Abstract
PurposeTo establish and validate a nomogram model for predicting stress-related gastrointestinal bleeding in critically ill patients with primary intracerebral hemorrhage.Patients and MethodsFrom 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.ResultsA 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, P < 0.001], ICH volume (OR: 1.03, 95% CI: 1.02–1.05, P < 0.001) and sepsis (OR: 2.56, 95% CI: 1.54–4.25, P < 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, DF = 8, P = 0.425). Decision curve analysis demonstrated that the nomogram was clinically beneficial.ConclusionThe 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.
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