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Enregistrement W4246439882 · doi:10.17504/protocols.io.udkes4w

Defining critical illness – a scoping review and thematic content analysis: Protocol for a scoping review. v2

2018· review· en· W4246439882 sur OpenAlexaboutno aff
Hedi Mollazadegan, Tim Baker, Helle Mølsted Alvesson, Martin Gerdin Wärnberg

Notice bibliographique

Revuenon disponible
Typereview
Langueen
DomaineMedicine
ThématiqueSepsis Diagnosis and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCritical appraisalIntensive careVariety (cybernetics)MedicineInclusion (mineral)Critical illnessCritically illMEDLINEProtocol (science)Thematic analysisSystematic reviewAlternative medicinePsychologyIntensive care medicineQualitative researchPolitical scienceComputer sciencePathologySocial scienceSociology

Résumé

récupéré en direct d'OpenAlex

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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,138
score de la tête « metaresearch » (Gemma)0,157
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Protocole · Signal consensuel: Protocole
Score de désaccord entre enseignants0,138
Score d'incertitude au seuil0,731

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1380,157
Méta-épidémiologie (sens strict)0,0050,006
Méta-épidémiologie (sens large)0,0110,013
Bibliométrie0,0180,021
Études des sciences et des technologies0,0050,005
Communication savante0,0080,010
Science ouverte0,0070,008
Intégrité de la recherche0,0080,009
Charge utile insuffisante (le modèle a refusé de juger)0,1360,025

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,465
Tête enseignante GPT0,569
Écart entre enseignants0,104 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreProtocole

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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