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Enregistrement W1982864087 · doi:10.3310/hta18250

Selective decontamination of the digestive tract in critically ill patients treated in intensive care units: a mixed-methods feasibility study (the SuDDICU study)

2014· article· en· W1982864087 sur OpenAlexaff
Jill Francis, Eilidh Duncan, Maria Prior, Graeme MacLennan, Stephan U Dombrowski, Geoff Bellingan, Marion Campbell, Martin Eccles, Louise Rose, Kathy Rowan, Rob Shulman, A Peter R Wilson, Brian H. Cuthbertson

Notice bibliographique

RevueHealth Technology Assessment · 2014
Typearticle
Langueen
DomaineMedicine
ThématiqueNosocomial Infections in ICU
Établissements canadiensHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Organismes subventionnairesChief Scientist Office, Scottish Government Health and Social Care DirectorateUniversity of AberdeenBritish Society for Antimicrobial ChemotherapyDepartment of Health and Social CareNational Institute for Health and Care ResearchIntensive Care SocietyHealth Technology Assessment ProgrammeScottish Government
Mots-clésMedicineIntensive careDelphi methodIntensive care medicineIntensive care unitMEDLINEIntervention (counseling)Nursing

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Hospital-acquired infections (HAIs) are a major cause of morbidity and mortality. Critically ill patients in intensive care units (ICUs) are particularly susceptible to these infections. One intervention that has gained much attention in reducing HAIs is selective decontamination of the digestive tract (SDD). SDD involves the application of topical non-absorbable antibiotics to the oropharynx and stomach and a short course of intravenous (i.v.) antibiotics. SDD may reduce infections and improve mortality, but has not been widely adopted in the UK or internationally. Hence, there is a need to identify the reasons for low uptake and whether or not further clinical research is needed before wider implementation would be considered appropriate. OBJECTIVES: The project objectives were to (1) identify and describe the SDD intervention, (2) identify views about the evidence base, (3) identify acceptability of further research and (4) identify feasibility of further randomised controlled trials (RCTs). DESIGN: A four-stage approach involving (1) case studies of two ICUs in which SDD is delivered including observations, interviews and documentary analysis, (2) a three-round Delphi study for in-depth investigation of clinicians' views, including semi-structured interviews and two iterations of questionnaires with structured feedback, (3) a nationwide online survey of consultants in intensive care medicine and clinical microbiology and (4) semistructured interviews with international clinical triallists to identify the feasibility of further research. SETTING: Case studies were set in two UK ICUs. Other stages of this research were conducted by telephone and online with NHS staff working in ICUs. PARTICIPANTS: (1) Staff involved in SDD adoption or delivery in two UK ICUs, (2) ICU experts (intensive care consultants, clinical microbiologists, hospital pharmacists and ICU clinical leads), (3) all intensive care consultants and clinical microbiologists in the UK with responsibility for patients in ICUs were invited and (4) international triallists, selected from their research profiles in intensive care, clinical trials and/or implementation trials. INTERVENTIONS: SDD involves the application of topical non-absorbable antibiotics to the oropharynx and stomach and a short course of i.v. antibiotics. MAIN OUTCOME MEASURES: Levels of support for, or opposition to, SDD in UK ICUs; views about the SDD evidence base and about barriers to implementation; and feasibility of further SDD research (e.g. likely participation rates). RESULTS: (1) The two case studies identified complexity in the interplay of clinical and behavioural components of SDD, involving multiple staff. However, from the perspective of individual staff, delivery of SDD was regarded as simple and straightforward. (2) The Delphi study (n = 42) identified (a) specific barriers to SDD implementation, (b) uncertainty about the evidence base and (c) bimodal distributions for key variables, e.g. support for, or opposition to, SDD. (3) The national survey (n = 468) identified uncertainty about the effect of SDD on antimicrobial resistance, infection rates, mortality and cost-effectiveness. Most participants would participate in further SDD research. (4) The triallist interviews (n = 10) focused largely on the substantial challenges of conducting a large, multinational clinical effectiveness trial. CONCLUSIONS: There was considerable uncertainty about possible benefits and harms of SDD. Further large-scale clinical effectiveness trials of SDD in ICUs may be required to address these uncertainties, especially relating to antimicrobial resistance. There was a general willingness to participate in a future effectiveness RCT of SDD. However, support was not unanimous. Future research should address the barriers to acceptance and participation in any trial. There was some, but a low level of, interest in adoption of SDD, or studies to encourage implementation of SDD into practice. FUNDING: This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 18, No. 25. See the NIHR Journals Library website for further project information.

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)0,059
score de la tête « metaresearch » (Gemma)0,031
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,059
Score d'incertitude au seuil0,313

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0590,031
Méta-épidémiologie (sens strict)0,0010,002
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,001
Communication savante0,0020,003
Science ouverte0,0020,003
Intégrité de la recherche0,0030,002
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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 Opus0,032
Tête enseignante GPT0,445
Écart entre enseignants0,412 · 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'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations45
Publié2014
Routes d'admission1
Résumé présentoui

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