Identifying Subjects at Risk for Diaphragm Atrophy During Mechanical Ventilation Using Routinely Available Clinical Data
| Autor: | Stefannie Vorona, Gordon D. Rubenfeld, Michael C. Sklar, Laurent Brochard, Martin Urner, Eddy Fan, Niall D. Ferguson, Lu Chen, Martin Dres, Ewan C. Goligher, Nicholas Mitsakakis |
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| Rok vydání: | 2020 |
| Předmět: |
Pulmonary and Respiratory Medicine
medicine.medical_specialty Respiratory rate medicine.medical_treatment Diaphragm Diaphragmatic breathing Critical Care and Intensive Care Medicine Contractility 03 medical and health sciences 0302 clinical medicine Atrophy Internal medicine medicine Humans Prospective Studies Ultrasonography Mechanical ventilation Receiver operating characteristic business.industry General Medicine Odds ratio medicine.disease Respiration Artificial Diaphragm (structural system) Editorial 030228 respiratory system Cardiology business |
| Zdroj: | Respir Care |
| ISSN: | 1943-3654 0020-1324 |
| DOI: | 10.4187/respcare.08223 |
| Popis: | Diaphragmatic respiratory effort during mechanical ventilation is an important determinant of patient outcome, but direct measurement of diaphragmatic contractility requires specialized instrumentation and technical expertise. We sought to determine whether routinely collected clinical variables can predict diaphragmatic contractility and stratify the risk of diaphragm atrophy.We conducted a secondary analysis of a prospective cohort study on diaphragm ultrasound in mechanically ventilated subjects. Clinical variables, such as breathing frequency, ventilator settings, and blood gases, were recorded longitudinally. Machine learning techniques were used to identify variables predicting diaphragm contractility and stratifying the risk of diaphragm atrophy (10% decrease in thickness from baseline). Performance of the variables was evaluated in mixed-effects logistic regression and random-effects tree models using the area under the receiver operating characteristic curve.Measurements were available for 761 study days in 191 subjects, of whom 73 (38%) developed diaphragm atrophy. No routinely collected clinical variable, alone or in combination, could accurately predict either diaphragm contractility or the development of diaphragm atrophy (model area under the receiver operating characteristic curve 0.63-0.75). The risk of diaphragm atrophy was not significantly different according to the presence or absence of patient-triggered breaths (38.3% vs 38.6%; odds ratio 1.01, 95% CI 0.05-2.03). Diaphragm thickening fraction15% during either of the first 2 d of the study was associated with a higher risk of atrophy (44.6% vs 26.1%; odds ratio 2.28, 95% CI 1.05-4.95).Diaphragmatic contractility and the risk of diaphragm atrophy could not be reliably determined from routinely collected clinical variables and ventilator settings. A single measurement of diaphragm thickening fraction measured within 48 h of initiating mechanical ventilation can be used to stratify the risk of diaphragm atrophy during mechanical ventilation. |
| Databáze: | OpenAIRE |
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