• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

开发并验证了一个针对美国成年糖尿病患者全因死亡率的列线图。

Development and validation of a nomogram of all-cause mortality in adult Americans with diabetes.

机构信息

Department of Nursing, School of Health and Nursing, Wuxi Taihu University, 68 Qian Rong Rode, Bin Hu District, Wuxi, China.

Cardiac Catheter Room, Wuxi People's Hospital, Jiangsu, No.299 Qing Yang Road, Wuxi, 214000, China.

出版信息

Sci Rep. 2024 Aug 19;14(1):19148. doi: 10.1038/s41598-024-69581-3.

DOI:10.1038/s41598-024-69581-3
PMID:39160223
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11333764/
Abstract

This study aimed to develop and validate a predictive model of all-cause mortality risk in American adults aged ≥ 18 years with diabetes. 7918 participants with diabetes were enrolled from the National Health and Nutrition Examination Survey (NHANES) 1999-2016 and followed for a median of 96 months. The primary study endpoint was the all-cause mortality. Predictors of all-cause mortality included age, Monocytes, Erythrocyte, creatinine, Nutrition Risk Index (NRI), neutrophils/lymphocytes (NLR), smoking habits, alcohol consumption, cardiovascular disease (CVD), urinary albumin excretion rate (UAE), and insulin use. The c-index was 0.790 (95% CI 0.779-0.801, P < 0.001) and 0.792 (95% CI: 0.776-0.808, P < 0.001) for the training and validation sets, respectively. The area under the ROC curve was 0.815, 0.814, 0.827 and 0.812, 0.818 and 0.829 for the training and validation sets at 3, 5, and 10 years of follow-up, respectively. Both calibration plots and DCA curves performed well. The model provides accurate predictions of the risk of death for American persons with diabetes and its scores can effectively determine the risk of death in outpatients, providing guidance for clinical decision-making and predicting prognosis for patients.

摘要

本研究旨在为年龄≥18 岁的美国成年糖尿病患者建立并验证一个全因死亡率风险预测模型。从 1999 年至 2016 年的全国健康和营养检查调查(NHANES)中纳入了 7918 名糖尿病患者,并对其进行了中位数为 96 个月的随访。主要研究终点为全因死亡率。全因死亡率的预测因子包括年龄、单核细胞、红细胞、肌酐、营养风险指数(NRI)、中性粒细胞/淋巴细胞比值(NLR)、吸烟习惯、饮酒、心血管疾病(CVD)、尿白蛋白排泄率(UAE)和胰岛素使用情况。训练集和验证集的 c 指数分别为 0.790(95%CI:0.779-0.801,P<0.001)和 0.792(95%CI:0.776-0.808,P<0.001)。训练集和验证集的 ROC 曲线下面积分别为 0.815、0.814、0.827 和 0.812、0.818 和 0.829,在随访 3、5 和 10 年时。校准图和 DCA 曲线均表现良好。该模型能准确预测美国糖尿病患者的死亡风险,其评分可有效确定门诊患者的死亡风险,为临床决策提供指导并预测患者预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/822b3a8461bc/41598_2024_69581_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/d4701b52f4df/41598_2024_69581_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/916da0d22805/41598_2024_69581_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/7af39e44ca1d/41598_2024_69581_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/1aa95b70123c/41598_2024_69581_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/356dc8b892e0/41598_2024_69581_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/822b3a8461bc/41598_2024_69581_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/d4701b52f4df/41598_2024_69581_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/916da0d22805/41598_2024_69581_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/7af39e44ca1d/41598_2024_69581_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/1aa95b70123c/41598_2024_69581_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/356dc8b892e0/41598_2024_69581_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/445e/11333764/822b3a8461bc/41598_2024_69581_Fig6_HTML.jpg

相似文献

1
Development and validation of a nomogram of all-cause mortality in adult Americans with diabetes.开发并验证了一个针对美国成年糖尿病患者全因死亡率的列线图。
Sci Rep. 2024 Aug 19;14(1):19148. doi: 10.1038/s41598-024-69581-3.
2
Development and validation of nomograms for predicting cardiovascular disease risk in patients with prediabetes and diabetes.开发和验证预测糖尿病前期和糖尿病患者心血管疾病风险的列线图。
Sci Rep. 2024 Sep 8;14(1):20909. doi: 10.1038/s41598-024-71904-3.
3
Development and Validation of a Nomogram Model for Individualizing the Risk of Osteopenia in Abdominal Obesity.腹型肥胖患者骨量减少风险个体化的列线图模型的建立与验证。
J Clin Densitom. 2024 Apr-Jun;27(2):101469. doi: 10.1016/j.jocd.2024.101469. Epub 2024 Jan 24.
4
[Development and validation of a nomogram for predicting 3-month mortality risk in patients with sepsis-associated acute kidney injury].[用于预测脓毒症相关性急性肾损伤患者3个月死亡风险的列线图的开发与验证]
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2024 May;36(5):465-470. doi: 10.3760/cma.j.cn121430-20231218-01091.
5
Development and validation of a nomogram for predicting all-cause mortality in American adult hypertensive populations.美国成年高血压人群全因死亡率预测列线图的开发与验证
Front Pharmacol. 2023 Nov 22;14:1266870. doi: 10.3389/fphar.2023.1266870. eCollection 2023.
6
Navigating the future of diabetes: innovative nomogram models for predicting all-cause mortality risk in diabetic nephropathy.糖尿病的未来展望:预测糖尿病肾病全因死亡率的创新诺模图模型。
BMC Nephrol. 2024 Apr 10;25(1):127. doi: 10.1186/s12882-024-03563-5.
7
Development and validation of a novel nomogram to predict overall survival of patients with moderate to severe chronic kidney disease.开发和验证一种新的列线图模型,以预测中重度慢性肾脏病患者的总生存情况。
Ren Fail. 2022 Jan 23;44(1):241-249. doi: 10.1080/0886022X.2022.2032744.
8
Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms.基于机器学习算法的行连续性肾脏替代治疗的急性肾损伤患者死亡率预测模型的构建与评估。
Ann Med. 2024 Dec;56(1):2388709. doi: 10.1080/07853890.2024.2388709. Epub 2024 Aug 19.
9
[Analysis of 28 day-mortality risk factors in sepsis patients and construction and validation of predictive model].[脓毒症患者28天死亡风险因素分析及预测模型的构建与验证]
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2024 May;36(5):478-484. doi: 10.3760/cma.j.cn121430-20231109-00961.
10
Development, validation, and visualization of a web-based nomogram to predict 5-year mortality risk in older adults with hypertension.开发、验证和可视化一个基于网络的列线图,以预测高血压老年患者 5 年死亡率风险。
BMC Geriatr. 2022 May 4;22(1):392. doi: 10.1186/s12877-022-03087-3.

引用本文的文献

1
Predictive value of the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) for all-cause and cardiovascular mortality with non-hyperhomocysteinemia: evidence from NHANES 1999 to 2006.非高密度脂蛋白胆固醇与高密度脂蛋白胆固醇比值(NHHR)对非高同型半胱氨酸血症患者全因死亡率和心血管死亡率的预测价值:来自1999年至2006年美国国家健康和营养检查调查(NHANES)的证据
Front Nutr. 2025 May 20;12:1586558. doi: 10.3389/fnut.2025.1586558. eCollection 2025.
2
Integration of the systemic inflammatory response index with pulse pressure enhances prognostication of cardiovascular mortality in the general population of the United States: insights from the NHANES database.全身炎症反应指数与脉压相结合可增强对美国普通人群心血管死亡率的预测:来自美国国家健康与营养检查调查(NHANES)数据库的见解。
Front Cardiovasc Med. 2024 Nov 18;11:1439239. doi: 10.3389/fcvm.2024.1439239. eCollection 2024.

本文引用的文献

1
Elevated serum creatinine levels and risk of cognitive impairment in older adults with diabetes: a NHANES study from 2011-2014.血清肌酐水平升高与老年糖尿病患者认知障碍风险的相关性研究:来自 2011-2014 年 NHANES 的研究。
Front Endocrinol (Lausanne). 2023 Oct 12;14:1149084. doi: 10.3389/fendo.2023.1149084. eCollection 2023.
2
Prognostic Utility of Nutritional Risk Index in Patients with Head and Neck Soft Tissue Sarcoma.营养风险指数对头颈部软组织肉瘤患者预后的预测价值。
Nutrients. 2023 Jan 26;15(3):641. doi: 10.3390/nu15030641.
3
Developing a prediction model for all-cause mortality risk among patients with type 2 diabetes mellitus in Shanghai, China.
建立中国上海 2 型糖尿病患者全因死亡率风险预测模型。
J Diabetes. 2023 Jan;15(1):27-35. doi: 10.1111/1753-0407.13343. Epub 2022 Dec 16.
4
Association Between Psoriasis and Nonalcoholic Fatty Liver Disease Among Outpatient US Adults.美国门诊成年人银屑病与非酒精性脂肪性肝病的相关性。
JAMA Dermatol. 2022 Jul 1;158(7):745-753. doi: 10.1001/jamadermatol.2022.1609.
5
Efficacy of the Nutritional Risk Index, Geriatric Nutritional Risk Index, BMI, and GLIM-Defined Malnutrition in Predicting Survival of Patients with Head and Neck Cancer Patients Qualified for Home Enteral Nutrition.营养风险指数、老年营养风险指数、BMI 和 GLIM 定义的营养不良在预测有条件接受家庭肠内营养的头颈部癌症患者生存中的疗效。
Nutrients. 2022 Mar 17;14(6):1268. doi: 10.3390/nu14061268.
6
Trends in all-cause mortality among people with diagnosed diabetes in high-income settings: a multicountry analysis of aggregate data.高收入国家确诊糖尿病患者全因死亡率趋势:汇总数据分析的多国研究
Lancet Diabetes Endocrinol. 2022 Feb;10(2):112-119. doi: 10.1016/S2213-8587(21)00327-2. Epub 2022 Jan 10.
7
Development and Validation of a Prediction Model for Survival in Diabetic Patients With Acute Kidney Injury.开发和验证糖尿病急性肾损伤患者生存预测模型。
Front Endocrinol (Lausanne). 2021 Dec 22;12:737996. doi: 10.3389/fendo.2021.737996. eCollection 2021.
8
The relationship between urinary albumin to creatinine ratio and all-cause mortality in the elderly population in the Chinese community: a 10-year follow-up study.尿白蛋白与肌酐比值与华裔老年人群全因死亡率的关系:一项为期 10 年的随访研究。
BMC Nephrol. 2022 Jan 5;23(1):16. doi: 10.1186/s12882-021-02644-z.
9
Nutritional Risk Index Improves the GRACE Score Prediction of Clinical Outcomes in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.营养风险指数改善接受经皮冠状动脉介入治疗的急性冠状动脉综合征患者临床结局的GRACE评分预测。
Front Cardiovasc Med. 2021 Dec 16;8:773200. doi: 10.3389/fcvm.2021.773200. eCollection 2021.
10
Developing a Prediction Model for 7-Year and 10-Year All-Cause Mortality Risk in Type 2 Diabetes Using a Hospital-Based Prospective Cohort Study.利用一项基于医院的前瞻性队列研究开发2型糖尿病患者7年和10年全因死亡风险预测模型。
J Clin Med. 2021 Oct 18;10(20):4779. doi: 10.3390/jcm10204779.