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Troisi F, Guida P, Vitulano N, Argentiero A, Passantino A, Iacoviello M, Grimaldi M. Clinical complexity of an Italian cardiovascular intensive care unit: the role of mortality and severity risk scores. J Cardiovasc Med (Hagerstown) 2024; 25:511-518. [PMID: 38829938 DOI: 10.2459/jcm.0000000000001632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
AIMS The identification of patients at greater mortality risk of death at admission into an intensive cardiovascular care unit (ICCU) has relevant consequences for clinical decision-making. We described patient characteristics at admission into an ICCU by predicted mortality risk assessed with noncardiac intensive care unit (ICU) and evaluated their performance in predicting patient outcomes. METHODS A total of 202 consecutive patients (130 men, 75 ± 12 years) were admitted into our tertiary-care ICCU in a 20-week period. We evaluated, on the first 24 h data, in-hospital mortality risk according to Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score 3 (SAPS 3); Sepsis related Organ Failure Assessment (SOFA) Score and the Mayo Cardiac intensive care unit Admission Risk Score (M-CARS) were also calculated. RESULTS Predicted mortality was significantly lower than observed (5% during ICCU and 7% at discharge) for APACHE II and SAPS 3 (17% for both scores). Mortality risk was associated with older age, more frequent comorbidities, severe clinical presentation and complications. The APACHE II, SAPS 3, SOFA and M-CARS had good discriminative ability in distinguishing deaths and survivors with poor calibration of risk scores predicting mortality. CONCLUSION In a recent contemporary cohort of patients admitted into the ICCU for a variety of acute and critical cardiovascular conditions, scoring systems used in general ICU had good discrimination for patients' clinical severity and mortality. Available scores preserve powerful discrimination but the overestimation of mortality suggests the importance of specific tailored scores to improve risk assessment of patients admitted into ICCUs.
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Affiliation(s)
- Federica Troisi
- Cardiology Department, Regional General Hospital 'F. Miulli', Acquaviva delle Fonti, Italy
| | - Pietro Guida
- Cardiology Department, Regional General Hospital 'F. Miulli', Acquaviva delle Fonti, Italy
| | - Nicola Vitulano
- Cardiology Department, Regional General Hospital 'F. Miulli', Acquaviva delle Fonti, Italy
| | - Adriana Argentiero
- Cardiology Department, Regional General Hospital 'F. Miulli', Acquaviva delle Fonti, Italy
| | - Andrea Passantino
- Scientific Clinical Institutes Maugeri, Institutes of Care and Research, Institute of Bari, Bari
| | - Massimo Iacoviello
- Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy
| | - Massimo Grimaldi
- Cardiology Department, Regional General Hospital 'F. Miulli', Acquaviva delle Fonti, Italy
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Rammos A, Bechlioulis A, Chatzipanteliadou S, Sioros SA, Floros CD, Stamou I, Lakkas L, Kalogeras P, Bouratzis V, Katsouras CS, Michalis LK, Naka KK. The Role of Prognostic Scores in Assessing the Prognosis of Patients Admitted in the Cardiac Intensive Care Unit: Emphasis on Heart Failure Patients. J Clin Med 2024; 13:2982. [PMID: 38792523 PMCID: PMC11122418 DOI: 10.3390/jcm13102982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 04/28/2024] [Accepted: 05/15/2024] [Indexed: 05/26/2024] Open
Abstract
Background/Objectives: Patient care in Cardiac Intensive Care Units (CICU) has evolved but data on patient characteristics and outcomes are sparse. This retrospective observational study aimed to define clinical characteristics and risk factors of CICU patients, their in-hospital and 30-day mortality, and compare it with established risk scores. Methods: Consecutive patients (n = 294, mean age 70 years, 74% males) hospitalized within 15 months were studied; APACHE II, EHMRG, GWTG-HF, and GRACE II were calculated on admission. Results: Most patients were admitted for ACS (48.3%) and acute decompensated heart failure (ADHF) (31.3%). Median duration of hospitalization was 2 days (IQR = 1, 4). In-hospital infection occurred in 20%, 18% needed mechanical ventilation, 10% renal replacement therapy and 4% percutaneous ventricular assist devices (33%, 29%, 20% and 4%, respectively, for ADHF). In-hospital and 30-day mortality was 18% and 11% for all patients (29% and 23%, respectively, for ADHF). Established scores (especially APACHE II) had a good diagnostic accuracy (area under the curve-AUC). In univariate and multivariate analyses in-hospital intubation and infection, history of coronary artery disease, hypotension, uremia and hypoxemia on admission were the most important risk factors. Based on these, a proposed new score showed a diagnostic accuracy of 0.954 (AUC) for in-hospital mortality, outperforming previous scores. Conclusions: Patients are admitted mainly with ACS or ADHF, the latter with worse prognosis. Several patients need advanced support; intubation and infections adversely affect prognosis. Established scores predict mortality satisfactorily, but larger studies are needed to develop CICU-directed scores to identify risk factors, improve prediction, guide treatment and staff training.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Katerina K. Naka
- Second Department of Cardiology, Faculty of Medicine, School of Health Sciences, University of Ioannina and University Hospital of Ioannina, 45110 Ioannina, Greece; (A.R.); (A.B.); (S.C.); (S.A.S.); (C.D.F.); (I.S.); (L.L.); (P.K.); (V.B.); (C.S.K.); (L.K.M.)
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Bouchlarhem A, Bazid Z, Ismaili N, Noha EO. Usefulness of the Quick-Sepsis Organ Failure Assessment Score in Cardiovascular Intensive Care Unit to Predict Prognosis in Acute Coronary Syndrome. Clin Appl Thromb Hemost 2023; 29:10760296231218705. [PMID: 38083859 PMCID: PMC10718056 DOI: 10.1177/10760296231218705] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 11/06/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023] Open
Abstract
Triage of patients with acute coronary syndrome (ACS) at high risk of in-hospital complications is essential. In this study, we evaluated the quick sepsis organ failure assessment (qSOFA) score as a tool for predicting the prognosis of 964 patients admitted to the cardiovascular intensive care unit (CICU) with ACS over a 4-year period. In total, out of 964 patients included, with a percentage of 4.6% for 30-day mortality. The risk of 30-day mortality was independently associated with qSOFA ≥ 2 at admission (hazard ratio = 2.76, 95% CI 1.32-5.74, p = 0.007). For MACEs, qSOFA ≥ 2 at admission was a predictive factor with (odds ratio = 2.42, 95% CI 1.37-4.36, p = .002). A qSOFA ≥ 2 on admission had an AUC of 0.729 (95% CI [0.694, 0.762]), with a good specificity of 91.6%. For 30-day mortality, an AUC of 0.759 (95%CI [0.726, 0.792]) for cardiogenic shock with specificity of 92.5%. For MACEs, an AUC of 0.702 (95% CI [0.64, 0.700] with a specificity of 95%. Concerning the different scores tested, we found no significant difference between the Zwolle score and the qSOFA score for predicting prognosis, whereas the CADILLAC score was better than qSOFA for predicting 30-day mortality (AUC = 0.829 and De long test = 0.03). However, there was no difference between qSOFA and CADILLAC scores for predicting cardiogenic shock (De Long test at 0.08). This is the first study to evaluate qSOFA as a predictive score for 30-day mortality and MACEs, and the results are very encouraging, particularly for cardiogenic shock.
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Affiliation(s)
- Amine Bouchlarhem
- Faculty of Medicine and Pharmacy, Mohammed Ist University, Oujda, Morocco
- Department of Cardiology, Mohammed VI University Hospital Mohammed I University, Oujda, Morocco
| | - Zakaria Bazid
- Faculty of Medicine and Pharmacy, Mohammed Ist University, Oujda, Morocco
- Department of Cardiology, Mohammed VI University Hospital Mohammed I University, Oujda, Morocco
| | - Nabila Ismaili
- Faculty of Medicine and Pharmacy, Mohammed Ist University, Oujda, Morocco
- Department of Cardiology, Mohammed VI University Hospital Mohammed I University, Oujda, Morocco
| | - El Ouafi Noha
- Faculty of Medicine and Pharmacy, Mohammed Ist University, Oujda, Morocco
- Department of Cardiology, Mohammed VI University Hospital Mohammed I University, Oujda, Morocco
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Rafie N, Jentzer JC, Noseworthy PA, Kashou AH. Mortality Prediction in Cardiac Intensive Care Unit Patients: A Systematic Review of Existing and Artificial Intelligence Augmented Approaches. Front Artif Intell 2022; 5:876007. [PMID: 35711617 PMCID: PMC9193583 DOI: 10.3389/frai.2022.876007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
The medical complexity and high acuity of patients in the cardiac intensive care unit make for a unique patient population with high morbidity and mortality. While there are many tools for predictions of mortality in other settings, there is a lack of robust mortality prediction tools for cardiac intensive care unit patients. The ongoing advances in artificial intelligence and machine learning also pose a potential asset to the advancement of mortality prediction. Artificial intelligence algorithms have been developed for application of electrocardiogram interpretation with promising accuracy and clinical application. Additionally, artificial intelligence algorithms applied to electrocardiogram interpretation have been developed to predict various variables such as structural heart disease, left ventricular systolic dysfunction, and atrial fibrillation. These variables can be used and applied to new mortality prediction models that are dynamic with the changes in the patient's clinical course and may lead to more accurate and reliable mortality prediction. The application of artificial intelligence to mortality prediction will fill the gaps left by current mortality prediction tools.
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Affiliation(s)
- Nikita Rafie
- Department of Medicine, Mayo Clinic, Rochester, MN, United States
- *Correspondence: Nikita Rafie
| | - Jacob C. Jentzer
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, United States
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
| | - Peter A. Noseworthy
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
| | - Anthony H. Kashou
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
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Patel SM, Jentzer JC, Alviar CL, Baird-Zars VM, Barsness GW, Berg DD, Bohula EA, Daniels LB, DeFilippis AP, Keeley EC, Kontos MC, Lawler PR, Miller PE, Park JG, Roswell RO, Solomon MA, van Diepen S, Katz JN, Morrow DA. A pragmatic lab-based tool for risk assessment in cardiac critical care: data from the Critical Care Cardiology Trials Network (CCCTN) Registry. EUROPEAN HEART JOURNAL. ACUTE CARDIOVASCULAR CARE 2022; 11:252-257. [PMID: 35134860 PMCID: PMC9123931 DOI: 10.1093/ehjacc/zuac012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 12/11/2021] [Accepted: 01/24/2022] [Indexed: 02/05/2023]
Abstract
AIMS Contemporary cardiac intensive care unit (CICU) outcomes remain highly heterogeneous. As such, a risk-stratification tool using readily available lab data at time of CICU admission may help inform clinical decision-making. METHODS AND RESULTS The primary derivation cohort included 4352 consecutive CICU admissions across 25 tertiary care CICUs included in the Critical Care Cardiology Trials Network (CCCTN) Registry. Candidate lab indicators were assessed using multivariable logistic regression. An integer risk score incorporating the top independent lab indicators associated with in-hospital mortality was developed. External validation was performed in a separate CICU cohort of 9716 patients from the Mayo Clinic (Rochester, MN, USA). On multivariable analysis, lower pH [odds ratio (OR) 1.96, 95% confidence interval (CI) 1.72-2.24], higher lactate (OR 1.40, 95% CI 1.22-1.62), lower estimated glomerular filtration rate (OR 1.26, 95% CI 1.10-1.45), and lower platelets (OR 1.18, 95% CI 1.05-1.32) were the top four independent lab indicators associated with higher in-hospital mortality. Incorporated into the CCCTN Lab-Based Risk Score, these four lab indicators identified a 20-fold gradient in mortality risk with very good discrimination (C-index 0.82, 95% CI 0.80-0.84) in the derivation cohort. Validation of the risk score in a separate cohort of 3888 patients from the Registry demonstrated good performance (C-index of 0.82; 95% CI 0.80-0.84). Performance remained consistent in the external validation cohort (C-index 0.79, 95% CI 0.77-0.80). Calibration was very good in both validation cohorts (r = 0.99). CONCLUSION A simple integer risk score utilizing readily available lab indicators at time of CICU admission may accurately stratify in-hospital mortality risk.
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Affiliation(s)
- Siddharth M Patel
- Levine Cardiac Intensive Care Unit, TIMI Study Group, Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Suite 7022, Boston, MA 02115, USA
| | - Jacob C Jentzer
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Carlos L Alviar
- Division of Cardiology, Department of Medicine, NYU Langone Medical Center, New York, NY, USA
| | - Vivian M Baird-Zars
- Levine Cardiac Intensive Care Unit, TIMI Study Group, Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Suite 7022, Boston, MA 02115, USA
| | | | - David D Berg
- Levine Cardiac Intensive Care Unit, TIMI Study Group, Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Suite 7022, Boston, MA 02115, USA
| | - Erin A Bohula
- Levine Cardiac Intensive Care Unit, TIMI Study Group, Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Suite 7022, Boston, MA 02115, USA
| | - Lori B Daniels
- Sulpizio Cardiovascular Center, University of California San Diego, La Jolla, CA, USA
| | - Andrew P DeFilippis
- Division of Cardiology, Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - Ellen C Keeley
- Division of Cardiology, Department of Medicine, University of Florida, Gainesville, FL, USA
| | - Michael C Kontos
- Division of Cardiology, Department of Internal Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Patrick R Lawler
- Peter Munk Cardiac Centre at Toronto General Hospital, Division of Cardiology and Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - P Elliott Miller
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Jeong-Gun Park
- Levine Cardiac Intensive Care Unit, TIMI Study Group, Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Suite 7022, Boston, MA 02115, USA
| | | | - Michael A Solomon
- Critical Care Medicine Department, National Institutes of Health Clinical Center and Cardiovascular Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, Bethesda, MD, USA
| | - Sean van Diepen
- Division of Cardiology, Department of Medicine, University of Alberta, Edmonton, AB, Canada,Division of Cardiology, Department of Critical Care, University of Alberta, Edmonton, AB, Canada
| | - Jason N Katz
- Division of Cardiology, Department of Medicine, Duke University, Durham, NC, USA
| | - David A Morrow
- Levine Cardiac Intensive Care Unit, TIMI Study Group, Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Suite 7022, Boston, MA 02115, USA,Corresponding author. Tel: +1 617 278 0181, Fax: +1 617 734 7329,
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Jentzer JC, Rossello X. Past, present, and future of mortality risk scores in the contemporary cardiac intensive care unit. EUROPEAN HEART JOURNAL-ACUTE CARDIOVASCULAR CARE 2021; 10:940-946. [PMID: 34453848 DOI: 10.1093/ehjacc/zuab072] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 08/09/2021] [Indexed: 12/17/2022]
Abstract
Risk stratification dates to the dawn of the cardiac intensive care unit (CICU). As the CICU has evolved from a dedicated unit caring for patients with acute myocardial infarction to a complex healthcare environment encompassing a broad array of acute and chronic cardiovascular pathology, an expanding array of risk scores are available that can be applied to CICU patients. Most of these scores were designed for use either in patients with a specific acute cardiovascular diagnosis or unselected critically ill patients, and risk scores developed in other populations often underperform in the CICU. More recently, risk scores have been developed specific to the CICU population, demonstrating improved performance. All existing risk scores have relevant limitations, both in terms of performance and applicability to patient care. Risk scores have been predominantly developed to predict short-term mortality, either by quantifying severity of illness or by incorporating other risk factors for mortality. It is essential to distinguish mortality risk attributable to severity of illness, which may be modifiable through intervention, from mortality risk attributable to non-modifiable risk factors. This review discusses established risk scores applicable to the CICU population, details how risk score performance is characterized, describes how new risk scores can be developed, explains how the information provided by risk scores can be used in clinical practice, and highlights how novel risk stratification approaches can be developed.
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Affiliation(s)
- Jacob C Jentzer
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.,Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Xavier Rossello
- Cardiology Department, Health Research Institute of the Balearic Islands (IdISBa), Hospital Universitari Son Espases, Palma, Spain.,Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.,Facultad de Medicina, Universitat de les Illes Balears (UIB), Palma de Mallorca, Balearic Islands, Spain.,Medical Statistics Department, London School of Hygiene & Tropical Medicine, London, UK
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