Epidemiological Pattern of Injuries in Iran; a Nationwide Review of Seven Million Emergency Department Admissions

Introduction: Globally, it is estimated that around 5.8 million people die annually as result of injuries, which causes 10% of all deaths and 16% of disability adjusted life years lost worldwide. This study aimed to determine the epidemiology of injuries in emergency departments in Iran.Method: This cross sectional study was carried out using national injury surveillance data registry from 21 March 2009 to 20 March 2014.Results: 7,176,344 patients with the mean age of 27.5 ± 17.8 years were registered to 657 EDs (70.6% male). Road Traffic Crash (RTC) was the most common cause of injury (31.0%) followed by hit (28.2%) and fall (10.1%). While roads were the commonest place of injuries, 34.0% of patients have been injured at home. More than 90% of injuries were unintentional. Assault and suicide attempt were causes of injury in 5.6% and 3.9% of patients, respectively.Conclusion:This paper addresses where prevention measures are most urgently needed and offers insights which could be useful for injury prevention programs in Iran and other developing countries

Reliability and Recalibration of the Persian Version of Cumberland Ankle Instability Tool Cut-off Score in Athletes with Functional Ankle Instability

Introduction: The Cumberland Ankle Instability Tool (CAIT) is a valid instrument for determining the presence and severity of functional ankle instability. This questionnaire was recently cross-culturally adapted into Persian; however, the reliability of the Persian version has not been examined in athletes. CAIT has also been used with various independently-selected cut-off scores to determine instability. Objective: The present study was conducted to evaluate the psychometric properties of the Persian version of CAIT and to determine its optimal cut-off score in athletic populations. Method: One-hundred and sixteen athletes (volleyball, basketball and track and field players) over 18 years old both with and without ankle instability completed the Persian version of the CAIT. The internal consistency, test-retest reliability and discriminative ability of the tool were assessed. A receiver operating characteristic (ROC) curve was drawn to confirm the cut-off point of the Persian version of CAIT using the Youden index. Results: The average CAIT score was 25.14±4.98 for the right and 25.76±4.94 for the left ankle. The Persian version of CAIT had a good internal consistency (Cronbach's α of 0.78 for the right ankle and 0.79 for the left ankle) and substantial reliability (ICC2, 1 = 0.88; 95% CI: 0.86 – 0.90) in athletes. No ceiling or floor effects were observed. The optimal cut-off score for discriminating between athletes with and without FAI was 24. Conclusion: The Persian version of CAIT was shown to be a reliable tool for assessing functional ankle instability among Iranian athletes

Reliability and Recalibration of the Persian Version of Cumberland Ankle Instability Tool Cut-off Score in Athletes with Functional Ankle Instability

Introduction: The Cumberland Ankle Instability Tool (CAIT) is a valid instrument for determining the presence and severity of functional ankle instability. This questionnaire was recently cross-culturally adapted into Persian; however, the reliability of the Persian version has not been examined in athletes. CAIT has also been used with various independently-selected cut-off scores to determine instability. Objective: The present study was conducted to evaluate the psychometric properties of the Persian version of CAIT and to determine its optimal cut-off score in athletic populations. Method: One-hundred and sixteen athletes (volleyball, basketball and track and field players) over 18 years old both with and without ankle instability completed the Persian version of the CAIT. The internal consistency, test-retest reliability and discriminative ability of the tool were assessed. A receiver operating characteristic (ROC) curve was drawn to confirm the cut-off point of the Persian version of CAIT using the Youden index. Results: The average CAIT score was 25.14±4.98 for the right and 25.76±4.94 for the left ankle. The Persian version of CAIT had a good internal consistency (Cronbach's α of 0.78 for the right ankle and 0.79 for the left ankle) and substantial reliability (ICC2, 1 = 0.88; 95% CI: 0.86 – 0.90) in athletes. No ceiling or floor effects were observed. The optimal cut-off score for discriminating between athletes with and without FAI was 24. Conclusion: The Persian version of CAIT was shown to be a reliable tool for assessing functional ankle instability among Iranian athletes

Sleepiness and Fatigue among Night - Shift Nurses with Three - Hour Nap and Day - Shift Nurses

Background: Deficiency of sleep among nurses working in shifts, results in sleepiness, fatigue, health, and safety problem, and it also can deteriorate the quality of care provision. The present study aimed to compare sleepiness and fatigue between night-shift nurses who have a 3-h nap and day-shift nurses.Methods: A prospective cohort study was done on 23 night-shift nurses with a 3-h nap and 24 day-shift nurses in Sina Hospital in Tehran (Iran) during 2015–2016. Subjective sleepiness and fatigue before and after their shifts were measured by Stanford Sleepiness Scale (SSS) and Swedish Occupational Fatigue Inventory (SOFI-20), respectively. Statistical analysis including independent t-test, Mann–Whitney test, multivariate analysis of variance, and discriminant analysis were performed to compare the two groups.Results: The difference in means of subjective sleepiness before and after the shifts was significantly greater among night-shift nurses having a 3-h nap (1.43±1.50) than the day-shift nurses (0.37±0.92) (P=0.007). Although after their working shifts, the night-shift nurses (1.40±2.30) were more fatigued than the day-shift ones (0.96±1.46), this was not statistically significant (P=0.81). Moreover, day or night shift working with a 3-h nap was an effective factor (P=0.015) while considering the interrelationship between sleepiness and fatigue in multivariate analysis. Discriminant analysis revealed the dominant role of subjective sleepiness in differentiating the two groups. Conclusions: Despite the 3-h nap, subjective sleepiness was seen more among the night-shift nurses than the day-shift ones; however, the mean difference scores of fatigue did not differ between the two groups. Presumably, getting a 3-h nap during night shift and a heavy work load for day-shift nurses might result in insignificant fatigue between the groups. Furthermore, studies with new strategies for napping among nurses are recommended

Sleepiness and Fatigue among Night - Shift Nurses with Three - Hour Nap and Day - Shift Nurses

Background: Deficiency of sleep among nurses working in shifts, results in sleepiness, fatigue, health, and safety problem, and it also can deteriorate the quality of care provision. The present study aimed to compare sleepiness and fatigue between night-shift nurses who have a 3-h nap and day-shift nurses.Methods: A prospective cohort study was done on 23 night-shift nurses with a 3-h nap and 24 day-shift nurses in Sina Hospital in Tehran (Iran) during 2015–2016. Subjective sleepiness and fatigue before and after their shifts were measured by Stanford Sleepiness Scale (SSS) and Swedish Occupational Fatigue Inventory (SOFI-20), respectively. Statistical analysis including independent t-test, Mann–Whitney test, multivariate analysis of variance, and discriminant analysis were performed to compare the two groups.Results: The difference in means of subjective sleepiness before and after the shifts was significantly greater among night-shift nurses having a 3-h nap (1.43±1.50) than the day-shift nurses (0.37±0.92) (P=0.007). Although after their working shifts, the night-shift nurses (1.40±2.30) were more fatigued than the day-shift ones (0.96±1.46), this was not statistically significant (P=0.81). Moreover, day or night shift working with a 3-h nap was an effective factor (P=0.015) while considering the interrelationship between sleepiness and fatigue in multivariate analysis. Discriminant analysis revealed the dominant role of subjective sleepiness in differentiating the two groups. Conclusions: Despite the 3-h nap, subjective sleepiness was seen more among the night-shift nurses than the day-shift ones; however, the mean difference scores of fatigue did not differ between the two groups. Presumably, getting a 3-h nap during night shift and a heavy work load for day-shift nurses might result in insignificant fatigue between the groups. Furthermore, studies with new strategies for napping among nurses are recommended

An intelligent parameter varying (IPV) approach for non-linear system identification of base excited structures

Health monitoring and damage detection strategies for base-excited structures typically rely on accurate models of the system dynamics. Restoring forces in these structures can exhibit highly non-linear characteristics, thus accurate non-linear system identification is critical. Parametric system identification approaches are commonly used, but require a priori knowledge of restoring force characteristics. Non-parametric approaches do not require this a priori information, but they typically lack direct associations between the model and the system dynamics, providing limited utility for health monitoring and damage detection. In this paper a novel system identification approach, the intelligent parameter varying (IPV) method, is used to identify constitutive non-linearities in structures subject to seismic excitations. IPV overcomes the limitations of traditional parametric and non-parametric approaches, while preserving the unique benefits of each. It uses embedded radial basis function networks to estimate the constitutive characteristics of inelastic and hysteretic restoring forces in a multi-degree-of-freedom structure. Simulation results are compared to those of a traditional parametric approach, the prediction error method. These results demonstrate the effectiveness of IPV in identifying highly non-linear restoring forces, without a priori information, while preserving a direct association with the structural dynamics

Tricuspid Annular Plane of Systolic Excursion for the Evaluation of Patients with Severe Sepsis and Septic Shock

Introduction: Sepsis is a systemic infection that can rapidly progress into multi organ failure and shock if left untreated. Previous studies have demonstrated the utility of point of care ultrasound (POCUS) in the evaluation of patients with sepsis. However, limited data exists on the evaluation of the tricuspid annular plane of systolic excursion (TAPSE) in patients with sepsis.Methods: We prospectively enrolled patients who presented to the emergency department (ED) with concern for severe sepsis or septic shock in a pilot study. In patients that screened positive, the treating physician then performed POCUS to measure the TAPSE value. We compared the intensive care unit (ICU) admission rate, hospital length of stay, and morbidity with their respective TAPSE values.Results: We enrolled 24 patients in the study. Eight patients had TAPSE values less than 16 millimeters (mm), two patients had TAPSE values between 16mm-20mm, and fourteen patients had TAPSE values greater than 20mm. There was no statistically significant association between TAPSE levels and ICU admission (p=0.16), or death (p=0.14). The difference of length of stay (LOS) was not statistically significant in case of hospital LOS (p= 0.72) or ICU LOS.Conclusion: Our pilot data did not demonstrate a correlation between severe sepsis or septic shock and TAPSE values. This may be due to several factors including patient comorbidities, strict definitions of sepsis and septic shock, as well as the absence of septic cardiomyopathy (SCM) in patients with sepsis and septic shock. Future large-scale studies are needed to determine if TAPSE can be beneficial in the ED evaluation of patients with concern for SCM

Structural health monitoring and damage detection using an intelligent parameter varying (IPV) technique

Most structural health monitoring and damage detection strategies utilize dynamic response information to identify the existence, location, and magnitude of damage. Traditional model-based techniques seek to identify parametric changes in a linear dynamic model, while non-model-based techniques focus on changes in the temporal and frequency characteristics of the system response. Because restoring forces in base-excited structures can exhibit highly non-linear characteristics, non-linear model-based approaches may be better suited for reliable health monitoring and damage detection. This paper presents the application of a novel intelligent parameter varying (IPV) modeling and system identification technique, developed by the authors, to detect damage in base-excited structures. This IPV technique overcomes specific limitations of traditional model-based and non-model-based approaches, as demonstrated through comparative simulations with wavelet analysis methods. These simulations confirm the effectiveness of the IPV technique, and show that performance is not compromised by the introduction of realistic structural non-linearities and ground excitation characteristics