dc.contributor.author | Serpa Neto, Ary | |
dc.contributor.author | Deliberato, Rodrigo O | |
dc.contributor.author | Johnson, Alistair Edward William | |
dc.contributor.author | Pollard, Tom Joseph | |
dc.contributor.author | Celi, Leo Anthony G. | |
dc.contributor.author | Pelosi, Paolo | |
dc.contributor.author | Gama de Abreu, Marcelo | |
dc.contributor.author | Schultz, Marcus J | |
dc.date.accessioned | 2021-12-17T17:23:58Z | |
dc.date.available | 2021-09-20T17:17:03Z | |
dc.date.available | 2021-12-17T17:23:58Z | |
dc.date.issued | 2019-10 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/131432.2 | |
dc.description.abstract | Recently, we showed how mechanical power (MP) was associated with patient–centered outcomes in two large prospective cohorts of critically ill patients under invasive ventilation [1]. Normalization of MP, e.g., to the predicted body weight (PBW), has been put forward [2]. One recent paper showed MP normalized to PBW to be a better predictor of mortality than the absolute MP, at least in ARDS patients [3]. We here report the results of a posthoc analysis of the datasets used in our abovementioned publication [1]. We tested the hypothesis that MP normalized to three common anthropometric indexes, i.e., PBW, body mass index (BMI), and body surface area (BSA) are better predictors of in–hospital mortality than absolute MP in critically ill patients under invasive ventilation. | en_US |
dc.publisher | Springer Berlin Heidelberg | en_US |
dc.relation.isversionof | https://doi.org/10.1007/s00134-019-05794-9 | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | Springer Berlin Heidelberg | en_US |
dc.title | Normalization of mechanical power to anthropometric indices: impact on its association with mortality in critically ill patients | en_US |
dc.type | Article | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Institute for Medical Engineering & Science | en_US |
dc.contributor.department | Harvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiology | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2020-09-24T20:45:18Z | |
dc.language.rfc3066 | en | |
dc.rights.holder | Springer-Verlag GmbH Germany, part of Springer Nature | |
dspace.embargo.terms | Y | |
dspace.date.submission | 2020-09-24T20:45:18Z | |
mit.license | PUBLISHER_POLICY | |
mit.metadata.status | Publication Information Needed | en_US |