Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning.

There are significant challenges to identifying which individuals require intervention following exposure to trauma, and a need for strategies to identify and provide individuals at risk for developing PTSD with timely interventions. The present study seeks to identify a minimal set of trauma-related symptoms, assessed during the weeks following traumatic exposure, that can accurately predict PTSD. Participants were 2185 adults (Mean age=36.4 years; 64% women; 50% Black) presenting for emergency care following traumatic exposure. Participants received a 'flash survey' with 6-8 varying symptoms (from a pool of 26 trauma symptoms) several times per week for eight weeks following the trauma exposure (each symptom assessed ∼6 times). Features (mean, sd, last, worst, peak-end scores) from the repeatedly assessed symptoms were included as candidate variables in a CART machine learning analysis to develop a pragmatic predictive algorithm. PTSD (PCL-5 ≥38) was present for 669 (31%) participants at the 8-week follow-up. A classification tree with three splits, based on mean scores of nervousness, rehashing, and fatigue, predicted PTSD with an Area Under the Curve of 0.836. Findings suggest feasibility for a 3-item assessment protocol, delivered once per week, following traumatic exposure to assess and potentially facilitate follow-up care for those at risk.

Utility of Wrist-Wearable Data for Assessing Pain, Sleep, and Anxiety Outcomes After Traumatic Stress Exposure.

Importance: Adverse posttraumatic neuropsychiatric sequelae after traumatic stress exposure are common and have higher incidence among socioeconomically disadvantaged populations. Pain, depression, avoidance of trauma reminders, reexperiencing trauma, anxiety, hyperarousal, sleep disruption, and nightmares have been reported. Wrist-wearable devices with accelerometers capable of assessing 24-hour rest-activity characteristics are prevalent and may have utility in measuring these outcomes. Objective: To evaluate whether wrist-wearable devices can provide useful biomarkers for recovery after traumatic stress exposure. Design, Setting, and Participants: Data were analyzed from a diverse cohort of individuals seen in the emergency department after experiencing a traumatic stress exposure, as part of the Advancing Understanding of Recovery After Trauma (AURORA) study. Participants recruited from 27 emergency departments wore wrist-wearable devices for 8 weeks, beginning in the emergency department, and completed serial assessments of neuropsychiatric symptoms. A total of 19 019 patients were screened. Of these, 3040 patients met study criteria, provided informed consent, and completed baseline assessments. A total of 2021 provided data from wrist-wearable devices, completed the 8-week assessment, and were included in this analysis. The data were randomly divided into 2 equal parts (n = 1010) for biomarker identification and validation. Data were collected from September 2017 to January 2020, and data were analyzed from May 2020 to November 2022. Exposures: Participants were recruited for the study after experiencing a traumatic stress exposure (most commonly motor vehicle collision). Main Outcomes and Measures: Rest-activity characteristics were derived and validated from wrist-wearable devices associated with specific self-reported symptom domains at a point in time and changes in symptom severity over time. Results: Of 2021 included patients, 1257 (62.2%) were female, and the mean (SD) age was 35.8 (13.0) years. Eight wrist-wearable device biomarkers for symptoms of adverse posttraumatic neuropsychiatric sequelae exceeded significance thresholds in the derivation cohort. One of these, reduced 24-hour activity variance, was associated with greater pain severity (r = -0.14; 95% CI, -0.20 to -0.07). Changes in 6 rest-activity measures were associated with changes in pain over time, and changes in the number of transitions between sleep and wake over time were associated with changes in pain, sleep, and anxiety. Simple cutoffs for these biomarkers identified individuals with good recovery for pain (positive predictive value [PPV], 0.85; 95% CI, 0.82-0.88), sleep (PPV, 0.63; 95% CI, 0.59-0.67, and anxiety (PPV, 0.76; 95% CI, 0.72-0.80) with high predictive value. Conclusions and Relevance: These findings suggest that wrist-wearable device biomarkers may have utility as screening tools for pain, sleep, and anxiety symptom outcomes after trauma exposure in high-risk populations.

All purulence is local - epidemiology and management of skin and soft tissue infections in three urban emergency departments.

BACKGROUND: Skin and soft tissue infection (SSTIs) are commonly treated in emergency departments (EDs). While the precise role of antibiotics in treating SSTIs remains unclear, most SSTI patients receive empiric antibiotics, often targeted toward methicillin-resistant Staphylococcus aureus (MRSA). The goal of this study was to assess the efficiency with which ED clinicians targeted empiric therapy against MRSA, and to identify factors that may allow ED clinicians to safely target antibiotic use. METHODS: We performed a retrospective analysis of patient visits for community-acquired SSTIs to three urban, academic EDs in one northeastern US city during the first quarter of 2010. We examined microbiologic patterns among cultured SSTIs, and relationships between clinical and demographic factors and management of SSTIs. RESULTS: Antibiotics were prescribed to 86.1% of all patients. Though S. aureus (60% MRSA) was the most common pathogen cultured, antibiotic susceptibility differed between adult and pediatric patients. Susceptibility of S. aureus from ED SSTIs differed from published local antibiograms, with greater trimethoprim resistance and less fluoroquinolone resistance than seen in S. aureus from all hospital sources. Empiric antibiotics covered the resultant pathogen in 85.3% of cases, though coverage was frequently broader than necessary. CONCLUSIONS: Though S. aureus remained the predominant pathogen in community-acquired SSTIs, ED clinicians did not accurately target therapy toward the causative pathogen. Incomplete local epidemiologic data may contribute to this degree of discordance. Future efforts should seek to identify when antibiotic use can be narrowed or withheld. Local, disease-specific antibiotic resistance patterns should be publicized with the goal of improving antibiotic stewardship.