The performance of acute versus antecedent patient characteristics for 1-year mortality prediction during intensive care unit admission: a national cohort study

被引:14
|
作者
Kerckhoffs, Monika C. [1 ]
Brinkman, Sylvia [2 ,3 ]
de Keizer, Nicolet [2 ,3 ]
Soliman, Ivo W. [1 ]
de Lange, Dylan W. [1 ,2 ]
van Delden, Johannes J. M. [4 ]
van Dijk, Diederik [1 ]
机构
[1] Univ Utrecht, Univ Med Ctr Utrecht, Dept Intens Care Med, Mail Stop F06-149,POB 85500, NL-3508 GA Utrecht, Netherlands
[2] Natl Intens Care Evaluat NICE Fdn, Amsterdam, Netherlands
[3] Univ Amsterdam, Dept Med Informat, Amsterdam UMC, Amsterdam Publ Hlth Res Inst, Amsterdam, Netherlands
[4] Univ Utrecht, Univ Med Ctr Utrecht, Dept Med Humanities, Julius Ctr Hlth Sci & Primary Care, Utrecht, Netherlands
来源
CRITICAL CARE | 2020年 / 24卷 / 01期
关键词
Intensive care; Mortality; Prognosis; Advance care planning; Long-term outcomes; Critical illness; CHRONIC HEALTH EVALUATION; LONG-TERM MORTALITY; CRITICAL ILLNESS; HOSPITAL MORTALITY; ACUTE PHYSIOLOGY; OUTCOMES; DETERMINANTS; FRAILTY; SURVIVORS; IMPACT;
D O I
10.1186/s13054-020-03017-y
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Background Multiple factors contribute to mortality after ICU, but it is unclear how the predictive value of these factors changes during ICU admission. We aimed to compare the changing performance over time of the acute illness component, antecedent patient characteristics, and ICU length of stay (LOS) in predicting 1-year mortality. Methods In this retrospective observational cohort study, the discriminative value of four generalized mixed-effects models was compared for 1-year and hospital mortality. Among patients with increasing ICU LOS, the models included (a) acute illness factors and antecedent patient characteristics combined, (b) acute component only, (c) antecedent patient characteristics only, and (d) ICU LOS. For each analysis, discrimination was measured by area under the receiver operating characteristics curve (AUC), calculated using the bootstrap method. Statistical significance between the models was assessed using the DeLong method (pvalue < 0.05). Results In 400,248 ICU patients observed, hospital mortality was 11.8% and 1-year mortality 21.8%. At ICU admission, the combined model predicted 1-year mortality with an AUC of 0.84 (95% CI 0.84-0.84). When analyzed separately, the acute component progressively lost predictive power. From an ICU admission of at least 3 days, antecedent characteristics significantly exceeded the predictive value of the acute component for 1-year mortality, AUC 0.68 (95% CI 0.68-0.69) versus 0.67 (95% CI 0.67-0.68) (pvalue < 0.001). For hospital mortality, antecedent characteristics outperformed the acute component from a LOS of at least 7 days, comprising 7.8% of patients and accounting for 52.4% of all bed days. ICU LOS predicted 1-year mortality with an AUC of 0.52 (95% CI 0.51-0.53) and hospital mortality with an AUC of 0.54 (95% CI 0.53-0.55) for patients with a LOS of at least 7 days. Conclusions Comparing the predictive value of factors influencing 1-year mortality for patients with increasing ICU LOS, antecedent patient characteristics are more predictive than the acute component for patients with an ICU LOS of at least 3 days. For hospital mortality, antecedent patient characteristics outperform the acute component for patients with an ICU LOS of at least 7 days. After the first week of ICU admission, LOS itself is not predictive of hospital nor 1-year mortality.
引用
收藏
页数:9
相关论文
共 50 条
  • [41] Impact of intensive care unit admission during morning bedside rounds and mortality: a multi-center retrospective cohort study
    de Souza, Ivens Augusto O.
    Karvellas, Constantine J.
    Gibney, R. T. Noel
    Bagshaw, Sean M.
    CRITICAL CARE, 2012, 16 (03)
  • [42] Impact of intensive care unit admission during morning bedside rounds and mortality: a multi-center retrospective cohort study
    IvensAugusto O de Souza
    Constantine J Karvellas
    RT Noel Gibney
    Sean M Bagshaw
    Critical Care, 16
  • [43] Association between afterhours admission to the intensive care unit, strained capacity, and mortality: a retrospective cohort study
    Hall, Adam M.
    Stelfox, Henry T.
    Wang, Xioaming
    Chen, Guanmin
    Zuege, Danny J.
    Dodek, Peter
    Garland, Allan
    Scales, Damon C.
    Berthiaume, Luc
    Zygun, David A.
    Bagshaw, Sean M.
    CRITICAL CARE, 2018, 22
  • [44] ASSESSMENT OF PERFORMANCE OF SIX MORTALITY PREDICTION SYSTEMS IN A DUTCH SURGICAL INTENSIVE CARE UNIT IN A SINGLE ICU ADMISSION: A PROSPECTIVE STUDY
    Timmers, T. K.
    Verhofstad, M. H. J.
    Moons, K. G. M.
    Leenen, L. P. H.
    INTENSIVE CARE MEDICINE, 2009, 35 : 96 - 96
  • [45] Intensive care unit versus high-dependency care unit admission on mortality in patients with septic shock: a retrospective cohort study using Japanese claims data
    Endo, Koji
    Mizuno, Kayoko
    Seki, Tomotsugu
    Joo, Woo Jin
    Takeda, Chikashi
    Takeuchi, Masato
    Kawakami, Koji
    JOURNAL OF INTENSIVE CARE, 2022, 10 (01)
  • [46] Risk factors for and influence of bloodstream infections on mortality: a 1-year prospective study in a Greek intensive-care unit
    Pratikaki, M.
    Platsouka, E.
    Sotiropoulou, C.
    Vassilakopoulos, T.
    Paniara, O.
    Roussos, C.
    Routsi, C.
    EPIDEMIOLOGY AND INFECTION, 2009, 137 (05): : 727 - 735
  • [47] Acute ischemic stroke in a university hospital intensive care unit: 1-year costs and outcome
    Kortelainen, Simon
    Curtze, Sami
    Martinez-Majander, Nicolas
    Raj, Rahul
    Skrifvars, Markus B.
    ACTA ANAESTHESIOLOGICA SCANDINAVICA, 2022, 66 (04) : 516 - 525
  • [48] Mortality rate, patient length of stay and medical cost prediction in different priority levels for patient admission to an intensive care unit
    Hosseinpour, Fariba
    Seddighi, Mahyar
    Amerzadeh, Mohammad
    Rafiei, Sima
    INTERNATIONAL JOURNAL OF HUMAN RIGHTS IN HEALTH CARE, 2024, 17 (01) : 87 - 97
  • [49] Changes in Intensive Care Unit Admission Rates, Organ Support, and Mortality in Patients with Acute Myeloid Leukemia: A Danish Nationwide Cohort Study
    Maeng, Cecilie Velsoe
    Oestgaard, Lene Sofie Granfeldt
    Christiansen, Christian Fynbo
    Liu, Kathleen Dori
    BLOOD, 2019, 134
  • [50] Predictors of 1-year mortality following discharge from the surgical intensive care unit after sepsis
    Jalilvand, Anahita
    Terrana, Tracie
    Kellett, Whitney
    Collins, Courtney
    Ireland, Megan
    Wahl, Wendy
    Wisler, Jon
    SURGERY, 2025, 179