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Enregistrement W4390738923 · doi:10.1093/eurjcn/zvad135

Evidence-based strategies for movement after sternotomy

2024· article· en· W4390738923 sur OpenAlexaboutno aff
Stein Ove Danielsen, Irene Lie

Notice bibliographique

RevueEuropean Journal of Cardiovascular Nursing · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueCardiac, Anesthesia and Surgical Outcomes
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineMovement (music)Physical medicine and rehabilitationIntensive care medicine

Résumé

récupéré en direct d'OpenAlex

This invited commentary refers to: ‘Post-sternotomy movement strategies in adults: a scoping review’, by K. Wiens et al., https://doi.org/10.1093/eurjcn/zvad109. The article ‘Post-sternotomy Movement Strategies in Adults: A scoping review’ is a comprehensive review focusing on post-sternotomy movement strategies for adults.1 More than 1.5 million patients experience sternotomy annually,2 and strategies for safe movements for adults have traditionally been based on expert opinions. Standard precautions (SPs) are the most common practice.3 However, restricting upper limb and truncus movements has little support in evidence-based international guidelines for cardiac rehabilitation,4 and a systematic review and meta-analysis from 2019 reveal that resistance training is likely safe and feasible with positive physical outcomes improving the rehabilitation.5 The restrictions in traditional movements post-surgery can contradict the goal of a quick return to the daily life activities and optimal healing.6 An alternative approach yielding a safe recovery is the movements strategy, Keep Your Move in the Tube (KYMITTTM), has become part of practice in the USA and Canada.7 The scoping review of Wiens et al. involved a systematic literature search, adhering to the PRISMA-ScR guidelines.8 The search was completed between October and November 2022. The studies included were published from 2010 onwards and originated from the USA, Australia, Canada, and Sweden. The study designs varied, and the quality of these studies was assessed using the Joanna Briggs Institute (JBI) Levels of Evidence for Effectiveness,9 with most studies aligning with Level 5 (the lowest level of evidence) and others ranging between Levels 1 and 3 (five of the studies). The studies suggested that the KYMITTTM was as safe as SP with no significant differences in patient complications. Moreover, KYMITTTM was associated with better functional status over the short-term and an earlier return to function without causing patient harm or adverse events. One of the important findings in this review is the potential re-evaluation of traditional practices, such as the use of SP, in light of the emerging evidence favouring KYMITTTM. This movement strategy not only instils confidence in patients but also represents a more patient-centred approach, allowing greater freedom in movement and potentially leading to enhanced rehabilitation outcomes. This is in line with previous research.5,6,10,11 However, it is known that there can be a significant delay in translating and implementing new evidence into healthcare, where a ‘17-year gap’ from research to practice is described.12,13 Therefore, this scoping review needs all the attention it can get to expedite its integration into clinical practice and improve patient outcomes. The review underlines the importance of transitioning towards evidence-informed practices in post-sternotomy care. It highlights that while traditional SP has been the norm, the findings from various studies, including those with lower levels of evidence, suggest that KYMITTTM could offer significant benefits in terms of patient safety and efficacy. This shift is crucial, especially considering the evolving landscape of patient care where individualized, patient-centred approaches are increasingly valued and warranted.14 However, what are the ways forward to narrow the gap from this evidence to the expert practitioners in the clinical field? Nilsen et al.15 state that implementation science and improvement science have the same endpoint: improving healthcare. To achieve this, increased collaboration is necessary to bridge the silos between the fields. Improvement science in terms of providing evidence is brought forward by the scoping review, but it can be questioned how implementation science can assist the cardiac healthcare workers to use it in practice. The Agency for Healthcare Research and Quality16 published a report on quality improvement strategies in 2004. The proposed strategies include the following: provider reminder systems; facilitated relay of clinical data to providers; audit and feedback; provider education; patient education; promotion of self-management; patient reminders; organizational change; and financial, regulatory, or legislative incentives.16 Implementation science gives clues to how research can be implemented. Brownson et al.17 provide recommendations that can support the work on advancing evidence and implementation science. Notably, they point to core areas that need more attention: ‘Reconsider how the evidence base is determined, improve understanding of contextual effects on implementation, sharpen the focus on health equity, conduct more policy implementation research and evaluation and pay greater attention to audience and stakeholder differences’.17 Sarkies et al.18 reviewed the effectiveness of research implementation strategies and conveyed the following: ‘knowledge brokering, targeted messaging, database access, policy briefs, workshops, digital materials, fellowship programmes, literature reviews/rapid reviews, consortium, certificate course, multi-stakeholder policy dialogue, and multifaceted strategies’. Worth mentioning, Sarkies et al.18 indicated that resource-intensive strategies are not always superior to less, meaning that simple strategies can be as effective as more complex and costly strategies. Moreover, inter-relating factors as having an ‘imperative for change, building trust, developing a shared vision, and action change mechanisms’ are important when considering strategies for changing practice based on new evidence.18 Providing effective communication strategies and accessing appropriate resources can support these factors.18 Regarding local implementation, Joyce et al.19 stated that a focus on factors that will work in the local context can drive the practice locally and be an effective way forward. This implies that local stakeholders who can be derailers for another movement strategy after sternotomy should be targeted for education in, e.g. KYMITTTM. Hence, educating and training clinical staff to increase their engagement with research can build a bridge between research and clinical care.20 The review calls for further research, particularly larger-scale multi-centre randomized controlled trials, to strengthen the level of evidence supporting KYMITTTM and other movement strategies. Doing so, the evidence base for KYMITTM would be more solid. It also emphasizes the need for future studies that incorporate patient perspectives, focusing on movement strategies that are not only consistently prescribed and easy to understand but also empower patients in their recovery journey. The authors also state that inclusion of patient perspectives is crucial in developing movement strategies, not only to adhere to clinical guidelines but also to resonate with the patients’ experiences and preferences. The latter is a complex task because it needs a multi-faceted approach and requires support from implementation science21 (Central Illustration). In conclusion, we believe that the scoping review by Wiens et al. adds evidence on the effectiveness and safety of different movement strategies after sternotomy. It indicates that KYMITTTM is promising, safe, and beneficial for patients recovering from sternotomy. Moreover, the review advocates for a paradigm shift towards evidence-informed practices and highlights the need of more high-quality research to solidify these strategies and develop patient-centred guidelines to empower patients in their rehabilitation phase. The authors received no financial support for the authorship or publication of this article. No new data were generated or analysed in support of this publication.

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)0,016
score de la tête « metaresearch » (Gemma)0,097
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,082

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0160,097
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0040,007
Bibliométrie0,0060,004
Études des sciences et des technologies0,0010,002
Communication savante0,0050,004
Science ouverte0,0040,003
Intégrité de la recherche0,0060,006
Charge utile insuffisante (le modèle a refusé de juger)0,0140,003

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 Opus0,042
Tête enseignante GPT0,289
Écart entre enseignants0,247 · 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'étudeRevue systématique
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

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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