Evidence map›Paper›PMID 36051941›Full record

ReviewWorld journal of critical care medicine2022

Health-related quality-of-life and health-utility reporting in critical care.

Vincent Issac Lau, Jeffrey A Johnson, Sean M Bagshaw, Oleksa G Rewa, John Basmaji, Kimberley A Lewis, M Elizabeth Wilcox, Kali Barrett, Francois Lamontagne, Francois Lauzier and 11 more

Abstract readReview
In one paragraph

Review in World journal of critical care medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Observational
  2. Measuring health-related quality of life in sepsis survivors and caregivers: a mapping review and a preliminary conceptual framework.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Review
  3. Article
  4. Review
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Vincent Issac LauDepartment of Critical Care Medicine, University of Alberta, Edmonton T6G 2B7, AB, Canada. vinceissaclau@gmail.com.
Jeffrey A JohnsonSchool of Public Health, Inst Hlth Econ, University of Alberta, Edmonton T6G 2B7, AB, Canada.
Sean M BagshawDepartment of Critical Care Medicine, University of Alberta, Edmonton T6G 2B7, AB, Canada.
Oleksa G RewaDepartment of Critical Care Medicine, University of Alberta, Edmonton T6G 2B7, AB, Canada.
John BasmajiDepartment of Medicine, Division of Critical Care, Western University, London N6A 5W9, Canada.
Kimberley A LewisDivision of Critical Care, McMaster University, Hamilton L8N 4A6, Canada.
M Elizabeth WilcoxInterdepartmental Division of Critical Care, University of Toronto, Toronto M5T 2S8, Canada.
Kali BarrettInterdepartmental Division of Critical Care, University of Toronto, Toronto M5T 2S8, Canada.
Francois LamontagneDepartment of Medicine, University Sherbrooke, Sherbrooke J1H 5N4, Canada.
Francois LauzierDepartments of Medicine and Anesthesiology, University Laval, Laval G1V 4G2, Canada.
Niall D FergusonDepartment Critical Care Medicine, University of Toronto, Toronto M5G 2C4, Canada.
Simon J W OczkowskiDepartment of Medicine, McMaster Clin, Hamilton Gen Hosp, McMaster University, Hamilton L8N 4A6, Canada.
Kirsten M FiestDepartment of Community Health Sciences & Institute for Public Health, University of Calgary, Calgary T2N 2T9, Canada.
Daniel J NivenDepartment of Critical Care Medicine, University Calgary, Calgary T2N 2T9, Canada.
Henry T StelfoxDepartment of Community Health Sciences, University of Calgary, Calgary T2N 2T9, Canada.
Waleed AlhazzaniDepartment of Medicine, McMaster University, Hamilton L8N 4A6, Canada.
Margaret HerridgeIndepartmental Division of Critical Care, University Health Network, Toronto M5G 2C4, Canada.
Robert FowlerDepartments of Medicine and Critical Care Medicine, Sunnybrook Health Sciences Center, Institute of Health Policy Management and Evaluation, University of Toronto, Toronto M4N 3M5, Canada.
Deborah J CookDepartment of Medicine, McMaster University, Hamilton L8N 4A6, Canada.
Bram RochwergDepartment of Medicine, McMaster University, Hamilton L8N 4A6, Canada.
Feng XieHealth Research Methods, Evidence and Impact, McMaster University, Hamilton L8N 3Z5, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mortality is a well-established patient-important outcome in critical care studies. In contrast, morbidity is less uniformly reported (given the myriad of critical care illnesses and complications of each) but may have a common end-impact on a patient's functional capacity and health-related quality-of-life (HRQoL). Survival with a poor quality-of-life may not be acceptable depending on individual patient values and preferences. Hence, as mortality decreases within critical care, it becomes increasingly important to measure intensive care unit (ICU) survivor HRQoL. HRQoL measurements with a preference-based scoring algorithm can be converted into health utilities on a scale anchored at 0 (representing death) and 1 (representing full health). They can be combined with survival to calculate quality-adjusted life-years (QALY), which are one of the most widely used methods of combining morbidity and mortality into a composite outcome. Although QALYs have been use for health-technology assessment decision-making, an emerging and novel role would be to inform clinical decision-making for patients, families and healthcare providers about what expected HRQoL may be during and after ICU care. Critical care randomized control trials (RCTs) have not routinely measured or reported HRQoL (until more recently), likely due to incapacity of some patients to participate in patient-reported outcome measures. Further differences in HRQoL measurement tools can lead to non-comparable values. To this end, we propose the validation of a gold-standard HRQoL tool in critical care, specifically the EQ-5D-5L. Both combined health-utility and mortality (disaggregated) and QALYs (aggregated) can be reported, with disaggregation allowing for determination of which components are the main drivers of the QALY outcome. Increased use of HRQoL, health-utility, and QALYs in critical care RCTs has the potential to: (1) Increase the likelihood of finding important effects if they exist; (2) improve research efficiency; and (3) help inform optimal management of critically ill patients allowing for decision-making about their HRQoL, in additional to traditional health-technology assessments.

Indexed as

Critical carehealth-related quality of lifeHealth-utilityKaplan-Meier curvesMorbidityMortalityQuality-adjusted life-years

Identifiers

PMID36051941
PMCPMC9305682

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.