ArticleInfection and drug resistance2023
Nomogram Prediction Model of Hypernatremia on Mortality in Critically Ill Patients.
Article in Infection and drug resistance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Admission Serum Sodium as an Early Integrative Marker of Shock Severity in Acute Myocardial Infarction-Complicated Cardiogenic Shock.Biomedicines · 2026Article
- Electronic health record dynamic features for in-hospital death among chronic kidney disease patients.Scientific reports · 2026Article
- Influence of hydrocortisone infusion method on the clinical outcome of patients with septic shock: A systematic review and meta-analysis.Journal of intensive medicine · 2025Article
- Effect of long-term serum sodium levels on the prognosis of patients on maintenance hemodialysis.Renal failure · 2024Article
- Prognostic Impact of the Early Use of Tolvaptan in Elderly Patients with Acute Decompensated Heart Failure.Journal of clinical medicine · 2023Article
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Authors and funding
6 authors.
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Abstract
Objective: To investigate the value of hypernatremia in the intensive care unit (ICU) for the risk prediction of mortality in severe patients. Methods: Clinical data of critically ill patients admitted to the ICU of Beijing Friendship Hospital, were collected for retrospective analysis. Univariate and multivariate logistic regression analyses were employed to analyze the influencing factors. Nomograms predicting the mortality were constructed with R software and validated with repeated sampling. Results: A total of 442 cases were eligible for this study. Hypernatremia within 48 hours of ICU admission, change in sodium concentration (CNa+) within 48 hours, septic shock, APACHE II score, hyperlactatemia within 48 hours, use of continuous renal replacement therapy (CRRT) within 48 hours, and the use of mechanical ventilation (MV) within 48 hours of ICU admission were all identified as independent risk factors for death within 28 days of ICU admission. These predictors were included in a nomogram of 28-day mortality in severe patients, which was constructed using R software. Conclusion: The nomogram could predict the individualized risk of 28-day mortality based on the above factors. The model has better discrimination and accuracy and has high clinical application value.
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