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BackgroundDaycare and school closures prompted by shelter-in-place orders may have increased opportunities for unintentional ingestions among young children.ObjectivesWe examined emergency department (ED) presentations for toxic exposures among young children during the COVID-19 pandemic in the San Francisco Bay Area, which had some of the strictest and most prolonged shelter-in-place policies in the United States.MethodsWe performed a retrospective cross-sectional study of children 0 to 5 years of age who presented with an ED International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis code of toxic exposure within a tertiary care hospital system between March 16, 2016 and March 15, 2021. We considered the period after March 16, 2020 to represent the pandemic.ResultsDuring the pandemic, the absolute number of poisonings among young children remained stable. Overall, ED encounters within this cohort decreased by 55%, which doubled the relative toxic exposure rate per 1000 ED encounters from 4.99 (95% confidence interval [CI] 3.19-5.90) to 9.79 (95% CI 8.09-11.49). Rates of admission, severe medical complications, operating room case requests, and length of stay were not significantly different. Shelter-in-place was associated with significantly higher odds of cannabis ingestion (odds ratio=2.70, 95% CI1.60-4.49).ConclusionDespite dramatic decreases in overall ED patient volumes, the absolute number and severity of toxic exposures were similar during the pandemic compared with previous years. © 2022 Elsevier Inc.

Introduction This study examined user behavior, e-cigarette dependence, and device characteristics on nicotine intake among users of pod-mod e-cigarettes. Aims and Methods In 2019–2020, people who use pod-mods in the San Francisco Bay Area completed questionnaires and provided a urine sample for analysis of total nicotine equivalents (TNE). The relationship between TNE and e-cigarette use, e-cigarette brands, e-liquid nicotine strength, e-cigarette dependence, and urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), as a measure of combustible cigarette exposure, were examined. Results Of 100 participants (64% male, 71% in the 18–34 age group, 45% white), 53 used JUUL primarily, 12 used Puff Bar primarily, and 35 used other brands, including Suorin; 48 participants reported current cigarette smoking. Participants most often reported use of e-liquid with 4.5%–6.0% nicotine (68%), fruit (35%), tobacco (28%), and menthol or mint flavors (26%), used e-cigarettes on 25.5 (SD = 6.3) days a month, 10.2 (SD = 14.2) times a day, and 40% used 1–2 pods/cartridges per week. In bivariate analysis, urinary TNE was higher with greater frequency (days used) and intensity (number of pods used) of e-cigarette use, e-cigarette dependence, and combustible cigarette use. In multivariable analysis, days of e-cigarette use in the last 30 days, number of pods used per week, and NNAL levels were significantly associated with TNE. There was no significant impact of e-liquid nicotine strength on TNE. Conclusions Nicotine intake among people who used pod-mod e-cigarettes increased with e-cigarette consumption and e-cigarette dependence, but not with e-liquid nicotine strength. Our findings may inform whether FDA adopts a nicotine standard for e-cigarettes. Implications The study examined how device and user characteristics influence nicotine intake among pod-mod e-cigarette users. Nicotine intake increased with frequency (days of e-cigarette use in past 30 days) intensity of use (number of pods used per day) and e-cigarette dependence but not with the flavor or nicotine concentration of the e-liquids. Regulation of nicotine concentration of e-liquids is unlikely to influence nicotine exposure among adult experienced pod-mod users.

Importance: The wide variation in the accuracy and reliability of the Focused Assessment With Sonography for Trauma (FAST) and the extended FAST (E-FAST) for children after blunt abdominal trauma reflects user expertise. FAST and E-FAST that are performed by experts tend to be more complete, better quality, and more often clinically valuable. Objective: To develop definitions of a complete, high-quality, and accurate interpretation for the FAST and E-FAST in children with injury using an expert, consensus-based modified Delphi technique. Design, Setting, and Participants: This consensus-based qualitative study was conducted between May 1 to June 30, 2021. It used a scoping review and iterative Delphi technique and involved 2 rounds of online surveys and a live webinar to achieve consensus among a 26-member panel. This panel consisted of international experts in pediatric emergency point-of-care ultrasonography. Main Outcomes and Measures: Definitions of complete, high-quality, and accurate FAST and E-FAST studies for children after injury. Results: Of the 29 invited pediatric FAST experts, 26 (15 men [58%]) agreed to participate in the panel. All 26 panelists completed the 2 rounds of surveys, and 24 (92%) participated in the live and asynchronous online discussions. Consensus was reached on FAST and E-FAST study definitions, and the panelists rated these 5 anatomic views as important and appropriate for a complete FAST: right upper-quadrant abdominal view, left upper-quadrant abdominal view, suprapubic views (transverse and sagittal), and subxiphoid cardiac view. For E-FAST, the same FAST anatomic views with the addition of the lung or pneumothorax view were deemed appropriate and important. In addition, the panelists rated a total of 32 landmarks as important for assessing completeness. Similarly, the panelists rated 14 statements on quality and 20 statements on accurate interpretation as appropriate. Conclusions and Relevance: This qualitative study generated definitions for complete FAST and E-FAST studies with high image quality and accurate interpretation in children with injury. These definitions are similar to those in adults with injury and may be used for future education, quality assurance, and research. Future research may focus on interpretation of trace volumes of abdominal free fluid and the use of serial FAST.

Objective The Pediatric Emergency Care Applied Research Network (PECARN) has developed a clinical-decision instrument (CDI) to identify children at very low risk of intra-abdominal injury. However, the CDI has not been externally validated. We sought to vet the PECARN CDI with the Predictability Computability Stability (PCS) data science framework, potentially increasing its chance of a successful external validation. Materials & methods We performed a secondary analysis of two prospectively collected datasets: PECARN (12,044 children from 20 emergency departments) and an independent external validation dataset from the Pediatric Surgical Research Collaborative (PedSRC; 2,188 children from 14 emergency departments). We used PCS to reanalyze the original PECARN CDI along with new interpretable PCS CDIs developed using the PECARN dataset. External validation was then measured on the PedSRC dataset. Results Three predictor variables (abdominal wall trauma, Glasgow Coma Scale Score Conclusion The PCS data science framework vetted the PECARN CDI and its constituent predictor variables prior to external validation. We found that the 3 stable predictor variables represented all of the PECARN CDI’s predictive performance on independent external validation. The PCS framework offers a less resource-intensive method than prospective validation to vet CDIs before external validation. We also found that the PECARN CDI will generalize well to new populations and should be prospectively externally validated. The PCS framework offers a potential strategy to increase the chance of a successful (costly) prospective validation.

ObjectiveAlthough current ethical standards mandate conflict of interest (COI) disclosure by authors of peer-reviewed publications, it is unknown whether disclosure affects a manuscript's fate. Our objective was to identify associations between author COI disclosure and editorial decision to publish.MethodsWe performed a cross-sectional observational study of editorial decisions for original research and brief research report manuscripts submitted to Annals of Emergency Medicine between June 2014 and January 2018 using data from the journal's editorial decision software and data from a prior study that characterized author COI for the same manuscripts. Outcomes of interest included final editor decision to publish (primary), initial editor decision, and number of revisions. We compared outcomes for manuscripts with COI versus those without and by type of COI (commercial/government/other).ResultsOut of 1312 manuscripts in the sample, 65.1% had no COI declarations, and 34.9% had one or more. Overall likelihood of editorial decision to publish was 13.5% (115/854) for articles without COI and 26.9% (123/458) for those with COI. Overall likelihood of editorial decision to publish was 19.8% (19/96) for articles with commercial COI only versus 33.3% (35/105) for those with government COI only.ConclusionsArticles with author-reported COI were more likely to be published than those without such a declaration. Additionally, results suggest that reports of government COI are associated with improved chance of publication. Authorities should consider relaxing COI requirements temporarily to allow investigators to perform larger scale, randomized controlled studies of the impact of mandated COI disclosure.

OBJECTIVE—: Pediatric focused assessment with sonography for trauma (FAST) is a sequence of ultrasound views rapidly performed by clinicians to diagnose hemorrhage. A technical limitation of FAST is the lack of expertise to consistently acquire all required views. We sought to develop an accurate deep learning view classifier using a large heterogeneous dataset of clinician-performed pediatric FAST. METHODS—: We developed and conducted a retrospective cohort analysis of a deep learning view classifier on real-world FAST studies performed on injured children less than 18 years old in two pediatric emergency departments by 30 different clinicians. FAST was randomly distributed to training, validation, and test datasets, 70:20:10; each child was represented in only one dataset. The primary outcome was view classifier accuracy for video clips and still frames. RESULTS—: There were 699 FAST studies, representing 4925 video clips and 1,062,612 still frames, performed by 30 different clinicians. The overall classification accuracy was 97.8% (95% confidence interval [CI]: 96.0–99.0) for video clips and 93.4% (95% CI: 93.3–93.6) for still frames. Per view still frames were classified with an accuracy: 96.0% (95% CI: 95.9–96.1) cardiac, 99.8% (95% CI: 99.8–99.8) pleural, 95.2% (95% CI: 95.0–95.3) abdominal upper quadrants, and 95.9% (95% CI: 95.8–96.0) suprapubic. CONCLUSION—: A deep learning classifier can accurately predict pediatric FAST views. Accurate view classification is important for quality assurance and feasibility of a multi-stage deep learning FAST model to enhance the evaluation of injured children.

ObjectivesThe WHO developed a 5-day basic emergency care (BEC) course using the traditional lecture format. However, adult learning theory suggests that lecture-based courses alone may not promote long-term knowledge retention. We assessed whether a mobile application adjunct (BEC app) can have positive impact on knowledge acquisition and retention compared with the BEC course alone and evaluated perceptions, acceptability and barriers to adoption of such a tool.DesignMixed-methods prospective cohort study.ParticipantsAdult healthcare workers in six health facilities in Tanzania who enrolled in the BEC course and were divided into the control arm (BEC course) or the intervention arm (BEC course plus BEC app).Main outcome measuresChanges in knowledge assessment scores, self-efficacy and perceptions of BEC app.Results92 enrolees, 46 (50%) in each arm, completed the BEC course. 71 (77%) returned for the 4-month follow-up. Mean test scores were not different between the two arms at any time period. Both arms had significantly improved test scores from enrolment (prior to distribution of materials) to day 1 of the BEC course and from day 1 of BEC course to immediately after BEC course completion. The drop-off in mean scores from immediately after BEC course completion to 4 months after course completion was not significant for either arm. No differences were observed between the two arms for any self-efficacy question at any time point. Focus groups revealed five major themes related to BEC app adoption: educational utility, clinical utility, user experience, barriers to access and barriers to use.ConclusionThe BEC app was well received, but no differences in knowledge retention and self-efficacy were observed between the two arms and only a very small number of participants reported using the app. Technologic-based, linguistic-based and content-based barriers likely limited its impact.