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Enregistrement W2321527120 · doi:10.1213/ane.0000000000000367

Goal-Directed Therapy

2014· letter· en· W2321527120 sur OpenAlexaboutno aff
Maurizio Cecconi, Andrew Rhodes

Notice bibliographique

RevueAnesthesia & Analgesia · 2014
Typeletter
Langueen
DomaineMedicine
ThématiqueHemodynamic Monitoring and Therapy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicinePsychology

Résumé

récupéré en direct d'OpenAlex

In the fields of anesthesia and intensive care medicine, goal-directed therapy (GDT) refers to the use of fluids and/or inotropes to target hemodynamic goals to improve oxygen delivery (DO2) to the tissues.1 Shoemaker et al.2 observed that high-risk patients with greater cardiac output (CO), DO2, and oxygen consumption after surgery were more likely to survive. These observations led them to hypothesize that patients with lower levels of DO2 develop an oxygen debt, which ultimately leads to tissue dysoxia, multiorgan failure, and death. In a milestone study published in 1988, Shoemaker et al.2 suggested that hemodynamic optimization (GDT) targeting the CO and DO2 levels observed in the survivors group lead to an improved outcome. Since then, in a series of studies, investigators have tested GDT during and after surgery. The majority of these studies showed an improved outcome, mainly in terms of complications and/or length of hospital stay.3–7 These studies were mostly single center, with a relatively small number of patients. Our group has published a series of meta-analyses to try to resolve the continuing uncertainty around the subject.1,8 We can summarize the findings in this way: mortality is reduced in the greatest-risk group of surgical patients and complications are reduced even in the lower-risk groups when there are predefined protocols to achieve hemodynamic targets. The volume of available evidence led the United Kingdom National Institute of Health and Care Excellence to endorse the use of esophageal Doppler for GDT in the perioperative care of high-risk surgical patients.9 At the same time, a number of new technologies have become available, allowing CO monitoring to be accomplished in a minimally invasive way.10,11 In this issue of Anesthesia & Analgesia, Pestaña et al.12 present the results of a multicenter randomized controlled trial on GDT (the Pulmonary Hypertension Screening, a Multidisciplinary Approach in Scleroderma [POEMAS] study) using one of these new technologies. The primary outcomes (incidence of postoperative complications and length of hospital stay) of the study were not different between the GDT group guided by the Cheetah NICOM (i.e., totally Non-Invasive Hemodynamic and Cardiac Output Monitoring System) monitor (Cheetah Medical, Israel) and the control group. There were more reoperations in the control group, and there was a trend toward a lower rate of postoperative wound infection, but this rate did not reach statistical significance. There are a number of possible explanations for these results, which include the following: the multicenter nature of the trial may have been a problem in terms of surgical standardization, with different centers reporting different surgical practices and very different length of stay and outcomes13; the study may have been underpowered (the complication rate in the control group was much lower than expected—41% vs 60%); the protocol may have not led to significantly different management; indeed, even if more inotropes were administered in the GDT group, there was no difference in the amount of fluid administered. Also, it is possible that the monitor did not provide data that were either accurate or precise enough to be used to change therapy. Although this is a possibility, validation studies have shown that the NICOM, based on the principle of bioreactance, should be reliable at least in tracking changes in CO.14,15 Nevertheless, this study adds to more recent ones showing no benefit for GDT.16–18 Over the years, in parallel to the development of GDT, our understanding of how to improve the care of surgical patients has evolved. We now focus on the overall process rather than on single aspects of perioperative care. This focus has led to the development of strategies such as enhanced recovery after surgery.19,20 This strategy is pragmatic, where best-available evidence is summarized to develop bundles of care that standardize processes with the aim of improving outcomes. With the bundle approach, it is often difficult to interpret the effect of any of the single interventions that form part of the bundle. This overall improvement in standard of care may partly explain the recent results in which improvements in outcome have not been found. It is quite possible that as care has evolved in the modern evidence-based environment, the ability of a single intervention to influence outcome has been reduced; there is a reduction in the signal-to-noise ratio. The more recent evidence suggests that GDT is not bringing the added benefit to the care of surgical patients that was previously described.21,22 There is also some evidence that stroke volume maximization strategies could be harmful in aerobically fit patients by leading to volume overload.21 It is also possible that the positive evidence of many published papers reflect publication bias,23 with positive results more likely to be published than negative ones, or it may reflect changes in perioperative care. Does it mean it is time to move on and get rid of all monitoring techniques? We believe that the truth is in the middle. It is important to remember that it is with the use of flow monitors that we have improved our understanding of cardiovascular physiology, for example, moving away from using central venous pressure as a marker of preload,24 to learn how to perform a fluid challenge rather than just giving maintenance fluids.25 We have learned how heart–lungs interactions work in patients during general anesthesia and how pulse pressure variation can predict fluid responsiveness.26 Our understanding of fluid requirements and needs has improved together with improvements in other areas of perioperative care. Medicine is both an art and a science, and a systematic approach may bother those who believe experience is the only thing that counts; the real expert, however, knows that he/she can bring valuable contributions on top of a standard of care. A learning curve has to be expected for delivering bundles of care effectively. The recent OPTIMISE (i.e., Optimisation of peri-operative cardiovascular management to improve surgical outcome) study showed no difference in the primary outcome between GDT and control; however, when a planned subanalysis was performed, removing the first 10 patients per site (i.e., removing the “learning curve”), the results became significant, with GDT leading to fewer postoperative complications.27 In summary, providing the best care remains as valid as ever. GDT is safe22; in the greatest-risk patients, it can bring both clinical and economical benefits.28 We do not think that this is the end of GDT. All therapy should be goal directed; the challenge is how to set the right goals. GDT may now not show the strong difference in outcome observed in the first studies, but it does not mean that we should get rid of it. It may only mean that just focusing solely on hemodynamics is too simplistic an approach. GDT has to be considered mainly as part of a bundle of treatments that encompasses all facets of care for these patients.29 New bundles for the care of surgical patients will have to take this into account and are largely awaited. DISCLOSURES Name: Maurizio Cecconi, MD, FRCA, MD(UK), FICM. Contribution: This author helped write the manuscript. Attestation: Maurizio Cecconi approved the final manuscript. Conflicts of Interest: Maurizio Cecconi has received honoraria or travel expenses or both in the last 5 years from Edwards Lifesciences, LiDCO, Cheetah Medical, Bmeye (Amsterdam, The Netherlands), Masimo (Neuchatel, Switzerland), and Deltex Medical. Name: Andrew Rhodes, FRCP, FRCA, FFICM, MD. Contribution: This author helped write the manuscript. Attestation: Andrew Rhodes approved the final manuscript. Conflicts of Interest: Andres Rhodes has received honoraria from and serves on an advisory board for LiDCO (London, UK) and has received honoraria from Covidien (Dublin, Ireland), Edwards Lifesciences, and Cheetah Medical (Vancouver, WA). This manuscript was handled by: Maxime Cannesson, MD, PhD.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

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

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 Opus0,019
Tête enseignante GPT0,265
Écart entre enseignants0,246 · 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 tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations9
Publié2014
Routes d'admission1
Résumé présentoui

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