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Record W2052110168 · doi:10.1177/175114371201300315

Regionalisation of Intensive Care and Extra-Corporeal Membrane Oxygenation Services in the UK: Beliefs about the Evidence, Benefits and Harm

2012· article· en· W2052110168 on OpenAlexaff
Neil I Stewart, K. Gunning, Brian H. Cuthbertson

Bibliographic record

VenueJournal of the Intensive Care Society · 2012
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersIntensive Care Society
KeywordsRegionalisationIntensive careMedicineService (business)HarmPandemicIntensive care medicineMedical emergencyBusinessCoronavirus disease 2019 (COVID-19)PsychologyPolitical science

Abstract

fetched live from OpenAlex

Extra-corporeal membrane oxygenation (ECMO) is used as rescue therapy for adults with severe acute respiratory failure. We aimed to determine the views of intensive care clinicians on regionalisation of critical care services and on the development of adult ECMO services in the UK. A survey was undertaken of all members of the UK Intensive Care Society; 2,133 participants were invited to complete the survey and 691 responded (32.7%). Among respondents, 65% believed that adult ECMO services should be expanded, 42.5% agreed that intensive care services in the UK should be regionalised, while 63.8% agreed the UK should develop regional ventilatory care centres including ECMO services. Experience during H1N1 influenza pandemics was the factor respondents most frequently identified as driving ECMO expansion (61.1%). Of respondents, 60.1% believe that an expanded ECMO service should be provided in 5–10 supra-regional centres. Patient safety, resources, guidelines and transportation of sick patients were also seen as important issues. We conclude that there is a reasonable level of support for regionalisation of intensive care services and for expansion in ECMO services for adults with severe acute respiratory failure in the UK. Clinicians support appropriate funding, investment in transport services and the development of national guidelines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.260
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2012
Admission routes1
Has abstractyes

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