Faculty Bibliography

INTRODUCTION/BACKGROUND:Direct oral anticoagulants (DOACs) effectively prevent recurrent venous thromboembolism (VTE). However, it is unknown which agents should be used to prevent recurrent VTE and which patients with unprovoked VTE should receive extended anticoagulation. We therefore sought to compare the efficacy and safety among DOACs for secondary prevention of VTE. We also determined a risk-adapted threshold for initiating extended anticoagulation based on the likelihood of VTE recurrence (without treatment) and bleeding (with treatment) in patients with unprovoked VTE. METHODS:Our systematic review of randomized controlled trials compares extended anticoagulation with DOACs to another DOAC, aspirin, or placebo for the prevention of recurrent VTE. We searched PubMed, EMBASE, and Cochrane Registry of Controlled Trials (CENTRAL) in October 2018. Our outcomes of interest were VTE recurrence, major bleeding, and all clinically relevant bleeding. We used network meta-analysis to make indirect comparisons among DOACs. We populated the threshold decision-analytic model with data from our meta-analysis to determine the risk of VTE recurrence above which the benefits of extended anticoagulation outweigh the harms compared with no treatment. RESULTS:We included four, high-quality, randomized trials comprising 8386 participants. Low-dose apixaban, full-dose apixaban, low-dose rivaroxaban, full-dose rivaroxaban, and dabigatran reduce VTE recurrence compared with placebo (RR = 0.19, 95% CI, 0.12-0.31; RR = 0.20, 95% CI, 0.12-0.32; RR = 0.08, 95% CI, 0.03-0.27; RR = 0.14, 95% CI, 0.06-0.35; RR = 0.19, 95% CI, 0.09-0.40, respectively). No DOACs increased major bleeding risk compared with placebo. A VTE recurrence risk above 0.3% to 0.4% at approximately 1 year is the threshold to treat a patient with unprovoked VTE with extended anticoagulation (with any DOAC). CONCLUSIONS:All DOACs exhibit comparable efficacy for the prevention of recurrent VTE. Given that the risk of VTE recurrence is much higher than the calculated threshold for treatment, extended thromboprophylaxis should be considered in all patients with unprovoked VTE who do not have increased bleeding risk.

PURPOSE/OBJECTIVE:The aim of this study was to evaluate the prevalence and clinical correlates of impaired sleep quality and excessive daytime sleepiness among patients receiving methadone for opioid use disorder (OUD). METHODS:Patients receiving methadone (n = 164) completed surveys assessing sleep quality (Pittsburgh Sleep Quality Index [PSQI]), daytime sleepiness (Epworth Sleepiness Scale [ESS]), and related comorbidities. We used bivariate and multivariable linear regression models to evaluate correlates of sleep quality and daytime sleepiness. RESULTS:Ninety percent of patients had poor sleep quality (PSQI >5), and the mean PSQI was high (11.0 ±4). Forty-six percent reported excessive daytime sleepiness (ESS > 10). In multivariable analyses, higher PSQI (worse sleep quality) was significantly associated with pain interference (coefficient = 0.40; 95% CI = 0.18-0.62; β = 0.31), somatization (coefficient = 2.2; 95% CI = 0.75-3.6; β = 0.26), and negatively associated with employment (coefficient = - 2.6; 95% CI = - 4.9 to - 0.19; β = - 0.17). Greater sleepiness was significantly associated with body mass index (coefficient = 0.32; 95% CI = 0.18-0.46; β = 0.33), and there was a non-significant association between sleepiness and current chronic pain (coefficient = 1.6; 95% CI = 0.26-3.5; β = 0.13; p value = 0.09). CONCLUSIONS:Poor sleep quality and excessive daytime sleepiness are common in patients receiving methadone for OUD. Chronic pain, somatization, employment status, and obesity are potentially modifiable risk factors for sleep problems for individuals maintained on methadone. People with OUD receiving methadone should be routinely and promptly evaluated and treated for sleep disorders.

OBJECTIVE:To test the hypothesis that people with focal epilepsy experience diagnostic delays that may be associated with preventable morbidity, particularly when seizures have only nonmotor symptoms, we compared time to diagnosis, injuries, and motor vehicle accidents (MVAs) in people with focal nonmotor versus focal seizures with motor involvement at epilepsy onset. METHODS:This retrospective study analyzed the enrollment data from the Human Epilepsy Project, which enrolled participants between 2012 and 2017 across 34 sites in the USA, Canada, Europe, and Australia, within 4 months of treatment for focal epilepsy. A total of 447 participants were grouped by initial seizure semiology (focal nonmotor or focal with motor involvement) to compare time to diagnosis and prediagnostic injuries including MVAs. RESULTS:Demographic characteristics were similar between groups. There were 246 participants (55%) with nonmotor seizures and 201 participants (45%) with motor seizures at epilepsy onset. Median time to diagnosis from first seizure was 10 times longer in patients with nonmotor seizures compared to motor seizures at onset (P < .001). The number and severity of injuries were similar between groups. However, 82.6% of MVAs occurred in patients with undiagnosed nonmotor seizures. SIGNIFICANCE/CONCLUSIONS:This study identifies reasons for delayed diagnosis and consequences of delay in patients with new onset focal epilepsy, highlighting a treatment gap that is particularly significant in patients who experience nonmotor seizures at epilepsy onset.

BACKGROUND:Myocardial injury is frequent among patients hospitalized with coronavirus disease-2019 (COVID-19) and is associated with a poor prognosis. However, the mechanisms of myocardial injury remain unclear and prior studies have not reported cardiovascular imaging data. OBJECTIVES/OBJECTIVE:This study sought to characterize the echocardiographic abnormalities associated with myocardial injury and their prognostic impact in patients with COVID-19. METHODS:We conducted an international, multicenter cohort study including 7 hospitals in New York City and Milan of hospitalized patients with laboratory-confirmed COVID-19 who had undergone transthoracic echocardiographic (TTE) and electrocardiographic evaluation during their index hospitalization. Myocardial injury was defined as any elevation in cardiac troponin at the time of clinical presentation or during the hospitalization. RESULTS:A total of 305 patients were included. Mean age was 63 years and 205 patients (67.2%) were male. Overall, myocardial injury was observed in 190 patients (62.3%). Compared with patients without myocardial injury, those with myocardial injury had more electrocardiographic abnormalities, higher inflammatory biomarkers and an increased prevalence of major echocardiographic abnormalities that included left ventricular wall motion abnormalities, global left ventricular dysfunction, left ventricular diastolic dysfunction grade II or III, right ventricular dysfunction and pericardial effusions. Rates of in-hospital mortality were 5.2%, 18.6%, and 31.7% in patients without myocardial injury, with myocardial injury without TTE abnormalities, and with myocardial injury and TTE abnormalities. Following multivariable adjustment, myocardial injury with TTE abnormalities was associated with higher risk of death but not myocardial injury without TTE abnormalities. CONCLUSIONS:Among patients with COVID-19 who underwent TTE, cardiac structural abnormalities were present in nearly two-thirds of patients with myocardial injury. Myocardial injury was associated with increased in-hospital mortality particularly if echocardiographic abnormalities were present.

Acute kidney injury (AKI) is the most common form of organ dysfunction occurring in patients admitted to the intensive care unit and contributes significantly to poor long-term outcomes. Despite this public health impact, no effective pharmacotherapy exists for AKI. One reason may be that heterogeneity is present within AKI as currently defined, thereby concealing unique pathophysiologic processes specific to certain AKI populations. Supporting this notion, we and others have shown that diversity within the AKI clinical syndrome exists, and the "one-size-fits-all" approach by current diagnostic guidelines may not be ideal. A "precision medicine" approach that exploits an individual's genetic, biologic, and clinical characteristics to identify AKI sub-phenotypes may overcome such limitations. Identification of AKI sub-phenotypes may address a critical unmet clinical need in AKI by (1) improving risk prognostication, (2) identifying novel pathophysiology, and (3) informing a patient's likelihood of responding to current therapeutics or establishing new therapeutic targets to prevent and treat AKI. This review discusses the current state of phenotyping AKI and future directions.

The COVID-19 pandemic has challenged front-line clinical decision-making, leading to numerous published prognostic tools. However, few models have been prospectively validated and none report implementation in practice. Here, we use 3345 retrospective and 474 prospective hospitalizations to develop and validate a parsimonious model to identify patients with favorable outcomes within 96 h of a prediction, based on real-time lab values, vital signs, and oxygen support variables. In retrospective and prospective validation, the model achieves high average precision (88.6% 95% CI: [88.4-88.7] and 90.8% [90.8-90.8]) and discrimination (95.1% [95.1-95.2] and 86.8% [86.8-86.9]) respectively. We implemented and integrated the model into the EHR, achieving a positive predictive value of 93.3% with 41% sensitivity. Preliminary results suggest clinicians are adopting these scores into their clinical workflows.