Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study.
An early diagnosis of Intensive Care Unit-acquired weakness (ICU-AW) using muscle strength assessment is not possible in most critically ill patients. We hypothesized that development of ICU-AW can be predicted reliably two days after ICU admission, using patient characteristics, early available cli...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4210178?pdf=render |
| _version_ | 1818333733504155648 |
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| author | Luuk Wieske Esther Witteveen Camiel Verhamme Daniela S Dettling-Ihnenfeldt Marike van der Schaaf Marcus J Schultz Ivo N van Schaik Janneke Horn |
| author_facet | Luuk Wieske Esther Witteveen Camiel Verhamme Daniela S Dettling-Ihnenfeldt Marike van der Schaaf Marcus J Schultz Ivo N van Schaik Janneke Horn |
| author_sort | Luuk Wieske |
| collection | DOAJ |
| description | An early diagnosis of Intensive Care Unit-acquired weakness (ICU-AW) using muscle strength assessment is not possible in most critically ill patients. We hypothesized that development of ICU-AW can be predicted reliably two days after ICU admission, using patient characteristics, early available clinical parameters, laboratory results and use of medication as parameters.Newly admitted ICU patients mechanically ventilated ≥2 days were included in this prospective observational cohort study. Manual muscle strength was measured according to the Medical Research Council (MRC) scale, when patients were awake and attentive. ICU-AW was defined as an average MRC score <4. A prediction model was developed by selecting predictors from an a-priori defined set of candidate predictors, based on known risk factors. Discriminative performance of the prediction model was evaluated, validated internally and compared to the APACHE IV and SOFA score.Of 212 included patients, 103 developed ICU-AW. Highest lactate levels, treatment with any aminoglycoside in the first two days after admission and age were selected as predictors. The area under the receiver operating characteristic curve of the prediction model was 0.71 after internal validation. The new prediction model improved discrimination compared to the APACHE IV and the SOFA score.The new early prediction model for ICU-AW using a set of 3 easily available parameters has fair discriminative performance. This model needs external validation. |
| first_indexed | 2024-12-13T13:56:20Z |
| format | Article |
| id | doaj.art-beb40d163e87482683ea523da2adbcb1 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-13T13:56:20Z |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-beb40d163e87482683ea523da2adbcb12022-12-21T23:42:53ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-01910e11125910.1371/journal.pone.0111259Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study.Luuk WieskeEsther WitteveenCamiel VerhammeDaniela S Dettling-IhnenfeldtMarike van der SchaafMarcus J SchultzIvo N van SchaikJanneke HornAn early diagnosis of Intensive Care Unit-acquired weakness (ICU-AW) using muscle strength assessment is not possible in most critically ill patients. We hypothesized that development of ICU-AW can be predicted reliably two days after ICU admission, using patient characteristics, early available clinical parameters, laboratory results and use of medication as parameters.Newly admitted ICU patients mechanically ventilated ≥2 days were included in this prospective observational cohort study. Manual muscle strength was measured according to the Medical Research Council (MRC) scale, when patients were awake and attentive. ICU-AW was defined as an average MRC score <4. A prediction model was developed by selecting predictors from an a-priori defined set of candidate predictors, based on known risk factors. Discriminative performance of the prediction model was evaluated, validated internally and compared to the APACHE IV and SOFA score.Of 212 included patients, 103 developed ICU-AW. Highest lactate levels, treatment with any aminoglycoside in the first two days after admission and age were selected as predictors. The area under the receiver operating characteristic curve of the prediction model was 0.71 after internal validation. The new prediction model improved discrimination compared to the APACHE IV and the SOFA score.The new early prediction model for ICU-AW using a set of 3 easily available parameters has fair discriminative performance. This model needs external validation.http://europepmc.org/articles/PMC4210178?pdf=render |
| spellingShingle | Luuk Wieske Esther Witteveen Camiel Verhamme Daniela S Dettling-Ihnenfeldt Marike van der Schaaf Marcus J Schultz Ivo N van Schaik Janneke Horn Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study. PLoS ONE |
| title | Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study. |
| title_full | Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study. |
| title_fullStr | Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study. |
| title_full_unstemmed | Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study. |
| title_short | Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study. |
| title_sort | early prediction of intensive care unit acquired weakness using easily available parameters a prospective observational study |
| url | http://europepmc.org/articles/PMC4210178?pdf=render |
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