BACKGROUND Colorectal polyps(CPs)are frequently occurring abnormal growths in the colorectum,and are a primary precursor of colorectal cancer(CRC).The triglyceride-glucose(TyG)index is a novel marker that assesses met...BACKGROUND Colorectal polyps(CPs)are frequently occurring abnormal growths in the colorectum,and are a primary precursor of colorectal cancer(CRC).The triglyceride-glucose(TyG)index is a novel marker that assesses metabolic health and insulin resistance,and has been linked to gastrointestinal cancers.AIM To investigate the potential association between the TyG index and CPs,as the relation between them has not been documented.METHODS A total of 2537 persons undergoing a routine health physical examination and colonoscopy at The First People's Hospital of Kunshan,Jiangsu Province,China,between January 2020 and December 2022 were included in this retrospective cross-sectional study.After excluding individuals who did not meet the eligibility criteria,descriptive statistics were used to compare characteristics between patients with and without CPs.Logistic regression analyses were conducted to determine the associations between the TyG index and the prevalence of CPs.The TyG index was calculated using the following formula:Ln[triglyceride(mg/dL)×glucose(mg/dL)/2].The presence and types of CPs was determined based on data from colonoscopy reports and pathology reports.RESULTS A nonlinear relation between the TyG index and the prevalence of CPs was identified,and exhibited a curvilinear pattern with a cut-off point of 2.31.A significant association was observed before the turning point,with an odds ratio(95% confidence interval)of 1.70(1.40,2.06),P<0.0001.However,the association between the TyG index and CPs was not significant after the cut-off point,with an odds ratio(95% confidence interval)of 0.57(0.27,1.23),P=0.1521.CONCLUSION Our study revealed a curvilinear association between the TyG index and CPs in Chinese individuals,suggesting its potential utility in developing colonoscopy screening strategies for preventing CRC.展开更多
BACKGROUND The birth of large-for-gestational-age(LGA)infants is associated with many shortterm adverse pregnancy outcomes.It has been observed that the proportion of LGA infants born to pregnant women with gestationa...BACKGROUND The birth of large-for-gestational-age(LGA)infants is associated with many shortterm adverse pregnancy outcomes.It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus(GDM)is significantly higher than that born to healthy pregnant women.However,traditional methods for the diagnosis of LGA have limitations.Therefore,this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants.AIM To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM,and provide strategies for the effective prevention and timely intervention of LGA.METHODS The multivariable prediction model was developed by carrying out the following steps.First,the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses,for which the P value was<0.10.Subsequently,Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations,and the optimal combination factors were se-lected by choosing lambda 1se as the criterion.The final predictors were deter-mined by multiple backward stepwise logistic regression analysis,in which only the independent variables were associated with LGA risk,with a P value<0.05.Finally,a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve,calibration curve and decision curve analyses.RESULTS After using a multistep screening method,we establish a predictive model.Several risk factors for delivering an LGA infant were identified(P<0.01),including weight gain during pregnancy,parity,triglyceride-glucose index,free tetraiodothyronine level,abdominal circumference,alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks.The nomogram’s prediction ability was supported by the area under the curve(0.703,0.709,and 0.699 for the training cohort,validation cohort,and t展开更多
基金Supported by Suzhou Municipal Science and Technology Program of China,No.SKJY2021012.
文摘BACKGROUND Colorectal polyps(CPs)are frequently occurring abnormal growths in the colorectum,and are a primary precursor of colorectal cancer(CRC).The triglyceride-glucose(TyG)index is a novel marker that assesses metabolic health and insulin resistance,and has been linked to gastrointestinal cancers.AIM To investigate the potential association between the TyG index and CPs,as the relation between them has not been documented.METHODS A total of 2537 persons undergoing a routine health physical examination and colonoscopy at The First People's Hospital of Kunshan,Jiangsu Province,China,between January 2020 and December 2022 were included in this retrospective cross-sectional study.After excluding individuals who did not meet the eligibility criteria,descriptive statistics were used to compare characteristics between patients with and without CPs.Logistic regression analyses were conducted to determine the associations between the TyG index and the prevalence of CPs.The TyG index was calculated using the following formula:Ln[triglyceride(mg/dL)×glucose(mg/dL)/2].The presence and types of CPs was determined based on data from colonoscopy reports and pathology reports.RESULTS A nonlinear relation between the TyG index and the prevalence of CPs was identified,and exhibited a curvilinear pattern with a cut-off point of 2.31.A significant association was observed before the turning point,with an odds ratio(95% confidence interval)of 1.70(1.40,2.06),P<0.0001.However,the association between the TyG index and CPs was not significant after the cut-off point,with an odds ratio(95% confidence interval)of 0.57(0.27,1.23),P=0.1521.CONCLUSION Our study revealed a curvilinear association between the TyG index and CPs in Chinese individuals,suggesting its potential utility in developing colonoscopy screening strategies for preventing CRC.
基金Supported by National Natural Science Foundation of China,No.81870546Nanjing Medical Science and Technique Development Foundation,No.YKK23151Science and Technology Development Foundation Item of Nanjing Medical University,No.NMUB20210117.
文摘BACKGROUND The birth of large-for-gestational-age(LGA)infants is associated with many shortterm adverse pregnancy outcomes.It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus(GDM)is significantly higher than that born to healthy pregnant women.However,traditional methods for the diagnosis of LGA have limitations.Therefore,this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants.AIM To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM,and provide strategies for the effective prevention and timely intervention of LGA.METHODS The multivariable prediction model was developed by carrying out the following steps.First,the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses,for which the P value was<0.10.Subsequently,Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations,and the optimal combination factors were se-lected by choosing lambda 1se as the criterion.The final predictors were deter-mined by multiple backward stepwise logistic regression analysis,in which only the independent variables were associated with LGA risk,with a P value<0.05.Finally,a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve,calibration curve and decision curve analyses.RESULTS After using a multistep screening method,we establish a predictive model.Several risk factors for delivering an LGA infant were identified(P<0.01),including weight gain during pregnancy,parity,triglyceride-glucose index,free tetraiodothyronine level,abdominal circumference,alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks.The nomogram’s prediction ability was supported by the area under the curve(0.703,0.709,and 0.699 for the training cohort,validation cohort,and t
文摘目的三酰甘油-葡萄糖(triglyceride-glucose,TyG)指数是胰岛素抵抗(insulin resistance,IR)的简易替代指标,脂肪组织IR(adipose-IR)引起的异位脂肪沉积可导致糖脂代谢紊乱。本研究旨在探讨TyG指数和adipose-IR的关系。方法纳入2019年4月至2022年3月于首都医科大学附属北京友谊医院就诊的向心性肥胖患者419例,收集患者的临床基本资料,检测患者的空腹血糖、胰岛素、血脂、糖化血红蛋白(glycosylated hemoglobin A1c,HbA1c)、游离脂肪酸等代谢相关指标。按照TyG指数中位数分为高TyG(≥9.07)组(n=209)和低TyG(<9.07)组(n=210);比较两组间糖脂代谢指标和adipose-IR指数的差异;二元Logistic回归分析TyG和adipose-IR指数之间的关系。结果高TyG组平均年龄(34.28±0.66)岁,男性76例(36.36%);低TyG组平均年龄(30.86±0.58)岁,男性66例(31.28%)。高TyG组平均年龄、男性患者占比均大于低TyG组(P<0.001)。与低TyG组相比,高TyG组adipose-IR指数[144.3(77.87,241.9)vs 104.1(63.40,174.1)]、稳态模型评估胰岛素抵抗(homeostasis model assessment of insulin resistance,HOMA-IR)指数[9.72(6.28,14.17)vs 6.00(3.64,9.84)]均显著增加(P<0.001);而高TyG组稳态模型胰岛素分泌功能(homeostasis model assessment ofβ-cell function,HOMA-β)指数明显低于低TyG组(P<0.001)。TyG指数与adipose-IR指数(r=0.310,P<0.001)、HOMA-IR指数(r=0.432,P<0.001)及HbA1c(r=0.553,P<0.001)均呈显著正相关,与HOMA-β(r=-0.397,P<0.001)呈显著负相关。二元Logistic回归分析结果显示TyG指数为adipose-IR的独立影响因素,OR值为1.004(95%CI:1.001~1.009)。结论TyG指数与adipose-IR指数呈显著正相关,高TyG预示着更严重的adipose-IR;TyG可以作为一种简易的手段用于评估肥胖患者adipose-IR。
