MétaCan
Menu
Retour à la cohorte
Enregistrement W2231637814 · doi:10.1155/2014/313020

Rapid Response Teams and End‐of‐Life Care

2014· article· en· W2231637814 sur OpenAlexaffabout
James Downar

Notice bibliographique

RevueCanadian Respiratory Journal · 2014
Typearticle
Langueen
DomaineMedicine
ThématiquePalliative Care and End-of-Life Issues
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineRapid response teamPalliative careEnd-of-life careIntensive care unitResuscitation OrdersIntensive careResuscitationNursingIntensive care medicineEmergency medicineCardiopulmonary resuscitation

Résumé

récupéré en direct d'OpenAlex

Rapid response teams (RRTs) were not originally intended to play a role in end-of-life (EoL) care; however, studies from around the world suggest that they do. In the current issue of the Canadian Respiratory Journal, Tam et al (1) (pages 302-307) present the results of a two-year retrospective chart review showing that an RRT participated in EoL discussions in 319 cases. They found that RRT participation in EoL discussions often triggered a change in resuscitation orders and was associated with a lower likelihood of intensive care unit (ICU) admission and a higher likelihood of palliative care consultation. These findings add to a growing body of evidence for the important role that RRTs play in EoL care. Overall, approximately one in 10 new RRT consultations result in a limitation of treatment order, and RRTs are consulted to see 25% to 50% of patients who die in hospital (2-4). In particular, RRTs appear to play an important role in EoL conversations that occur later in hospitalization and after hours (5). Of note, the incidence of RRT involvement in EoL discussions is broadly consistent among studies from around the world, suggesting that this is not an idiosyncratic cultural phenomenon, but rather a reflection of human nature. Humans tend to procrastinate, and EoL discussions are no exception. Studies routinely show that patients want to talk about their EoL preferences, and physicians believe that EoL discussions are important. Yet, EoL discussions are typically delayed until very late in the course of disease, and are often prompted by a significant event such as an unscheduled hospital admission or a clinical deterioration. For many patients, families and physicians, EoL conversations cannot occur unless they are in earnest. The importance of the RRT then becomes obvious – it is the first team to arrive when a clinical deterioration appears to be imminent, and it is the final opportunity to deviate from the ‘default’ pathway of aggressive care before the patient is admitted to the ICU. Is it appropriate for the RRT to be discussing EoL care? In many ways, the RRT is well suited to this role. RRT staff have experience with critical care and are the most appropriate individuals to obtain ‘consent’ for a course of ICU treatment. They also have experience with this type of discussion from their time in the ICU. Some may argue that it is the role of the most responsible physician(s) (MRPs) to discuss resuscitation orders and EoL care. However, in that sense, EoL discussions are no different than fluid boluses, diuretics, antibiotics and many of the other common RRT interventions. In theory, the MRPs should be the ones using these interventions in a timely fashion to prevent deterioration. The RRT exists because they don’t. There are also concerns about using the RRT in this manner. The RRT usually has no previous relationship with the patient or family; therefore, the emotional and time burden of taking on this role for a large proportion of inpatients could be overwhelming. The RRT may also be forced to make decisions in a crisis situation, without the benefit of input from the patient (who is clinically deteriorating), which is not ideal. Furthermore, the RRT’s behaviour may be influenced by the availability of ICU resources. Stelfox et al (6) found that the availability or unavailability of ICU beds was significantly associated with the probability that an RRT consult would result in an ICU admission or a limitation of treatment order. However, the overall hospital mortality for these patients was not affected by bed availability, suggesting that empty beds were leading to ‘soft’ admissions, rather than full beds leading to inadequate care. Following on the earlier theme, an empty ICU bed was simply another opportunity to delay the EoL conversation. Although we may wish to move EoL discussions to earlier in the disease course, RRTs will always have a role to play in EoL discussions and care, and we need to equip them properly for this role. Communication training is a critical element, and can improve both comfort and skill at participating in challenging discussions. But highquality EoL care is more complicated than simply avoiding an ICU admission. We found that RRTs often missed important opportunities to improve symptom management and psychosocial issues (4); therefore, we should consider automatic consultations to palliative care and other services, as well as preprinted order sets for comfort care. Tam et al (1) found that the introduction of a preprinted order set was associated with an increase in limitation of treatment orders; however, improving symptom control and other aspects of EoL care may be more challenging. If a complex, well-funded, multicomponent EoL intervention is ineffective for improving EoL care in the ICU (7), then we must temper our expectations for a similar intervention on the wards. editoRial

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)0,008
score de la tête « metaresearch » (Gemma)0,033
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: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,041

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,033
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0020,004
Communication savante0,0060,006
Science ouverte0,0010,005
Intégrité de la recherche0,0060,007
Charge utile insuffisante (le modèle a refusé de juger)0,0090,001

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 Opus0,060
Tête enseignante GPT0,340
Écart entre enseignants0,279 · 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
GenreSynthèse

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

En bref

Citations1
Publié2014
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueCanadian Respiratory JournalMême sujetPalliative Care and End-of-Life IssuesTravaux en français237 207