Cognitive phenotypes 1 month after ICU discharge in mechanically ventilated patients: a prospective observational cohort study

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To access the full text documents, please follow this link: http://hdl.handle.net/20.500.12328/2539

dc.contributor.author	Fernández-Gonzalo, Sol
dc.contributor.author	Navarra-Ventura, Guillem
dc.contributor.author	Bacardit, Neus
dc.contributor.author	Gomà Fernández, Gemma
dc.contributor.author	De Haro, Candelaria
dc.contributor.author	Subirà Cuyàs, Carles
dc.contributor.author	López-Aguilar, Josefina
dc.contributor.author	Magrans, Rudys
dc.contributor.author	Sarlabous, Leonardo
dc.contributor.author	Aquino‑Esperanza, José
dc.contributor.author	Jodar, Mercè
dc.contributor.author	Rué, Montserrat
dc.contributor.author	Ochagavia, Ana
dc.contributor.author	Palao, Diego J.
dc.contributor.author	Fernández, Rafael
dc.contributor.author	Fernández Fernández, Rafael
dc.contributor.author	Blanch, Lluís
dc.date	2021-05-13T16:57:53Z
dc.date	2021-05-13T16:57:53Z
dc.date	2020
dc.identifier	Fernández-Gonzalo, Sol; Navarra-Ventura, Guillem; Bacardit, Neus [et al.]. Cognitive phenotypes 1 month after ICU discharge in mechanically ventilated patients: a prospective observational cohort study.
dc.identifier	1364-8535
dc.identifier	http://hdl.handle.net/20.500.12328/2539
dc.identifier	https://dx.doi.org/10.1186/s13054-020-03334-2
dc.identifier.uri	http://hdl.handle.net/20.500.12328/2539
dc.description	Background: ICU patients undergoing invasive mechanical ventilation experience cognitive decline associated with their critical illness and its management. The early detection of different cognitive phenotypes might reveal the involvement of diverse pathophysiological mechanisms and help to clarify the role of the precipitating and predisposing factors. Our main objective is to identify cognitive phenotypes in critically ill survivors 1 month after ICU discharge using an unsupervised machine learning method, and to contrast them with the classical approach of cognitive impairment assessment. For descriptive purposes, precipitating and predisposing factors for cognitive impairment were explored. Methods: A total of 156 mechanically ventilated critically ill patients from two medical/surgical ICUs were prospectively studied. Patients with previous cognitive impairment, neurological or psychiatric diagnosis were excluded. Clinical variables were registered during ICU stay, and 100 patients were cognitively assessed 1 month after ICU discharge. The unsupervised machine learning K-means clustering algorithm was applied to detect cognitive phenotypes. Exploratory analyses were used to study precipitating and predisposing factors for cognitive impairment. Results: K-means testing identified three clusters (K) of patients with different cognitive phenotypes: K1 (n = 13), severe cognitive impairment in speed of processing (92%) and executive function (85%); K2 (n = 33), moderate-to-severe deficits in learning-memory (55%), memory retrieval (67%), speed of processing (36.4%) and executive function (33.3%); and K3 (n = 46), normal cognitive profile in 89% of patients. Using the classical approach, moderate-to-severe cognitive decline was recorded in 47% of patients, while the K-means method accurately classified 85.9%. The descriptive analysis showed significant differences in days (p = 0.016) and doses (p = 0.039) with opioid treatment in K1 vs. K2 and K3. In K2, there were more women, patients were older and had more comorbidities (p = 0.001) than in K1 or K3. Cognitive reserve was significantly (p = 0.001) higher in K3 than in K1 or K2. Conclusion: One month after ICU discharge, three groups of patients with different cognitive phenotypes were identified through an unsupervised machine learning method. This novel approach improved the classical classification of cognitive impairment in ICU survivors. In the exploratory analysis, gender, age and the level of cognitive reserve emerged as relevant predisposing factors for cognitive impairment in ICU patients.
dc.format	11
dc.format	application/pdf
dc.language	eng
dc.publisher	Springer Nature
dc.relation	Critical Care
dc.relation	24;
dc.rights	© The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
dc.rights	https://creativecommons.org/licenses/by/4.0/
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Cognició
dc.subject	Respiració artificial
dc.subject	Fenotip
dc.subject	Envelliment
dc.subject	Cognición
dc.subject	Respiración artificial
dc.subject	Fenotipos
dc.subject	Envejecimiento
dc.subject	Cognition
dc.subject	Artificial respiration
dc.subject	Phenotype
dc.subject	Aging
dc.subject	61
dc.subject	616.8
dc.title	Cognitive phenotypes 1 month after ICU discharge in mechanically ventilated patients: a prospective observational cohort study
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion

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