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IntroductionCOVID -19 pandemic has threatened the optimal achievement on type-2 diabetes mellitus (T2DM) target in primary health care (PHC), due to our priority in COVID-19 management, limited access of patients to PHC and their lifestyle changes as the impact of social restrictions. Therefore, the empowerment of capability of patients on diabetes self-care is required through optimal education and support. The use of telehealth in T2DM management has benefits on improving outcomes of patients. We aim to assess the role of telehealth diabetes self-management education (DSME) versus hybrid (telehealth and face-to-face method) diabetes self-management education and support (DSMES) to improve T2DM outcomes in PHC during COVID-19 pandemic. Methods and analysisThis study is an open label randomized-controlled trial that will be conducted in 10 PHCs in Jakarta, Indonesia, involving patients with T2DM. Subjects are classified into 2 groups: DSME group and DSMES group. Intervention will be given every 2 weeks. DSME group will receive 1 educational video every 2 weeks discussing topics about diabetes self-management, while DSMES group will receive 1 educational video and undergo 1 coaching session every 2 weeks. All interventions will be conducted by trained health workers of PHC, who are physicians, nurses, and nutritionists. Our primary outcome is the change of HbA1C level and our secondary outcomes are the changes of nutritional intake, physical activity, quality of life, anthropometric parameter, fasting blood glucose, lipid profile, inflammatory markers, and progression of diabetes complications at 3 and 6 months after intervention compare to the baseline. Ethics and disseminationThis study protocol has been approved by the Health Research Ethics Committee University of Indonesia. Subjects agree to participate will be given written informed consent prior to data collection. Findings from this study will be published in peer-reviewed journals and presented at conferences. Trial Registrationhttp://www.clinicalstrials.gov with identifier number NCT05090488. SummaryO_ST_ABSStrengths and limitations of the studyC_ST_ABSO_LIThis study evaluates the role of hybrid DSMES, which is useful in areas with limited access or on lockdowns. C_LIO_LIThis study will evaluates the implementation of hybrid DSMES, its benefits, difficulties, and obstacles. C_LIO_LIWe uses validated questionnaire instruments and routinely collected clinical data. C_LIO_LIBecause all of our interventions will be conducted by PHCs health workers, our results depend on the ability and adherence of PHCs health workers. C_LI
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AimTo determine association between diabetes in confirmed cases of COVID-19 and intensive care admission and in-hospital mortality, evaluate several laboratory parameters as mortality predictor, and develop predictors of in-hospital mortality among diabetics with COVID-19. MethodsThis retrospective cohort recruited all cases of COVID-19 hospitalized in Fatmawati General Hospital during March to October 2020. Inclusion criteria was RT-PCR confirmed cases of COVID-19 who aged 18 years and older while exclusion criteria were incomplete medical record or cannot be found and pregnant women. ResultsWe enrolled 506 participants to this study with median age of 51 years (IQR:22), female (56.32%), and diabetes (28.46%). Diabetes increased intensive care admission (adjusted OR:6.07;95%CI:3.52-10,43) and in-hospital mortality (adjusted OR:50;95%CI:1.61-3.89). In predicting in-hospital mortality, ferritin and lactate dehydrogenase offered an acceptable discrimination, AUC:0.71 (95%CI: 0.62-0.79) and AUC:0.70 (95%CI: 0.61-0.78), respectively. The optimal cut-off of predicting mortality for ferritin was 786 g/mL and for LDH was 514.94 u/L. Factors include age above 70 years old, RBGs level on admission above 250 mg/dL or below 140 mg/dL, ferritin level above 786 ng/mL, and presence of ARDS increased the odds of mortality among individuals with diabetes. ConclusionsDiabetes increases risk of intensive care admission and in hospital mortality in COVID-19. Multivariate analysis showed that older age, RBG on admission, high ferritin level, presence of ARDS increased the odds of mortality among individuals with diabetes.
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Objective@#The objective of our study was to determine the genotype frequencies of CYP2C19*2 and *3 gene polymorphisms among Javanese farmers exposed to chlorpyrifos (CPF) in Central Java, Indonesia. @*Methods@#This cross-sectional study was conducted from July to October 2020 in Central Java, Indonesia, involving 151 vegetable farmers aged 18-65 years who used CPF for at least one year. CYP2C19*2 and *3 gene polymorphisms were analyzed using PCR-RFLP. Direct calculations were applied to calculate allele and genotype frequencies. The difference in genotype frequencies among the sex and cumulative exposure level (CEL) group was performed using the Chi-square test. In contrast, the proportion difference of allele frequencies was analyzed using Z-test. @*Results@#The frequency of CYP2C19 genotypes *1/*1, *1/*3, *1/*2, and *2/*2 were 64 %, 7 %, 23 % and 6 %. We observed no significant difference in the genotype distribution according to sex group and CEL group. @*Conclusion@#In summary, the prevalence of toxicologically relevant CYP2C19 polymorphisms was determined in the Javanese agricultural population. The CYP2C19 genotype may be helpful as an essential biomarker of genetic susceptibility towards CPF exposure. Nevertheless, further studies to confirm the role of CYP2C19 in this context are still needed.
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Citocromo P-450 CYP2C19 , PraguicidasRESUMO
Objectives@#One of the most widely used pesticides today is chlorpyrifos (CPF). Cytochrome P450 (CYP)2B6, the most prominent catalyst in CPF bioactivation, is highly polymorphic. The objective of our study was to evaluate the role of CYP2B6*6, which contains both 516G>T and 785A>G polymorphisms, in CPF toxicity, as represented by the concentration of 3,5,6-trichloro-2-pyridinol (TCPy), among vegetable farmers in Central Java, Indonesia, where CPF has been commonly used. @*Methods@#A cross-sectional study was conducted among 132 vegetable farmers. Individual socio-demographic and occupational characteristics, as determinants of TCPy levels, were obtained using a structured interviewer-administered questionnaire and subsequently used to estimate the cumulative exposure level (CEL). TCPy levels were detected with liquid chromatography-mass spectrometry. CYP2B6*6 gene polymorphisms were analyzed using a TaqMan® SNP Genotyping Assay and Sanger sequencing. Linear regression analysis was performed to analyze the association between TCPy, as a biomarker of CPF exposure, and its determinants. @*Results@#The prevalence of CYP2B6*6 polymorphisms was 31% for *1/*1, 51% for *1/*6, and 18% for *6/*6. TCPy concentrations were higher among participants with CYP2B6*1/*1 than among those with *1/*6 or *6/*6 genotypes. CYP2B6*6 gene polymorphisms, smoking, CEL, body mass index, and spraying time were retained in the final linear regression model as determinants of TCPy. @*Conclusions@#The results suggest that CYP2B6*6 gene polymorphisms may play an important role in influencing susceptibility to CPF exposure. CYP2B6*6 gene polymorphisms together with CEL, smoking habits, body mass index, and spraying time were the determinants of urinary TCPy concentrations, as a biomarker of CPF toxicity.
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Objective@#This study aims to identify predictors of 72-hour mortality in patients with diabetic ketoacidosis (DKA).@*Methodology@#In this retrospective cohort study, data were obtained from medical records of adult patients with DKA in Cipto Mangunkusumo General Hospital from January 2011 to June 2017. Associations of predictors (age, type of diabetes, history of DKA, comorbidities, level of consciousness, renal function, bicarbonate, potassium, lactate, betahydroxybutyrate levels, and anion gap status) and 72-hour mortality were analyzed. The mortality prediction model was formulated by dividing the coefficient B by the standard error for all variables with p<0.05 in the multivariate analysis.@*Results@#Eighty-six of 301 patients did not survive 72 hours after hospital admission. Comorbidities (HR 2.407; 95% CI 1.181–4.907), level of consciousness (HR 10.345; 95% CI 4.860–22.019), history of DKA (HR 2.126; 95% CI 1.308–3.457), and lactate level (HR 5.585; 95% CI 2.966–10.519) were significant predictors from multivariate analysis and were submitted to the prediction model. The prediction model had good performance. Patients with total score less than 3 points were at 15.41 % risk of mortality, 3 – 4 points were 78.01% and 5 – 6 points were 98.22% risk of mortality. @*Conclusion@#The 72-hour mortality rate in Cipto Mangunkusumo General Hospital was 28.57%. The mortality prediction model had a good performance and consisted of comorbidities, history of DKA, level of consciousness and lactate level.
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Mortalidade , Cetoacidose DiabéticaRESUMO
@#Untreated thyroid dysfunction during pregnancy increases morbidity in the mother and fetus. Anti-thyroid medication is the first-line therapy for hyperthyroidism during pregnancy. The diagnosis of thyroid dysfunction in pregnancy is complicated because of seemingly insignificant and non-specific symptoms which overlap with normal changes during pregnancy. Early detection and management should be done to prevent maternal and fetal complications.
