Archives of Academic Emergency Medicine最新文献

Introduction: Amiodarone has been reported to be associated with QTc interval prolongation and Torsades de pointes (TdP). This study aimed to assess the incidence and identify the risk factors of QTc prolongation and TdP associated with intravenous amiodarone therapy in patients diagnosed with atrial fibrillation (AF).

Methods: A retrospective cohort study was conducted using electronic health records of Buddhachinaraj Hospital, a tertiary care center in Thailand, between January 2016 and September 2019. The study population comprised patients with AF who received intravenous amiodarone therapy. Incidence and associated risk factors for QTc interval prolongation and TdP were assessed using multivariable logistic regression analysis.

Results: A total of 2,944 patients were included in the analysis. Among these, 49 cases of intravenous amiodarone-associated QTc interval prolongation or TdP were identified (33 (1.12%) and 16 (0.54%) cases, respectively), corresponding to an overall incidence of 1.66% (95% confidence interval (CI): 1.23 - 2.19). Multivariable analysis revealed that diabetes mellitus (adjusted odds ratio (aOR): 1.85; 95% CI: 1.02 - 3.38; p-value = 0.045), history of stroke (aOR: 3.09; 95% CI: 1.26 - 7.57; p-value = 0.014), use of antipsychotic medications (aOR: 3.07; 95% CI: 1.64 - 5.74; p-value < 0.001), and use of anticholinergic medications (aOR: 3.89; 95% CI: 1.54 - 9.85; p-value = 0.004) were significantly associated with an increased risk of QTc interval prolongation and TdP following amiodarone therapy for AF patients.

Conclusion: Although the incidence of QTc interval prolongation and TdP related to intravenous amiodarone therapy in patients with AF was relatively low, the risk was significantly elevated in individuals with diabetes mellitus, a history of stroke, or concurrent use of antipsychotic or anticholinergic agents. These findings underscore the importance of vigilant risk assessment and monitoring in clinical practice to mitigate the potential for intravenous amiodarone-induced arrhythmic complications.

This letter suggests that relabelling often reflects documentation differences rather than diagnostic error. It highlights higher mismatch rates in paediatric and neurological patients and considers whether improved coding systems or earlier access to investigations could reduce these gaps. Future studies assessing diagnostic confidence at admission and stronger collaboration between emergency and inpatient teams may also help improve concordance.

Cardiac arrest is a life-threatening condition with a high mortality rate, necessitating prompt recognition and treatment of reversible causes to enhance patient survival. Point-of-care ultrasound (POCUS) has emerged as a useful tool that contributes to optimizing resuscitative efforts. This imaging modality offers real-time visualization that assists in detecting reversible causes such as cardiac tamponade, pulmonary embolism, tension pneumothorax and hypovolemia. This review aims to explore the expanding role of ultrasound in the assessment and management of cardiac arrest, emphasizing its utility in identifying cardiac arrest, differentiating between true pulseless electrical activity (PEA) and pseudo-PEA, detecting the reversible causes, guiding clinical decision-making, and potentially predicting outcomes. A comprehensive literature search was performed using the PubMed database from inception to April 2025. Articles were selected based on their relevance to the role and applications of POCUS in cardiac arrest.

Introduction: In patients with out-of-hospital cardiac arrest (OHCA) who receive advanced cardiac life support (ACLS) for 20 minutes, the decision of whether to continue or terminate resuscitation at the scene is difficult and complicated. This study aimed to develop and validate a simple and reliable clinical scoring system for identifying cardiopulmonary resuscitation (CPR) failure at the scene after 20 minutes of ACLS.

Methods: In this cross-sectional study we evaluated the adults with nontraumatic OHCA who received ACLS for 20 minutes. The independent predictors of CPR failure were identified using multivariate regression analysis and trying to develop a clinical decision rule. Receiver operating characteristic (ROC) curve was used for evaluating the performance of the developed model.

Results: 455 patients with the mean age of 63.85 ± 19.21 years were included (65.1% male). In most cases of OHCA, the cause of cardiac arrest was respiratory (54.9%). The first cardiac rhythm recorded in 68.1% was asystole. 313 (68.79%) cases were affiliated to the failed CPR group. The independent predictive factors of CPR failure based on multivariate analysis were the first cardiac rhythm recorded (p < 0.001), unwitnessed cardiac arrest (p < 0.001), lack of pupillary response (p < 0.001), advanced airway management at the scene (p < 0.001), and administration of drugs at the scene during CPR, including amiodarone (p = 0.020) and atropine (p = 0.002). The area under the ROC curve of the model was 0.832 (95% confidence interval (CI): 0.793-0.870) with 70.0% sensitivity, 82.4% specificity, 89.8% positive predictive value, 55.5% negative predictive value, 3.97 positive likelihood ratio, and 0.36 negative likelihood ratio.

Conclusion: Using data from routine care practices by EMS personnel, we devised a simple clinical scoring system for predicting CPR failure at the scene of OHCA after 20 minutes of complete ACLS.

Introduction: Emergence agitation (EA) occurs shortly after emergence from anesthesia in pediatric patients causing disorientation, restlessness, and non-purposeful movement. This study aimed to compare intranasal dexmedetomidine (DEX) and oral midazolam in managing EA in pediatric patients scheduled for neurosurgical procedures.

Methods: This double-blinded randomized clinical trial was conducted on 50 pediatric patients who underwent neurosurgical procedure in an educational hospital between March and June 2024. One group received intranasal DEX (2 mcg/kg) and other group received oral midazolam (1 mg/kg of midazolam) before induction of anesthesia. The rate of EA as well as vital signs changes were compared between the two groups using statistical analysis.

Results: 50 participants were enrolled in the study and randomly divided to DEX and midazolam groups (25 participants in each group). The two groups were similar regarding age (p = 0.538); sex (p = 0.417); pre-operation heart rate (p = 0.675); systolic (p = 0.226) and diastolic (p = 0.753) blood pressure; and pre-operative mean arterial blood pressure (p = 0.634). Among all participants, 13 (26.00%) patients showed signs of EA after extubation (2 patients (8.00%) in DEX group and 11 (44.00%) patients in midazolam group; p = 0.004). Regrading vital signs, only the decrease in heart rate after extubation in the DEX group was significantly greater than that observed in the midazolam group (-9.28±12.88 vs. -2.48±8.23, respectively; p = 0.0310). The number needed to treat (NNT), relative risk reduction (RRR), and absolute risk reduction (ARR) of using intranasal DEX in management of EA were 2.77 (95%confidence interval (CI): 1.72-7.19), 81.8% (95%CI: 26.0%-95.5%), and 36.0% (95%CI: 13.9%-58.1%) respectively.

Conclusion: Intranasal DEX compare to oral midazolam demonstrated superior efficacy in managing postoperative EA in pediatric patients.

Introduction: High stress hyperglycemia ratio (SHR) and low hemoglobin-to-red blood cell distribution width ratio (HB/RDW) are each known predictors of mortality in acute ischemic stroke (AIS). This study aimed to assess the predictive performance of high SHR (≥1.18) and low HB/RDW (≤0.76) together in stroke patients treated with thrombolysis.

Methods: We retrospectively collected data from 345 AIS patients treated with thrombolysis. HB/RDW values were obtained from pre-recombinant tissue plasminogen activator complete blood counts; while fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) levels were measured in the morning after an 8-14-hour overnight fast. Patients were categorized into four groups based on SHR and HB/RDW levels. We used multivariable Poisson regression with robust variance to estimate risk ratios (RRs) and 95% confidence intervals (CIs). Models assessed associations with in-hospital mortality (IHM), early neurological deterioration (END), and functional outcomes at discharge and 3 months, adjusting for age, sex, prior stroke, pre-existing disability, myocardial infarction, atrial fibrillation, heart failure, chronic kidney disease, and malignancy. Propensity score weighting analysis was further conducted as a sensitivity analysis.

Results: Among 345 patients, only 37 were in the high SHR (SHR+) and low HB/RDW (HB/RDW+) group. A total of 65 patients (18.8%) died during hospitalization. The SHR+ HB/RDW+ group had significantly higher risks of IHM (adjusted RR: 9.97, 95% CI: 4.95-20.08), END (adjusted RR: 2.95, 95% CI: 1.51-5.77), 3-month mortality (adjusted RR: 6.23, 95% CI: 3.49-11.12), and poor 3-month functional outcomes (adjusted RR: 2.86, 95% CI: 2.01-4.06) compared to the SHR- HB/RDW- group. These associations remained robust across sensitivity analyses. The combination of SHR ≥1.18 and HB/RDW ≤0.76 predicted IHM with an AuROC of 0.78 (95% CI: 0.73-0.83). Although the combined biomarker improved sensitivity and net benefit, its AUROC was not statistically superior to that of individual markers.

Conclusions: Combined high SHR and low HB/RDW levels at admission significantly predict poor outcomes in thrombolysis-treated AIS, performing better than either biomarker alone. Further validation in larger, diverse cohorts is warranted.

Introduction: Acute respiratory failure (ARF) is a critical complication of heat-related illness (HRI). This study aimed to identify predictors of HRI-induced ARF in patients presenting to the emergency department (ED).

Methods: Patients aged 20 years and above diagnosed with HRI (ICD-9-CM code 992 or ICD-10 code T67) who visited the EDs of the three hospitals in Tainan, Taiwan between January 2010 and October 2021, were included. Demographic characteristics, comorbidities, and laboratory data were collected. Logistic regression models using the backward elimination method were constructed to identify the independent predictors of HRI-induced ARF.

Results: 820 patients with the mean age of 50.0 ± 18.4 years were studied (80.0% male). 29 (3.5%) cases experienced ARF. Patients with ARF were less likely to walk on arrival compared to those without it (27.6% vs. 61.8%, p < 0.001). Additionally, they had higher prevalence of Glasgow Coma Scale (GCS) scores ≤ 8 (p = 0.003), respiratory rate > 20 breaths/min (p < 0.001), body temperature ≥ 40°C (p < 0.001), hypertension (p = 0.001), cerebrovascular disease (p = 0.001), and chronic obstructive pulmonary disease (p = 0.042). The multivariable logistic regression revealed that body temperature ≥ 40 °C on arrival (odds ratio (OR): 7.76; 95% confidence interval (CI): 3.14-19.15), an initial respiratory rate > 20 breaths/min (OR: 8.19; 95% CI: 3.48-19.24), and history of hypertension (OR: 3.38; 95% CI: 1.52-7.52) were predictors of HRI-induced ARF.

Conclusions: Elevated body temperature, respiratory rate, and a history of hypertension were key predictors of ARF in HRI patients, aiding in patient stratification for emergency care.

Introduction: In 2017, WHO endorsed the Emergency Medical Team (EMT) Minimum Data Set (MDS) for real-time data collection during health emergencies. It was first activated during Cyclone Idai in Mozambique in 2019. The objective of the study is to evaluate the completeness of data collected by EMTs during the Cyclone Idai response in Mozambique.

Methods: This study evaluated data completeness from Cyclone Idai, analyzing 277 daily reports with 18,468 patient consultations from 13 international teams between 27 March and 12 July, 2019. Completeness of team information, demographics, health events, disaster relation, and outcomes were compared across EMT types and classifications using box plots, Kruskal-Wallis, t-tests, and multivariable logistic regression.

Results: During the 110-day response, 13 EMTs submitted 277 daily reports on patient information. Findings showed that, out of the 277 daily reports, demographic information was complete in 92.8% of reports, health event information in 62.1%, information on the relation of health events to disaster in 57.4%, and outcome data in 50.2%. Type 2 EMTs exhibited higher data completeness, likely due to greater resources and personnel, compared to Type 1 Mobile and Type 1 Fixed EMTs. Type 1 Fixed EMTs demonstrated lower completeness for outcomes, health events, and disaster relation, potentially due to heavier workloads. Type 1 Mobile EMTs likely benefited from enhanced training and frequent interactions with data managers, which may have contributed to their higher data completeness compared to Type 1 Fixed EMTs. Classified EMTs performed better overall.

Conclusion: This study underscores the need for standardized training, and the data collection applications that enable the automatic inclusion of information such as geotags.

Introduction: Although emergency medicine is crucial globally, it remains underdeveloped in Iran, facing low recruitment rates. This study aimed to explore barriers deterring Iranian general practitioners (GPs) from pursuing emergency medicine as a specialty.

Methods: A cross-sectional survey was conducted in Kerman, Iran, in 2023. Data were collected from GPs using a structured questionnaire assessing demographic characteristics and barriers to choosing emergency medicine. Statistical analyses, including chi-square and Mann-Whitney U-tests, were performed.

Results: 198 GPs were involved in this study. 95.5% of the participants cited a mismatch between income and workload as the primary deterrent, while high psychological stress (87.4%) and limited private sector opportunities (86.9%) were also significant barriers. Additionally, 82.8% reported high burnout levels, with frequent night shifts (81.8%) and long working hours (75.3%) as contributing factors. Demographic analysis showed younger GPs and those with fewer years since graduation perceived financial and emotional strains more strongly, indicating that early-career physicians may feel more vulnerable to these challenges. Further, GPs lacking emergency department experience rated career uncertainties higher, suggesting unfamiliarity with the field might amplify negative perceptions. Rural GPs emphasized high patient loads and exposure risks, while urban GPs noted stress from crowded settings.

Conclusion: Findings highlight financial and workload issues as major deterrents to choosing emergency medicine as a specialty. Addressing these concerns through better compensation, work-life balance improvements, and enhanced career prospects could attract more GPs to this specialty.

Introduction: Meta-analyses of diagnostic/prognostic studies for calculating the pooled sensitivity and specificity require true positive (TP), true negative (TN), false positive (FP), and false negative (FN) counts. However, few studies report these values directly. This study aimed to consolidate practical methods to reconstruct sensitivity and specificity from minimal data.

Methods: Our framework addresses three main situations: (1) algebraic rearrangements to compute specificity given partial metrics; (2) digitization of receiver operating characteristic (ROC) curves to obtain threshold-specific sensitivity and specificity; and (3) application of the binormal model when only AUC and prevalence are available. We tested these methods on a dataset related to mortality prediction in myocardial infarction (MI) using machine learning models, assessing how well they reconstructed sensitivity and specificity.

Results: Algebraic formulas and ROC digitization yielded reliable estimates when partial metrics or graphical curves were sufficiently detailed. However, the binormal model, which assumes equal variances, showed noticeable inaccuracies, especially for sensitivity. Linear regression analyses indicated that higher prevalence and higher AUC reduced estimation errors.

Conclusion: These methods offer practical alternatives for reconstructing diagnostic accuracy measures when data are incomplete. Relying solely on AUC-based estimations may introduce substantial bias, particularly in low-prevalence contexts. We recommend that primary studies report threshold-specific sensitivity and specificity to support more accurate meta-analytic estimations.