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Improvements in living conditions and increasing life expectancy have combined to result in ever older patients being admitted to hospital. In parallel, the increasing incidence of cancer, along with the improved efficacy of anti-cancer therapies has led to greater needs for intensive care among cancer patients.The objectives underpinning the management of cancer patients in the intensive care unit (ICU) are to achieve a return to a clinical status that would allow the patient to be either, transferred back to the original unit, or discharged from the hospital with an acceptable quality of life, and where warranted, pursuit of cancer therapy. The relevance of ICU admission should be assessed systematically for patients with active cancer. The decision needs to be made taking into account the expected benefit for the patient, the lifesupport therapies that are possible with discussion about a care project, and also considering the future quality of life and the short and long-term prognosis. Anticipating the question of potential ICU admission should help protect the patient against both inappropriate refusal of intensive care, and inappropriate admission to the ICU that might only lead to unreasonable therapeutic obstinacy. The intensive care physician has a major role to play in helping the cancer patient to develop an appropriate and flexible healthcare project. Anticipating the question of ICU admission in advance, as well as a close alliance between the oncologist and the intensive care physician are the two keys to the success of a healthcare project focused on the patient.

BackgroundDifferent video-laryngoscopes (VDLs) for endotracheal intubation (ETI) have recently been developed. We compared the performance of the VDL Airway Scope (AWS) with the direct laryngoscopy by Macintosh (DLM) for ETI success, time and learning.Methods We performed an experimental manikin controlled study. Twenty experienced (experts) and 40 inexperienced operators (novices) for DLM-ETI were enrolled. None of them had experience with the use of AWS-VDL. Novices were assigned to start learning with DLM or AWS, and two sub-groups of 20 novices were formed. Experts group constituted the control group. Each participant performed 10 ETI attempts with each device on the same standard manikin. The primary endpoint was the ETI success probability. Secondary endpoints were ETI time, technical validity and qualitative evaluation for each technique. We also assessed the learning order and the successive attempts effects for these parameters.ResultsOverall, 1200 ETI attempts were performed. ETI success probability was higher with the AWS than with the DLM for all operators (98 vs. 81 %; p < 0.0001) and for experts compared to novices using devices in the same order (97 vs. 83 %; p = 0.0002). Overall ETI time was shorter with the AWS than with the DLM (13 vs. 20 s; p < 0.0001) and for experts compared to novices using devices in the same order (11 vs. 21 s; p < 0.0001). Among novices, those starting learning with AWS had higher ETI success probability (89 vs. 83 %; p = 0.03) and shorter ETI time (18 vs. 21 s; p = 0.02). Technical validity was found better with the AWS than DLM for all operators. Novices expressed global satisfaction and device preference for the AWS, whereas experts were indifferent.ConclusionsAWS-VDL permits faster, easier and more reliable ETI compared to the DLM whatever the previous airway ETI experience and could be a useful device for DLM-ETI learning.

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