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Record W3134859256 · doi:10.17504/protocols.io.txiepke

Defining critical illness – a scoping review and thematic content analysis: Protocol for a scoping review. v1

2018· review· en· W3134859256 on OpenAlexaboutno aff
Hedi Mollazadegan, Tim Baker, Helle Mølsted Alvesson, Martin Gerdin Wärnberg

Bibliographic record

Venuenot available
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsCritical appraisalVariety (cybernetics)Intensive careInclusion (mineral)MedicineCritical illnessCritically illThematic analysisMEDLINEProtocol (science)Systematic reviewAlternative medicinePsychologyIntensive care medicineQualitative researchPolitical scienceComputer scienceSociologySocial sciencePathology

Abstract

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Introduction Due to the wide variety of definitions for critical illness, it is hard to define and estimate the burden of critically ill patients internationally. To be able to academically discuss both implementations and improvements, one needs to stand on a common ground on what the definition of critical illness is. Method Arksey and O’Malley’s scoping review methodology and Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) will guide the conduct of this scoping review. We will search electronic databases PubMed, Web of Science and publication lists from Association of Anaesthetists of Great Britain and Ireland, The Scandinavian Society of Anaesthesiology and Intensive Care Medicine, European Society of Intensive Care Medicine, World Federation of Societies of Intensive and Critical Care Medicine will be hand searched to identify appropriate studies for inclusion. Two reviewers will independently screen all abstracts and full-text studies for inclusion. The included studies must focus on discussing critical illness. The results will be produced by using a thematic content analysis on the included studies. Background Due to the wide variety of definitions for critical illness, it is hard to define and estimate the burden of critically ill patients globally. It is estimated that 74 500 deaths occur every year only in the USA due to being critically ill, this number exceeds the yearly number of deaths from breast cancer, HIV/AIDS and asthma, this shows the underappreciated burden of critical illness. (1) When searching different databases there seems to be a wide variety of what the definition of critical illness is. Kumar et al. describe in their study the treatment and outcome in patients in Canada with 2009 influenza infection. They defined critically ill patients after 3 criteria depending on whether the patient was requiring mechanical ventilation or had deranged vital parameters (2). In another study by Vincent JL et al. They only look at patients with sepsis. (3) The absence of a reliable international data on critical illness is because of several challenges such as: Critical illness syndromes have a brief prodromal and high short-term mortality compared to other chronical diseases which could especially be high in countries with low to few intensive care unit (ICU) resources (1). When studying patients admitted to the ICU as critically ill, it seems like the outcome of patients admitted to the ICU differs even internationally due to differences in national income. In a study made by Vincent J et al. they examined 10 069 patients admitted to the ICU in Europe, Asia, Middle East, Oceania and Africa. The study suggests significant between-country variations in the risk of in-hospital death. They concluded that their findings highlight a significant association and stepwise increase between risk of death and the global national income and suggest that the ICU organization has a vital effect on the risk of death. (2) Why do we need to define critical illness? There is a need to academically and clinically discuss both improvements and implementations such as identifying patients with critical illness and ultimately decrease the mortality rate by receiving basic healthcare regardless of national income. There is a need for a national effort to prevent each of the complications leading to a critically ill patient as described by To K, Napolitano L (4). The first step is to find an internationally agreed definition for critical illness and would greatly benefit the increasing need for critical illness research and is not only limited to the ICU as patients who are critically ill is also present in other departments (2). Aim The aim of this study is to operationally define critical illness and attempt to answer the question: What are the main elements of existing definitions of critical illness and can these be homogenized to form a common definition? Design This study will be a scoping review complemented by a thematic content analysis including expert interview with health professionals working clinically to broaden the view. Rather than being dictated by a highly focused research question that forces the research on specific study designs, a scoping method is guided by the requirement to study all relevant literature regardless of study design. The scoping review methodology is particularly suited for questions not answerable by a systematic review because the scope is too broad. The review will be conducted using the Arksey and O’Malley framework and PRISMA-ScR hence first relevant studies will be identified, second studies will be selected for inclusion, third data will be charted and finally, the data will be summarized. (5, 6) References [1] Adhikari N, Fowler R, Bhagwanjee S, Rubenfeld G. Critical care and the global burden of critical illness in adults. The Lancet. 2010;376(9749):1339-1346. [2] Kumar A. Critically Ill Patients With 2009 Influenza A(H1N1) Infection in Canada. JAMA. 2009;302(17):1872. [3] Vincent J, Marshall J, Ñamendys-Silva S, François B, Martin-Loeches I, Lipman J et al. Assessment of the worldwide burden of critical illness: the Intensive Care Over Nations (ICON) audit. The Lancet Respiratory Medicine. 2014;2(5):380-386. [4] To K, Napolitano L. Common Complications in the Critically Ill Patient. Surgical Clinics of North America. 2012;92(6):1519-1557. [5] Arksey H, O'Malley L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology. 2005;8(1). [6] Tricco A, Lillie E, Zarin W, O'Brien K, Colquhoun H, Levac D et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Annals of Internal Medicine. 2018;. [7] Vaismoradi M, Turunen H, Bondas T. Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nursing & Health Sciences. 2013;15(3):398-405.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.142
metaresearch head score (Gemma)0.161
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.142
Threshold uncertainty score0.749

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1420.161
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0110.013
Bibliometrics0.0180.022
Science and technology studies0.0050.005
Scholarly communication0.0080.010
Open science0.0070.009
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.1310.025

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 head0.458
GPT teacher head0.565
Teacher spread0.107 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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