Michele C Balas1, Alai Tan2, Lorraine C Mion3, Brenda Pun4, Jin Jun3, Audrey Brockman5, Jinjian Mu2, E Wesley Ely6, Eduard E Vasilevskis7. 1. College of Nursing, University of Nebraska Medical Center, Omaha, NE. Electronic address: mibalas@unmc.edu. 2. Centers for Research and Health Analytics, College of Nursing, The Ohio State University, Columbus, OH. 3. Centers of Healthy Aging, Self-Management, and Complex Care, College of Nursing, The Ohio State University, Columbus, OH. 4. Critical Illness, Brain Dysfunction, and Survivorship Center, Vanderbilt University Medical Center, Nashville, TN. 5. College of Nursing, The Ohio State University, Columbus, OH. 6. Critical Illness, Brain Dysfunction, and Survivorship Center, Vanderbilt University Medical Center, Nashville, TN; Division of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN; The Geriatric Research Education Clinical Center (GRECC), Veterans Administration Tennessee Valley Healthcare System, Nashville, TN; Center for Health Services Research, Vanderbilt University Medical Center, Nashville, TN; Center for Quality Aging, Vanderbilt University Medical Center, Nashville, TN. 7. The Geriatric Research Education Clinical Center (GRECC), Veterans Administration Tennessee Valley Healthcare System, Nashville, TN; Section of Hospital Medicine, Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.
Abstract
BACKGROUND: Broad-scale adoption of spontaneous awakening trials (SATs) and spontaneous breathing trials (SBTs) into everyday practice has been slow, and uncertainty exists regarding what factors facilitate or impede their routine delivery. RESEARCH QUESTION: What patient, practice, and pharmacologic factors are associated with SAT and SBT performance and to what extent do they predict overall SAT/SBT performance? STUDY DESIGN AND METHODS: This secondary analysis used data collected from a national quality improvement collaborative composed of 68 diverse ICUs. Adults with critical illness adults who received mechanical ventilation and/or continuously infused sedative medications were included. We performed mixed-effects logistic regression modeling, created receiver operating characteristic curves, and calculated the area under the curve (AUC). RESULTS: Included in the SAT and SBT analysis were 4,847 and 4,938 patients, respectively. In multivariable models controlling for admitting patient characteristics, factors independently associated with higher odds of a next-day SAT and SBT included physical restraint use (adjusted odds ratio [AOR], 1.63; 95% CI, 1.42-1.87; AOR, 1.83; 95% CI, 1.60-2.09), documented target sedation level (AOR, 1.68; 95% CI, 1.41-2.01; AOR, 1.46; 95% CI, 1.24-1.72), more frequent level of arousal assessments (AOR, 1.22; 95% CI, 1.03-1.43; AOR, 1.32; 95% CI, 1.13-1.54), and dexmedetomidine administration (AOR, 1.23; 95% CI, 1.05-1.45; AOR, 1.52; 95% CI, 1.27-1.80). Factors independently associated with lower odds of a next-day SAT and SBT included deep sedation/coma (AOR, 0.69; 95% CI, 0.60-0.80; AOR, 0.33; 95% CI, 0.28-0.37) and benzodiazepine (AOR, 0.83; 95% CI, 0.72-0.95; AOR, 0.67; 95% CI, 0.59-0.77) or ketamine (AOR, 0.34; 95% CI, 0.16-0.71; AOR, 0.40; 95% CI, 0.18-0.88) administration. Models incorporating admitting, daily, and unit variations displayed moderate discriminant accuracy in predicting next-day SAT (AUC, 0.73) and SBT (AUC, 0.72) performance. INTERPRETATION: There are a number of modifiable factors associated with SAT/SBT performance that are amenable to the development and testing of implementation interventions.
BACKGROUND: Broad-scale adoption of spontaneous awakening trials (SATs) and spontaneous breathing trials (SBTs) into everyday practice has been slow, and uncertainty exists regarding what factors facilitate or impede their routine delivery. RESEARCH QUESTION: What patient, practice, and pharmacologic factors are associated with SAT and SBT performance and to what extent do they predict overall SAT/SBT performance? STUDY DESIGN AND METHODS: This secondary analysis used data collected from a national quality improvement collaborative composed of 68 diverse ICUs. Adults with critical illness adults who received mechanical ventilation and/or continuously infused sedative medications were included. We performed mixed-effects logistic regression modeling, created receiver operating characteristic curves, and calculated the area under the curve (AUC). RESULTS: Included in the SAT and SBT analysis were 4,847 and 4,938 patients, respectively. In multivariable models controlling for admitting patient characteristics, factors independently associated with higher odds of a next-day SAT and SBT included physical restraint use (adjusted odds ratio [AOR], 1.63; 95% CI, 1.42-1.87; AOR, 1.83; 95% CI, 1.60-2.09), documented target sedation level (AOR, 1.68; 95% CI, 1.41-2.01; AOR, 1.46; 95% CI, 1.24-1.72), more frequent level of arousal assessments (AOR, 1.22; 95% CI, 1.03-1.43; AOR, 1.32; 95% CI, 1.13-1.54), and dexmedetomidine administration (AOR, 1.23; 95% CI, 1.05-1.45; AOR, 1.52; 95% CI, 1.27-1.80). Factors independently associated with lower odds of a next-day SAT and SBT included deep sedation/coma (AOR, 0.69; 95% CI, 0.60-0.80; AOR, 0.33; 95% CI, 0.28-0.37) and benzodiazepine (AOR, 0.83; 95% CI, 0.72-0.95; AOR, 0.67; 95% CI, 0.59-0.77) or ketamine (AOR, 0.34; 95% CI, 0.16-0.71; AOR, 0.40; 95% CI, 0.18-0.88) administration. Models incorporating admitting, daily, and unit variations displayed moderate discriminant accuracy in predicting next-day SAT (AUC, 0.73) and SBT (AUC, 0.72) performance. INTERPRETATION: There are a number of modifiable factors associated with SAT/SBT performance that are amenable to the development and testing of implementation interventions.
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