information regarding detailed clinical features and functional impact of valproate-induced tremor. METHODS: We studied a cohort of patients treated with anticonvulsants for neurological disorders, through blinded evaluations using the Clinical Rating Scale for Tremor (CRST); we compared the frequency, severity and functional impact of drug-induced tremor between patients treated with valproate and those treated with other anticonvulsants. RESULTS: From a cohort of 218 consecutive patients, 171 were fully evaluated; 118 patients were taking valproate alone or combined with other anticonvulsants and 53 patients were taking other anticonvulsants. Mean age (±SD) at evaluation of the cohort was 32 ± 13 years, females represented 55.6% of cases. Tremor was more frequently observed in patients taking valproate particularly postural upper limb tremor: 49% vs. 15% (right-side) (P < 0.001) and 48.3% vs. 13.2% (left-side), (P < 0.001); had a higher total CRST score: 12.14 vs. 3.06 (P < 0.001), and required more frequently treatment for drug-induced tremor: 23.7% vs. 5.6% (P=0.005) compared with patients taking other anticonvulsants. Among 118 patients taking valproate, women had a higher total CRST score compared with men: 14.54 ± 14.9 vs. 9.56 ± 9.55 (P=0.034). A weak correlation between the total CRST score, dose per Kg of valproate and serum levels of valproate were observed. CONCLUSIONS: Tremor is frequently observed in patients taking valproate and is severe enough to require treatment in about 24% of cases.


Subject(s)
Anticonvulsants/adverse effects , Tremor/chemically induced , Valproic Acid/adverse effects , Adult , Aged , Cohort Studies , Female , Humans , Male , Middle Aged , Nervous System Diseases/drug therapy , Tremor/epidemiology , Young Adult
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