Lung Injury Prediction Score for the Emergency Department: First Step Towards Prevention in Patients at Risk

Background: Early identification of patients at risk of developing acute lung injury (ALI) is critical for potential preventive strategies. We aimed to derive and validate an acute lung injury prediction score (EDLIPS) in a multicenter sample of emergency department (ED) patients. Methods: We performed a subgroup analysis of 4,361 ED patients enrolled in the previously reported multicenter observational study. ED risk factors and conditions associated with subsequent ALI development were identified and included in the EDLIPS model. Scores were derived and validated using logistic regression analyses. The model was assessed with the area under the receiver-operating curve (AUC) and compared to the original LIPS model (derived from a population of elective high-risk surgical and ED patients) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score. Results: The incidence of ALI was 7.0% (303/4361). EDLIPS discriminated patients who developed ALI from those who did not with an AUC of 0.78 (95% CI 0.75, 0.82), better than the APACHE II AUC 0.70 (p ≤ 0.001) and similar to the original LIPS score AUC 0.80 (p = 0.07). At an EDLIPS cutoff of 5 (range −0.5, 15) positive and negative likelihood ratios (95% CI) for ALI development were 2.74 (2.43, 3.07) and 0.39 (0.30, 0.49), respectively, with a sensitivity 0.72(0.64, 0.78), specificity 0.74 (0.72, 0.76), and positive and negative predictive value of 0.18 (0.15, 0.21) and 0.97 (0.96, 0.98). Conclusion: EDLIPS may help identify patients at risk for ALI development early in the course of their ED presentation. This novel model may detect at-risk patients for treatment optimization and identify potential patients for ALI prevention trials

Towards Prevention of Acute Lung Injury: Frequency and Outcomes of Emergency Department Patients At-Risk: A Multicenter Cohort Study

Background: Few emergency department (ED) evaluations on acute lung injury (ALI) have been carried out; hence, we sought to describe a cohort of hospitalized ED patients at risk for ALI development. Methods: Patients presenting to the ED with at least one predisposing condition to ALI were included in this study, a subgroup analysis of a multicenter observational cohort study (USCIITG-LIPS 1). Patients who met ALI criteria within 6 h of initial ED assessment, received end-of-life care, or were readmitted during the study period were excluded. Primary outcome was frequency of ALI development; secondary outcomes were ICU and hospital mortality. Results: Twenty-two hospitals enrolled 4,361 patients who were followed from the ED to hospital discharge. ALI developed in 303 (7.0 %) patients at a median onset of 2 days (IQR 2–5). Of the predisposing conditions, frequency of ALI development was highest in patients who had aortic surgery (43 %) and lowest in patients with pancreatitis (2.8 %). Compared to patients who did not develop ALI, those who did had higher ICU (24 % vs. 3.0 %, p < 0.001) and hospital (28 % vs. 4.6 %, p < 0.001) mortality, and longer hospital length of stay (16 vs. 5 days, p < 0.001). Among the 22 study sites, frequency of ALI development varied from less than 1 % to more than 12 % after adjustment for APACHE II. Conclusions: Seven percent of hospitalized ED patients with at least one predisposing condition developed ALI. The frequency of ALI development varied significantly according to predisposing conditions and across institutions. Further research is warranted to determine the factors contributing to ALI development

Trauma Simulation Training Increases Confidence Levels in Prehospital Personnel Performing Life-Saving Interventions in Trauma Patients

Introduction. Limited evidence is available on simulation training of prehospital care providers, specifically the use of tourniquets and needle decompression. This study focused on whether the confidence level of prehospital personnel performing these skills improved through simulation training. Methods. Prehospital personnel from Alachua County Fire Rescue were enrolled in the study over a 2-to 3-week period based on their availability. Two scenarios were presented to them: a motorcycle crash resulting in a leg amputation requiring a tourniquet and an intoxicated patient with a stab wound, who experienced tension pneumothorax requiring needle decompression. Crews were asked to rate their confidence levels before and after exposure to the scenarios. Timing of the simulation interventions was compared with actual scene times to determine applicability of simulation in measuring the efficiency of prehospital personnel. Results. Results were collected from 129 participants. Pre-and postexposure scores increased by a mean of 1.15 (SD 1.32; 95% CI, 0.88-1.42; &lt; 0.001). Comparison of actual scene times with simulated scene times yielded a 1.39-fold difference (95% CI, 1.25-1.55) for Scenario 1 and 1.59 times longer for Scenario 2 (95% CI, 1.43-1.77). Conclusion. Simulation training improved prehospital care providers&apos; confidence level in performing two life-saving procedures

Evaluation of Healthcare Use Trends of High-Risk Female Intimate Partner Violence Victims

Introduction: Practitioners need more information about intimate partner violence (IPV) victims’ healthcare use trends. We used a novel data-linkage method and complaint categorization allowing us to evaluate IPV victims healthcare use trends compared to the date of their victimization. Methods: This was a retrospective case series using data-linking techniques cross-referencing databases of Medicaid-eligible women between the ages of 16 and 55 years, an IPV Case Database for 2007 and the Florida State Agency for Healthcare Administration, which tracks hospital inpatient, ambulatory and emergency department (ED) use within the State of Florida. We analyzed resulting healthcare visits 1.5 years before and 1.5 years after the women’s reported IPV offense. Using all available claims data a ‘complaint category’ representing categories of presenting chief complaints was assigned to each healthcare visit. Analysis included descriptive statistics, correlation coefficients between time of offense and visits, and a logistic regression analysis. Results: The 695 victims were linked with 4,344 healthcare visits in the four-year study period. The victims were young (46% in the 16-25 age group and 79% were younger than 35). Healthcare visits were in the ED (83%) rather than other healthcare sites. In the ED, IPV victims mostly had complaint categories of obstetrics and gynaecology-related visits (28.7%), infection-related visits (18.9%), and trauma-related visits (16.3%). ED use escalated approaching the victim’s date of offense (r=0.59, p<0.0001) compared to use of non-ED sites of healthcare use (r=0.07,p=0.5817). ED use deescalated significantly after date of reported offense for ED visits (r=0.50,p<0.0001) versus non-ED use (r=0.00,p=0.9958). The victims’ age group more likely to use the ED than any other age group was the 36-45 age group (OR 4.67, CI [3.26- 6.68]). Conclusion: IPV victims use the ED increasingly approaching their date of offense. Presenting complaints were varied and did not reveal unique identifiers of IPV victims. This novel method of database matching between claims data and government records has been shown to be a valid way to evaluate healthcare utilization of at-risk populations. [West J Emerg Med. 2015;16(1):107-113.

Development of a personalized diagnostic model for kidney stone disease tailored to acute care by integrating large clinical, demographics and laboratory data: the diagnostic acute care algorithm - kidney stones (DACA-KS)

Abstract Background Kidney stone (KS) disease has high, increasing prevalence in the United States and poses a massive economic burden. Diagnostics algorithms of KS only use a few variables with a limited sensitivity and specificity. In this study, we tested a big data approach to infer and validate a ‘multi-domain’ personalized diagnostic acute care algorithm for KS (DACA-KS), merging demographic, vital signs, clinical, and laboratory information. Methods We utilized a large, single-center database of patients admitted to acute care units in a large tertiary care hospital. Patients diagnosed with KS were compared to groups of patients with acute abdominal/flank/groin pain, genitourinary diseases, and other conditions. We analyzed multiple information domains (several thousands of variables) using a collection of statistical and machine learning models with feature selectors. We compared sensitivity, specificity and area under the receiver operating characteristic (AUROC) of our approach with the STONE score, using cross-validation. Results Thirty eight thousand five hundred and ninety-seven distinct adult patients were admitted to critical care between 2001 and 2012, of which 217 were diagnosed with KS, and 7446 with acute pain (non-KS). The multi-domain approach using logistic regression yielded an AUROC of 0.86 and a sensitivity/specificity of 0.81/0.82 in cross-validation. Increase in performance was obtained by fitting a super-learner, at the price of lower interpretability. We discussed in detail comorbidity and lab marker variables independently associated with KS (e.g. blood chloride, candidiasis, sleep disorders). Conclusions Although external validation is warranted, DACA-KS could be integrated into electronic health systems; the algorithm has the potential used as an effective tool to help nurses and healthcare personnel during triage or clinicians making a diagnosis, streamlining patients’ management in acute care

Trauma Simulation Training Increases Confidence Levels in Prehospital Personnel Performing Life-Saving Interventions in Trauma Patients

Introduction. Limited evidence is available on simulation training of prehospital care providers, specifically the use of tourniquets and needle decompression. This study focused on whether the confidence level of prehospital personnel performing these skills improved through simulation training. Methods. Prehospital personnel from Alachua County Fire Rescue were enrolled in the study over a 2- to 3-week period based on their availability. Two scenarios were presented to them: a motorcycle crash resulting in a leg amputation requiring a tourniquet and an intoxicated patient with a stab wound, who experienced tension pneumothorax requiring needle decompression. Crews were asked to rate their confidence levels before and after exposure to the scenarios. Timing of the simulation interventions was compared with actual scene times to determine applicability of simulation in measuring the efficiency of prehospital personnel. Results. Results were collected from 129 participants. Pre- and postexposure scores increased by a mean of 1.15 (SD 1.32; 95% CI, 0.88–1.42; P<0.001). Comparison of actual scene times with simulated scene times yielded a 1.39-fold difference (95% CI, 1.25–1.55) for Scenario 1 and 1.59 times longer for Scenario 2 (95% CI, 1.43–1.77). Conclusion. Simulation training improved prehospital care providers’ confidence level in performing two life-saving procedures

Emergency Department Crowding and Time to Antibiotic Administration in Febrile Infants

Introduction: Early antibiotic administration is recommended in newborns presenting with febrile illness to emergency departments (ED) to avert the sequelae of serious bacterial infection. Although ED crowding has been associated with delays in antibiotic administration in a dedicated pediatric ED, the majority of children that receive emergency medical care in the U.S. present to EDs that treat both adult and pediatric emergencies. The purpose of this study was to examine the relationship between time to antibiotic administration in febrile newborns and crowding in a general ED serving both an adult and pediatric population.Methods: We conducted a retrospective chart review of 159 newborns presenting to a general ED between 2005 and 2011 and analyzed the association between time to antibiotic administration and ED occupancy rate at the time of, prior to, and following infant presentation to the ED.Results: We observed delayed and variable time to antibiotic administration and found no association between time to antibiotic administration and occupancy rate prior to, at the time of, or following infant presentation (P > 0.05). ED time to antibiotic administration was not associated with hospital length of stay, and there was no inpatient mortality.Conclusion: Delayed and highly variable time to antibiotic treatment in febrile newborns was common but unrelated to ED crowding in the general ED study site. Guidelines for time to antibiotic administration in this population may reduce variability in ED practice patterns. [West J Emerg Med. 2013;14(5):518-524.

User Experience of Access to Sexual Assault Nurse Examiner and Emergency Contraception in Emergency Departments in the United States: A National Survey

Background: Despite the prevalence of sexual assault presentations to emergency departments (ED) in the United States, current access to sexual assault nurse examiners (SANE) and emergency contraception (EC) in EDs is unknown.Methods: In this study we employed a “secret shopper,” cross-sectional telephonic survey. A team attempted phone contact with a representative sample of EDs and asked respondents about the availability of SANEs and EC in their ED. Reported availability was correlated with variables including region, urban/rural status, hospital size, faith affiliation, academic affiliation, and existence of legislative requirements to offer EC.Results: Over a two-month period in 2019, 1,046 calls to hospitals were attempted and 960 were completed (91.7% response rate). Of the 4,360 eligible hospitals listed in a federal database, 960 (22.0%) were contacted. Access to SANEs and EC were reported to be available in 48.9% (95%confidence interval [CI] 45.5–52.0) and 42.5% (95% CI 39.4–45.7) of hospitals, respectively. Access to EC was positively correlated with SANE availability. The EDs reporting SANE and EC availability were more likely to be large, rural, and affiliated with an academic institution. Those reporting access to EC were more likely to be in the Northeast and in states with legislative requirements to offer EC.Conclusion: Our results suggest that perceived access to sexual assault services and emergency contraception in EDs in the United States remains poor with regional and legislative disparities. Results suggest disparities in perceived access to EC and SANE in the ED, which have implications for improving ED practices regarding care of sexual assault victims

Ultra-early serum concentrations of neuronal and astroglial biomarkers predict poor neurological outcome after out-of-hospital cardiac arrest—a pilot neuroprognostic study

Objectives: To assess ultra-early neuroprognostic significance of GFAP, NF-L, UCH-L1, tau, and S100B concentrations, change trajectory, and combination profile after Out-of-Hospital Cardiac Arrest (OHCA). Methods: Prospective enrollment of 22 OHCA and 10 control patients at an academic tertiary care center between May 1, 2017 and January 28, 2020. Blood was collected within one hour of return of spontaneous circulation (ROSC) (H0), at hours 6 (H6), 12, 18, 24, and daily or until discharge or death. Biomarker concentrations, multifactor score, and trajectory change were assessed and compared to final neurologic status (good vs poor Cerebral Performance Category; CPC 1–2 vs CPC 3–5, respectively). Results: 10 patients had good and 12 had poor neurologic outcomes. Poor outcome patients had higher biomarker concentrations and combined biomarker scores at early time points. The earliest significant difference between good and poor outcome patients’ serum biomarkers were at H12 for GFAP (good median: 425 pg/mL [IQR:370−630] vs poor: 5954[1712–65,055] pg/mL; p < 0.001), H12 for NF-L (64[41–69] vs 898[348–1990] pg/mL; p < 0.001), H0 for Tau (31[8–51] vs 124[53–238] pg/mL; p = 0.025), H0 for UCH-L1 (898[375–1600] vs 2475[1898–4098] pg/mL; p = 0.008), and H6 for S100B (123[70–290] vs 895[360–1199] pg/mL; p = 0.002). Four biomarker composite scores differed by H12 (78.03[52.03–111.25] vs 749 [198.46–4870.63] pg/mL; p = 0.003). Machine-learning approach also identified that four-marker score trajectory group memberships are in concordance with patient outcome. Conclusions: Ultra-early serial serum concentrations of neuronal and astroglial biomarkers may be of neuroprognostic significance following OHCA