Diabetes & Metabolic Syndrome-Clinical Research & Reviews最新文献_第10页

Using nephropathy as an outcome to determine the HbA1c diagnostic threshold for type 2 diabetes 将肾病作为确定 2 型糖尿病 HbA1c 诊断阈值的结果

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-04-01 DOI: 10.1016/j.dsx.2024.103005

Alexandra E. Butler , Steven C. Hunt , Eric S. Kilpatrick

Objective

The hemoglobin A1c (HbA1c) diagnostic threshold for type 2 diabetes (T2D) of 6.5 % (48 mmol/mol) was based on the prevalence of retinopathy found in populations not known to have T2D. It is unclear if nephropathy has a similar HbA1c threshold, partly because it is a rarer complication of early diabetes. This cohort study investigated a very high diabetes prevalence population to determine if a better diagnostic HbA1c value can be established for predicting nephropathy rather than retinopathy in subjects without T2D.

Methods

The urine albumin:creatinine ratios (UACRs) of 2920 healthy individuals from the Qatar Biobank who had an HbA1c ≥ 5.6 %. were studied. Nephropathy was defined as a UACR≥30 mg/g and its prediction by HbA1c was assessed using cut-points ranging from 5.7 to 7.0 % to dichotomize high from low HbA1c.

Results

Although there was a significant trend for an increased prevalence of abnormal UACR as the HbA1c threshold increased (p < 0.01), significance was due mostly to subjects with HbA1c ≥ 7.0 % (53 mmol/mol). The odds ratios for abnormal UACR were similar over the 5.7–6.9 % HbA1c threshold range, with a narrow odds ratio range of 1.2–1.6. Utilizing area-under-receiver-operating characteristic curves, no HbA1c threshold <7.0 % was identified as the best predictor of nephropathy.

Conclusion

Even in a population with a high prevalence of known and unknown diabetes, no HbA1c threshold <7.0 % could be found predicting an increased prevalence of nephropathy. This means there is not a requirement to change the existing retinopathy-based HbA1c threshold of 6.5 % to also accommodate diabetes nephropathy risk.

目标2型糖尿病（T2D）的血红蛋白A1c（HbA1c）诊断阈值为6.5%（48 mmol/mol），其依据是在未发现T2D的人群中发现的视网膜病变患病率。目前还不清楚肾病是否也有类似的 HbA1c 临界值，部分原因是肾病是早期糖尿病的一种罕见并发症。这项队列研究对糖尿病发病率非常高的人群进行了调查，以确定是否可以建立一个更好的诊断 HbA1c 值，用于预测未患 T2D 的受试者的肾病而非视网膜病变。方法研究了卡塔尔生物库中 HbA1c ≥ 5.6 % 的 2920 名健康人的尿白蛋白：肌酐比率（UACRs）。结果虽然随着 HbA1c 临界值的增加，UACR 异常发生率呈显著增加趋势（p <0.01），但显著性主要来自 HbA1c≥7.0 %（53 mmol/mol）的受试者。在 5.7-6.9 % HbA1c 临界值范围内，UACR 异常的几率相似，几率范围较窄，为 1.2-1.6。结论即使在已知和未知糖尿病患病率较高的人群中，也没有发现任何 HbA1c 临界值 <7.0 % 可以预测肾病患病率的增加。这意味着不需要改变现有的基于视网膜病变的 HbA1c 临界值 6.5%，以同时考虑糖尿病肾病风险。

{"title":"Using nephropathy as an outcome to determine the HbA1c diagnostic threshold for type 2 diabetes","authors":"Alexandra E. Butler , Steven C. Hunt , Eric S. Kilpatrick","doi":"10.1016/j.dsx.2024.103005","DOIUrl":"https://doi.org/10.1016/j.dsx.2024.103005","url":null,"abstract":"<div><h3>Objective</h3><p>The hemoglobin A1c (HbA1c) diagnostic threshold for type 2 diabetes (T2D) of 6.5 % (48 mmol/mol) was based on the prevalence of retinopathy found in populations not known to have T2D. It is unclear if nephropathy has a similar HbA1c threshold, partly because it is a rarer complication of early diabetes. This cohort study investigated a very high diabetes prevalence population to determine if a better diagnostic HbA1c value can be established for predicting nephropathy rather than retinopathy in subjects without T2D.</p></div><div><h3>Methods</h3><p>The urine albumin:creatinine ratios (UACRs) of 2920 healthy individuals from the Qatar Biobank who had an HbA1c ≥ 5.6 %. were studied. Nephropathy was defined as a UACR≥30 mg/g and its prediction by HbA1c was assessed using cut-points ranging from 5.7 to 7.0 % to dichotomize high from low HbA1c.</p></div><div><h3>Results</h3><p>Although there was a significant trend for an increased prevalence of abnormal UACR as the HbA1c threshold increased (p < 0.01), significance was due mostly to subjects with HbA1c ≥ 7.0 % (53 mmol/mol). The odds ratios for abnormal UACR were similar over the 5.7–6.9 % HbA1c threshold range, with a narrow odds ratio range of 1.2–1.6. Utilizing area-under-receiver-operating characteristic curves, no HbA1c threshold <7.0 % was identified as the best predictor of nephropathy.</p></div><div><h3>Conclusion</h3><p>Even in a population with a high prevalence of known and unknown diabetes, no HbA1c threshold <7.0 % could be found predicting an increased prevalence of nephropathy. This means there is not a requirement to change the existing retinopathy-based HbA1c threshold of 6.5 % to also accommodate diabetes nephropathy risk.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":10.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140548083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial intelligence facial recognition system for diagnosis of endocrine and metabolic syndromes based on a facial image database 基于面部图像数据库诊断内分泌和代谢综合征的人工智能面部识别系统

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-04-01 DOI: 10.1016/j.dsx.2024.103003

Danning Wu , Jiaqi Qiang , Weixin Hong , Hanze Du , Hongbo Yang , Huijuan Zhu , Hui Pan , Zhen Shen , Shi Chen

Aim

To build a facial image database and to explore the diagnostic efficacy and influencing factors of the artificial intelligence-based facial recognition (AI-FR) system for multiple endocrine and metabolic syndromes.

Methods

Individuals with multiple endocrine and metabolic syndromes and healthy controls were included from public literature and databases. In this facial image database, facial images and clinical data were collected for each participant and dFRI (disease facial recognition intensity) was calculated to quantify facial complexity of each syndrome. AI-FR diagnosis models were trained for each disease using three algorithms: support vector machine (SVM), principal component analysis k-nearest neighbor (PCA-KNN), and adaptive boosting (AdaBoost). Diagnostic performance was evaluated. Optimal efficacy was achieved as the best index among the three models. Effect factors of AI-FR diagnosis were explored with regression analysis.

Results

462 cases of 10 endocrine and metabolic syndromes and 2310 controls were included into the facial image database. The AI-FR diagnostic models showed diagnostic accuracies of 0.827–0.920 with SVM, 0.766–0.890 with PCA-KNN, and 0.818–0.935 with AdaBoost. Higher dFRI was associated with higher optimal area under the curve (AUC) (P = 0.035). No significant correlation was observed between the sample size of the training set and diagnostic performance.

Conclusions

A multi-ethnic, multi-regional, and multi-disease facial database for 10 endocrine and metabolic syndromes was built. AI-FR models displayed ideal diagnostic performance. dFRI proved associated with the diagnostic performance, suggesting inherent facial features might contribute to the performance of AI-FR models.

目的建立一个面部图像数据库，并探讨基于人工智能的面部识别（AI-FR）系统对多种内分泌和代谢综合征的诊断效果和影响因素。方法从公开文献和数据库中纳入患有多种内分泌和代谢综合征的个体和健康对照组。在该面部图像数据库中，收集了每位参与者的面部图像和临床数据，并计算了疾病面部识别强度（dFRI），以量化每种综合征的面部复杂性。使用支持向量机（SVM）、主成分分析 k-nearest neighbor（PCA-KNN）和自适应提升（AdaBoost）三种算法对每种疾病的 AI-FR 诊断模型进行了训练。对诊断性能进行了评估。在三个模型中，最佳疗效是最佳指标。结果 10 种内分泌和代谢综合征的 462 个病例和 2310 个对照组被纳入面部图像数据库。AI-FR诊断模型的诊断准确率分别为：SVM为0.827-0.920，PCA-KNN为0.766-0.890，AdaBoost为0.818-0.935。较高的 dFRI 与较高的最佳曲线下面积 (AUC) 相关（P = 0.035）。结论针对 10 种内分泌和代谢综合征建立了一个多种族、多地区和多疾病的面部数据库。dFRI 被证明与诊断性能相关，表明固有的面部特征可能有助于提高 AI-FR 模型的性能。

{"title":"Artificial intelligence facial recognition system for diagnosis of endocrine and metabolic syndromes based on a facial image database","authors":"Danning Wu , Jiaqi Qiang , Weixin Hong , Hanze Du , Hongbo Yang , Huijuan Zhu , Hui Pan , Zhen Shen , Shi Chen","doi":"10.1016/j.dsx.2024.103003","DOIUrl":"https://doi.org/10.1016/j.dsx.2024.103003","url":null,"abstract":"<div><h3>Aim</h3><p>To build a facial image database and to explore the diagnostic efficacy and influencing factors of the artificial intelligence-based facial recognition (AI-FR) system for multiple endocrine and metabolic syndromes.</p></div><div><h3>Methods</h3><p>Individuals with multiple endocrine and metabolic syndromes and healthy controls were included from public literature and databases. In this facial image database, facial images and clinical data were collected for each participant and dFRI (disease facial recognition intensity) was calculated to quantify facial complexity of each syndrome. AI-FR diagnosis models were trained for each disease using three algorithms: support vector machine (SVM), principal component analysis k-nearest neighbor (PCA-KNN), and adaptive boosting (AdaBoost). Diagnostic performance was evaluated. Optimal efficacy was achieved as the best index among the three models. Effect factors of AI-FR diagnosis were explored with regression analysis.</p></div><div><h3>Results</h3><p>462 cases of 10 endocrine and metabolic syndromes and 2310 controls were included into the facial image database. The AI-FR diagnostic models showed diagnostic accuracies of 0.827–0.920 with SVM, 0.766–0.890 with PCA-KNN, and 0.818–0.935 with AdaBoost. Higher dFRI was associated with higher optimal area under the curve (AUC) (P = 0.035). No significant correlation was observed between the sample size of the training set and diagnostic performance.</p></div><div><h3>Conclusions</h3><p>A multi-ethnic, multi-regional, and multi-disease facial database for 10 endocrine and metabolic syndromes was built. AI-FR models displayed ideal diagnostic performance. dFRI proved associated with the diagnostic performance, suggesting inherent facial features might contribute to the performance of AI-FR models.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":10.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140550859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Incorporating polygenic risk into the Leicester Risk Assessment score for 10-year risk prediction of type 2 diabetes 将多基因风险纳入莱斯特风险评估评分，预测 2 型糖尿病的 10 年风险

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-04-01 DOI: 10.1016/j.dsx.2024.102996

Xiaonan Liu , Thomas J. Littlejohns , Jelena Bešević , Fiona Bragg , Lei Clifton , Jennifer A. Collister , Eirini Trichia , Laura J. Gray , Kamlesh Khunti , David J. Hunter

Aims

We evaluated whether incorporating information on ethnic background and polygenic risk enhanced the Leicester Risk Assessment (LRA) score for predicting 10-year risk of type 2 diabetes.

Methods

The sample included 202,529 UK Biobank participants aged 40–69 years. We computed the LRA score, and developed two new risk scores using training data (80% sample): LRArev, which incorporated additional information on ethnic background, and LRAprs, which incorporated polygenic risk for type 2 diabetes. We assessed discriminative and reclassification performance in a test set (20% sample). Type 2 diabetes was ascertained using primary care, hospital inpatient and death registry records.

Results

Over 10 years, 7,476 participants developed type 2 diabetes. The Harrell's C indexes were 0.796 (95% Confidence Interval [CI] 0.785, 0.806), 0.802 (95% CI 0.792, 0.813), and 0.829 (95% CI 0.820, 0.839) for the LRA, LRArev and LRAprs scores, respectively. The LRAprs score significantly improved the overall reclassification compared to the LRA (net reclassification index [NRI] = 0.033, 95% CI 0.015, 0.049) and LRArev (NRI = 0.040, 95% CI 0.024, 0.055) scores.

Conclusions

Polygenic risk moderately improved the performance of the existing LRA score for 10-year risk prediction of type 2 diabetes.

目的我们评估了纳入种族背景和多基因风险信息是否会提高莱斯特风险评估（LRA）预测 2 型糖尿病 10 年风险的得分。方法样本包括 202,529 名年龄在 40-69 岁之间的英国生物库参与者。我们计算了 LRA 评分，并利用训练数据（80% 的样本）开发了两种新的风险评分：LRArev 包含种族背景的附加信息，LRAprs 包含 2 型糖尿病的多基因风险。我们评估了测试集（20% 样本）的判别和再分类性能。2 型糖尿病是通过初级保健、医院住院病人和死亡登记记录确定的。LRA、LRArev 和 LRAprs 评分的哈雷尔 C 指数分别为 0.796（95% 置信区间 [CI] 0.785，0.806）、0.802（95% CI 0.792，0.813）和 0.829（95% CI 0.820，0.839）。与 LRA（净再分类指数 [NRI] = 0.033，95% CI 0.015，0.049）和 LRArev（净再分类指数 [NRI] = 0.040，95% CI 0.024，0.055）相比，LRAprs 评分明显改善了总体再分类效果。

{"title":"Incorporating polygenic risk into the Leicester Risk Assessment score for 10-year risk prediction of type 2 diabetes","authors":"Xiaonan Liu , Thomas J. Littlejohns , Jelena Bešević , Fiona Bragg , Lei Clifton , Jennifer A. Collister , Eirini Trichia , Laura J. Gray , Kamlesh Khunti , David J. Hunter","doi":"10.1016/j.dsx.2024.102996","DOIUrl":"10.1016/j.dsx.2024.102996","url":null,"abstract":"<div><h3>Aims</h3><p>We evaluated whether incorporating information on ethnic background and polygenic risk enhanced the Leicester Risk Assessment (LRA<em>)</em> score for predicting 10-year risk of type 2 diabetes.</p></div><div><h3>Methods</h3><p>The sample included 202,529 UK Biobank participants aged 40–69 years. We computed the <em>LRA score</em>, and developed two new risk scores using training data (80% sample): <em>LRArev</em>, which incorporated additional information on ethnic background, and <em>LRAprs</em>, which incorporated polygenic risk for type 2 diabetes. We assessed discriminative and reclassification performance in a test set (20% sample). Type 2 diabetes was ascertained using primary care, hospital inpatient and death registry records.</p></div><div><h3>Results</h3><p>Over 10 years, 7,476 participants developed type 2 diabetes. The Harrell's C indexes were 0.796 (95% Confidence Interval [CI] 0.785, 0.806), 0.802 (95% CI 0.792, 0.813), and 0.829 (95% CI 0.820, 0.839) for the <em>LRA</em>, <em>LRArev</em> and <em>LRAprs</em> scores, respectively. The <em>LRAprs</em> score significantly improved the overall reclassification compared to the <em>LRA</em> (net reclassification index [NRI] = 0.033, 95% CI 0.015, 0.049) and <em>LRArev</em> (NRI = 0.040, 95% CI 0.024, 0.055) <em>scores</em>.</p></div><div><h3>Conclusions</h3><p>Polygenic risk moderately improved the performance of the existing <em>LRA score</em> for 10-year risk prediction of type 2 diabetes.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":10.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1871402124000572/pdfft?md5=9424f3ac9af33735a2cee24ff4916bd4&pid=1-s2.0-S1871402124000572-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140401081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Diabetic foot ulcers, their characteristics, and trends in survival: Real world outcomes at a tertiary care facility in India 糖尿病足溃疡、其特征和存活趋势：印度一家三级医疗机构的实际成果

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-04-01 DOI: 10.1016/j.dsx.2024.103011

Zachariah Thomas , Shrirang Kishor Bhurchandi , Bharathi Saravanan , Flory Christina , Ruth Volena , Grace Rebekah , Vasanth Mark Samuel , Pranay Gaikwad , Bobeena Chandy , Anand Samuel , Kripa Elizabeth Cherian , Sheeba Varghese , Felix K. Jebasingh , Nihal Thomas

Aims

Characteristics of diabetes-related foot ulcers (DFU), association with recurrence and amputation are poorly described in the Asian Indian population.

Methods

A prospectively maintained database was reviewed to characterize DFU and its association with amputation and recurrence.

Results

Of 200 patients, 63.5 % were male, the median age was 62 years (Min-Max:40–86), and median BMI was 27.90 kg/m² (Min-Max:18.5–42.7). Median duration of Diabetes mellitus was 15 years (Min-Max:2–43). Complete healing occurred at a median of three months (Min-Max:0.23–37.62). Amputation for the current ulcer was required in 43.4 % of individuals. Ulcer recurrence was documented in 42.4 % instances, 66.1 % evolving on the ipsilateral side. Previous amputation was associated with the risk of subsequent amputation (Adjusted OR-3.08,p-0.047). Median time to ulcer recurrence was 4.23 years among those with amputation, in contrast to 9.61 years in those with healing. Cardiovascular death was the commonest cause of mortality, followed by sepsis. At a median follow up of 6.08 years, mortality at 1,3,5 and 10 years was 2.5 %,2.5 %,8.2 % and 30.9 % respectively among those who underwent amputation versus 0 %,0 %,10.1 % and 24.5 % respectively for those who achieved healing.

Conclusions

Patients with DFU in India incur amputations at rates higher than conventionally described. With previous amputation, subsequent amputation risk triples. Ten-year mortality is 25%–30 %. Underestimates of the burden of recurrence and mortality are consequential of limited follow-up.

目的对亚洲印度人群中糖尿病相关足部溃疡（DFU）的特征、与复发和截肢的关系描述不足。糖尿病病程中位数为 15 年（最小值：2-43 年）。完全愈合的时间中位数为三个月（最小值-最大值：0.23-37.62）。43.4%的患者需要截肢治疗当前的溃疡。据记录，42.4%的患者溃疡复发，66.1%复发于同侧。之前的截肢手术与随后截肢的风险有关（调整后OR-3.08,p-0.047）。截肢者溃疡复发的中位时间为4.23年，而愈合者为9.61年。心血管疾病是最常见的死亡原因，其次是败血症。中位随访 6.08 年，截肢者 1、3、5 和 10 年的死亡率分别为 2.5%、2.5%、8.2% 和 30.9%，而痊愈者分别为 0%、0%、10.1% 和 24.5%。以前截肢过的患者，以后截肢的风险会增加三倍。十年死亡率为 25%-30%。对复发率和死亡率的低估是随访有限的结果。

{"title":"Diabetic foot ulcers, their characteristics, and trends in survival: Real world outcomes at a tertiary care facility in India","authors":"Zachariah Thomas , Shrirang Kishor Bhurchandi , Bharathi Saravanan , Flory Christina , Ruth Volena , Grace Rebekah , Vasanth Mark Samuel , Pranay Gaikwad , Bobeena Chandy , Anand Samuel , Kripa Elizabeth Cherian , Sheeba Varghese , Felix K. Jebasingh , Nihal Thomas","doi":"10.1016/j.dsx.2024.103011","DOIUrl":"10.1016/j.dsx.2024.103011","url":null,"abstract":"<div><h3>Aims</h3><p>Characteristics of diabetes-related foot ulcers (DFU), association with recurrence and amputation are poorly described in the Asian Indian population.</p></div><div><h3>Methods</h3><p>A prospectively maintained database was reviewed to characterize DFU and its association with amputation and recurrence.</p></div><div><h3>Results</h3><p>Of 200 patients, 63.5 % were male, the median age was 62 years (Min-Max:40–86), and median BMI was 27.90 kg/m<sup>2</sup> (Min-Max:18.5–42.7). Median duration of Diabetes mellitus was 15 years (Min-Max:2–43). Complete healing occurred at a median of three months (Min-Max:0.23–37.62). Amputation for the current ulcer was required in 43.4 % of individuals. Ulcer recurrence was documented in 42.4 % instances, 66.1 % evolving on the ipsilateral side. Previous amputation was associated with the risk of subsequent amputation (Adjusted OR-3.08,p-0.047)<strong>.</strong> Median time to ulcer recurrence was 4.23 years among those with amputation, in contrast to 9.61 years in those with healing. Cardiovascular death was the commonest cause of mortality, followed by sepsis. At a median follow up of 6.08 years, mortality at 1,3,5 and 10 years was 2.5 %,2.5 %,8.2 % and 30.9 % respectively among those who underwent amputation versus 0 %,0 %,10.1 % and 24.5 % respectively for those who achieved healing.</p></div><div><h3>Conclusions</h3><p>Patients with DFU in India incur amputations at rates higher than conventionally described. With previous amputation, subsequent amputation risk triples. Ten-year mortality is 25%–30 %. Underestimates of the burden of recurrence and mortality are consequential of limited follow-up.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":10.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140794625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A review of the application of deep learning in obesity: From early prediction aid to advanced management assistance 深度学习在肥胖症中的应用综述：从早期预测辅助到高级管理辅助

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-04-01 DOI: 10.1016/j.dsx.2024.103000

Xinghao Yi , Yangzhige He , Shan Gao , Ming Li

Background and aims

Obesity is a chronic disease which can cause severe metabolic disorders. Machine learning (ML) techniques, especially deep learning (DL), have proven to be useful in obesity research. However, there is a dearth of systematic reviews of DL applications in obesity. This article aims to summarize the current trend of DL usage in obesity research.

Methods

An extensive literature review was carried out across multiple databases, including PubMed, Embase, Web of Science, Scopus, and Medline, to collate relevant studies published from January 2018 to September 2023. The focus was on research detailing the application of DL in the context of obesity. We have distilled critical insights pertaining to the utilized learning models, encompassing aspects of their development, principal results, and foundational methodologies.

Results

Our analysis culminated in the synthesis of new knowledge regarding the application of DL in the context of obesity. Finally, 40 research articles were included. The final collection of these research can be divided into three categories: obesity prediction (n = 16); obesity management (n = 13); and body fat estimation (n = 11).

Conclusions

This is the first review to examine DL applications in obesity. It reveals DL's superiority in obesity prediction over traditional ML methods, showing promise for multi-omics research. DL also innovates in obesity management through diet, fitness, and environmental analyses. Additionally, DL improves body fat estimation, offering affordable and precise monitoring tools. The study is registered with PROSPERO (ID: CRD42023475159).

背景和目的肥胖是一种慢性疾病，可导致严重的代谢紊乱。事实证明，机器学习（ML）技术，尤其是深度学习（DL），在肥胖症研究中非常有用。然而，关于深度学习在肥胖症中的应用的系统性综述还很缺乏。本文旨在总结当前 DL 在肥胖症研究中的应用趋势。方法在多个数据库（包括 PubMed、Embase、Web of Science、Scopus 和 Medline）中进行了广泛的文献综述，以整理 2018 年 1 月至 2023 年 9 月期间发表的相关研究。重点是详细介绍 DL 在肥胖症方面应用的研究。我们提炼出了与所使用的学习模型有关的重要见解，包括其发展、主要成果和基础方法等方面。结果我们的分析最终归纳出了有关在肥胖症背景下应用 DL 的新知识。最后，共收录了 40 篇研究文章。这些研究的最终成果可分为三类：肥胖预测（16 篇）；肥胖管理（13 篇）；体脂估算（11 篇）。它揭示了 DL 在肥胖预测方面优于传统的 ML 方法，显示了多组学研究的前景。通过饮食、健身和环境分析，DL 在肥胖管理方面也有创新。此外，DL 还能改进体脂估计，提供经济实惠的精确监测工具。该研究已在 PROSPERO 注册（ID：CRD42023475159）。

{"title":"A review of the application of deep learning in obesity: From early prediction aid to advanced management assistance","authors":"Xinghao Yi , Yangzhige He , Shan Gao , Ming Li","doi":"10.1016/j.dsx.2024.103000","DOIUrl":"https://doi.org/10.1016/j.dsx.2024.103000","url":null,"abstract":"<div><h3>Background and aims</h3><p>Obesity is a chronic disease which can cause severe metabolic disorders. Machine learning (ML) techniques, especially deep learning (DL), have proven to be useful in obesity research. However, there is a dearth of systematic reviews of DL applications in obesity. This article aims to summarize the current trend of DL usage in obesity research.</p></div><div><h3>Methods</h3><p>An extensive literature review was carried out across multiple databases, including PubMed, Embase, Web of Science, Scopus, and Medline, to collate relevant studies published from January 2018 to September 2023. The focus was on research detailing the application of DL in the context of obesity. We have distilled critical insights pertaining to the utilized learning models, encompassing aspects of their development, principal results, and foundational methodologies.</p></div><div><h3>Results</h3><p>Our analysis culminated in the synthesis of new knowledge regarding the application of DL in the context of obesity. Finally, 40 research articles were included. The final collection of these research can be divided into three categories: obesity prediction (n = 16); obesity management (n = 13); and body fat estimation (n = 11).</p></div><div><h3>Conclusions</h3><p>This is the first review to examine DL applications in obesity. It reveals DL's superiority in obesity prediction over traditional ML methods, showing promise for multi-omics research. DL also innovates in obesity management through diet, fitness, and environmental analyses. Additionally, DL improves body fat estimation, offering affordable and precise monitoring tools. The study is registered with PROSPERO (ID: CRD42023475159).</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":10.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140543998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Association of ethnicity and socioeconomic status with health outcomes in women with gestational diabetes: Clinical practice research datalink cohort study 妊娠糖尿病妇女的种族和社会经济地位与健康结果的关系：临床实践研究数据链队列研究

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-04-01 DOI: 10.1016/j.dsx.2024.103010

Elpida Vounzoulaki , Joanne K. Miksza , Francesco Zaccardi , Bee K. Tan , Melanie J. Davies , Kamlesh Khunti , Clare L. Gillies

Aims

To investigate in women with prior gestational diabetes mellitus (GDM), differences by ethnicity and socioeconomic status in the incidence of recurrent GDM, type 2 diabetes (T2D), hypertension, and depression.

Methods

This was a retrospective cohort study including 10,868 women diagnosed with GDM in the Clinical Practice Research Datalink (CPRD GOLD) between January 01, 2000 and November 05, 2018. Linked data were obtained for Hospital Episode Statistics and the Index of Multiple Deprivation. We estimated incidence rates and hazard ratios, by ethnicity and socioeconomic status.

Results

During a follow-up of 58,479 person years (mean (SD): 5.38 (3.67) years), the crude incidence was 9.67 (95 % confidence interval: 9.30–10.00) per 100 person years for recurrent GDM, 3.86 (3.70–4.02) for depression, 2.15 (2.03–2.27) for T2D and 0.89 (0.81–0.97) for hypertension. South Asian ethnicity was associated with an increased risk of T2D compared to White (adjusted hazard ratio: 1.65; 1.34–2.05) and Black ethnicity was associated with a greater risk of hypertension (2.93; 1.93–4.46). Black and South Asian ethnicity were associated with a reduced risk of depression compared to White: 0.23 (0.13–0.39) and 0.37 (0.29–0.46), respectively. Incidence rates were higher for all conditions with increasing deprivation level.

Conclusions

The risk of health complications in women with a prior history of GDM differs by ethnicity and socio-economic status, suggesting the opportunity for targeted assessment in the years following pregnancy. These findings may inform future guidelines on screening for health outcomes in women with GDM.

目的研究曾患妊娠糖尿病（GDM）的妇女在复发性GDM、2型糖尿病（T2D）、高血压和抑郁症的发病率方面因种族和社会经济地位而存在的差异。我们获得了医院事件统计和多重贫困指数的关联数据。我们按种族和社会经济地位估算了发病率和危险比。结果在58 479人年（平均（标清）：5.38（3.67）年）的随访期间，复发性GDM的粗发病率为每100人年9.67（95%置信区间：9.30-10.00），抑郁症为每100人年3.86（3.70-4.02），T2D为每100人年2.15（2.03-2.27），高血压为每100人年0.89（0.81-0.97）。与白人相比，南亚裔患 T2D 的风险更高（调整后危险比：1.65；1.34-2.05），黑人患高血压的风险更高（2.93；1.93-4.46）。与白人相比，黑人和南亚裔患抑郁症的风险较低：分别为 0.23 (0.13-0.39) 和 0.37 (0.29-0.46)。结论不同种族和社会经济地位的妇女在既往有 GDM 病史的妇女中发生健康并发症的风险不同，这表明有机会在怀孕后的几年中进行有针对性的评估。这些研究结果可为今后制定GDM妇女健康状况筛查指南提供参考。

{"title":"Association of ethnicity and socioeconomic status with health outcomes in women with gestational diabetes: Clinical practice research datalink cohort study","authors":"Elpida Vounzoulaki , Joanne K. Miksza , Francesco Zaccardi , Bee K. Tan , Melanie J. Davies , Kamlesh Khunti , Clare L. Gillies","doi":"10.1016/j.dsx.2024.103010","DOIUrl":"https://doi.org/10.1016/j.dsx.2024.103010","url":null,"abstract":"<div><h3>Aims</h3><p>To investigate in women with prior gestational diabetes mellitus (GDM), differences by ethnicity and socioeconomic status in the incidence of recurrent GDM, type 2 diabetes (T2D), hypertension, and depression.</p></div><div><h3>Methods</h3><p>This was a retrospective cohort study including 10,868 women diagnosed with GDM in the Clinical Practice Research Datalink (CPRD GOLD) between January 01, 2000 and November 05, 2018. Linked data were obtained for Hospital Episode Statistics and the Index of Multiple Deprivation. We estimated incidence rates and hazard ratios, by ethnicity and socioeconomic status.</p></div><div><h3>Results</h3><p>During a follow-up of 58,479 person years (mean (SD): 5.38 (3.67) years), the crude incidence was 9.67 (95 % confidence interval: 9.30–10.00) per 100 person years for recurrent GDM, 3.86 (3.70–4.02) for depression, 2.15 (2.03–2.27) for T2D and 0.89 (0.81–0.97) for hypertension. South Asian ethnicity was associated with an increased risk of T2D compared to White (adjusted hazard ratio: 1.65; 1.34–2.05) and Black ethnicity was associated with a greater risk of hypertension (2.93; 1.93–4.46). Black and South Asian ethnicity were associated with a reduced risk of depression compared to White: 0.23 (0.13–0.39) and 0.37 (0.29–0.46), respectively. Incidence rates were higher for all conditions with increasing deprivation level.</p></div><div><h3>Conclusions</h3><p>The risk of health complications in women with a prior history of GDM differs by ethnicity and socio-economic status, suggesting the opportunity for targeted assessment in the years following pregnancy. These findings may inform future guidelines on screening for health outcomes in women with GDM.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":10.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1871402124000717/pdfft?md5=21398a741c596433ad55f2eb365e37ae&pid=1-s2.0-S1871402124000717-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140645868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explanatory variables of objectively measured 24-h movement behaviors in people with prediabetes and type 2 diabetes: A systematic review 客观测量糖尿病前期和 2 型糖尿病患者 24 小时运动行为的解释变量：系统回顾

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-04-01 DOI: 10.1016/j.dsx.2024.102995

Lotte Bogaert , Iris Willems , Patrick Calders , Eveline Dirinck , Manon Kinaupenne , Marga Decraene , Bruno Lapauw , Boyd Strumane , Margot Van Daele , Vera Verbestel , Marieke De Craemer

Aim

Physical activity (PA), sedentary behavior (SB) and sleep (i.e. 24-h movement behaviors) are associated with health indicators in people with prediabetes and type 2 diabetes (T2D). To optimize 24-h movement behaviors, it is crucial to identify explanatory variables related to these behaviors. This review aimed to summarize the explanatory variables of 24-h movement behaviors in people with prediabetes or T2D.

Methods

A systematic search of four databases (PubMed, Web of Science, Scopus & Embase) was performed. Only objective measurements of 24-h movement behaviors were included in the search strategy. The explanatory variables were classified according to the levels of the socio-ecological model (i.e. intrapersonal, interpersonal and environmental). The risk of bias was assessed using the Joanna Briggs Institute appraisal checklist.

Results

None of the 78 included studies investigated 24-h movement behaviors. The majority of the studies investigated PA in isolation. Most studied explanatory variables were situated at the intrapersonal level. Being male was associated with more moderate to vigorous PA but less light PA in people with T2D, and more total PA in people with prediabetes. An older age was associated with a decrease in all levels of PA in people with T2D. HbA1c was positively associated with sleep and SB in both groups. No associations were found at the interpersonal or environmental level.

Conclusion

The results of this review underscore the lack of a socio-ecological approach toward explanatory variables of 24-h movement behaviors and the lack of focus on an integrated 24-h movement behavior approach in both populations.

目的体力活动（PA）、久坐行为（SB）和睡眠（即 24 小时运动行为）与糖尿病前期和 2 型糖尿病（T2D）患者的健康指标相关。为了优化 24 小时运动行为，确定与这些行为相关的解释变量至关重要。本综述旨在总结糖尿病前期或 2 型糖尿病患者 24 小时运动行为的解释变量。方法对四个数据库（PubMed、Web of Science、Scopus & Embase）进行了系统检索。搜索策略只包括对 24 小时运动行为的客观测量。解释变量根据社会生态模型的层次（即人内、人际和环境）进行分类。结果在纳入的 78 项研究中，没有一项研究调查了 24 小时运动行为。大多数研究对运动负荷进行了单独调查。大多数研究的解释变量都位于个人内部层面。在患有 T2D 的人群中，男性与中度到剧烈运动较多但轻度运动较少有关，而在糖尿病前期人群中，男性与总运动量较多有关。年龄越大，T2D 患者所有水平的 PA 都越少。两组患者的 HbA1c 均与睡眠和 SB 呈正相关。结论：本综述的结果表明，在解释 24 小时运动行为的变量方面缺乏社会生态学方法，而且在这两种人群中缺乏对 24 小时运动行为综合方法的关注。

{"title":"Explanatory variables of objectively measured 24-h movement behaviors in people with prediabetes and type 2 diabetes: A systematic review","authors":"Lotte Bogaert , Iris Willems , Patrick Calders , Eveline Dirinck , Manon Kinaupenne , Marga Decraene , Bruno Lapauw , Boyd Strumane , Margot Van Daele , Vera Verbestel , Marieke De Craemer","doi":"10.1016/j.dsx.2024.102995","DOIUrl":"https://doi.org/10.1016/j.dsx.2024.102995","url":null,"abstract":"<div><h3>Aim</h3><p>Physical activity (PA), sedentary behavior (SB) and sleep (i.e. 24-h movement behaviors) are associated with health indicators in people with prediabetes and type 2 diabetes (T2D). To optimize 24-h movement behaviors, it is crucial to identify explanatory variables related to these behaviors. This review aimed to summarize the explanatory variables of 24-h movement behaviors in people with prediabetes or T2D.</p></div><div><h3>Methods</h3><p>A systematic search of four databases (PubMed, Web of Science, Scopus & Embase) was performed. Only objective measurements of 24-h movement behaviors were included in the search strategy. The explanatory variables were classified according to the levels of the socio-ecological model (i.e. intrapersonal, interpersonal and environmental). The risk of bias was assessed using the Joanna Briggs Institute appraisal checklist.</p></div><div><h3>Results</h3><p>None of the 78 included studies investigated 24-h movement behaviors. The majority of the studies investigated PA in isolation. Most studied explanatory variables were situated at the intrapersonal level. Being male was associated with more moderate to vigorous PA but less light PA in people with T2D, and more total PA in people with prediabetes. An older age was associated with a decrease in all levels of PA in people with T2D. HbA1c was positively associated with sleep and SB in both groups. No associations were found at the interpersonal or environmental level.</p></div><div><h3>Conclusion</h3><p>The results of this review underscore the lack of a socio-ecological approach toward explanatory variables of 24-h movement behaviors and the lack of focus on an integrated 24-h movement behavior approach in both populations.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":10.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Serum BAFF (B-cell activating factor) and APRIL (a proliferation-inducing ligand) levels in the first trimester may predict the future development of GDM (gestational diabetes mellitus) 妊娠头三个月的血清 BAFF（B 细胞活化因子）和 APRIL（一种增殖诱导配体）水平可预测未来 GDM（妊娠糖尿病）的发展情况

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-04-01 DOI: 10.1016/j.dsx.2024.103019

Sudipta Banerjeee, Pieu Adhikary, Bishal Kumar Dey, Subhankar Chowdhury, Rana Bhattacharjee

Background

Gestational diabetes mellitus (GDM) is a prevalent condition with an unclear pathogenesis. B-cell activating factor (BAFF) and a proliferation-inducing ligand (APRIL) are potential key players in GDM.

Participants, materials, and methods

In a longitudinal observational study, we monitored women from the first trimester through 24–28 weeks of gestation, focusing on the development of GDM. Serum levels of BAFF and APRIL, as well as their mRNA expression, were evaluated in both the first and third trimesters. Furthermore, we assessed cytokines, adipokines, and placental hormones in the serum.

Results

In the first trimester, participants who later developed GDM exhibited elevated serum BAFF and reduced serum APRIL levels, although the mRNA expression of these molecules was similar to controls. Serum BAFF exhibited significant positive correlations with metabolic markers and placental hormones. Conversely, serum APRIL was negatively correlated with insulin resistance and inflammatory markers but positively correlated with adiponectin. In the early third trimester, GDM participants continued to display higher serum BAFF levels and lower serum APRIL levels than controls. There was no significant difference in mRNA expression of BAFF between GDM and control groups. Conversely, APRIL mRNA expression was significantly lower in the GDM group. The predictive potential of first-trimester BAFF and APRIL levels for future GDM development was explored, with both molecules demonstrating strong predictive capability.

Discussion and conclusion

This study suggests that elevated serum BAFF and reduced serum APRIL levels during pregnancy may be associated with the development of GDM. These biomarkers can serve as potential early predictors for GDM.

背景妊娠糖尿病（GDM）是一种发病机制尚不清楚的常见疾病。参与者、材料和方法在一项纵向观察研究中，我们对妊娠头三个月至妊娠 24-28 周的妇女进行了监测，重点关注 GDM 的发展。在妊娠的前三个月和后三个月，我们对血清中 BAFF 和 APRIL 的水平及其 mRNA 表达进行了评估。此外，我们还评估了血清中的细胞因子、脂肪因子和胎盘激素。结果在妊娠头三个月，后来发展成 GDM 的参与者的血清 BAFF 水平升高，血清 APRIL 水平降低，但这些分子的 mRNA 表达与对照组相似。血清 BAFF 与代谢指标和胎盘激素呈显著正相关。相反，血清 APRIL 与胰岛素抵抗和炎症指标呈负相关，但与脂肪连通素呈正相关。与对照组相比，在妊娠早期三个月，GDM 参与者的血清 BAFF 水平仍然较高，而血清 APRIL 水平较低。GDM 组和对照组之间 BAFF 的 mRNA 表达没有明显差异。相反，GDM 组的 APRIL mRNA 表达明显较低。这项研究表明，妊娠期血清 BAFF 水平升高和血清 APRIL 水平降低可能与 GDM 的发生有关。这些生物标志物可作为 GDM 的潜在早期预测指标。

{"title":"Serum BAFF (B-cell activating factor) and APRIL (a proliferation-inducing ligand) levels in the first trimester may predict the future development of GDM (gestational diabetes mellitus)","authors":"Sudipta Banerjeee, Pieu Adhikary, Bishal Kumar Dey, Subhankar Chowdhury, Rana Bhattacharjee","doi":"10.1016/j.dsx.2024.103019","DOIUrl":"https://doi.org/10.1016/j.dsx.2024.103019","url":null,"abstract":"<div><h3>Background</h3><p>Gestational diabetes mellitus (GDM) is a prevalent condition with an unclear pathogenesis. B-cell activating factor (BAFF) and a proliferation-inducing ligand (APRIL) are potential key players in GDM.</p></div><div><h3>Participants, materials, and methods</h3><p>In a longitudinal observational study, we monitored women from the first trimester through 24–28 weeks of gestation, focusing on the development of GDM. Serum levels of BAFF and APRIL, as well as their mRNA expression, were evaluated in both the first and third trimesters. Furthermore, we assessed cytokines, adipokines, and placental hormones in the serum.</p></div><div><h3>Results</h3><p>In the first trimester, participants who later developed GDM exhibited elevated serum BAFF and reduced serum APRIL levels, although the mRNA expression of these molecules was similar to controls. Serum BAFF exhibited significant positive correlations with metabolic markers and placental hormones. Conversely, serum APRIL was negatively correlated with insulin resistance and inflammatory markers but positively correlated with adiponectin. In the early third trimester, GDM participants continued to display higher serum BAFF levels and lower serum APRIL levels than controls. There was no significant difference in mRNA expression of BAFF between GDM and control groups. Conversely, APRIL mRNA expression was significantly lower in the GDM group. The predictive potential of first-trimester BAFF and APRIL levels for future GDM development was explored, with both molecules demonstrating strong predictive capability.</p></div><div><h3>Discussion and conclusion</h3><p>This study suggests that elevated serum BAFF and reduced serum APRIL levels during pregnancy may be associated with the development of GDM. These biomarkers can serve as potential early predictors for GDM.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":10.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140632519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Highlights of the current issue 本期要点

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-04-01 DOI: 10.1016/j.dsx.2024.103035

Ningjian Wang (Associate Editor) , Anoop Misra (Editor-in-Chief)

引用次数: 0

Association of platelet-to-lymphocyte ratio levels with the risk of cardiac adverse events in people with type 2 diabetes undergoing percutaneous coronary intervention: A large-scale prospective cohort study 接受经皮冠状动脉介入治疗的 2 型糖尿病患者的血小板淋巴细胞比值水平与心脏不良事件风险的关系：大规模前瞻性队列研究

IF 1 Q1 Medicine

Diabetes & Metabolic Syndrome-Clinical Research & Reviews

Pub Date : 2024-03-01 DOI: 10.1016/j.dsx.2024.102987

Yanjun Song , Zhangyu Lin , Jining He , Kongyong Cui , Chenxi Song , Rui Zhang , Zechen Liu , Tao An , Guofeng Gao , Ying Gao , Kefei Dou

Background

The platelet-to-lymphocyte ratio (PLR), a promising inflammatory biomarker, contributes to the development of atherosclerosis and type 2 diabetes (T2D). Therefore, this study aimed to elucidate the importance of PLR in predicting adverse events in people undergoing percutaneous coronary intervention (PCI) with T2D.

Methods

We consecutively enrolled 8831 people who underwent PCI and divided them into four groups according to PLR and glycemic metabolic status (PLR-Low/High without T2D, PLR-Low/High with T2D). The endpoints were major adverse cardiovascular and cerebrovascular events (MACCE) and stent thrombosis. A multivariate Cox regression analysis was performed to determine this association.

Results

During the 2.4-year follow-up, 663 (7.5%) MACCE and 75 (0.85%) stent thromboses were recorded. The risk of MACCE (hazard ratio [HR]: 1.30, 95% confidence interval [CI]: 1.10–1.53, P = 0.002) and stent thrombosis (HR: 2.32, 95% CI: 1.38–3.90, P = 0.002) was significantly higher in people with high PLR levels than in those with low PLR. Among people with T2D, the PLR-High group showed a significantly higher risk of MACCE (HR: 1.59, 95% CI: 1.21–2.09, P = 0.001) and stent thrombosis (HR: 3.15, 95% CI: 1.32–7.52, P = 0.010). However, these associations were not significant in people without T2D.

Conclusions:

PLR has been originally documented as a significant predictor of poor prognosis and a high incidence of stent thrombosis in people undergoing PCI, especially in those with T2D.

背景血小板淋巴细胞比值（PLR）是一种很有前景的炎症生物标志物，它有助于动脉粥样硬化和 2 型糖尿病（T2D）的发展。因此，本研究旨在阐明 PLR 在预测接受经皮冠状动脉介入治疗（PCI）的 2 型糖尿病患者不良事件中的重要性。方法我们连续招募了 8831 名接受 PCI 治疗的患者，并根据 PLR 和血糖代谢状态将他们分为四组（PLR-低/高，无 2 型糖尿病；PLR-低/高，有 2 型糖尿病）。终点为主要不良心脑血管事件（MACCE）和支架血栓。结果在 2.4 年的随访中，共记录了 663 例（7.5%）MACCE 和 75 例（0.85%）支架血栓。PLR水平高者发生MACCE（危险比[HR]：1.30，95%置信区间[CI]：1.10-1.53，P = 0.002）和支架血栓（HR：2.32，95%置信区间[CI]：1.38-3.90，P = 0.002）的风险显著高于PLR水平低者。在患有 T2D 的人群中，PLR 高的人群发生 MACCE（HR：1.59，95% CI：1.21-2.09，P = 0.001）和支架血栓（HR：3.15，95% CI：1.32-7.52，P = 0.010）的风险明显更高。结论：PLR是PCI患者预后不良和支架血栓发生率高的重要预测因素，尤其是在T2D患者中。

{"title":"Association of platelet-to-lymphocyte ratio levels with the risk of cardiac adverse events in people with type 2 diabetes undergoing percutaneous coronary intervention: A large-scale prospective cohort study","authors":"Yanjun Song , Zhangyu Lin , Jining He , Kongyong Cui , Chenxi Song , Rui Zhang , Zechen Liu , Tao An , Guofeng Gao , Ying Gao , Kefei Dou","doi":"10.1016/j.dsx.2024.102987","DOIUrl":"https://doi.org/10.1016/j.dsx.2024.102987","url":null,"abstract":"<div><h3>Background</h3><p>The platelet-to-lymphocyte ratio (PLR), a promising inflammatory biomarker, contributes to the development of atherosclerosis and type 2 diabetes (T2D). Therefore, this study aimed to elucidate the importance of PLR in predicting adverse events in people undergoing percutaneous coronary intervention (PCI) with T2D.</p></div><div><h3>Methods</h3><p>We consecutively enrolled 8831 people who underwent PCI and divided them into four groups according to PLR and glycemic metabolic status (PLR-Low/High without T2D, PLR-Low/High with T2D). The endpoints were major adverse cardiovascular and cerebrovascular events (MACCE) and stent thrombosis. A multivariate Cox regression analysis was performed to determine this association.</p></div><div><h3>Results</h3><p>During the 2.4-year follow-up, 663 (7.5%) MACCE and 75 (0.85%) stent thromboses were recorded. The risk of MACCE (hazard ratio [HR]: 1.30, 95% confidence interval [CI]: 1.10–1.53, <em>P</em> = 0.002) and stent thrombosis (HR: 2.32, 95% CI: 1.38–3.90, <em>P</em> = 0.002) was significantly higher in people with high PLR levels than in those with low PLR. Among people with T2D, the PLR-High group showed a significantly higher risk of MACCE (HR: 1.59, 95% CI: 1.21–2.09, <em>P</em> = 0.001) and stent thrombosis (HR: 3.15, 95% CI: 1.32–7.52, <em>P</em> = 0.010). However, these associations were not significant in people without T2D.</p></div><div><h3>Conclusions:</h3><p>PLR has been originally documented as a significant predictor of poor prognosis and a high incidence of stent thrombosis in people undergoing PCI, especially in those with T2D.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":10.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140181026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0