학술논문
Prognosticating the outcome of intensive care in older patients-a narrative review.
Document Type
Academic Journal
Author
Beil M; Department of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.; Moreno R; Unidade Local de Saúde São José, Hospital de São José, Lisbon, Portugal.; Centro Clínico Académico de Lisboa, Lisbon, Portugal.; Faculdade de Ciências da Saúde, Universidade da Beira Interior, Covilhã, Portugal.; Fronczek J; Center for Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, Krakow, Poland.; Kogan Y; Institute for Medical Biomathematics, Bene Ataroth, Israel.; Moreno RPJ; Imperial College Business School, London, UK.; Flaatten H; Department of Research and Development, Haukeland University Hospital, Bergen, Norway.; Guidet B; INSERM, Institut Pierre Louis d'Epidémiologie Et de Santé Publique, AP-HP, Hôpital Saint Antoine, Sorbonne Université, Service MIR, Paris, France.; de Lange D; Department of Intensive Care Medicine, University Medical Center, University Utrecht, Utrecht, The Netherlands.; Leaver S; General Intensive Care, St George's University Hospitals NHS Foundation Trust, London, UK.; Nachshon A; General Intensive Care Unit, Department of Anaesthesiology, Critical Care and Pain Medicine, Faculty of Medicine, Hebrew University and, Hadassah University Medical Center, Jerusalem, Israel.; van Heerden PV; General Intensive Care Unit, Department of Anaesthesiology, Critical Care and Pain Medicine, Faculty of Medicine, Hebrew University and, Hadassah University Medical Center, Jerusalem, Israel.; Joskowicz L; School of Computer Science and Engineering and Center for Computational Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.; Sviri S; Department of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.; Jung C; Department of Cardiology, Pulmonology and Vascular Medicine, Faculty of Medicine, Heinrich-Heine-University, University Duesseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany. christian.jung@med.uni-duesseldorf.de.; Szczeklik W; Center for Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, Krakow, Poland.
Source
Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 101562873 Publication Model: Electronic Cited Medium: Print ISSN: 2110-5820 (Print) Linking ISSN: 21105820 NLM ISO Abbreviation: Ann Intensive Care Subsets: PubMed not MEDLINE
Subject
Language
English
ISSN
2110-5820
Abstract
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.
(© 2024. The Author(s).)
(© 2024. The Author(s).)