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The neighborhoods were grouped into 25 counties. The regional rates of EMS use varied from 18.3% to 46.5%. The final adjusted logistic model revealed that the use of EMS was significantly associated with the average number of households (neighborhood level factor) and symptoms of syncope, cardiac arrest, and history of cardiovascular disease (individual level factors).

The individual levels factors had a greater influence on the use of EMS compared to the neighborhood-level factors.

The individual levels factors had a greater influence on the use of EMS compared to the neighborhood-level factors.

The primary aim of this study was to prospectively compare the performance of the Broselow tape, Mercy method, pediatric advanced weight prediction in the emergency room extra-long (PAWPER XL) tape, and PAWPER XL mid-arm circumference (MAC) method in estimating the weight of children from a low-income setting. The secondary aim was to analyze the time taken to perform each method.

This analyzed a convenience study sample of 300 children aged 0 to 18 years at the Baragwanath Hospital in South Africa. Weight estimations were obtained using each of the weight estimation systems on each child. These weight estimations were then compared against the actual weight to determine bias, precision, and accuracy of the estimation methods.

The PAWPER XL tape and PAWPER XL-MAC methods performed the best and provided estimated weights within 10% of the actual weight in 62.7% and 67.3% of cases, respectively, followed by the Mercy method (56.5%) and Broselow tape (43.9%). The use of MAC improved the accuracy of estimation, especially in heavier and taller children. The median times taken to perform measurements using the Broselow tape, Mercy method, PAWPER XL tape, and PAWPER XL-MAC method were 11.3 seconds, 34.7 seconds, 9.3 seconds, and 33.9 seconds respectively.

The PAWPER XL tape and PAWPER XL-MAC methods were the most accurate methods of estimating weight in this group of children. These methods may be considered in preference to the Broselow tape or the Mercy method for emergency weight estimation in low socioeconomic status populations.

The PAWPER XL tape and PAWPER XL-MAC methods were the most accurate methods of estimating weight in this group of children. These methods may be considered in preference to the Broselow tape or the Mercy method for emergency weight estimation in low socioeconomic status populations.

The Trauma and Injury Severity Score (TRISS) has been used to predict trauma patient mortality and to assess the quality of trauma care systems. The goal of this investigation was to develop a modified trauma-related injury severity score (termed the TRISS-D) for predicting disability in acute trauma patients.

We used data collected by emergency medical services and entered into the Korea Centers for Disease Control and Prevention severe trauma database. The TRISS-D was based on age category (0-14, 15-54, ≥55 years), the Revised Trauma Score, and the Injury Severity Score. The outcome measures were severe disability and worsening disability. Worsening disability was defined as a lower Glasgow Outcome Scale score at hospital discharge than before the traumatic incident. buy 1-Methylnicotinamide Two types of cases were examined those with penetrating or blunt injuries (group 1) and those with severe head injuries (group 2). We assessed the discriminatory power of the TRISS-D by calculating the area under a receiver operating characteristic curve (AUROC).

The database comprised 14,791 patients; overall, 3,757 (25%) had severe disability and 6,018 (41%) had worsening disability. For severe disability, the AUROC (95% confidence interval) for the TRISS-D was 0.948 (0.944-0.952) in group 1 and 0.950 (0.946-0.954) in group 2. The corresponding values for worsening disability were 0.810 (0.803-0.817) and 0.816 (0.809-0.823), respectively.

The TRISS-D showed excellent discriminatory power for severe disability and very good discriminatory power for worsening disability.

The TRISS-D showed excellent discriminatory power for severe disability and very good discriminatory power for worsening disability.

The history, electrocardiogram, age, risk factors, troponin (HEART), the thrombolysis in myocardial infarction (TIMI), and Global Registry of Acute Coronary Events (GRACE) scores are useful risk stratification tools in the emergency department (ED). However, the accuracy of these scores in the cancer population is not well known. This study aimed to compare the performance of cardiac risk stratification scores in cancer patients with suspected acute coronary syndrome (ACS) in the ED.

This prospective cohort study recruited patients with cancer who visited the ED because of suspected ACS. The development of any major adverse cardiac events (MACE) within 6 weeks was recorded, with the study outcome being a MACE within 6 weeks of ED admission.

A total of 178 patients participated in this study, of whom 5.6% developed a MACE. Statistically significant differences were found between the mean HEART and TIMI scores in predicting MACE. The HEART score had the highest area under the curve (0.64; 95% confidence interval, 0.48-0.81), highest sensitivity (80%), and highest negative predictive value (97.5) in patients with cancer.

We found a similar rate of MACE in cancer patients with low-risk chest pain compared to that in the general population. However, the HEART, TIMI, and GRACE scores had a lower performance in cancer patients with MACE compared to that in the general population.

We found a similar rate of MACE in cancer patients with low-risk chest pain compared to that in the general population. However, the HEART, TIMI, and GRACE scores had a lower performance in cancer patients with MACE compared to that in the general population.

Rapid determination of acute coronary syndrome (ACS) in the emergency department (ED) is very important for patients presenting with ischemic symptoms. The aim of this study was to determine the predictive value of HEART score for ACS and significant coronary artery stenosis (SCS).

We retrospectively analyzed data of patients who visited the ED with chest discomfort and were admitted to the cardiology department. Enrolled patients were classified into ACS and non-ACS groups according to their discharge diagnosis. Patients who underwent imaging were further divided into SCS and non-SCS groups according to study results. We compared age, sex, vital signs, risk factors, electrocardiogram, troponin, and HEART score for each group. For ACS and SCS predictive performance, the test characteristics of HEART score was calculated using sensitivity, specificity, predictive value, likelihood ratio, and receiver operating characteristic (ROC) curve analysis.

Of 207 patients, 112 had ACS. Among enrolled patients, 155 underwent imaging workup, of whom 67 had SCS.