Liu Shucheng, Wang Yilin, Gao Bin, Peng Jun
Department of Urology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang City, Hunan Province, People's Republic of China.
Department of Neurology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang City, Hunan Province, People's Republic of China.
Neuropsychiatr Dis Treat. 2022 Feb 9;18:221-229. doi: 10.2147/NDT.S342861. eCollection 2022.
To establish and validate a nomogram model for predicting stress-related gastrointestinal bleeding in critically ill patients with primary intracerebral hemorrhage.
From January 2018 to March 2021, we conducted a hospital-based study by screening eligible patients with acute intracerebral hemorrhage. Univariate and multivariate logistic regression analyses were performed to determine the predictors for stress-related gastrointestinal bleeding in patients with primary intracerebral hemorrhage. The nomogram was constructed on the basis of multivariate logistic model and was internally validated by bootstrap resampling. The discriminative performance of the nomogram was evaluated using the calibration and concordance index (C-index), which was equal to the area under the curve of receiver-operating characteristics. Hosmer-Lemeshow test was performed to check the model's goodness of fit. A decision curve analysis was used to assess its clinical utility.
A total of 410 patients were enrolled in this study. Stress-related gastrointestinal bleeding occurred in 115 patients (28.0%). Multivariate analysis demonstrated that gastric pH at admission [odds ratio (OR): 0.52, 95% confidence interval (CI): 0.41-0.66, < 0.001], ICH volume (OR: 1.03, 95% CI: 1.02-1.05, < 0.001) and sepsis (OR: 2.56, 95% CI: 1.54-4.25, < 0.001) were independent predictors for stress-related gastrointestinal bleeding in critically ill patients with ICH. The nomogram including gastric pH at admission, ICH volume and sepsis presented good discrimination with C-index of 0.770 (95% CI: 0.716 to 0.822), which was confirmed to be 0.764 through bootstrapping validation. The calibration plot showed good agreement between the predicted and observed outcomes. The Hosmer-Lemeshow test showed a goodness-of-fit (Chi-Square = 8.085, = 8, = 0.425). Decision curve analysis demonstrated that the nomogram was clinically beneficial.
The proposed nomogram based on gastric pH at admission, ICH volume and sepsis can accurately predict the risk of stress-related gastrointestinal bleeding in critically ill patients with primary intracerebral hemorrhage.
建立并验证一种用于预测原发性脑出血重症患者应激性胃肠道出血的列线图模型。
2018年1月至2021年3月，我们通过筛选符合条件的急性脑出血患者进行了一项基于医院的研究。进行单因素和多因素逻辑回归分析，以确定原发性脑出血患者应激性胃肠道出血的预测因素。列线图基于多因素逻辑模型构建，并通过自抽样重采样进行内部验证。使用校准和一致性指数（C指数）评估列线图的判别性能，C指数等于受试者操作特征曲线下面积。进行Hosmer-Lemeshow检验以检查模型的拟合优度。采用决策曲线分析评估其临床实用性。
本研究共纳入410例患者。115例患者（28.0%）发生应激性胃肠道出血。多因素分析表明，入院时胃pH值[比值比（OR）：0.52，95%置信区间（CI）：0.41 - 0.66，P < 0.001]、脑出血体积（OR：1.03，95%CI：1.02 - 1.05，P < 0.001）和脓毒症（OR：2.56，95%CI：1.54 - 4.25，P < 0.001）是脑出血重症患者应激性胃肠道出血的独立预测因素。包含入院时胃pH值、脑出血体积和脓毒症的列线图表现出良好的判别能力，C指数为0.770（95%CI：0.716至0.82）经自抽样验证为0.764。校准图显示预测结果与观察结果之间具有良好的一致性。Hosmer-Lemeshow检验显示拟合优度良好（卡方 = 8.085，自由度 = 8，P = 0.425）。决策曲线分析表明列线图具有临床益处。
基于入院时胃pH值、脑出血体积和脓毒症提出的列线图能够准确预测原发性脑出血重症患者应激性胃肠道出血的风险。
