Notice bibliographique
Résumé
It is widely accepted that randomized clinical trials (RCT) provide a high level of scientific evidence. It is undisputable that RCTs have led to great advances in critically ill patient management in general and in patients with acute respiratory failure and the acute respiratory distress syndrome (ARDS) in particular [1–3]. However, RCTs have many limitations and are not exempt of flaws [4]: their sample-size calculations are often ‘optimized’ and the treatment effect overestimated to make study recruitment feasible (thus are actually underpowered); they usually take years from the initial hypothesis to the publication of their results; generally test only one approach versus another; and strict inclusion criteria to obtain a homogeneous population often prevent extrapolation of their results to the global population admitted to intensive care units. Last, examples of RCTs with different or contradictory results when replicated are not infrequent. On the other hand, observational studies have been criticized for their lower internal validity, the impossibility to adjust on unmeasured confounders, and their inability to provide causal inference. Nevertheless, they allow the inclusion of more ‘real life’ populations, focus on a specific subpopulation usually excluded from RCTs and have the practical advantage to be completed in a relatively short time [5]. When it comes to comparative effectiveness research, statistical tools such as propensity score or instrumental variables can markedly improve observational studies design. Taking ARDS as an example, the LUNG SAFE [6] study, an international observational study of patients with hypoxemic respiratory failure and ARDS, provided crucial information such as: underrecognition of the syndrome (how would you enroll patients with ARDS in a RCT when half of the patients meeting the inclusion criteria are not identified?); complexity of treatments choice (early treatment with noninvasive ventilation could be deleterious in patients with PaO2/FiO2 lower than 150 mmHg [7]); importance of the geo-economic variations on management and outcomes (survival was higher in countries with higher gross national income per person [8]); different managements in specific populations such as immunocompromised [9] or a lack of extensive workup when a cause of ARDS was not identified [10]. The bottom line is the paramount importance of identifying specific patients with specific needs. Close monitoring (of the respiratory system) in the ICU could solve this and help to optimize patient management individually. The inherent essence of intensive care is not only to grant organ-supportive treatments but to be able to provide close monitoring and to adapt treatment to this continuous assessment on the basis of physiological responses. The 11 articles written for the respiratory system issue of Current Opinion in Critical Care well reflect the importance of monitoring critically ill patients and personalizing their management. First of all, Beitler (pp. 3–11) discusses the tools available at the bedside to monitor the patient's respiratory system from the most widely available (physical examination) to the most recent technology (electrical impedance tomography) and their potential use to tailor ventilation to specific patients. As different types of patients likely require different investigations and treatments, Sinha and Calfee (pp. 12–20) provide an updated overview of the current research identifying homogeneous subgroups and phenotypes in ARDS and their different trajectories and responses to treatments; Ferreyro and Munshi (pp. 21–28) highlight the specificities and challenges of respiratory failure in immunocompromised patients, including a very informative focus on complications related to recent drugs such as immune checkpoint inhibitors or chimeric antigen receptor T-cell therapy; and Gibelin et al. (pp. 29–36) share their astute approach to rare respiratory diseases in the ICU including useful diagnosis strategy for intensivists facing these challenging cases. Finally, Cordioli et al. (pp. 37–44) present a modern and innovative approach to an old concept. Their physiological view of interactions between ventilation and circulation during cardiopulmonary resuscitation and interpretation of the capnogram may change the future management of cardiac arrest. Monitoring and treatments have to be adapted to the unique ICU environment in which the critically ill patient is admitted as emphasized by Inglis et al. (pp. 45–53) who remind us that there is not one but many different types of resource limited settings. Low and middle-income countries are too often left out of RCTs and observational studies and care providers in these underprivileged contexts develop inventive solutions to tackle the lack of expensive devices or supplies. Following on the theme of monitoring and personalized treatment, the importance of using the appropriate device (from the least to the most invasive) according to the situation is highlighted by the articles on noninvasive ventilation, airway pressure release ventilation (APRV) in pediatric patients, and extracorporeal membrane oxygenation (ECMO). García-de-Acilu et al. (pp. 54–62) take up the challenge of summarizing the current (and contradicting) knowledge and evidences on noninvasive ventilatory supports for acute hypoxemic respiratory failure. They wisely suggest to closely monitor patients receiving such treatments and avoid delaying intubations when time to move to invasive ventilation has come. Lalgudi Ganesan (pp. 63–70) synthesizes the physiology of APRV, its benefits, and limits and provides an insider analysis of the most recent RCT of use of APRV in children. Schmidt et al. (pp. 71–76) give their expert view of the recent advances in veno-venous ECMO in light of the recent ‘EOLIA’ trial which interpretation is controversial: ECMO benefit on mortality did not reach statistical significance but can be considered as being clinically significant. Monitoring and personalizing respiratory system management should not be limited to the lung but should also take into account respiratory muscles and the consequences of respiratory failure (dyspnea). Mirroring the concept of lung protective ventilation, Schepens et al. (pp. 77–85) nicely introduce the concept of diaphragm protective ventilation and explore the mechanisms of diaphragm myotrauma. Last but not least, Decavèle et al. (pp. 86–94) review the appropriate detection and treatment of patients’ dyspnea during mechanical ventilation giving a practical approach to this frequent and invalidating symptom. All these topics covered by acknowledged experts as well as brilliant and promising researchers/intensivists still in the early phase of their carrier give a fantastic overview of the modern approach of respiratory assessment, monitoring and management in critically ill patients. Precision medicine is still in its early days and it is clearer and clearer that the future of ventilation will be optimized by more accurate assessment, continuous monitoring with appropriate tools and personalized treatment based on the patient's trajectory, initial presentation, responses to treatment, and evolution in the ICU. Now take a deep breath and enjoy your reading. Acknowledgements The authors thank Thomas Piraino (RT, Department of Respiratory Therapy, St. Michael's Hospital, Toronto, Canada) for his careful English edition of the manuscript. Financial support and sponsorship L.B. holds the Keenan Chair in Critical Care and Respiratory Medicine. L.B. reports grants from Medtronic Covidien, grants and nonfinancial support from Air Liquide, nonfinancial support from Philips, nonfinancial support and other from General Electric, grants and nonfinancial support from Fisher Paykel, and nonfinancial support from Drager, consulting with Baxter, outside the submitted work. Conflicts of interest There are no conflicts of interest.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».