Development and validation of a risk prediction model for gastroesophageal reflux disease: Gastroesophageal Reflux Disease Risk Scoring System.

Shanmathi Subramanian, Umashri Sundararaju, Hamrish Kumar Rajakumar, Varsha Coimbatore Sathyabal, Arun Murugan, Pavithra Gnanavel, Kasinathan Sathishkumar
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Abstract

Background: The rising global prevalence of gastroesophageal reflux disease (GERD) has been closely linked to lifestyle changes driven by globalization. GERD imposes a substantial public health burden, affecting quality of life and leading to potential complications. Early intervention through lifestyle modification can prevent disease onset; however, there is a lack of effective risk prediction models that emphasize primary prevention.

Aim: To develop and validate a GERD Risk Scoring System (GRSS) aimed at identifying high-risk individuals and promoting primary prevention strategies.

Methods: A 45-item questionnaire encompassing major lifestyle and demographic risk factors was developed and validated. It was administered to healthy controls and GERD patients. Two regression models-one using continuous variables and another using categorized variables-were used to develop a computational prediction equation and a clinically applicable scoring scale. An independent validation cohort of 355 participants was used to assess model performance in terms of discrimination (C-index), calibration, sensitivity, specificity, internal consistency (Cronbach's alpha), and test-retest reliability (intraclass correlation coefficient, Bland-Altman analysis).

Results: Significant associations were observed between GERD and key lifestyle factors. The derived GRSS equation and scoring scale demonstrated strong discriminative ability, with high sensitivity and specificity. The scoring system exhibited excellent internal consistency (Cronbach's alpha) and strong test-retest reliability. The C-index indicated excellent predictive accuracy in both derivation and validation cohorts.

Conclusion: GRSS offers a novel and validated approach to GERD risk prediction, combining a robust equation for digital applications and a practical scale for clinical use. Its ability to accurately identify at-risk individuals supports a paradigm shift toward primary prevention, underscoring its significance in addressing the growing burden of GERD at the population level.

胃食管反流疾病风险预测模型的建立与验证:胃食管反流疾病风险评分系统。
背景:胃食管反流病(GERD)的全球患病率上升与全球化推动的生活方式改变密切相关。胃食管反流症给公众健康造成了沉重负担,影响生活质量并导致潜在并发症。通过改变生活方式进行早期干预可以预防疾病的发生;然而,目前缺乏强调初级预防的有效风险预测模型。目的:开发并验证一种GERD风险评分系统(GRSS),旨在识别高危人群并促进一级预防策略。方法:编制并验证了包含主要生活方式和人口危险因素的45项问卷。它被用于健康对照和胃食管反流患者。两个回归模型——一个使用连续变量,另一个使用分类变量——被用来建立一个计算预测方程和一个临床适用的评分量表。采用355名参与者的独立验证队列,从辨别力(c指数)、校准、敏感性、特异性、内部一致性(Cronbach’s alpha)和重测信度(类内相关系数、Bland-Altman分析)等方面评估模型的性能。结果:胃食管反流与主要生活方式因素有显著相关性。推导出的GRSS方程和评分量表判别能力强,具有较高的敏感性和特异性。评分系统具有良好的内部一致性(Cronbach’s alpha)和较强的重测信度。c指数在推导和验证队列中都显示出极好的预测准确性。结论:GRSS为GERD风险预测提供了一种新颖而有效的方法,结合了数字应用的稳健方程和临床应用的实际规模。它准确识别高危个体的能力支持了向初级预防的范式转变,强调了它在解决人口水平上日益增长的胃食管反流病负担方面的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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