Ultrasound-guided analgesic injection for acromioclavicular joint separation in the emergency department.

We present the first documented case of an emergency clinician treating the pain of an acute Acromioclavicular (AC) joint separation through ultrasound (US) guided injection of an anesthetic agent. A 41 year old male presented with an acute traumatic grade III AC joint separation after falling off a scooter, and his pain was not significantly improved with oral medication. The AC joint was located by US, and bupivacaine was injected into the joint effusion under US guidance, yielding near complete resolution of pain. In orthopedics and physiatry literature, US guided AC joint injections have been shown to be far more efficacious than landmark guided AC joint injections, yet this is the first known case documenting injection in the Emergency Department (ED). The superficial location of the AC joint, its ease of identification by US, and the rapid onset of analgesia by intra-articular injection makes the US-guided anesthetic injection of the AC joint an ideal tool to incorporate into a multimodal approach to pain management in AC joint separations.

Passive Detection of Atrial Fibrillation Using a Commercially Available Smartwatch.

Importance: Atrial fibrillation (AF) affects 34 million people worldwide and is a leading cause of stroke. A readily accessible means to continuously monitor for AF could prevent large numbers of strokes and death. Objective: To develop and validate a deep neural network to detect AF using smartwatch data. Design, Setting, and Participants: In this multinational cardiovascular remote cohort study coordinated at the University of California, San Francisco, smartwatches were used to obtain heart rate and step count data for algorithm development. A total of 9750 participants enrolled in the Health eHeart Study and 51 patients undergoing cardioversion at the University of California, San Francisco, were enrolled between February 2016 and March 2017. A deep neural network was trained using a method called heuristic pretraining in which the network approximated representations of the R-R interval (ie, time between heartbeats) without manual labeling of training data. Validation was performed against the reference standard 12-lead electrocardiography (ECG) in a separate cohort of patients undergoing cardioversion. A second exploratory validation was performed using smartwatch data from ambulatory individuals against the reference standard of self-reported history of persistent AF. Data were analyzed from March 2017 to September 2017. Main Outcomes and Measures: The sensitivity, specificity, and receiver operating characteristic C statistic for the algorithm to detect AF were generated based on the reference standard of 12-lead ECG-diagnosed AF. Results: Of the 9750 participants enrolled in the remote cohort, including 347 participants with AF, 6143 (63.0%) were male, and the mean (SD) age was 42 (12) years. There were more than 139 million heart rate measurements on which the deep neural network was trained. The deep neural network exhibited a C statistic of 0.97 (95% CI, 0.94-1.00; P < .001) to detect AF against the reference standard 12-lead ECG-diagnosed AF in the external validation cohort of 51 patients undergoing cardioversion; sensitivity was 98.0% and specificity was 90.2%. In an exploratory analysis relying on self-report of persistent AF in ambulatory participants, the C statistic was 0.72 (95% CI, 0.64-0.78); sensitivity was 67.7% and specificity was 67.6%. Conclusions and Relevance: This proof-of-concept study found that smartwatch photoplethysmography coupled with a deep neural network can passively detect AF but with some loss of sensitivity and specificity against a criterion-standard ECG. Further studies will help identify the optimal role for smartwatch-guided rhythm assessment.

Efficient reversal of phiC31 integrase recombination in mammalian cells.

Over the past decade, the integrase enzyme from phage phiC31 has proven to be a useful genome engineering tool in a wide variety of species, including mammalian cells. The enzyme efficiently mediates recombination between two distinct sequences, attP and attB, producing recombinant product sites, attL and attR. The reaction proceeds exclusively in a unidirectional manner, because integrase is unable to synapse attL and attR. To date, use of phiC31 integrase has been limited to attP × attB recombination. The factor needed for the reverse reaction--the excisionase or recombination directionality factor (RDF)--was identified recently and shown to function in vitro and in bacterial cells. To determine whether the phiC31 RDF could also function in mammalian cells, we cloned and tested several vectors that permit assessment of phiC31 RDF activity in mammalian environments. In the human and mouse cell lines tested (HeLa, HEK293, and NIH3T3), we observed robust RDF activity, using plasmid and/or genomic assays. This work is the first to demonstrate attL-attR serine integrase activity in mammalian cells and validates phiC31 RDF as a new tool that will enable future studies to take advantage of phiC31 integrase recombination in the forward or reverse direction.