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医学实习生饮食与营养咨询能力的地区差异:一项前瞻性多中心队列研究的机器学习增强倾向评分分析

Regional variations in medical trainee diet and nutrition counseling competencies: Machine learning-augmented propensity score analysis of a prospective multi-site cohort study.

作者信息

Patnaik Anish, Tran Justin, McWhorter John W, Burks Helen, Ngo Alexandra, Nguyen Tu Dan, Mody Avni, Moore Laura, Hoelscher Deanna M, Dyer Amber, Sarris Leah, Harlan Timothy, Chassay C Mark, Monlezun Dominique

机构信息

McGovern Medical School, University of Texas Health Sciences Center at Houston (UTHealth), Houston, TX USA.

School of Public Health, University of Texas Health Sciences Center at Houston (UTHealth), Houston, TX USA.

出版信息

Med Sci Educ. 2020 May 20;30(2):911-915. doi: 10.1007/s40670-020-00973-6. eCollection 2020 Jun.

Abstract

BACKGROUND

Medical professionals and students are inadequately trained to respond to rising global obesity and nutrition-related chronic disease epidemics, primarily focusing on cardiovascular disease. Yet, there are no multi-site studies testing evidence-based nutrition education for medical students in preventive cardiology, let alone establishing student dietary and competency patterns.

METHODS

Cooking for Health Optimization with Patients (CHOP; NIH NCT03443635) was the first multi-national cohort study using hands-on cooking and nutrition education as preventive cardiology, monitoring and improving student diets and competencies in patient nutrition education. Propensity-score adjusted multivariable regression was augmented by 43 supervised machine learning algorithms to assess students outcomes from UT Health versus the remaining study sites.

RESULTS

3,248 medical trainees from 20 medical centers and colleges met study criteria from 1 August 2012 to 31 December 2017 with 60 (1.49%) being from UTHealth. Compared to the other study sites, trainees from UTHealth were more likely to consume vegetables daily (OR 1.82, 95%CI 1.04-3.17, p=0.035), strongly agree that nutrition assessment should be routine clinical practice (OR 2.43, 95%CI 1.45-4.05, p=0.001), and that providers can improve patients' health with nutrition education (OR 1.73, 95%CI 1.03-2.91, p=0.038). UTHealth trainees were more likely to have mastered 12 of the 25 competency topics, with the top three being moderate alcohol intake (OR 1.74, 95%CI 0.97-3.11, p=0.062), dietary fats (OR 1.26, 95%CI 0.57-2.80, p=0.568), and calories (OR 1.26, 95%CI 0.70-2.28, p=0.446).

CONCLUSION

This machine learning-augmented causal inference analysis provides the first results that compare medical students nationally in their diets and competencies in nutrition education, highlighting the results from UTHealth. Additional studies are required to determine which factors in the hands-on cooking and nutrition curriculum for UTHealth and other sites produce optimal student - and, eventually, preventive cardiology - outcomes when they educate patients in those classes.

摘要

背景

医疗专业人员和学生在应对全球肥胖率上升和营养相关慢性病流行方面的培训不足,主要侧重于心血管疾病。然而,尚无多中心研究测试针对预防心脏病学专业医学生的循证营养教育,更不用说确立学生的饮食和能力模式了。

方法

“与患者一起进行健康烹饪优化”(CHOP;美国国立卫生研究院NCT03443635)是第一项多国队列研究,将实践烹饪和营养教育作为预防心脏病学的内容,监测并改善学生的饮食以及他们在患者营养教育方面的能力。倾向得分调整后的多变量回归通过43种监督机器学习算法进行增强,以评估德克萨斯大学健康科学中心(UT Health)的学生与其他研究地点的学生的结果。

结果

2012年8月1日至2017年12月31日,来自20个医疗中心和学院的3248名医学实习生符合研究标准,其中60名(1.49%)来自UT Health。与其他研究地点相比,UT Health的实习生更有可能每天食用蔬菜(比值比1.82,95%置信区间1.04 - 3.17,p = 0.035),强烈同意营养评估应成为常规临床实践(比值比2.43,95%置信区间1.

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