Journal of the American College of Emergency Physicians open最新文献

Objectives: This study aimed to characterize emergency department (ED)-based policies related to documentation of adverse social drivers of health (aSDOH) among a national sample of US EDs.

Methods: We conducted a cross-sectional survey of ED leaders from a 5% stratified random sample of US EDs (n = 280) from January to October 2023. For EDs reporting written screening policies for core aSDOH (housing, food, transportation, and utilities) or regulatory requirement-driven screening (intimate partner violence, other violence, substance use, and mental health), we assessed documentation policies, including personnel responsible and documentation methods. Using survey-weighted analyses and multivariable logistic regression, we examined associations between documentation policies and ED characteristics (practice setting, urbanicity, visit volume, and 24/7 social work availability).

Results: Of 232 responding EDs (83% response rate), 213 (93.2%, 95% CI, 89.3-95.7) reported screening for at least 1 risk factor. Among these, 196 (93.8%, 95% CI, 87.9-96.9) had policies requiring documentation of positive screens. Documentation requirements were higher for regulatory requirement-driven screening (84-93.5) compared with core aSDOH screening (56.8-68.9). Clinical providers most commonly documented findings (97.8%, 95% CI, 94.8-99.1), followed by social workers/care coordinators (52.6%, 95% CI, 42.4-62.6). All documentation occurred in the electronic health record. In adjusted analyses, 24/7 social work availability was associated with greater odds of having at least 1 aSDOH documentation policy (odds ratio, 2.86; 95% CI, 1.09-7.52).

Conclusion: Although most EDs with screening policies required documentation of positive screens, requirements varied by domain. Future research should focus on standardizing documentation practices and developing systems to effectively translate documented social needs into meaningful interventions.

Objectives: Older adults are vulnerable to infection and are difficult to diagnose. This study assessed the performance of MeMed BV (MMBV), a host-protein test for differentiating bacterial from viral infection, in adults ≥65 years.

Methods: Post hoc pooled and meta-analysis of adults with suspected acute infections enrolled in 3 prospective studies. MMBV results were interpreted as bacterial/viral/equivocal per manufacturer's instructions. Reference standard infection etiology was adjudicated by experienced physicians who were blinded to MMBV. Diagnostic accuracy for bacterial infection was calculated for MMBV results (area under the receiver operating characteristic curve [AUC], bin analysis) and for unequivocal MMBV results (sensitivity/specificity). MMBV's potential impact on antibiotic use was estimated by comparing MMBV-guided decisions to actual practice.

Results: A total of 754 younger (18-64 years) and 248 older (≥65 years) adults were included. Among older adults, the median age was 75.0 years (IQR, 69.0, 82.0), 53.2% were male, 68.1% were hospitalized, and 79.0% had ≥3 comorbidities. Respiratory tract infections were common (76.2%), and 85.1% were prescribed antibiotics. A total of 111 patients were assigned a bacterial reference standard infection etiology, 77 a viral etiology, and 60 an indeterminate etiology. In pooled analysis, MMBV attained comparable AUC in older (0.95; 95% CI, 0.92-0.98) vs younger adults (0.95; 0.93-0.97). Focusing on older adults, 96.2% (90.3-98.8) sensitivity and 85.7% (74.8-92.5) specificity with 10.6% equivocal results were observed. MMBV could reduce potentially unwarranted antibiotic prescriptions 2.5-fold (from 62.3% to 24.7%; P < .0001). Using a bivariate model, MMBV similarly attained AUC 0.92 (0.81-0.97).

Conclusions: MMBV demonstrated high diagnostic accuracy in older adults, supporting its potential to optimize antibiotic use in this population. Further studies are needed to evaluate real-world utility.

Objectives: This systematic review aims to evaluate the diagnostic accuracy of artificial intelligence (AI) algorithms in acute coronary syndrome (ACS) detection using 12-lead electrocardiograms (ECGs).

Methods: Adhering to Preferred Reporting Items for Systematic Reviews guidelines, Ovid MEDLINE, Ovid Embase, Cochrane Central, and Cochrane Database of Systematic Reviews were searched up to June 15, 2023. Eligible studies involved adults with suspected ACS and employed AI for 12-lead ECG interpretation. The primary outcomes were sensitivity and specificity, with secondary outcomes including positive predictive value (PPV), negative predictive value (NPV), and accuracy. Risk of bias was evaluated using Prediction model Risk Of Bias Assessment Tool (PROBAST).

Results: From 2051 records, 24 studies were included. The sensitivity of AI-based diagnosis for ACS among the 24 studies varied from 68% to 98%, and the specificity varied from 41% to 98%. For subgroup analysis of ST-elevated myocardial infarction/occlusion myocardial infarction, sensitivity ranged from 68% to 97% and specificity from 68% to 99%. AI models outperformed clinicians interpreting ECGs retrospectively without knowledge of outcomes in sensitivity (90% of studies) and PPV (100% of studies), whereas clinicians had better NPV (70% of studies). One study compared AI with real-time emergency department physician interpretations. Three studies reported code availability. Thirty-eight percentage of studies showed a high risk of bias, with 50% showing unclear risk, although applicability concerns were minimal.

Conclusion: AI models show high diagnostic accuracy for ACS using 12-lead ECGs, with potential to enhance early diagnosis. However, variability in performance, transparency challenges with limited code availability, a high risk of bias in some studies, and minimal real-time comparisons underscore the necessity for standardized reporting and open-access practices.

Objectives: We evaluated factors associated with the need for full admission (greater than 2 days) for patients with skin and soft tissue infection (SSTI) placed in an emergency department (ED) observation unit (EDOU) in order to inform a new SSTI protocol.

Methods: Retrospective cohort study of adult ED patients assigned to the EDOU for treatment of a SSTI from 2017 to 2018. Data elements included demographics, vital signs, SSTI location and cause, procedures, consults, length of stay, and disposition. Significant relationships identified under univariable analysis were further examined in multivariable logistic regression.

Results: Four hundred eight patient charts were included, of which 100 (24.5%) were admitted. The mean age was 47.3 ± 17.5 years (range, 18-95 years), and 58.0% were men. SSTI complicated by intravenous drug abuse (odds ratio [OR], 1.47; 95% CI, 0.58-3.72) and diabetes (OR, 1.38; 95% CI, 0.41-4.60) had the highest univariable odds of admission for types of infection. Infections treated with a procedure such as incision and drainage had lower odds of admission (OR, 0.56; 95% CI, 0.32-0.98). On multivariate logistic regression, tachycardia (OR, 1.85; 95% CI, 1.09-3.13) was associated with higher odds of admission. SSTI on the torso (OR, 0.23; 95% CI, 0.06-0.80), plan for expert consultation (OR, 0.32; 95% CI, 0.19-0.54), and having a procedure (OR, 0.42; 95% CI, 0.22-0.76) were associated with lower odds of admission. Based on this information, the EDOU protocol for patients with SSTI was updated. In the year after update, admission rate among patients with SSTI was 22.4%.

Conclusion: Tachycardia in the ED may be an early sign of a more complicated SSTI that is more likely to require hospital admission. Adjusting an EDOU protocol to the local population may be helpful for improving EDOU patient selection.