Persistent post-discharge opioid prescribing after traumatic brain injury requiring intensive care unit admission: A cross-sectional study with longitudinal outcome.

Traumatic brain injury (TBI) is associated with increased risk for psychological and substance use disorders. The study aim is to determine incidence and risk factors for persistent opioid prescription after hospitalization for TBI. Electronic medical records of patients age ≥ 18 admitted to a neuroscience intensive care unit between January 2013 and February 2017 for an intracranial injury were retrospectively reviewed. Primary outcome was opioid use through 12 months post-hospital discharge. A total of 298 patients with complete data were included in the analysis. The prevalence of opioid use among preadmission opioid users was 48 (87%), 36 (69%) and 22 (56%) at 1, 6 and 12-months post-discharge, respectively. In the opioid naïve group, 69 (41%), 24 (23%) and 17 (19%) were prescribed opioids at 1, 6 and 12 months, respectively. Preadmission opioid use (OR 324.8, 95% CI 23.1-16907.5, p = 0.0004) and higher opioid requirements during hospitalization (OR 4.5, 95% CI 1.8-16.3, p = 0.006) were independently associated with an increased risk of being prescribed opioids 12 months post-discharge. These factors may be used to identify and target at-risk patients for intervention.

Impact of predictive analytics based on continuous cardiorespiratory monitoring in a surgical and trauma intensive care unit.

Predictive analytics monitoring, the use of patient data to provide continuous risk estimation of deterioration, is a promising new application of big data analytical techniques to the care of individual patients. We tested the hypothesis that continuous display of novel electronic risk visualization of respiratory and cardiovascular events would impact intensive care unit (ICU) patient outcomes. In an adult tertiary care surgical trauma ICU, we displayed risk estimation visualizations on a large monitor, but in the medical ICU in the same institution we did not. The risk estimates were based solely on analysis of continuous cardiorespiratory monitoring. We examined 4275 individual patient records within a 7 month time period preceding and following data display. We determined cases of septic shock, emergency intubation, hemorrhage, and death to compare rates per patient care pre-and post-implementation. Following implementation, the incidence of septic shock fell by half (p < 0.01 in a multivariate model that included age and APACHE) in the surgical trauma ICU, where the data were continuously on display, but by only 10% (p = NS) in the control Medical ICU. There were no significant changes in the other outcomes. Display of a predictive analytics monitor based on continuous cardiorespiratory monitoring was followed by a reduction in the rate of septic shock, even when controlling for age and APACHE score.

New-Onset Atrial Fibrillation in the Critically Ill.

OBJECTIVE: To determine the association of new-onset atrial fibrillation with outcomes, including ICU length of stay and survival. DESIGN: Retrospective cohort of ICU admissions. We found atrial fibrillation using automated detection (≥ 90 s in 30 min) and classed as new-onset if there was no prior diagnosis of atrial fibrillation. We identified determinants of new-onset atrial fibrillation and, using propensity matching, characterized its impact on outcomes. SETTING: Tertiary care academic center. PATIENTS: A total of 8,356 consecutive adult admissions to either the medical or surgical/trauma/burn ICU with available continuous electrocardiogram data. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: From 74 patient-years of every 15-minute observations, we detected atrial fibrillation in 1,610 admissions (19%), with median burden less than 2%. Most atrial fibrillation was paroxysmal; less than 2% of admissions were always in atrial fibrillation. New-onset atrial fibrillation was subclinical or went undocumented in 626, or 8% of all ICU admissions. Advanced age, acute respiratory failure, and sepsis were the strongest predictors of new-onset atrial fibrillation. In propensity-adjusted regression analyses, clinical new-onset atrial fibrillation was associated with increased hospital mortality (odds ratio, 1.63; 95% CI, 1.01-2.63) and longer length of stay (2.25 d; CI, 0.58-3.92). New-onset atrial fibrillation was not associated with survival after hospital discharge (hazard ratio, 0.99; 95% CI, 0.76-1.28 and hazard ratio, 1.11; 95% CI, 0.67-1.83, respectively, for subclinical and clinical new-onset atrial fibrillation). CONCLUSIONS: Automated analysis of continuous electrocardiogram heart rate dynamics detects new-onset atrial fibrillation in many ICU patients. Though often transient and frequently unrecognized, new-onset atrial fibrillation is associated with poor hospital outcomes.