Academic Emergency Medicine最新文献

Background: Emergency tracheal intubation is associated with a risk of clinical adverse events, including the risk of first-attempt failure. Induction agents usually include a sedative and a neuromuscular blocking agent (i.e., paralytic). Whether the order of administration (i.e., sedative vs. paralytic given first) is associated with first-attempt failure or adverse events is unknown.

Methods: This study analyzed data from a single-center prospective cohort collected from 2021 to 2024 at Hennepin County Medical Center, which included all patients undergoing orotracheal intubation in the emergency department. Patients with no detail on administration sequence order were excluded. A Bayesian logistic regression analysis was used to measure the effect of drug sequence order (sedative first vs. paralytic first). The primary outcome was first-attempt failure. The key secondary outcome was peri-intubation hypoxemia (SpO₂ < 90%). We estimated the odds ratio (OR), 95% credible interval (CrI), and the probability that the OR was inferior to 1 (existence of an effect) and inferior to 0.9 (significant effect). Frequentist analysis and reanalysis with various priors were performed as sensitivity analyses.

Results: A total of 2216 patients were included for analysis. The most frequently used sedative and paralytic agents were etomidate (88.9%) and rocuronium (77.8%), respectively. The paralytic was given first to 56.6% of the patients. After adjustment for age, sex, body mass index, and sedative and paralytic agents, the OR for a paralytic-first strategy for first-attempt failure was 0.73 (95% CrI 0.46-1.02). The probability that the OR was less than 1 was estimated at 95.7% and less than 0.9 at 87.6%. There was a 33.5% and 8.0% probability that administering the paralytic first resulted in an OR < 1 and OR < 0.9 for the risk of hypoxemia, respectively. Sensitivity analyses were consistent with the main results.

Conclusions: In this Bayesian analysis a paralytic-first drug sequence was associated with reduced first-attempt failure during emergency tracheal intubation.

Objectives: The objective was to compare the incidence of recovery agitation and efficacy of two different intravenous (IV) doses of ketamine (0.5 mg/kg vs. 1 mg/kg) in adult patients who presented to the emergency department (ED) requiring procedural sedation with ketamine.

Methods: This randomized, prospective clinical trial included patients aged 18-75 years who required procedural sedation with ketamine in the ED. Patients were randomized to receive IV ketamine at either 0.5 mg/kg (low dose) or 1 mg/kg (high dose). The primary outcome was the incidence of recovery agitation, assessed by the Richmond Agitation-Sedation Scale (RASS) at 5, 15, and 30 min following the procedure, in both dosage groups. Secondary outcomes included overall efficacy, sedation duration, and changes in vital signs.

Results: A total of 108 patients were enrolled in the study, 54 in each group. The median (IQR) RASS scores at 5, 15, and 30 min were -4 (-5 to -4), -1 (-1.3 to 0), and 0 (-1 to 0.5), respectively, in the low-dose group and -4 (-5 to -4), -1 (-3 to 0), and 0 (0 to 0), respectively, in the high-dose group. The incidence of recovery agitation was similar between the low- and high-dose groups (difference 1.9%, 95% confidence interval [CI] -14.8% to 18.4%). No significant difference was observed in sedation duration between the two groups (difference 0%, 95% CI -3.0% to 4.0%). While no additional ketamine was required in the high-dose group, four patients (7.4%) in the low-dose group required an additional half-dose (difference 7.4%, 95% CI -2.3% to 18.7%). Changes in vital signs were similar between the two groups.

Conclusions: There was no significant difference in recovery agitation, sedation duration, and changes in vital signs between 0.5 and 1 mg/kg IV ketamine for procedural sedation in the ED.

Background: Cervical cancer (CC) is preventable. CC screening decreases CC mortality. Emergency department (ED) patients are at disproportionately high risk for nonadherence with CC screening recommendations. The ED, therefore, is a target-rich environment for interventions to promote CC screening.

Methods: We conducted a randomized clinical trial to test and compare the efficacies of (1) basic referral for CC screening and (2) basic referral plus a text messaging intervention, grounded in behavioral change theory, to promote uptake of CC screening among ED patients. Participants aged 21-65, identified as in need of CC screening, were randomized to study arms and followed up at 150 days to assess interval CC screening uptake (primary outcome) and analyze methods-related moderators of intervention effects. Participants were recruited from a large, urban ED and a small, rural ED within the same health care system. Intervention arms were compared to historical controls.

Results: A total of 4035 patients were surveyed, with 1089 identified as requiring CC screening and subsequently randomized. Upon 150-day follow-up, 20% of individuals in the basic referral arm and 23% of individuals in the basic referral plus text messaging arm had obtained screening. Screening uptake in the historical control group was found to be 10% over a 150-day period. The overall difference between prospective arms was not significant (p = 0.219). However, moderation analysis found that women ≥40 years old demonstrated greater uptake of screening after the higher intensity intervention compared to the lower (p = 0.032). The differences in screening uptake between both interventions, individually and combined, when compared to controls was significant (p ≤ 0.001).

Conclusions: This study demonstrates that both of the evaluated low-intensity ED-based interventions significantly increase subsequent CC screening uptake compared to historical controls. The higher intensity intervention significantly increased screening uptake compared to the lower intensity intervention among women ≥40 years old.

Background: Prehospital emergencies require providers to rapidly identify patients' medical condition and determine treatment needs. We tested whether medics' initial, written impressions of patient condition contain information that can help identify patients who require prehospital lifesaving interventions (LSI) prior to or during transport.

Methods: We analyzed free-text medic impressions of prehospital patients encountered at the scene of an accident or injury, using data from STAT MedEvac air medical transport service from 2012 to 2021. EMR records were used to identify LSIs performed for these patients in prehospital settings. Text was cleaned via natural language processing and transformed using term frequency-inverse document frequency. A gradient boosting machine learning (ML) model was used to predict individual patient need for prehospital LSI as well as seven LSI subcategories (e.g., airway interventions, blood transfusion, vasopressor medication).

Results: A total of 12,913 prehospital patients were included in our sample (mean age = 52.3 years, 63% men). We observed good ML performance in predicting overall LSI (area under the receiver operating curve = 0.793, 95% confidence interval = [0.776-0.810]; average precision = 0.670, 95% confidence interval = [0.643-0.695] vs. LSI rate of 0.282) and equivalent-or-better performance in predicting each LSI subcategory except for crystalloid fluid administration. We identified individual words within medic impressions that portended high (e.g., unresponsive, hemorrhage) or low (e.g., droop, rib) LSI rates. Calibration analysis showed that models could prioritize correct LSI identification (i.e., high sensitivity) or accurate triage (i.e., low false-positive rate). Sensitivity analyses showed that model performance was robust when removing from medic impressions words that directly labeled an LSI.

Conclusions: ML based on free-text medic impressions can help identify patient need for prehospital LSI. We discuss future work, such as applying similar methods to 9-1-1 call requests, and potential applications, including voice-to-text translation of medic impressions.

Background: Vertigo is a priority for training and decision support in emergency departments (ED). Benign paroxysmal positional vertigo (BPPV), though manageable at bedside, remains frequently underdiagnosed and undertreated. This study assessed the effectiveness of a two-tiered educational intervention on posterior and horizontal BPPV management in the ED setting.

Methods: Longitudinal program evaluation study conducted over a year in a French ED, following GRACE-3 guidelines, involving patients with triggered episodic vestibular syndrome or brief vertigo without nystagmus. Two 6-month periods were compared: before (control cohort) and after (intervention cohort) an educational intervention of standardized training and an online decision support tool. The primary outcome was the prevalence of evidence-based BPPV diagnoses.

Results: Of the 382 patients included, 166 were in the control cohort (43.5%) and 216 were in the intervention cohort (56.5%). The intervention cohort had a higher rate of evidence-based BPPV diagnoses compared to the control cohort (38.0% vs. 16.9%), with an effect size of 21.1 (95% confidence interval [CI] 11.5-29.6, p < 0.0001). Canalith repositioning maneuvers were performed more frequently in the intervention cohort (90.2% vs. 57.7%), with an effect size of 33.1 (95% CI 13.2-53.1). Posttreatment tests showed a nonsignificant difference of 79.5% of intervention cohort patients testing negative versus 75.0% in the control cohort. ED length of stay was shorter in the intervention cohort (137 min vs. 247 min), with an effect size of -109.5 (95% CI -154.0 to -65.0). ED revisits within 1 month were similar (2.3% vs. 1.2%). During the intervention period, clinicians' satisfaction was correlated with the effectiveness of their clinical management.

Conclusions: A standardized educational intervention demonstrated enhancing BPPV screening and improved evidence-based diagnosis, showing promise of more efficient treatment in the ED. Further multicenter studies are warranted to evaluate impacts on patient-reported outcomes and resource optimization.