Machine Learning Model in Predicting Sarcopenia in Crohn's Disease Based on Simple Clinical and Anthropometric Measures.
Machine Learning Model in Predicting Sarcopenia in Crohn's Disease Based on Simple Clinical and Anthropometric Measures.
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基于简单临床和人体测量测量的机器学习模型预测克罗恩病肌肉减少症
DOI：
10.3390/ijerph20010656
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发表时间：
2022-12-30
影响因子：
--
通讯作者：
Luo, Zhongguang
中科院分区：
文献类型：
--
作者：
Tseng, Yujen;Mo, Shaocong;Zeng, Yanwei;Zheng, Wanwei;Song, Huan;Zhong, Bing;Luo, Feifei;Rong, Lan;Liu, Jie;Luo, Zhongguang
肌减少症与克罗恩病的发病率和死亡率增加有关。本研究旨在研究不同机器学习模型在识别克罗恩病肌肉减少症方面的不同诊断性能。在我们中心诊断为克罗恩病的患者提供了临床、人体测量和放射学数据。L3的横截面CT切片用于分割和身体成分的计算。计算肌肉减少症的患病率，并比较临床参数。本研究共纳入167例患者，其中男性127例（76.0%），女性40例（24.0%），平均年龄36.1 ± 14.3岁。根据先前定义的肌肉减少症的临界值，118例（70.7%）患者患有肌肉减少症。7个机器学习模型使用随机分配的训练队列（80%）进行训练，然后在验证队列（20%）上进行评估。综合比较，LightGBM是最理想的诊断模型，AUC为0.933，AUCPR为0.970，灵敏度为72.7%，特异度为87.0%。LightGBM模型可以促进群体管理策略，早期识别克罗恩病中的肌肉减少症，同时为营养支持提供指导，并为长期患者随访提供替代监测模式。
Sarcopenia is associated with increased morbidity and mortality in Crohn’s disease. The present study is aimed at investigating the different diagnostic performance of different machine learning models in identifying sarcopenia in Crohn’s disease. Patients diagnosed with Crohn’s disease at our center provided clinical, anthropometric, and radiological data. The cross-sectional CT slice at L3 was used for segmentation and the calculation of body composition. The prevalence of sarcopenia was calculated, and the clinical parameters were compared. A total of 167 patients were included in the present study, of which 127 (76.0%) were male and 40 (24.0%) were female, with an average age of 36.1 ± 14.3 years old. Based on the previously defined cut-off value of sarcopenia, 118 (70.7%) patients had sarcopenia. Seven machine learning models were trained with the randomly allocated training cohort (80%) then evaluated on the validation cohort (20%). A comprehensive comparison showed that LightGBM was the most ideal diagnostic model, with an AUC of 0.933, AUCPR of 0.970, sensitivity of 72.7%, and specificity of 87.0%. The LightGBM model may facilitate a population management strategy with early identification of sarcopenia in Crohn’s disease, while providing guidance for nutritional support and an alternative surveillance modality for long-term patient follow-up.
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DOI：
10.3390/molecules21080983
发表时间：
2016-07-28
期刊：
Molecules (Basel, Switzerland)
影响因子：
--
作者：
Babajide Mustapha I;Saeed F
通讯作者：
Saeed F
影响因子：
3.9
作者：
Nishikawa H;Nakamura S;Miyazaki T;Kakimoto K;Fukunishi S;Asai A;Nishiguchi S;Higuchi K
通讯作者：
Higuchi K
影响因子：
8
作者：
Cushing, Kelly C.;Kordbacheh, Hamed;Ananthakrishnan, Ashwin N.
通讯作者：
Ananthakrishnan, Ashwin N.
影响因子：
7.6
作者：
Subramaniam, K.;Fallon, K.;Taupin, D.
通讯作者：
Taupin, D.
影响因子：
6.3
作者：
Cederholm, T.;Barazzoni, R.;Singer, P.
通讯作者：
Singer, P.