ArticleIndian heart journal
First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU).
Article in Indian heart journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Article
- Sardjito Cardiovascular Intensive Care Score as an Alternative to Mayo Cardiac Admission Risk Score for Predicting Mortality in Cardiovascular Intensive Care Patients.Cardiology research · 2026Article
- Biventricular dysfunction predicts mortality in ST elevation myocardial infarction patients with cardiogenic shock.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesThe application of prognostic scoring systems to identify risk of death within 24 h of CICU admission has significant consequences for clinical decision-making. Previous score of parameters collected after 24 h was considered too late to predict mortality. As a result, we attempted to develop a CICU admission risk score to predict hospital mortality using indicators collected within 24 h.
methodsData were obtained from SCIENCE registry from January 1, 2021 to December 21, 2021. Outcomes of 657 patients (mean age 58.91 ± 12.8 years) were recorded retrospectively. Demography, risk factors, comorbidities, vital signs, laboratory and echocardiography data at 24-h of patient admitted to CICU were analysed by multivariate logistic regression to create two models of scoring system (probability and cut-off model) to predict in-hospital mortality of any cause.
resultsFrom a total of 657 patients, the hospital mortality was 15%. The significant predictors of mortality were male, acute heart failure, hemodynamic instability, pneumonia, baseline creatinine ≥1.5 mg/dL, TAPSE <17 mm, and the use of mechanical ventilator within first 24-h of CICU admission. Based on Receiver Operating Characteristic (ROC) curve analysis a cut off of ≥3 is considered to be a high risk of in-hospital mortality (sensitivity 75% and specificity 65%).
conclusionThe initial 24-h SCIENCE admission risk rating system can be used to predict in-hospital mortality in patients admitted to the CICU with a high degree of sensitivity and specificity.
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