Development and validation of a novel scoring system based on a nomogram for predicting inadequate bowel preparation

Xiaxia Zhao, Yanglin Pan, Jinyong Hao, Jie Feng, Zhongyuan Cui, Huimin Ma, Xiaojun Huang
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Abstract

Background and aims

Adequate bowel preparation (BP) is crucial for the diagnosis of colorectal diseases. Identifying patients at risk of inadequate BP allows for targeted interventions and improved outcomes. We aimed to develop a model for predicting inadequate BP based on preparation-related factors.

Methods

Adult outpatients scheduled for colonoscopy between May 2022 and October 2022 were enrolled. One set (N = 913) was used to develop and internally validate the predictive model. The primary predictive model was displayed as a nomogram and then modified into a novel scoring system, which was externally validated in an independent set (N = 177). Inadequate BP was defined as a Boston Bowel Preparedness Scale (BBPS) score of less than 2 for any colonic segment. The model was evaluated by the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA).

Results

Independent factors included in the prediction model were stool frequency ≤ 5 (15 points), preparation-to-colonoscopy interval ≥ 5 h (15 points), incomplete dosage (100 points), non-split dose (90 points), unrestricted diet (88 points), no additional water intake (15 points), and last stool appearance as an opaque liquid (0–80 points). The training set exhibited the following performance metrics for identifying BP failure: area under the curve (AUC) of 0.818, accuracy (ACC) of 0.818, positive likelihood ratio (PLR) of 2.397, negative likelihood ratio (NLR) of 0.162, positive predictive value (PPV) of 0.850, and negative predictive value (NPV) of 0.723. In the internal validation set, these metrics were 0.747, 0.776, 2.099, 0.278, 0.866, and 0.538, respectively. The external validation set showed values of 0.728, 0.757, 2.10, 0.247, 0.782, and 0.704, respectively, indicating strong discriminative ability. Calibration curves demonstrated close agreement, and DCA indicated superior clinical benefits at a threshold probability of 0.73 in the training cohort and 0.75 in the validation cohort for this model.

Conclusions

This novel scoring system was developed from a prospective study and externally validated in an independent set based on 7 easily accessible variables, demonstrating robust performance in predicting inadequate BP.

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基于预测肠道准备不足的提名图,开发并验证新型评分系统
背景和目的充分的肠道准备(BP)对结直肠疾病的诊断至关重要。识别有肠道准备不足风险的患者可进行有针对性的干预并改善预后。我们旨在开发一种基于准备相关因素预测 BP 不足的模型。其中一组(N = 913)用于开发和内部验证预测模型。主要预测模型以提名图的形式显示,然后修改为新的评分系统,并在一组独立样本(样本数 = 177)中进行外部验证。任何结肠段的波士顿肠道准备量表 (BBPS) 评分低于 2 分即为血压不足。结果预测模型中的独立因素包括大便次数≤5 次(15 分)、准备到结肠镜检查时间间隔≥5 小时(15 分)、剂量不完全(100 分)、非分次剂量(90 分)、饮食不受限制(88 分)、无额外水摄入(15 分)以及最后一次大便外观为不透明液体(0-80 分)。训练集在识别 BP 失败方面表现出以下性能指标:曲线下面积(AUC)为 0.818,准确率(ACC)为 0.818,正似然比(PLR)为 2.397,负似然比(NLR)为 0.在内部验证集中,这些指标分别为 0.747、0.776、2.099、0.278、0.866 和 0.538。外部验证集显示的值分别为 0.728、0.757、2.10、0.247、0.782 和 0.704,表明了很强的判别能力。校准曲线显示两者接近一致,DCA 显示该模型在训练队列中的阈值概率为 0.73,在验证队列中的阈值概率为 0.75,具有较好的临床效益。结论该新型评分系统是根据一项前瞻性研究开发的,并基于 7 个易于获取的变量在一个独立集上进行了外部验证,在预测血压不足方面表现出了强劲的性能。
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