First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU)
Background and objectives: The 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...
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| Format: | Article |
| Language: | English |
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Cardiology Society of India
2022
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| Online Access: | https://repository.ugm.ac.id/284215/1/Bagaswoto_KKMK.pdf |
| _version_ | 1826050763393073152 |
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| author | Bagaswoto, Hendry Purnasidha Ardelia, Yuwinda Prima Setianto, Budi Yuli |
| author_facet | Bagaswoto, Hendry Purnasidha Ardelia, Yuwinda Prima Setianto, Budi Yuli |
| author_sort | Bagaswoto, Hendry Purnasidha |
| collection | UGM |
| description | Background and objectives: The 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. Methods: Data 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. Results: From 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 inhospital mortality (sensitivity 75% and specificity 65%).
Conclusion: The 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. |
| first_indexed | 2024-03-14T00:09:42Z |
| format | Article |
| id | oai:generic.eprints.org:284215 |
| institution | Universiti Gadjah Mada |
| language | English |
| last_indexed | 2024-03-14T00:09:42Z |
| publishDate | 2022 |
| publisher | Cardiology Society of India |
| record_format | dspace |
| spelling | oai:generic.eprints.org:2842152023-11-29T07:45:16Z https://repository.ugm.ac.id/284215/ First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU) Bagaswoto, Hendry Purnasidha Ardelia, Yuwinda Prima Setianto, Budi Yuli Cardiovascular Medicine and Haematology Cardiology (incl. Cardiovascular Diseases) Background and objectives: The 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. Methods: Data 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. Results: From 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 inhospital mortality (sensitivity 75% and specificity 65%). Conclusion: The 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. Cardiology Society of India 2022-11-01 Article PeerReviewed application/pdf en https://repository.ugm.ac.id/284215/1/Bagaswoto_KKMK.pdf Bagaswoto, Hendry Purnasidha and Ardelia, Yuwinda Prima and Setianto, Budi Yuli (2022) First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU). Indian Heart Journal, 74 (6). pp. 513-518. ISSN 00194832 https://www.clinicalkey.com/#!/content/playContent/1-s2.0-S0019483222003583?returnurl=https:%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0019483222003583%3Fshowall%3Dtrue&referrer= https://doi.org/10.1016/j.ihj.2022.11.002 |
| spellingShingle | Cardiovascular Medicine and Haematology Cardiology (incl. Cardiovascular Diseases) Bagaswoto, Hendry Purnasidha Ardelia, Yuwinda Prima Setianto, Budi Yuli First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU) |
| title | First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU) |
| title_full | First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU) |
| title_fullStr | First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU) |
| title_full_unstemmed | First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU) |
| title_short | First 24-h Sardjito Cardiovascular Intensive Care (SCIENCE) admission risk score to predict mortality in cardiovascular intensive care unit (CICU) |
| title_sort | first 24 h sardjito cardiovascular intensive care science admission risk score to predict mortality in cardiovascular intensive care unit cicu |
| topic | Cardiovascular Medicine and Haematology Cardiology (incl. Cardiovascular Diseases) |
| url | https://repository.ugm.ac.id/284215/1/Bagaswoto_KKMK.pdf |
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