Evidence map›Paper›PMID 40350182›Full record

SynthesisBMJ open respiratory research2025

Uncertainty and decision-making in critical care: lessons from managing COVID-19 ARDS in preparation for the next pandemic.

Kenki Matsumoto, John R Prowle, Zudin Puthucheary, Maurizio Cecconi, Brigitta Fazzini, Hannah Malcolm, Peter Nydahl, Magda Osman, Alessandro Santini, Stefan J Schaller and 4 more

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMJ open respiratory research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. 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

14 authors.

Kenki MatsumotoBarts Health NHS Trust, London, UK.
John R ProwleBarts Health NHS Trust, London, UK.
Zudin PuthuchearyQueen Mary University of London Faculty of Medicine and Dentistry, London, UK.ORCID http://orcid.org/0000-0003-4267-1892
Maurizio CecconiAnesthesia and Critical Care, Istituto Clinico Humanitas, Rozzano, Lombardia, Italy.
Brigitta FazziniBarts Health NHS Trust, London, UK.
Hannah MalcolmBarts Health NHS Trust, London, UK.
Peter NydahlUniversity Hospital Schleswig Holstein, Kiel, Germany.
Magda OsmanUniversity of Cambridge, Cambridge, UK.
Alessandro SantiniDepartment of Biomedical Sciences, Humanitas University, Milan, Italy.
Stefan J SchallerCharité - Universitätsmedizin Berlin, Berlin, Germany.
William ThomsonBarts Health NHS Trust, London, UK.
Danielle van den BerkeDepartment of Intensive Care Medicine, Maastricht University Medical Center, Maastricht, The Netherlands.
Marcel PollDepartment of Intensive Care Medicine, Maastricht University Medical Center, Maastricht, The Netherlands.
Timothy StephensBarts Health NHS Trust, London, UK t.t.stephens@qmul.ac.uk.ORCID http://orcid.org/0000-0002-0206-0280

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeCoronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS) was an emergent syndrome that led to high volumes of critically ill ventilated patients. We explored influences on decision-making regarding management of COVID-19 ARDS mechanical ventilation to identify modifiable factors to improve preparedness for future pandemics.

methodsA systematic review and small group interviews informed the development of an international questionnaire (UK, Italy, Germany and Netherlands) on factors influencing COVID-19 ARDS ventilation decision-making in critical care professionals. Participants ranked four themes in order of importance: disease (uncertainties around COVID-19 ARDS), contextual (cognitive strain), environmental (structural logistics) and team factors. Participants also ranked the subthemes within each theme. Thematic analysis was used to derive findings from qualitative data. Kruskal-Wallis, Mann-Whitney U and Kendall's tau were used for quantitative data analysis.

resultsPatient factors (comorbidities, clinical/biochemical parameters) were the most studied influences in the extant literature on decision-making; uncertainty was one of the least studied. 371 critical care professionals responded to the questionnaire. Disease uncertainty (lack of applicable guidelines, unfamiliarity with pathophysiology) was ranked as the most important influence on ventilation decision-making for COVID-19 ARDS across regions, professions and experience levels (p<0.001). Participants expressed underconfidence in their decision-making (median score: 9/20); this was unaffected by experience (p=0.79) or profession (p=0.58). Qualitative findings supported and extended the initial proposed influences, including the impact of team factors (+ve) and resource limitations (-ve) on disease uncertainty.

conclusionFuture pandemic preparedness programmes should target modifiable influences such as information sharing, teamworking and resource limitations to mitigate against the negative influence of uncertainty and thereby improve decision-making overall.

Indexed as

Clinical Decision-MakingCOVID-19Critical CareDecision MakingRespiration, ArtificialRespiratory Distress SyndromeHumansPandemicsSARS-CoV-2Surveys and QuestionnairesUncertaintyARDSCOVID-19Critical Care

Identifiers

PMID40350182
PMCPMC12067812

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.