Archives of Academic Emergency Medicine最新文献

Ozone therapy, often marketed as an immune-boosting alternative treatment, lacks robust evidence of efficacy and poses significant safety risks. Despite claims of therapeutic benefits, Regulatory agencies, such as the U.S. Food and Drug Administration (FDA), warn against its use due to its toxic properties and lack of proven benefits at tolerable exposure levels. This case report highlights severe neurological complications, including ischemic infarcts and persistent cognitive deficits, following intravenous ozone (O₃) therapy in a previously healthy patient. A 36-year-old woman presented to the emergency department with chest pain, syncope, and generalized seizure shortly after receiving intravenous ozone therapy. Diagnostic imaging revealed multiple ischemic infarcts in the thalamus and cerebellum, consistent with an embolic event. The patient required intensive care unit (ICU) admission, and despite improved neurological function experienced lasting cognitive impairments necessitating long-term rehabilitation.

Introduction: Emergency department discharge destination is an important topic in both clinical practice and management. This study aimed to analyze the association of Care Complexity Individual Factors (CCIFs) with discharge destinations in patients who visit the emergency department (ED).

Methods: This is a retrospective cohort study with consecutive sampling, including all patients who visited the ED of a tertiary hospital during 2021-2022. Data were collected from electronic health records. The main study outcomes were discharge destinations (mortality, intensive care unit admission, hospitalization, left without being seen/discharge against medical advice, and home discharge) and 26 CCIFs. Independent multinomial logistic regression was used for assessing the association of each factor and the discharge destinations, adjusted for age, sex, and triage level. All analyses were performed with R, version 4.3.2.

Results: A total of 35,383 patients were included. Of these, 60.8% were home discharged, 34.1% were hospitalized, 2.6% were transferred to the intensive care unit, 2.1% were left without being seen, and 0.4% died. The presence of CCIFs was a risk factor of ED mortality (odds ratio (OR): 13.49 [95% confidence interval (CI): 4.99;36.46]), intensive care unit admission (OR:1.26 [95%CI:1.08;1.47]), and hospitalization (OR: 1.62 [95%CI:1.53;1.71]), whilst the presence of care complexity factors was a protective factor of discharge against medical advice (OR:0.64 [95%CI:0.55;0.74]).

Conclusion: The discharge destinations from the ED showed strong associations with the patient's complexity factors. Health professionals should consider these relationships for the design of early detection strategies and as an aid in decision-making, to ensure equity and quality of care.

Introduction: Surgical site infection (SSI) constitutes a substantial complication after knee arthroplasty, contributing to notable morbidity. This study aimed to review the existing literature on the incidence and risk factors of SSI following knee arthroplasty.

Methods: A systematic search was undertaken across various international electronic databases, including Scopus, PubMed, Web of Science, and Persian electronic databases such as Iranmedex and the Scientific Information Database. The search strategy involved the use of keywords derived from Medical Subject Headings, such as "incidence", "Surgical wound infection", "Surgical site infection", and "Arthroplasty", covering records from the earliest available up to March 17, 2024.

Results: The study incorporated a collective participant group of 1,366,494 knee arthroplasty procedures from twenty-three chosen studies. The pooled incidence rate of SSI after knee arthroplasty was 1.7% (95% confidence interval (CI): 1.1% to 2.6%; I²=99.687%; P<0.001). The Odds Ratio (OR) for the incidence of SSI in males was observed to be significantly higher than that in females (OR: 1.617; 95% CI: 1.380 to 1.894; Z=5.951; P<0.001). The pooled incidence of SSI among diabetic patients was 1.3% (95% CI: 0.6% to 2.8%; I²=99.126%; P<0.001).

Conclusion: Based on the main findings, SSIs continue to be a significant complication of knee arthroplasty, with an incidence of 1.1% to 2.6%. Male gender and diabetes mellitus were associated with an augmented probability of SSIs following knee arthroplasty.

Introduction: Previous studies have investigated different methods for estimating neurological outcomes after cardiac arrest. However, there is still much uncertainty about using optic nerve sheath diameter (ONSD) measurement as an indirect method for predicting neurological outcomes following cardiac arrest. In this meta-analysis, we aimed to investigate the value of ONSD for predicting the neurological outcomes of cardiac arrest survivors.

Methods: We comprehensively performed a systematic search in three main electronic databases, including Scopus, Medline, and Web of Science Cochrane, from inception to August 2024. Based on the heterogeneity evaluation results, fixed or random effects models were used to estimate the pooled diagnostic parameters. Meta-regressions were performed for subgroup analysis.

Results: The pooled sensitivity and specificity of ONSD for predicting the neurological outcomes were 0.56 (95% CI, 0.35-0.74) and 0.92 (95% CI, 0.85-0.96), respectively. Meta-regression revealed that as the cutoff level of ONSD increases, the sensitivity significantly decreases (P < 0.01), while the specificity significantly increases (P = 0.01). Furthermore, meta-regression analysis revealed that ONSD measurement using CT scans is significantly associated with lower sensitivity and higher specificity compared to ultrasound (P = 0.009 and P = 0.01).

Conclusion: Our meta-analysis showed that ONSD has low sensitivity and high specificity for predicting neurological outcomes in survivors of cardiac arrest. However, since the cut-off values and methods of ONSD measurement affect its predictive performance, further studies will be required to standardize these factors to achieve optimal predictive parameters.

Introduction: Acute kidney injury (AKI) is one of the most frequent complications in septic shock cases, and has a high mortality rate. The aim of this study was to determine the value of urinary liver-type fatty acid binding protein (L-FABP) in early detection and outcome prediction of AKI in patients with sepsis and septic shock.

Methods: This prospective cohort study was conducted on patients who presented to the emergency department (ED) with sepsis or septic shock. Urinary L-FABP levels were measured at the time of admission and patients were classified into AKI and non-AKI groups within 7 days according to the KIDGO Criteria. The screening performance characteristics of urinary L-FABP in early detection of AKI within seven days of admission and need for renal replacement therapy (RRT) were calculated and reported.

Results: 212 patients with the mean age of 66.5 ± 16.2 (range 18-99) years were included (60.4% male). 54 (25.5%) patients had sepsis, and septic shock was developed in 158 (74.53%) cases. 143 (67.5%) patients were complicated with AKI. The area under the receiver operating characteristic (ROC) curve (AUC) of urinary L-FABP in early detection of sepsis-associated AKI was 0.94 (95% confidence interval (CI): 0.90 - 0.97), compared to the AUC of 0.64 (95% CI: 0.54-0.74) for serum creatinine. The sensitivity and specificity of urinary L_FABP at its best cutoff point (13.90 μg L-FABP/g Cr) were 89.9% and 86.3%, respectively. The area under the ROC curve of urinary L-FABP in predicting the need for RRT in sepsis-associated AKI patients was 0.74 (95% CI: 0.64-0.85), compared to the AUC of 0.53 (95% CI: 0.41-0.64) for serum creatinine. The sensitivity and specificity of urinary L-FABP at its best cutoff point (22.05 μg L-FABP/g Cr) were 63.6% and 71.4%, respectively.

Conclusions: It seems that, L-FABP could be considered as a valuable biomarker for early detection and predicting the severity of AKI in septic patients.

Introduction: The National Early Warning Score (NEWS) is commonly used to identify patients at high mortality risk. However, it has notable limitations. In this study, to enhance the accuracy, we revised it and evaluated the performance of modified NEWS (MNEWS) in predicting the outcomes of suspected sepsis patients.

Methods: This single-center, prospective cohort study was conducted on patients with suspected sepsis to evaluate the accuracy of MNEWS in predicting mortality, survival to discharge, vasopressor requirements, and the need for mechanical ventilation. The MNEWS comprises the NEWS variables plus age, chronic major organ dysfunction, malignancy, functional status, and specific infected organ involvement. Sensitivity, specificity, likelihood ratio (LR), and area under the receiver operating characteristic curve (AUROC) were used to evaluate the performance of the MNEWS in predicting the studied outcomes.

Results: Of the 1,393 patients included in this study, 209 died. Mean MNEWS was significantly higher in non-survivors than survivors (19.8 vs. 14.9, p<0.001). The AUROC of MNEWS in predicting 30-day mortality was 0.82 (95% CI: 0.79-0.85). MNEWS ≥ 18 had the highest accuracy for 30-day mortality prediction with 76.1% sensitivity, 75% specificity, positive LR of 3.13, and AUROC of 0.76 (95% CI: 0.73-0.79). The AUROC of MNEWS ≥18 for predicting survival until discharge, need for vasopressors, and need for mechanical ventilation were 0.75 (95% CI: 0.72-0.78), 0.72 (95% CI: 0.69-0.75), and 0.76 (95% CI: 0.73-0.79), respectively. Additionally, MNEWS ≥18 demonstrated superior predictive performance, compared with NEWS ≥7 and qSOFA ≥2 for various clinical outcomes.

Conclusions: The MNEWS was similar to the NEWS in overall predictive accuracy for 30-day mortality but exhibited a higher predictive accuracy than did the qSOFA score. Notably, MNEWS ≥18 was a significant indicator of 30-day mortality risk, as well as the likelihood of requiring vasopressors, survival to discharge, and 7-day mortality.

Introduction: Determining the trauma patients' prognosis is crucial for patients' safety, triage, and appropriate management. This study aimed to evaluate the screening performance of Traumatic Emergency Room Major Injury Death At Least 24 hours (TERMINAL-24) score in predicting the mortality of trauma patients.

Methods: This cross-sectional study was conducted in the emergency department (ED) of a referral trauma center, between October 2023 and September 2024. The main goals of the project were determining the value of TERMINAL-24 score in predicting early (within 8 hours of admission to ED) and in-hospital mortality of multi-trauma patients as well as comparing the accuracy of TERMINAL-24 with other trauma severity scores (GAP, RGAP, NTS) in this regard.

Results: 963 multi-trauma patients were included in this study. The mean age of the patients was 37.75±17.10 years (73.2% male). 55 patients died in the emergency department and 46 patients died during hospitalization in other departments. Male gender (p = 0.009), older age (p =0.011), traffic accidents (p = 0.005), more critical vital signs (p = <0.001), admitting in neurosurgery ward (p < 0.001), and higher trauma severity (P < 0.001) were significantly associated with higher mortality rate. The area under the curve (AUC) of TERMINAL-24 score in predicting early and in-hospital mortality of trauma patients were 0.964 (95%CI: 0.937-0.991) and 0.954 (95%CI: 0.925-0.983), respectively. The specificity and sensitivity of TERMINAL-24 score for predicting early mortality at its best cut-off point (cut-off = 2.5) were 95.04% (95%CI: 93.43-96.28) and 96.36% (95%CI: 87.63-99.35), respectively. For predicting in-hospital mortality, these measures were 98.84% (95%CI: 97.88-99.37) and 87.13% (95%CI: 79.22-92.32), respectively (best cut-off = 2.5).

Conclusions: It seems that, TERMINAL-24 score has the same accuracy in predicting both early and in-hospital outcomes of trauma patients. Considering the calculation formula of this score and its simplicity, it can be used in pre-hospital and in-hospital settings to predict the outcome of trauma patients.

Introduction: Traumatic out-of-hospital cardiac arrest (TOHCA) presents significant public health challenges. The high accident rates and variability in prehospital management in Thailand further complicate TOHCA treatment. This study aimed to analyze prehospital prognostic factors of survival in TOHCA cases.

Methods: This study is a retrospective cohort study utilizing data from the Information Technology of Emergency Medicine System (ITEMS) from January 2012 to December 2022. It included TOHCA patients who received prehospital care and were transported to the emergency department (ED). We used an exploratory approach, incorporating all prognostic variables into a multivariable logistic regression model. Results are presented as odds ratios (OR) with 95% confidence intervals (CIs) and p-values.

Results: Over an 11-year period, 35,724 patients with the mean age of 39.69±20.53 (range: 1-99) years were included in the final analysis (78.69% male). Of these, 6,590 (18.45%) survived to hospital admission, while 29,134 (81.55%) died in the ED. Prehospital management factors significantly increasing the likelihood of survival to hospital admission included stopping bleeding (OR=1.38, 95% CI=1.24-1.54, P<0.001), endotracheal intubation (ETT) (OR=2.09, 95% CI=1.74-2.50, P<0.001), intravenous fluid administration (OR=1.66, 95% CI=1.35-2.05, P<0.001), defibrillation (OR = 2.35, 95% CI=1.96-2.81, P<0.001), age (aOR = 0.99, 95% CI = 0.98-0.99, P < 0.001), closed fracture (aOR = 0.59, 95% CI = 0.53-0.66, P < 0.001), open fracture (aOR = 0.54, 95% CI = 0.48-0.61, P < 0.001), dislocation (aOR = 0.60, 95% CI = 0.45-0.81, P = 0.001), and on scene time <10 min (aOR = 0.63, 95% CI = 0.54-0.75, P < 0.001).

Conclusions: To improve survival to hospital admission in TOHCA, several factors should be prioritized. These include administering intravenous fluid boluses, controlling external bleeding, delivering defibrillation when indicated, and performing ETT.

Introduction: Identifying the people who try to hide illegal substances in the body for smuggling is of considerable importance in forensic medicine and poisoning. This study aimed to develop a new diagnostic method using artificial intelligence to detect body packs in real-time Abdominal computed tomography (CT) scans.

Methods: In this cross-sectional study, abdominal CT scan images were employed to create a machine learning-based model for detecting body packs. A single-step object detection called RetinaNet using a modified neck (Proposed Model) was performed to achieve the best results. Also, an angled Bbox (oriented bounding box) in the training dataset played an important role in improving the results.

Results: A total of 888 abdominal CT scan images were studied. Our proposed Body Packs Detection (BPD) model achieved a mean average precision (mAP) value of 86.6% when the intersection over union (IoU) was 0.5, and a mAP value of 45.6% at different IoU thresholds (from 0.5 to 0.95 in steps of 0.05). It also obtained a Recall value of 58.5%, which was the best result among the standard object detection methods such as the standard RetinaNet.

Conclusion: This study employed a deep learning network to identify body packs in abdominal CT scans, highlighting the importance of incorporating object shape and variability when leveraging artificial intelligence in healthcare to aid medical practitioners. Nonetheless, the development of a tailored dataset for object detection, like body packs, requires careful curation by subject matter specialists to ensure successful training.

Introduction: Quantitative and qualitative evaluations of the publication trends and architecture can be useful for guiding future research agendas of both researchers and journals. This study aimed to investigate the bibliometric characteristics of emergency medicine (EM) researches across different journal quartiles.

Methods: A systematic search was conducted in the Scopus database to retrieve published documents from journals in Q1 to Q4 categories (based on Scimago Journal Ranking) from inception to April 2024. The bibliometric analyses were carried out using the Visualization of Similarities viewer (VOSviewer) software.

Results: Based on author keywords analysis, we identified 7 (96 nodes), 7 (110 nodes), 6 (89 nodes), and 7 (110 nodes) clusters for Q1 to Q4 categories, respectively. The most frequent author keywords in Q1 to Q4 categories were resuscitation, trauma, COVID-19, and pediatric, respectively. Among the top 10 author keywords in Q1 to Q4 categories, cardiac arrest, disaster, burn, and trauma with average of 19.58, 9.56, 4.92, and 1.61 citations were the most cited topics.

Conclusion: This bibliometric analysis highlights that main focus of research in EM researches varies across different journal quartiles. The most commonly studied topics in EM journal categories are resuscitation, trauma, COVID-19, and pediatric.