Admission diagnosis and mortality risk prediction in a contemporary cardiac intensive care unit population

被引:70
作者
Jentzer, Jacob C. [1 ,2 ]
van Diepen, Sean [3 ,4 ]
Murphree, Dennis H. [5 ]
Ismail, Abdalla S. [6 ]
Keegan, Mark T. [7 ]
Morrow, David A. [8 ,9 ]
Barsness, Gregory W. [1 ]
Anavekar, Nandan S. [1 ]
机构
[1] Mayo Clin, Dept Cardiovasc Med, 200 First St SW, Rochester, MN 55905 USA
[2] Mayo Clin, Div Pulm & Crit Care Med, Dept Internal Med, 200 First St SW, Rochester, MN 55905 USA
[3] Univ Alberta Hosp, Dept Crit Care Med, Edmonton, AB, Canada
[4] Univ Alberta Hosp, Div Cardiol, Dept Med, Edmonton, AB, Canada
[5] Mayo Clin, Dept Hlth Sci Res, Rochester, MN 55905 USA
[6] Mayo Clin, Multidisciplinary Epidemiol & Translat Res Intens, Rochester, MN 55905 USA
[7] Mayo Clin, Dept Anesthesiol & Perioperat Med, Rochester, MN 55905 USA
[8] Brigham & Womens Hosp, Div Cardiovasc, TIMI Study Grp, 75 Francis St, Boston, MA 02115 USA
[9] Harvard Med Sch, Boston, MA 02115 USA
关键词
HOSPITAL MORTALITY; ACUTE PHYSIOLOGY; APACHE IV; ILLNESS; FAILURE; SCORE; VALIDATION; SEVERITY; REGISTRY;
D O I
10.1016/j.ahj.2020.02.018
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background Critical care risk scores can stratify mortality risk among cardiac intensive care unit (CICU) patients, yet risk score performance across common CICU admission diagnoses remains uncertain. Methods We evaluated performance of the Acute Physiology and Chronic Health Evaluation (APACHE)-III, APACHE-IV, Sequential Organ Failure Assessment (SOFA) and Oxford Acute Severity of Illness Score (OASIS) scores at the time of CICU admission in common CICU admission diagnoses. Using a database of 9,898 unique CICU patients admitted between 2007 and 2015, we compared the discrimination (c-statistic) and calibration (Hosmer-Lemeshow statistic) of each risk score in patients with selected admission diagnoses. Results Overall hospital mortality was 9.2%. The 3182 (32%) patients with a critical care diagnosis such as cardiac arrest, shock, respiratory failure, or sepsis accounted for >85% of all hospital deaths. Mortality discrimination by each risk score was comparable in each admission diagnosis (c-statistic 95% CI values were generally overlapping for all scores), although calibration was variable and best with APACHE-III. The c-statistic values for each score were 0.85-0.86 among patients with acute coronary syndromes, and 0.76-0.79 among patients with heart failure. Discrimination for each risk score was lower in patients with critical care diagnoses (c-statistic range 0.68-0.78) compared to non-critical cardiac diagnoses (c-statistic range 0.76-0.86). Conclusions The tested risk scores demonstrated inconsistent performance for mortality risk stratification across admission diagnoses in this CICU population, emphasizing the need to develop improved tools for mortality risk prediction among critically-ill CICU patients.
引用
收藏
页码:57 / 64
页数:8
相关论文
共 24 条
  • [1] Prospective validation of a near real-time EHR-integrated automated SOFA score calculator
    Aakre, Christopher
    Franco, Pablo Moreno
    Ferreyra, Micaela
    Kitson, Jaben
    Li, Man
    Herasevich, Vitaly
    [J]. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2017, 103 : 1 - 6
  • [2] Comparative evaluation of Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment scoring systems in patients admitted to the cardiac intensive care unit
    Argyriou, George
    Vrettou, Charikleia S.
    Filippatos, Gerasimos
    Sainis, George
    Nanas, Serafeim
    Routsi, Christina
    [J]. JOURNAL OF CRITICAL CARE, 2015, 30 (04) : 752 - 757
  • [3] Severity of illness assessment with application of the APACHE IV predicted mortality and outcome trends analysis in an academic cardiac intensive care unit
    Bennett, Courtney E.
    Wright, R. Scott
    Jentzer, Jacob
    Gajic, Ognjen
    Murphree, Dennis H.
    Murphy, Joseph G.
    Mankad, Sunil V.
    Wiley, Brandon M.
    Bell, Malcolm R.
    Barsness, Gregory W.
    [J]. JOURNAL OF CRITICAL CARE, 2019, 50 : 242 - 246
  • [4] Bohula EA, 2019, JAMA CARDIOL
  • [5] Mapping physicians' admission diagnoses to structured concepts towards fully automatic calculation of acute physiology and chronic health evaluation score
    Chandra, Subhash
    Kashyap, Rahul
    Trillo-Alvarez, Cesar A.
    Tsapenko, Mykola
    Yilmaz, Murat
    Hanson, Andrew C.
    Pickering, Brian W.
    Gajic, Ognjen
    Herasevich, Vitaly
    [J]. BMJ OPEN, 2011, 1 (02):
  • [6] Noncardiovascular Disease and Critical Care Delivery in a Contemporary Cardiac and Medical Intensive Care Unit
    Goldfarb, Michael
    van Diepen, Sean
    Liszkowski, Mark
    Jentzer, Jacob C.
    Pedraza, Isabel
    Cercek, Bojan
    [J]. JOURNAL OF INTENSIVE CARE MEDICINE, 2019, 34 (07) : 537 - 543
  • [7] Predictors of hospital mortality in the global registry of acute coronary events
    Granger, CB
    Goldberg, RJ
    Dabbous, O
    Pieper, KS
    Eagle, KA
    Cannon, CP
    Van de Werf, F
    Avezum, A
    Goodman, SG
    Flather, MD
    Fox, KAA
    [J]. ARCHIVES OF INTERNAL MEDICINE, 2003, 163 (19) : 2345 - 2353
  • [8] Clinical picture and risk prediction of short-term mortality in cardiogenic shock
    Harjola, Veli-Pekka
    Lassus, Johan
    Sionis, Alessandro
    Kober, Lars
    Tarvasmaki, Tuukka
    Spinar, Jindrich
    Parissis, John
    Banaszewski, Marek
    Silva-Cardoso, Jose
    Carubelli, Valentina
    Di Somma, Salvatore
    Tolppanen, Heli
    Zeymer, Uwe
    Thiele, Holger
    Nieminen, Markku S.
    Mebazaa, Alexandre
    [J]. EUROPEAN JOURNAL OF HEART FAILURE, 2015, 17 (05) : 501 - 509
  • [9] Informatics Infrastructure for Syndrome Surveillance, Decision Support, Reporting, and Modeling of Critical Illness
    Herasevich, Vitaly
    Pickering, Brian W.
    Dong, Yue
    Peters, Steve G.
    Gajic, Ognjen
    [J]. MAYO CLINIC PROCEEDINGS, 2010, 85 (03) : 247 - 254
  • [10] Acute Noncardiovascular Illness in the Cardiac Intensive Care Unit
    Holland, Eric M.
    Moss, Travis J.
    [J]. JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2017, 69 (16) : 1999 - 2007