| Background:With the rapid development of the global economy and acceleration of the industrialization process,the change of lifestyle and the acceleration of the aging process,diabetes is rapidly rising,and become the third important chronic non communicable diseases that seriously threatening people's health.Diabetes not only brings physical and mental damage to the sick individual,but also shortens the life span,which brings heavy financial burden to the individual and the country.Generally,over the disease course of type 2 diabetes,individuals progress from normal glucose tolerance(NGT)to pre-diabetes[isolated impaired fasting glucose(1FG),isolated impaired glucose tolerance(IGT),or combined status of IFG and IGT(IFG-IGT)]and finally develop to overt diabetes.Pre-diabetes is the intermediate state between normal glucose metabolism and diabetes.A number of epidemiological data show that the prevalence of pre diabetes is as high as 15.5%-50.1%.And there is increasing evidence that the risk of macro vascular complications has increased dramatically in Pre diabetes.Pre diabetes is not only a risk factor for diabetes,but also a risk factor for macrovascular complications.The prevalence of diabetes in China,the high proportion of undiagnosed patients and the high risk population of diabetes suggest that we still have more work to do in the prevention of diabetes.Because of China's large population,it is not feasible by screening blood glucose to find the pre-diabetes or other high-risk groups in the non-diabetic population,Thusit is important to find risk factors associating with the development of pre diabetes or diabetesin non-diabetic individuals,and is of great significance to save medical resources.Longitudinal investigations of predictors for glycemic outcomes have been conducted in various populations of non-diabetic subjects.However,previous studies focused on either the identification of risk factors for the deterioration from NGT or pre-diabetes to overt diabetes,or that associated with the reversion from pre-diabetes to NGT.Andthere is a lack of study that investigating the risk factors for the two opposite outcomes in the same population.Indeed,such an approach can help to understandhow the spectrum of risk factors varies at the dynamic stages of type 2 diabetes,and thus provide data that is more informative for directing more precise preventive strategies for diabetes.Our study observed the changes in blood glucose metabolism of non diabetes population through a 3 years of follow-up,and calculate the incidence of pre-diabetes or diabetes,and further analysis of the risk factors in the process of glucose transformation.Indeed,such an approach can help to understandhow the spectrum of risk factors varies at the dynamic stages of type 2 diabetes,and thus provide data that is more informative for directing more precise preventive strategies for diabetes.Objective:1.To access the incidence of pre-diabetes or diabetes of non-diabetes.2.To explore risk factors for the deterioration from NGT or pre-diabetes to overt diabetes.2.To explore factors related to the reversion from pre-diabetes to NGT.Methods:1.Study participants:The REACTION study was a non-interventional cohort study which enrolled 259.657 Chinese people(?40 years of age)from 25 communities in mainland China between 2011 and 2012 with follow-ups planned at 3,5 and 10 years.Data of one of the 25 communities,in Ningyang County,Shandong Province,were selected for this study.Overall,7,068 subjects participated in the baseline survey.Fasting blood samples,oral glucose tolerance test(OGTT)questionnaire and physical examination was conducted for each subject.Individuals with diabetes,either self-reported previous diagnosis or detected by the standardized oral glucose tolerance test(OGTT)performed at baseline survey;missing vital data,such as age,gender,or results of OGTT;individuals with malignant tumors,serious liver(either alanine aminotransferase or aspartate aminotransferase higher than 100 U/L)or renal dysfunction(creatinine higher than 105 ?mol/L and a glomerular filtration rate below 60 ml/min)(n=78);and individuals receiving medications in the three months prior to the baseline survey that affect lipid metabolism or blood pressure(n=527),including statins,fibrates,angiotensin-converting enzyme inhibitors,angiotensin receptor blockers,?-adrenoceptor blockers,calcium channel blockers,or diuretics.Ultimately.5,213 individuals with NGT or pre-diabetes were eligible for the current study.The study protocol conformed to the 1975 Declaration of Helsinki,and was approved by the Committee on Human Research at Rui Jin Hospital,Shanghai Jiao Tong University School of Medicine.All study participants provided written informed consent.2.Data collection:The 3-year follow-up visit was conducted in 2014-2015.Study measurements included detailed questionnaires,clinical and biochemical measurementswere collected both at Baseline and at the 3-year follow-up visit.General information was recorded through questionnaires,including age,gender,family history,and drug use.Height.weight,waist circumference,hip circumference and blood pressure was recorded by physical examination.All subjects underwent fasting blood test and glucose tolerance test.Glucose,blood lipid profiles(TC,TG,LDL-C,and HDL-C),liver function,and renal function were measured by Abbott ARCHITECT ci16200 system,and the intra-assay and inter-assay coefficients variation were always below 5%for all of the above parameters.3.Statistical analysis:Outcome rates were estimated by dividing the number of events by the number of persons at risk.The incidence of diabetes and pre-diabetes per 1,000 person-years with 95%CI were calculated using the number of persons developing these conditions at 3-year follow-up as the numerator and the total person-years as the denominator.Person-years were calculated from the date of the baseline survey until the diabetes or pre-diabetes occurred or until the 3-year follow-up survey,whichever came first.Age-and sex-standardized estimates of incidence were calculated using the direct method,taking the 2010 census of the Chinese rural population aged 40-79 years as the standard.Quantitative characteristics of the cohort were expressed as mean±standard deviation(SD)or median(inter-quartile range)according to their distributions,which were judged by histogram.Categorical data were presented as number(percentage).One-way ANOVA or the Mann-Whitney U-test were used to test differences between continuous variables among groups.Differences in categorical data were evaluated by Chi-squared test.Multivariate logistic regression analysis was used to evaluate the association between baseline clinical characteristics and conversions in glycemic status.The variables that were clinically relevant or had a P value<0.2 in univariate analysis were included as co-variables in the multivariate model.Finally,age,sex,family history of diabetes,smoking status,drinking status,physical inactive,FPG(for individuals with NGT at Baseline)or categories ofpre-diabetes(for individuals with pre-diabetes at Baseline),BMI,serum total cholesterol(TC),serum triglyceride(TG),and systolic blood pressure(SBP)entered into the model.BMI,TC,TG,and SBP were categorized according to their values,and odds ratios(ORs)were calculated as the ratio of each category to the reference group.BM1 was categorized as<24 kg/m2(normal),24-28 kg/m2(overweight)or>28 kg/m2(obese);TC was grouped as<5.18mmol/l(normal),5.18-6.19mmol/l(marginally elevated)or>6.19mmol/l(elevated);TG was grouped as<1.70mmol/l(normal),1.70-2.25mmol/l(marginally elevated)or>2.25mmol/l(elevated);SBP was categorized as<140 mmHg(normal)or ?140 mmHg(high);ORs per one SD change in baseline BMI,TC,TG,and SBP were calculated to identify the variables with the strongest effect on each path of conversion.A two-tailed value of P<0.05 was regarded as significant.All statistical analyses were performed using SPSS version 22.0 for Windows.Results:1.Conversions in glycemic status of the participantsOf the 2.833 individuals with NGT at Baseline,28.7%progressed to pre-diabetes and 6.6%developed to diabetes after a median follow-up of 3.1 years.Among the study participants with pre-diabetes at Baseline,21.1%progressed to diabetes and 33.1%reverted to NGT.A total of 314 subjects had IFG-IGT at Baseline,of whom 19.4%reverted to NGT and 30.3%developed diabetes at 3-year follow-up.Individuals with IFG at Baseline were more likely to progress to more advanced stages of dysglycemia(IFG-IGT or diabetes)(34.2%vs.23.2%;P<0.001)and less likely to revert to NGT(32.0%vs.39.4%;P=0.004),compared with subjects with IGT.2.Incidence rates of pre-diabetes and diabetesOverall,the age-and sex-standardized incidence of diabetes for the entire cohort was 42.2 per 1,000 person-years.The incidence rates of pre-diabetes and diabetes among individuals with NGT were 93.6 and 24.2per 1,000 person-years,respectively,representing a total dysglycemia conversion rate of 117.8‰.Of all individuals with pre-diabetes.theincidenceof diabetes was 70.3per 1.000 person-years.The progression rates fromlFG.IGT,and IFG-IGT to diabetes were 2.9.2.4.and 4.3 times higher,respectively,than the progression rate from NGT to diabetes.3.Analysis of risk factors of different glucose metabolism outcomesParticipants who progressed from NGT to pre-diabetes or diabetes had less metabolically favorable clinical and biochemical baseline characteristics compared with those who maintained NGT,included older age,higher BMI,waist,serum TC,TG,LDL-C,blood pressure,FPG,2hPQ and HbA1c(P<0.05 for all).Individuals with pre-diabetes at Baseline who developed diabetes by 3-year follow-up were older in age,had higher baseline SBP,FPG,2hPG,and HbA1c,compared with those who maintained pre-diabetes.Unsurprisingly,participants who regressed from pre-diabetes to NGT had lower BMI,serum TC,TG,LDL-C,FPG,2hPG,and HbA1c compared with those who maintained pre-diabetes(P<0.05 for all).4.Serum TG was the strongest metabolic risk factor for incident diabetesFor individuals with NGT at Baseline,multivariate analysis identified BMI,serum TC,serum TG,SBP,and FPG as significant risk factors of progression to pre-diabetes,while sex,serum TC,serum TG,SBP,and FPG were associated with progression to diabetes.Baseline factors significantly associated with progression from pre-diabetes to diabetes included serum TG,SBP,and the three categories of pre-diabetes.A one SD increase in serum TG was associated with a 1.27(95%CI 1.07-1.49;P = 0.002)or 1.13(95%CI 1.02-1.28;P-0.039)fold higher risk of diabetes for individuals with NGT or pre-diabetes at Baseline.Compared with subjects with normal baseline serum TG levels,elevated serum TG(>2.25 mmol/L)was associated with a I.95(95%CI 1.21-3.11;P = 0.006)and 1.36(95%CI 1.13-1.87;P = 0.024)times higher risk of developing diabetes from NGT or pre-diabetes,respectively.Among subjects with NGT at Baseline.those in the normal-high TG group were 1.96(95%CI1.50-2.55;P<0.001)and 1.73(95%CI1.06-2.84;P =0.029)times more likely to develop pre-diabetes or diabetes,respectively,compared with those in the normal-normal TG group.Remarkably,in participants with high TG at Baseline,normal TG at 3-year follow-up was associated with decreased risk of pre-diabetes or diabetes;ORs for pre-diabetes and diabetes were 2.29(95%CI1.72-3.03;P<0.001)and 3.52(95%CI2.29-5.41;P<0.001)in the high-high group compared with the normal-normal group,but decreased to 1.32(95%CI0.98-1.77;P =0.064)and 1.34(95%CI0.78-2.30;P =0.286)for the high-normal group.5.BMI was most prominent for regression from pre-diabetes to NGTLower BMI,lower serum TC,and IGT or IFG compared with IFG-IGT were the predictors for regression from pre-diabetes to NGT.BMI was identified as the strongest factor associated with reversion to NGT:a one SD increment in baseline BMI was associated with a 20%decrease(OR 0.80;95%CI 0.74-0.92;P<0.001)in rate of regression to NGT(Fig.1).Elevated serum TC was also an independent factor that impede the regression from pre-diabetes to NGT;subjects with pre-diabetes who had normal serum TC at Baseline were 2.01(95%CI 1.44-2.81;P<0.001)times more likely to revert to NGT compared with those with elevated serum TC level.Conclusion:1.IFG-IGT is found at the highest risk of developing diabetes,followed by IFG and finally,IGT.2.Serum TG is the strongest risk factor for the incidence of diabetes.3.BMI is the strongest predictor of the reversion from pre-diabetes to NGT.Background:Type 2 diabetes mellitus is a progressive disease with high morbidity and mortality.The Prevalence of type 2 diabetes is reported to be 9%among Caucasians and around 10%to 20%among Asian Indians,Arabs,Chinese,Africans,and Hispanics.As in other countries,a rising trend in the prevalence of type 2 diabetes has been observed in China.A recent comprehensive epidemiological survey of diabetes revealed that 11.6%of Chinese adults,or 114 million people,have type 2 diabetes which represents 1 in 3 patients with the condition globally.Thus,preventing and controlling the progress of diabetes in China is regarded as an important public health objective.Professional organizations in China have produced national treatment guidelines recommending that patients with type 2 diabetes should have their glycated hemoglobin(HbAlc)level maintained below<7.0%(<53mmol/mol)to minimize the risk of developing macrovascular and microvascular complications such as cardiovascular events,retinopathy,and nephropathy.In the USA,the American Diabetes Association also recommends a HbAlc goal of<7%(<53mmol/mol).Since type 2 diabetes cannot be adequately controlled with diet or oral anti-diabetic drugs in the long-term,the majority of patients eventually require insulin therapy,which is regarded as the most effective measure to improve glycemic control[6].However,a study conducted in China by Lu et al reported that even with effective insulin treatment,only 27.04%of patients reach the HbAlc target of<7.0%(<53mmol/mol).The reason for this has not been fully explained.Interest in real-world outcomes in patients with diabetes has been growing.In China,hospitals are divided into 3 grades according to their size and the range of medical services they provide,with the highest grade being grade 3 and the lowest grade 1.The higher the grade of a hospital,the more expensive its fees.In addition,clinicians receive different training at the different grades of hospitals,and those trained at higher grade hospitals are more often regarded as specialists.Consequently,patients attending hospitals of different grades often receive different medical care.To obtain a better understanding of the effectiveness of anti-diabetic treatment in routine clinical practice in China,a real-world,observational study known as the SciLin Efficacy And Safety(SEAS)study was performed.In this subgroup analysis of data from the SEAS study,the efficacy and safety of routine insulin therapy was investigated in Chinese patients with type 2 diabetes treated at two different grades of hospitals.Objective:1.To access the efficacy of insulin treatment in different grades of hospitals:Ratio of reaching HbAlc target;Change in following Parameters at 12 week(the final visit)compared to baseline:FPG,PPG(after breakfast/lunch/supper),Body weight,Insulin dosage,Blood pressure and Lipids(low-density lipoprotein C[LDL-C],high-density lipoprotein C[HDL-C];total cholesterol,and triglyceride)2.To access the safety of insulin treatment in different grades of hospitals:Occurrence rate of serious adverse drug reactions(also including severe hypoglycaemic events)?adverse drug reactions and hypoglycaemic events from baseline to final visit.3.To access the injection compliance of insulin treatment in different grades of hospital:Comparison the injection time between doctors' advice and patients' actual practice;Number and ratio of missing injections.Methods:1.Study participants:The SEAS study was a multicenter,nonrandomized,open-label,non-interventional,observational,12-week clinical trial conducted at 62 medical centers in China between August 10,2012 and January 15,2014.The original study protocol for the SEAS study was approved by the Institutional Review Boards and/or Ethics Committees of all participating hospitals.Eligible patients participated in the study voluntarily,and all provided their written informed consent to do so.All study procedures performed were in accordance with the Declaration of Helsinki and Good Clinical Practice(GCP)principles.Patients were permitted to withdraw from the study at any time.The study was registered with the ClinicalTrials.gov database(No.NCT01588639:"To Evaluate Clinical Outcome and Injection Compliance of Scilin"[SEAS]).Patients who were treated with SciLin human insulin were considered eligible for the study based on their physicians' clinical judgment.All SciLin insulins and oral anti-diabetic drugs administered in the study were purchased by the patients from their local pharmacies.All patients were diagnosed with type 2 diabetes according to the 1999 World Health Organization(WHO)criteria.Patients were excluded if they were pregnant or breast-feeding or wished to conceive within the next3 months,were receiving concomitant therapy with other types of insulin,or were participating in other clinical trials of anti-diabetic medications.A total of 2683 patients with type 2 diabetes received routine treatment with SciLin human insulin(Bayer Schering pharma,China)at the various centers.The 2683 patients enrolled in the study were divided into 2 groups based on the grade of hospital they were treated at:812 were treated at second-grade hospitals and 1871 at third-grade hospitals.2.Data collection:All procedures performed in this real-world,observational study were consistent with routine clinical practice.Patients visited their medical centers twice during the trial-at baseline and after 12 weeks of insulin therapy(final visit).Patient data collected at the baseline visit included demographic and anthropometric data(gender,age,height,weight,and body mass index[BMI]),medical history(type and duration of diabetes and insulin dosage),and clinical data(blood pressure within 4 weeks Prior to recruitment,glycated hemoglobin(HbAlc)at 4 weeks prior to recruitment,and fasting plasma glucose[FPG]and postprandial blood glucose[PBG]levels at 1 week Prior to recruitment).Data collected at the final visit after 12 weeks of insulin treatment included body weight,current insulin therapy,the most recent HbAlc measurement during the previous 4 weeks,the most recent FPG measurement during the previous week,blood pressure during the last 4 weeks,and all serious adverse events(SAEs),adverse reactions(AEs),and pregnancies.Hypoglycemia was defined as blood glucose levels<70mg/dl(3.9mmol/L).Severe Hypoglycemia was defined as confirmed symptoms consistent with a hypoglycemia,the subjects can't manage low blood sugar themselves.3.Statistical analysis:The evaluation of efficacy outcomes was undertaken in the eff-icacy analysis set included changes from baseline in HbAlc,the percentage of patients achieving a HbAlc level<7%(<53 mmol/mol),and changes in fasting blood glucose(FBG)and post-prandial blood glucose(PBG)levels,insulin dosages,body weight,systolic blood pressure(SBP),diastolic blood Pressure(DBP),and serum lipid concentrations.Safety outcomes,which were evaluated in the safety analysis set included the incidence of severe AEs(including severe hypoglycemic events),the overall incidence of hypoglycemia,and the incidences of daytime and nocturnal hypoglycemia.No method of imputation was applied for missing data.Continuous variables were presented as means and the standard deviation(SD).Categorical variables were presented as numbers(%).T-tests were performed to analyze continuous variables,and paired t-tests were performed to compare changes in efficacy parameters from baseline.Chi-square or Fisher's exact probability tests were used to compare categorical variables.Univariate analysis of covariance model was used to adjust the baseline data of PBQ DBP,LDL-C,insulirn dosage and body weight.All statistical analyses were performed using SAS(?)software,version 9.2(Cary,NC.,USA).A significance level of 0.05 was applied for all tests.Results:1.Baseline characteristics of the Patients:Clinical characteristics such as age,gender,weight,HbAlc,FBG level,SBP and oral anti-diabetic drugs at baseline were not significantly different between the groups of patients treated at second-grade and third-grade hospitals.However,there were some statistically significant differences between the groups,such as BMI,diabetes diagnosed before,duration of diabetes,PBG-breakfast,PBG-lunch,PBG-dinner,DBP and LDL-C.2.Efficacy evaluation2.1 HbAlc:The proportion of patients achieving the target HbAlc level of<7.0%(<53mmol/mol)was significantly higher in patients treated at second-grade hospitals than in those treated at third-grade hospitals(46.94%vs 38.85%,respectively;P<0.001).The mean HbAlc level decreased from 9.75%(83mmol/mol)at baseline to 7.07%(54mmol/mol)at week 12 in patients treated at second-grade hospital,and from 9.66%(82mmol/mol)at baseline to 7.48%(58mmol/mol)at Week 12 in patients treated at third-grade hospitals.The mean change in HbAlc was significantly greater in the former group(-2.68%[-29.3mmol/mol]vs-2.18%[-23.8mmol/mol].respectively;P<0.001).2.2 FBG and PBG:FBG and PBG values decreased in both treatment groups.Mean FBG levels decreased from 11.76 ± 4.22 mmol/L at baseline to 7.07 ± 1.13 mmol/L at week 12 in patients treated at second-grade hospitals,and from 11.52 ± 4.03 to 7.48 ± 1.33 mmol/L in patients treated at third-grade hospitals.The mean change in FBG was significantly greater in the former group.Similarly,mean changes in breakfast,lunch,and dinner PBG levels were also significantly greater in patients treated at second-grade hospitals than in those treated at third-grade hospitals after adjusting the baseline level of PBG(all P<0.001).Mean breakfast,lunch,and dinner PBG decreased 7.41 ±5.24mmol/L,6.80±14.90 mmol/L,5.84±4.63mmo/L separately at week 12 in patients treated at second-grade hospitals,and decreased 5.74±4.87mmol/L,5.20±4.62mmol/L,4.91 ±4.7mmol/L separately in patients treated at third-grade hospitals.2.3 Serum lipids:Among all treated patients,the LDL-C,total cholesterol(TC)and triglycerides(TG)levels at week 12 were significantly lower than those measured at baseline,while the HDL-C level at week 12 was significantly higher.In the comparison of patients treated at second-grade and third-grade hospitals,the change of HDL-C(-0.10±0.46mmol/L vs-0.05±0.47mmol/L)and total cholesterol(-0.44± 1.24mmol/L vs-0,56±1.20mmol/L)were significantly different between the 2 groups.While the change of LDL-C(-0.26±0.0.95mmol/L vs-0.35 ± 0.92mmol/L)and triglycerides(-0.58 ± 1.71mmol/L vs-0.54±1.89mmol/L)were not significantly different between the 2 groups.2.4 Blood pressure,body weight and insulin dosagesThe mean changes in SBP and DBP from baseline were not significantly different between the 2 groups.Although changes in body weight during the study period were small,there was a significant difference between the 2 groups,with patients treated at second-grade hospital showing a significantly greater mean weight gain(0.29 kg vs 0.04 kg,respectively;P<0.0001).After 12 weeks of treatment,patients who were treated at second-grade hospitals were receiving significantly greater mean daily dosages of insulin than those treated at third-grade hospitals(0.49 IU/kg/day vs 0.43IU/kg/day,respectively;P<0.0001),and the changes from baseline were significantly different between the 2 groups.3.Safety evaluation:The incidence of serious adverse events of the second-grade and third-grade hospitals was 0.37%and 0.21%respectively and the incidence of adverse events of the two groups was 1.97%and 1.28%respectively.Both of the incidences were no significant different.Differences in the incidences of hypoglycemic events between patients treated at second-grade and third-grade hospitals were statistically significant.The total incidence of hypoglycemic events during the study was 21.82%in patients treated at second-grade hospital and 16.79%in patients treated at third-grade hospitals.The incidences of hypoglycemic events occurring during the day and at night in the 2 groups were 17.02%and 12.98%,respectively,and 8.83%and 6.35%,respectively.The difference was statistically significant.4.Injection compliance:In the second-grade and third-grade hospitals,the ratio of patients' actual injection time in accordance with the doctors' advice were 26.39%and 18.02%respectively,and the difference was statistically significant(P=0.0493).The number of missing injection between the two groups of patients were 2.94 ± 10.28 and 5.59 ± 19.15,the difference was statistically significant(P=0.0018).The ratio of patients' 80-120%compliance between the two groups were 98.28%and 95.5%,with no significant difference(P=0.0632).Conclusion:1.Between38.85%and 46.94%of patients treated at second-grade and third-grade hospitals achieved the HbAlc goal level[<7%(<53mmol/mol)].The FBG and blood glucose blood glucose after meals was better controlled in second-grade hospitals than in third-grade hospitals.Consistent with the better controlled blood glucose,patients treated at second-grade hospitals have more insulin dosage and weight gain than those treated at third-grade hospitals.2.The incidence of hypoglycemia in patients treated with insulin at the second-grade hospital(including total hypoglycemia,daytime and night hypoglycemia)was higher than that of patients treated at third-grade hospitals.3.In the second-grade hospitals,the ratio of patients' actual injection time in accordance with the doctors' advice was higher than that of the third-grade hospitals,and the number of missing injection is less than that of third-grade hospitals.The patients'compliance in the second-grade hospitals is higher than that of the third-grade hospitals. |
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