Prognosticating the outcome of intensive care in older patients-a narrative review

被引:5
作者
Beil, Michael [1 ,2 ]
Moreno, Rui [3 ,4 ,5 ]
Fronczek, Jakub [6 ]
Kogan, Yuri [7 ]
Moreno, Rui Paulo Jorge [8 ]
Flaatten, Hans [9 ]
Guidet, Bertrand [10 ]
de Lange, Dylan [11 ]
Leaver, Susannah [12 ]
Nachshon, Akiva [13 ,14 ]
van Heerden, Peter Vernon [13 ,14 ]
Joskowicz, Leo [15 ,16 ]
Sviri, Sigal [1 ,2 ]
Jung, Christian [17 ]
Szczeklik, Wojciech [6 ]
机构
[1] Hebrew Univ Jerusalem, Hadassah Med Ctr, Dept Med Intens Care, Jerusalem, Israel
[2] Hebrew Univ Jerusalem, Fac Med, Jerusalem, Israel
[3] Hosp Sao Jose, Unidade Local Saude Sao Jose, Lisbon, Portugal
[4] Ctr Clin Acad Lisboa, Lisbon, Portugal
[5] Univ Beira Interior, Fac Ciencias Saude, Covilha, Portugal
[6] Jagiellonian Univ Med Coll, Ctr Intens Care & Perioperat Med, Krakow, Poland
[7] Inst Med Biomath, Bene Ataroth, Israel
[8] Imperial Coll, Business Sch, London, England
[9] Haukeland Hosp, Dept Res & Dev, Bergen, Norway
[10] Sorbonne Univ, Hop St Antoine, AP HP, INSERM,Inst Pierre Louis Epidemiol & Sante Publ,Se, Paris, France
[11] Univ Utrecht, Univ Med Ctr, Dept Intens Care Med, Utrecht, Netherlands
[12] St Georges Univ Hosp NHS Fdn Trust, Gen Intens Care, London, England
[13] Hebrew Univ Jerusalem, Fac Med, Dept Anaesthesiol Crit Care & Pain Med, Gen Intens Care Unit, Jerusalem, Israel
[14] Hadassah Univ, Med Ctr, Jerusalem, Israel
[15] Hebrew Univ Jerusalem, Sch Comp Sci & Engn, Jerusalem, Israel
[16] Hebrew Univ Jerusalem, Ctr Computat Med, Jerusalem, Israel
[17] Univ Duesseldorf, Heinrich Heine Univ, Fac Med, Dept Cardiol Pulmonol & Vasc Med, Moorenstr 5, D-40225 Dusseldorf, Germany
来源
ANNALS OF INTENSIVE CARE | 2024年 / 14卷 / 01期
关键词
Intensive care; Critical care; Prediction; Very old patients; CRITICAL ILLNESS; HOSPITAL MORTALITY; DECISION-MAKING; PREDICTION; HEALTH; ICU; UNCERTAINTY; SOCIETY; MODELS; SAPS-3;
D O I
10.1186/s13613-024-01330-1
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Prognosis determines major decisions regarding treatment for critically ill patients. Statistical models have been developed to predict the probability of survival and other outcomes of intensive care. Although they were trained on the characteristics of large patient cohorts, they often do not represent very old patients (age >= 80 years) appropriately. Moreover, the heterogeneity within this particular group impairs the utility of statistical predictions for informing decision-making in very old individuals. In addition to these methodological problems, the diversity of cultural attitudes, available resources as well as variations of legal and professional norms limit the generalisability of prediction models, especially in patients with complex multi-morbidity and pre-existing functional impairments. Thus, current approaches to prognosticating outcomes in very old patients are imperfect and can generate substantial uncertainty about optimal trajectories of critical care in the individual. This article presents the state of the art and new approaches to predicting outcomes of intensive care for these patients. Special emphasis has been given to the integration of predictions into the decision-making for individual patients. This requires quantification of prognostic uncertainty and a careful alignment of decisions with the preferences of patients, who might prioritise functional outcomes over survival. Since the performance of outcome predictions for the individual patient may improve over time, time-limited trials in intensive care may be an appropriate way to increase the confidence in decisions about life-sustaining treatment.
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页数:12
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共 97 条
  • [1] Tailoring treatments to older people in intensive care. A way forward
    Aliberti, Marlon Juliano Romero
    Bailly, Sebastien
    Anstey, Matthew
    [J]. INTENSIVE CARE MEDICINE, 2022, 48 (12) : 1775 - 1777
  • [2] Anderljung M, 2023, Arxiv, DOI [arXiv:2307.03718, 10.48550/arXiv.2307.03718]
  • [3] Analysis of Physicians' Probability Estimates of a Medical Outcome Based on a Sequence of Events
    Arkes, Hal R.
    Aberegg, Scott K.
    Arpin, Kevin A.
    [J]. JAMA NETWORK OPEN, 2022, 5 (06)
  • [4] Variations in end-of-life practices in intensive care units worldwide (Ethicus-2): a prospective observational study
    Avidan, Alexander
    Sprung, Charles L.
    Schefold, Joerg C.
    Ricou, Bara
    Hartog, Christiane S.
    Nates, Joseph L.
    Jaschinski, Ulrich
    Lobo, Suzana M.
    Joynt, Gavin M.
    Lesieur, Olivier
    Weiss, Manfred
    Antonelli, Massimo
    Bulow, Hans-Henrik
    Bocci, Maria G.
    Robertsen, Annette
    Anstey, Matthew H.
    Estebanez-Montiel, Belen
    Lautrette, Alexandre
    Gruber, Anastasiia
    Estella, Angel
    Mullick, Sudakshina
    Sreedharan, Roshni
    Michalsen, Andrej
    Feldman, Charles
    Tisljar, Kai
    Posch, Martin
    Ovu, Steven
    Tamowicz, Barbara
    Demoule, Alexandre
    Ganz, Freda DeKeyser
    Pargger, Hans
    Noto, Alberto
    Metnitz, Philipp
    Zubek, Laszlo
    de la Guardia, Veronica
    Danbury, Christopher M.
    Szucs, Orsolya
    Protti, Alessandro
    Filipe, Mario
    Simpson, Steven Q.
    Green, Cameron
    Giannini, Alberto M.
    Soliman, Ivo W.
    Piras, Claudio
    Caser, Eliana B.
    Hache-Marliere, Manuel
    Mentzelopoulos, Spyros
    [J]. LANCET RESPIRATORY MEDICINE, 2021, 9 (10) : 1101 - 1110
  • [5] A clinical prediction tool for hospital mortality in critically ill elderly patients
    Ball, Ian M.
    Bagshaw, Sean M.
    Burns, Karen E. A.
    Cook, Deborah J.
    Day, Andrew G.
    Dodek, Peter M.
    Kutsogiannis, Demetrios J.
    Mehta, Sangeeta
    Muscedere, John G.
    Stelfox, Henry T.
    Turgeon, Alexis F.
    Wells, George A.
    Stiell, Ian G.
    [J]. JOURNAL OF CRITICAL CARE, 2016, 35 : 206 - 212
  • [6] Comparison of Severity of Illness Scores and Artificial Intelligence Models That Are Predictive of Intensive Care Unit Mortality: Meta-analysis and Review of the Literature
    Barboi, Cristina
    Tzavelis, Andreas
    Muhammad, Lutfiyya NaQiyba
    [J]. JMIR MEDICAL INFORMATICS, 2022, 10 (05)
  • [7] UK Intensivists' Preferences for Patient Admission to ICU: Evidence From a Choice Experiment
    Bassford, Christopher R.
    Krucien, Nicolas
    Ryan, Mandy
    Griffiths, Frances E.
    Svantesson, Mia
    Fritz, Zoe
    Perkins, Gavin D.
    Quinton, Sarah
    Slowther, Anne-Marie
    [J]. CRITICAL CARE MEDICINE, 2019, 47 (11) : 1522 - 1530
  • [8] The need for uncertainty quantification in machine-assisted medical decision making
    Begoli, Edmon
    Bhattacharya, Tanmoy
    Kusnezov, Dimitri
    [J]. NATURE MACHINE INTELLIGENCE, 2019, 1 (01) : 20 - 23
  • [9] Beil M., 2022, The very old critically ill patients. lessons from the ICU, P251, DOI [10.1007/978-3-030-94133-816, DOI 10.1007/978-3-030-94133-816]
  • [10] Limiting life-sustaining treatment for very old ICU patients: cultural challenges and diverse practices
    Beil, Michael
    van Heerden, Peter Vernon
    Joynt, Gavin M.
    Lapinsky, Stephen
    Flaatten, Hans
    Guidet, Bertrand
    de Lange, Dylan
    Leaver, Susannah
    Jung, Christian
    Forte, Daniel Neves
    Bin, Du
    Elhadi, Muhammed
    Szczeklik, Wojciech
    Sviri, Sigal
    [J]. ANNALS OF INTENSIVE CARE, 2023, 13 (01)