Objective: Congestive heart failure (CHF) is a clinical syndrome in which heart disease progresses to a severe stage. Risk assessment and early diagnosis of death in patients with CHF are critical to patient prognosis and treatment. The purpose of this study was to establish a nomogram predicting in-hospital death for CHF patients in the ICU. Design: A retrospective observational cohort study. Setting and participants: The data of study from 30,411 CHF patients in the Medical Information Mart for Intensive Care (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD). Primary outcome: In-hospital mortality. Results: The inclusion criteria were met by 15983 subjects, whose in-hospital mortality rate was 12.4%. Multivariate analysis determined that the independent risk factors were age, race, norepinephrine, dopamine, phenylephrine, vasopressin, mechanical ventilation, intubation, HepF, heart rate, respiratory rate, temperature, SBP, AG, BUN, creatinine, chloride, MCV, RDW, and WBC. The C-index of the nomogram (0.767, 95%CI: 0.759–0.779) was superior to that of the traditional SOFA, APSIII and GWTGHF score, indicating its discrimination power. Calibration plots demonstrated that the predicted results are in good agreement with the observed results. The decision curves of the derivation and validation sets both had net benefits. Conclusion: The twenty independent risk factors for in-hospital mortality of CHF patients were age, race, norepinephrine, dopamine, phenylephrine, vasopressin, mechanical ventilation, intubation, HepF, heart rate, respiratory rate, temperature, SBP, AG, BUN, creatinine, chloride, MCV, RDW, and WBC. The nomogram that included these factors accurately predicted the in-hospital mortality of CHF patients. The novel nomogram has the potential to be a clinical practice aided predictive tool for predicting and assessing mortality in CHF patients in the ICU.

Additional file 2.

Additional file 2.

Additional file 2: Table S1. the single nucleotide polymorphisms (SNPs) that showed significant genome-wide association with AD,(the SNP loci of newly discovered genes in the UKB database were not included). Table S2. BMI served as the exposure (based on the UKB study , https://gwas.mrcieu.ac.uk/ ; GWAS ID: ukb-b-19953). Table S3. The datasets as AD outcome (based on another GWASs, https://gwas.mrcieu.ac.uk/ ; GWAS ID: ieu-b-2). Table S4. AD served as the exposure (based on another GWASs, https://gwas.mrcieu.ac.uk/ ; GWAS ID: ieu-b-2). Table S5. BMI served as the outcome (based on the UKB study , https://gwas.mrcieu.ac.uk/ ; GWAS ID: ukb-b-19953)

Additional file 2: Table S1. the single nucleotide polymorphisms (SNPs) that showed significant genome-wide association with AD,(the SNP loci of newly discovered genes in the UKB database were not included). Table S2. BMI served as the exposure (based on the UKB study , https://gwas.mrcieu.ac.uk/ ; GWAS ID: ukb-b-19953). Table S3. The datasets as AD outcome (based on another GWASs, https://gwas.mrcieu.ac.uk/ ; GWAS ID: ieu-b-2). Table S4. AD served as the exposure (based on another GWASs, https://gwas.mrcieu.ac.uk/ ; GWAS ID: ieu-b-2). Table S5. BMI served as the outcome (based on the UKB study , https://gwas.mrcieu.ac.uk/ ; GWAS ID: ukb-b-19953)