AUTHOR=Du Shenghua , Su Ning , Yu Zhaoxian , Li Junhong , Jiang Yingyi , Zeng Limeng , Hu Jinxing 

TITLE=A prediction model for prognosis of nephrotic syndrome with tuberculosis in intensive care unit patients: a nomogram based on the MIMIC-IV v2.2 database

JOURNAL=Frontiers in Medicine

VOLUME=Volume 11 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2024.1413541

DOI=10.3389/fmed.2024.1413541

ISSN=2296-858X

ABSTRACT=such patients. combined with TB Therefore, it can aid clinicians in assessing the condition, judging prognosis, and making clinical decisions for Our clinical prediction model nomogram demonstrated a good predictive ability for in-hospital mortality among patients with NS Conclusion the risk threshold was 0.1 and 0.81. error of 0.013. The cross-validated C-index was 0.860. The decision curves indicated that patients benefited from this model when operating characteristic evaluation was 0.847 (0.812-0.881), with a calibration curve slope of 1.00 (0.83-1.17) and a mean absolute mortality, utilizing Alb, Bun, INR, HR, Abp, Resp, Glu, CVD, Sepsis-3, and AKI stage 7 days. The area under the curve of the receiver The cumulative in-hospital mortality rate for patients with NS and TB was 18.7%. A nomogram was created to predict in-hospital Results curve, calibration curves, internal cross-validation, and clinical decision curve analysis. regression model. The performance of the nomogram was tested and validated using the concordance index (C-index) of the ROC characteristic(ROC) curve analyses were used to select determinant variables. A nomogram was established by using a logistic Least Absolute Shrinkage and Selection Operator (LASSO) regression and the diagnostic experiment the receiver operating complicated by TB infection. Confounding factors included demographics, vital signs, laboratory indicators, and comorbidities. The We utilized the Medical Information Mart for Intensive Care IV version 2.2 (MIMIC-IV v2.2) database to include 1063 patients with NS Methods decision-making. crucial risk factors, and create a sturdy prognostic prediction model that can improve disease evaluation and guide clinical tuberculosis. The purpose of this study was to assess the in-hospital mortality status of NS patients with tuberculosis, identify Currently, a scarcity of prognostic research exists that concentrates on patients with nephrotic syndrome (NS) who also have Background 283