Fatal Occurrence Research Articles

Structural Changes in the Impact of Covid-19 Pandemic on the Performance of Financial Markets. Stock Market by Using Least Squares WHTI Breaks

The global outbreak of COVID-19 in 2020 became unprecedented and sent shockwaves through financial markets worldwide. This study investigates the impact of the pandemic on the performance of the U.S. financial market from March 1, 2020, to April 14, 2022. Utilizing Bai and Perron’s (1998) least squares with breaks during this period. The study’s test findings validate the existence of seven structural changes, signifying the occurrence of eight effects of independent factors on the S&P 500 index. The empirical findings demonstrate a substantial influence of COVID-19 pandemic on the performance of financial markets. Specifically, the impact of the number of COVID-19 cases and new fatalities on financial market performance, exhibits variations in terms of direction, nature, depth, and level. Based on an analysis of the structural changes, it can be inferred that the initial period exhibits the most pronounced negative impact on the number of new COVID-19 cases. Subsequently, the direction and nature of this impact undergo a transformation from the second to the eighth periods. Specifically, the impact of the number of new COVID-19 cases becomes positive in the second, third, sixth, seventh, and eighth periods, gradually diminishing until it reaches its lowest levels of impact in the eighth period. The research further identifies a detrimental impact on the occurrence of new fatalities. However, the periods spanning from the third to the fifth period exhibit very modest levels of influence, which then transition into a beneficial effect during the fifth period. Moreover, the research reveals that the impact of mortality rates on the performance of the United States stock market was greater than that of COVID-19 cases across all periods linked to structural changes. Additionally, the exchange rate of the dollar has a consistent and favorable impact, and the real interest rate has a pronounced negative impact, which gradually reduces over time and eventually transitions into a positive value by the eighth period.

Association of white blood cell count-to-mean platelet volume ratio with the risk of fatal stroke occurrence in older Chinese

White blood cell (WBC) and mean platelet volume (MPV) counts are related to stroke events, but relationship between their combined indicator (WBC count-to-MPV count ratio (WMR)) and the risk of fatal stroke occurrence is unclear so far. In this prospective analysis, we enrolled 27,163 participants aged 50 years or older without a stroke history in the Guangzhou Biobank Cohort Study. After a mean follow-up time of 15.0 (SD = 2.2) years with 389,242 person-years, 816 stroke (401 ischaemic, 259 haemorrhagic and 156 unclassified) deaths were recorded. Cox’s proportional hazards regression was used to estimate the hazard ratios (HRs) and the 95% confidence intervals (CIs). Compared with those in the lowest quartile, participants with the highest WMR had different risks for fatal all stroke and fatal ischaemic stroke, respectively, although an increased risk for fatal ischaemic stroke was observed among participants in the fourth WMR quartile and further hs-CRP adjustment; those in the WMR change with 10% increase had a 36% increased risk of fatal all stroke and a 79% increased risk of fatal haemorrhagic stroke, compared to those in a stable (the WMR change between −10% and 10%). Our findings suggest that higher WMR and its longitudinal change were associated with an increased risk of fatal stroke occurrence in middle-aged to older Chinese; it may be a potential indicator for the future fatal stroke occurrence in relatively healthy elderly populations.

Bayesian spatio-temporal statistical modeling of violent-related fatality in western and central Africa

Fatality arising from violent events is a critical public health problem in Africa. Although numerous studies on crime and violent events have been conducted, adequate attention has not been given to the distribution of fatalities arising from these events. This study unraveled the spatio-temporal pattern of fatality from violent events in Western and Central Africa. A two-component spatio-temporal zero-inflated model on a continuous spatial domain within a Bayesian framework was adopted. The stochastic partial differential equation was used to quantify the continuous pattern and make projections in unsampled regions. Fatality data from 1997 to 2021 was obtained from the Armed Conflict Location and Event Data Project (ACLED). Findings from the result revealed a spatial and temporal divide in the prevalence of fatality in the study region. Between the years 1997 and 2010, fatality from violence was most prevalent in Central Africa, whereas in more recent years, it was most prevalent in Western Africa. The posterior predictive probabilities of fatality occurrence due to violent events in Nigeria and Cameroon were highest and above 0.6, and the probability of more than one death per violent event is highest in Angola and Chad with probability 0.2. On violent event type, findings showed that suicide bombs had the highest likelihood of fatality occurrence whereas the event of violent non-state actors overtaking territory had the highest impact on the likelihood of multiple fatality counts. Among the armed actors who participated in violent events, armed religious groups were linked to the highest likelihood of fatality occurrence whereas Military forces were linked to the highest likelihood of multiple fatality counts per event. The finding also revealed that there is a higher likelihood of multiple fatalities in the Winter temperate season. These findings could be used for planning and policy design geared towards mitigating fatality and providing a guide towards resource distribution to support the affected communities.

Analysis of local density during football stadium access: Integrating pedestrian flow simulations and empirical data

This study analyzes numerically the access of football fans to a typical football stadium through pedestrian flow simulations. With this aim, we introduce a novel framework to address the difficulty of simulating pedestrian dynamics in highly complex geometries with multiple accesses. The framework consists of a combination of the Social Force Model (SFM) and Computational Fluid Dynamics tools to calculate multiple desired velocity maps. The introduction of this framework allows the predefinition of the desired velocity fields for the complex geometries in both the interior and surrounding area of the stadium. We validate the results of the proposed framework using actual entry-rate data from the turnstiles of three gates for 15 matches provided by the football club. Remarkably, the validation process allows us to describe the temporal evolution of the spatial distribution of pedestrians during their arrival with a single set of parameters valid for all the analyzed matches. Finally, we assess the potential fatality risk based on the local pedestrian density varying the total number of attendees and their arrival rate. The outcome evidences permanent clogs emerge at the entrance in the most extreme cases with high attendance or low standard deviation of the arrival rate, indicating the possibility of fatality occurrence.

Fatal Crash Occurrence Prediction and Pattern Evaluation by Applying Machine Learning Techniques

Background Highway safety remains a significant issue, with road crashes being a leading cause of fatalities and injuries. While several studies have been conducted on crash severity, few have analyzed and predicted specific types of crashes, such as fatal crashes. Identifying the key factors associated with fatal crashes and predicting their occurrence can help develop effective preventative measures. Objective This study intended to develop cluster analysis and ML-based models using crash data to extract the prominent factors behind fatal crash occurrences and analyze the inherent pattern of variables contributing to fatal crashes. Methods Several branches and categories of supervised ML models have been implemented for fatality prediction and their results have been compared. SHAP analysis was conducted using the ML model to explore the contributing factors of fatal crashes. Additionally, the underlying hidden patterns of fatal crashes have been evaluated using K-means clustering, and specific fatal crash scenarios have been extracted. Results The deep neural networks model achieved 85% accuracy in predicting fatal crashes in Kansas. Factors, such as speed limits, nighttime, darker road conditions, two-lane highways, highway interchange areas, motorcycle and tractor-trailer involvement, and head-on collisions were found to be influential. Moreover, the clusters were able to discern certain scenarios of fatal crashes. Conclusion The study can provide a clear image of the important factors related to fatal crashes, which can be utilized to create new safety protocols and countermeasures to reduce fatal crashes. The results from cluster analysis can facilitate transportation professionals with representative scenarios, which will benefit in identifying potential fatal crash conditions.

INVESTIGATING THE RISK FACTORS AFFECTING THE OCCURRENCE, FREQUENCY, AND SEVERITY OF LARGE TRUCK ACCIDENTS IN AL-NAJAF GOVERNORATE, IRAQ

In spite of the established literature-based evidence regarding the consequences of large truck accidents, limited body of research has been done on the characteristics and risk factors of such road accidents in Iraqi cities and governorates. According to national statistics, there has been a steady increase in the number of trucks and truck-related crashes over the past ten years. This paper aims to investigate the characteristics and risk factors associated with accidents involving large trucks in Al-Najaf governorate. A sample of 400 truck drivers were randomly selected and interviewed to collect the needed accident data. Four generalized linear models have been built; ordinal regression model for total injuries, binary logistic model for fatal accident occurrence, multinomial logit model for accident frequency, and ordinal regression model for accident cost. The analysis results revealed several influential predictors including truck driver age, education level, type of collision, truck speed, truck type, and street lighting condition. The obtained findings should be enlightening and helpful for government organizations looking to promote safety measures for sustainable freight truck transport.

An updated review on the safety of N, N-diethyl-meta-toluamide insect repellent use in children and the efficacy of natural alternatives.

N, N-diethyl-meta-toluamide (DEET) has been considered the 'gold standard' for insect repellent use since the 1950s and constitutes most insect repellents on the market. However, conflicting data in the scientific literature and confusing information in the media are at the core of debates about the safety of DEET insect repellents for the protection of children against arthropod bites. The few fatal occurrences involving DEET insect repellents and complications of their use in the pediatric population are typically the result of accidental overdoses or misuse of insect repellents that disregard warnings on product labels. With appropriate application, the safety record of DEET insect repellents continues to be excellent with few side effects. The purpose of this review is to provide a summary of the literature on safety outcomes of DEET insect repellent use in children; outline the pediatric recommendations relating to DEET insect repellents; and provide an overview of EPA-approved and naturally derived alternatives to DEET that possess low toxicity while providing a similar level of protection to synthetic insect repellents.

The Relationship Between the Atmospheric Environment and Road Traffic Fatalities - Shandong Province, China, 2012-2021.

This study aims to analyze the potential impact of the meteorological environment and air pollutants on road traffic fatalities. Road traffic fatality data in Shandong Province from 2012 to 2021 were obtained from the Population Death Information Registration Management System. Meteorological and air pollutant data for the same period were collected from the U.S. National Oceanic and Atmospheric Administration and the Ecological Environment Monitoring Center of Shandong Province, China. Pearson's correlation and ridge regression were used to analyze the impact of the meteorological environment and air pollutants on road traffic fatalities. From 2012 to 2021, there were 163,863 road traffic fatality cases. The results of the ridge regression analysis showed that the daily average temperature was negatively correlated with total fatalities and passengers and positively correlated with pedestrians, nonmotorized drivers, and motorized drivers. The daily minimum temperature was negatively correlated with total fatalities and positively correlated with motorized drivers. The daily maximum temperature was positively correlated with both pedestrian and nonmotorized drivers. The daily accumulated precipitation was negatively correlated with pedestrians. Sunshine duration was positively correlated with both nonmotorized and motorized drivers. Inhalable particulate matter (PM10) and nitrogen dioxide (NO2) were positively correlated with total fatalities, pedestrians, and nonmotorized drivers. Sulfur dioxide (SO2) was positively correlated with total fatalities but negatively correlated with nonmotorized drivers, passengers, and motorized drivers. Atmospheric factors associated with the occurrence of road traffic fatalities include air temperature, daily accumulated precipitation, sunshine duration, and air pollutants such as PM10, NO2, and SO2.

Colorimetric assay for α-amanitin based on inhibition of carbon dots/AuNPs nanoenzyme activity.

Accidental ingestion of poisonous mushrooms leading to poisoning is a global issue. The most important and lethal toxin causing mushroom poisoning is α-amanitin, with a lethal dose of about 0.1 mg kg-1. Rapid detection of wild mushrooms before consumption or rapid identification of toxins after poisoning can effectively reduce the occurrence of fatalities. This study established a method for detecting α-amanitin using carbon dots/AuNPs nanoenzymes (D-Glu-CDs/AuNPs) with robust peroxidase-like activity. This nanoenzyme was prepared employing glucose carbon dots and sodium citrate as reducing and stabilizing agents, respectively. It could oxidize the substrate TMB (tetramethylbenzidine) to produce blue o-TMB. When α-amanitin specifically bound to the active site of the nanoenzyme, a resultant decrease was observed in catalytic activity and the absorbance value at 652 nm. The regression equation Y = -0.06083x + 0.9643, with an R2 value of 0.996, was obtained. The limit of detection was determined to be 48.03 ng mL-1, and the recoveries in urine ranged from 91.2% to 97.6%. This method enabled the visualization of α-amanitin, and the whole detection process was completed within 20 min. The approach holds promise for the quantitative and qualitative determination of α-amanitin in urine samples.

ACUTE MYOCARDIAL INFARCTION IN A PUERPERA: A CASE REPORT

We report a lethal case of acute myocardial infarction in a puerpera. Cardiovascular diseases rank as the leading causes of mortality during pregnancy and the postpartum period, with myocardial infarction (MI) being a rare yet frequently fatal occurrence. Research indicates that MI typically manifests between 6 to 12 weeks postpartum, though instances may also occur at later stages. The reported case is interesting in terms of the mismatch between the timing of clinical symptoms of acute coronary syndrome (less than 24 hours) in the puerpera and alterations in myocardial infarction (2-3 days), which was diagnosed morphologically. Therefore, we searched for possible causes that led to the clinical and morphological changes described above. At first glance, the main cause of myocardial infarction development is coronary artery dissection with the formation of hematoma in the wall of the blood vessel, which narrows its lumen and leads to necrosis of the heart muscle. A brief analysis of the case has established that ischemic damage to the myocardium preceded the development of spontaneous coronary artery dissection and could be caused by one of the factors or a combination of them: coronary artery spasm caused by ergometrine and anemia due to uterine atony-related postpartum hemorrhage. The formation of intramural hematoma of the vascular wall, which narrowed the lumen of the coronary artery, could be the result of the prescription of antithrombotic therapy, which complicated the health status of the woman and led to death. When providing medical care to puerperas with postpartum hemorrhage, it is necessary to take into account the risk for cardiovascular complications that could develop due to anemia or administration of ergometrine.

Spatiotemporal analysis of fatal earthquakes between 1800 and 2015 at a global scale

Earthquakes are catastrophic natural disasters and along with their aftereffects, they have caused significant fatalities, injuries and economic losses throughout history, and have changed the landscape physically. There is a need to understand the distribution and associated damage patterns of earthquakes to be better prepared and to ensure mitigation of damage in the future. This study analyses the spatial and spatiotemporal trends of earthquake occurrence and associated fatality at a global scale over the 215-year period between 1800 and 2015. Spatial and spatiotemporal analyses revealed that certain countries in Asia including Türkiye, China, India, Pakistan and Indonesia suffered the most both in terms of fatality and earthquake occurrence. There were significant spatiotemporal clusters of earthquake occurrence over this time period on the southern half of Asia, Türkiye and southwest Europe and northern Africa. The findings of the study provide a spatial and spatiotemporal characterization of fatal earthquakes and improve our understanding of these patterns at the global scale. Spatial analyses covering longer time intervals at regional and global scales should be undertaken in future studies to provide a more comprehensive understanding of earthquake occurrence and associated damage patterns

Evaluation of ISTH Severe Bleeding Criteria and Development of a Mortality Prognosis Model for Hospitalized Immune Thrombocytopenia Patients: A Multicenter, Retrospective and Prospective Cohort Study

Introduction: Immune thrombocytopenia (ITP) is an autoimmune disorder characterized by the immune system's erroneous destruction of platelets, which play a crucial role in blood clot formation. This condition precipitates a decreased platelet count and consequently heightens the risk of bleeding events, ranging from mild petechiae to severe, potentially fatal occurrences such as intracranial hemorrhage. Therefore, accurate anticipation and management of these severe bleeding risks form an integral facet of clinical care for ITP patients. The International Society on Thrombosis and Hemostasis (ISTH) has instituted criteria designed to classify and forecast severe bleeding in patients with thrombotic disorders. Despite their widespread use in diverse clinical scenarios, the validity and efficacy of these criteria for ITP patients remain underexplored. Furthermore, disparities in the application and interpretation of these criteria among practitioners underscore the necessity for a comprehensive evaluation within the ITP context. Consequently, our study is poised to fill these crucial gaps. We intend to evaluate the performance and applicability of the ISTH severe bleeding criteria specifically within the ITP patient population. Concurrently, we aspire to develop and validate a robust, reliable mortality prediction model for this unique group of hospitalized patients. Methods: This study was a multicenter, retrospective cohort investigation conducted across 20 medical centers nationwide. A total of 1487 adult patients diagnosed with immune thrombocytopenia were enrolled. The study period spanned from Jan 2020 to Jan 2023, ensuring a comprehensive assessment of patient outcomes. To further evaluate the joint impact of multiple prognostic factors, a multivariate Cox regression model was constructed. Prospective observational cohorts were subsequently established with the objective of assessing the real-world performance of the mortality prognosis model. Results: In our study, out of the 1487 enrolled adult patients with immune thrombocytopenia (ITP), 420 patients (28.24%) experienced bleeding events. The incidence of major bleeding types among these patients was assessed based on the critical bleeding diagnostic criteria. Intracranial bleeding was found to be the most common type, occurring in 229 patients (54.46%). This was followed by respiratory compromise in 87 patients (20.66%) and hemodynamic instability bleeding in 76 patients (18.08%). Intramuscular bleeding was the least common, observed in only 3 patients (0.70%). Furthermore, we evaluated the efficacy of the ISTH severe bleeding criteria in predicting mortality among ITP patients. Our analysis unveiled a significant association between meeting the ISTH severe bleeding criteria and increased mortality rates. Patients who met the criteria demonstrated a higher incidence of death compared to those who did not meet the criteria. Additionally, we developed a mortality prognosis model for hospitalized ITP patients, incorporating various clinical and laboratory parameters. The model considered the presence of intracranial bleeding, admission platelet count, cardiovascular disease, diabetes mellitus, and admission creatinine levels as predictive factors. The mortality prognosis model demonstrated strong predictive power, with an area under the receiver operating characteristic curve of 0.82. This indicates its ability to distinguish between patients at high and low risk of mortality. Kaplan‒Meier survival analyses further confirmed significant survival differences between patients who met the ISTH severe bleeding criteria and those who did not. Conclusions: Our study reaffirms the substantial relevance of ISTH severe bleeding criteria in assessing bleeding profiles and prognosis among hospitalized ITP patients. The developed mortality prognosis model demonstrates excellent predictive capabilities for mortality in this patient population and is currently undergoing validation in a prospective cohort. These findings emphasize the importance of individualized management strategies to optimize outcomes in ITP patients. Further research and validation are warranted to refine and validate the mortality prognosis model for broader clinical application.

An empirical flood fatality model for Italy using random forest algorithm

Due to the increasing occurrence of natural hazards, such as floods, a significant number of lives are lost each year worldwide. The risk of experiencing catastrophic losses from flooding is exacerbated due to the changing climate and increasing anthropogenic activities. Consequently, predicting the conditions leading to fatalities is crucial in the assessment of flood risk. However, the existing modeling capabilities in this field are limited, emphasizing the critical need for the development of such tools. Here, we show that the occurrence of flood fatalities can be estimated using a random forest (RF) algorithm applied to nine explanatory variables characterizing each fatality. Furthermore, by converting the RF model outcomes into a user-friendly tool, it is possible to predict the probability of the occurrence of flood-related fatalities, based on variables describing hazard intensity and the environmental and sociodemographic conditions contributing to such events. Our results represent an initial attempt towards a predictive model of flood fatalities in the Italian context. They reveal the key factors that together influence flood fatalities, enabling the prediction of such occurrences. These findings can serve as a foundational framework for quantitatively assessing the risk to the population from such events and as a valuable resource for identifying strategies to mitigate flood risk.

Analysis of factors contributing to road fatalities in the Emfuleni local Municipality, South Africa

The objective of this study is to examine and analyze the many factors that contribute to the occurrence of automobile deaths within the Emfuleni Local Municipality. This study employed a hybrid analytics approach, employing a non-probability convenience sampling strategy. The researchers employed a descriptive study methodology to gather a sample of 168 participants, consisting of both traffic cops and motorists. The primary outcomes of the investigation revealed that road configuration, including small roads, hills, and sharp curves, was one of several influential elements in the occurrence of road traffic accidents (RTA). The dataset under analysis reveals that a substantial proportion of respondents possessing a standard 10/matric/grade 12 certificate had a higher level of agreement compared to those with a diploma/bachelor's degree about the primary responsibility of road layout in road traffic accidents (RTAs). The majority of participants identified stray or wild animals as a significant contributing cause to road accidents. Notably, female respondents and motorists residing in Emfuleni Municipality exhibited the highest level of agreement on this matter. Another significant contributing element was the presence of malfunctioning traffic signals, which was widely acknowledged as a causative factor in road collisions. The majority of respondents who possessed a standard 10/matric/grade 12 education exhibited the highest level of agreement. The results ultimately demonstrated that a majority of the participants concurred that a significant portion of the drivers and automobiles present on the road were not suitable for sharing the roads with other drivers, leading to the elevated occurrence of road traffic fatalities. The present circumstance necessitates prompt attention. Suggestions were proposed to provide assistance to the pertinent parties.

Chronobiology discrepancies between patients with acute type a aortic dissection complicated with and without sleep apnea syndrome: a single-center seven-year retrospective study

BackgroundThe present study aimed to investigate the differences in chronobiology and prevention between patients with acute type-A aortic dissection (ATAAD) complicated with sleep apnea syndrome (SAS) and without sleep apnea syndrome (non-SAS).MethodsWe retrospectively analyzed the clinical information of ATAAD patients using hospital medical records and regional meteorological and chronological information between January 2013 and December 2019.ResultsAn early mortality rate of 16.9% (196 out of 1160 cases) was observed, comprising 95 cases of aortic rupture before surgery and 101 surgery-related deaths. Eighty-one of the 964 survivors were screened for SAS using complete morphological characteristics. Of these patients, 291 (33.0%) suffered from SAS, while 590 (67.0%) had no SAS. Based on a Circular Von Mises distribution analysis, the non-SAS patients experienced a significant morning peak in the occurrence of ATAAD at 10:04 (r1 = 0.148, p < 0.01). In contrast, the SAS patients experienced a significantly different (non-SAS vs. SAS, U2 = 0.947, p < 0.001) nighttime peak at 23:48 (r2 = 0.489, p < 0.01). Moreover, both non-SAS (Z = 39.770, P < 0.001) and SAS (Z = 55.663, P < 0.001) patients showed a comparable peak during January (non-SAS vs. SAS, U2 = 0.173, p > 0.05). Furthermore, SAS patients experienced a peak on Fridays (χ2 = 36.419, p < 0.001), whereas there was no significant difference in the weekly distribution in non-SAS patients (χ2 = 11.315, p = 0.079).ConclusionsThe analyses showed that both SAS and non-SAS patients showed distinct rhythmicity in ATAAD onset. These findings highlight the chronobiological triggers within different ATAAD subpopulations and may contribute to the prevention of this potentially fatal occurrence.

The Prognostic Value of Creatine Kinase-MB Dynamics after Primary Angioplasty in ST-Elevation Myocardial Infarctions.

In STEMIs, the evaluation of the relationship between biomarkers of myocardial injury and patients' prognoses has not been completely explored. Increased levels of CK-MB in patients with a STEMI undergoing primary angioplasty are known to be associated with higher mortality rates, yet the correlation of these values with short-term evolution remains unknown. The research encompassed a sample of 80 patients diagnosed with STEMIs, and its methodology entailed a retrospective analysis of the data collected during their hospital stays. The study population was then categorized into three distinct analysis groups based on the occurrence or absence of acute complications and fatalities. The findings indicated that there is a notable correlation between rising levels of CK-MB upon admission and peak CK-MB levels with a reduction in left ventricular ejection fraction. Moreover, the CK-MB variation established a point of reference for anticipating complications at 388 U/L, and a cut-off value for predicting death at 354 U/L. CK-MB values are reliable indicators of the progress of patients with STEMIs. Furthermore, the difference between the peak and admission CK-MB levels demonstrates a high accuracy of predicting complications and has a significant predictive power to estimate mortality risk.

Diabetic Ketoacidosis Complications and Management in Pediatrics: A Narrative Review

Diabetic ketoacidosis (DKA) is an endocrine emergency that affects both newly diagnosed and long-term type I diabetic patients as a result of decreasing insulin levels in the blood, insulin resistance, and elevated levels of counter-regulatory hormones. A common and deadly acute consequence in kids with diabetes mellitus is diabetic ketoacidosis. When type I diabetes is newly diagnosed, it can be accompanied by diabetic ketoacidosis. It can also happen when type I diabetes is already present, such as when the demands of an acute illness are more than usual or when insulin administration is decreased as a result of missed doses or insulin pump failure. Furthermore, there are more reports of diabetic ketoacidosis events in kids with type II diabetes mellitus. Although the diagnosis is typically simple in a patient with established diabetes and the anticipated symptoms, a sizable portion of patients with new-onset diabetes initially present with diabetic ketoacidosis. Children with diabetic ketoacidosis are typically treated in an emergency room for the first time. The differential diagnosis of pediatric metabolic acidosis must take diabetic ketoacidosis into account as a significant factor. The pathogenesis, therapy, and probable consequences of this illness will be explained to emergency medicine doctors in this review) Heddy, 2021). The management of pediatric patients draws attention to the uncommon but fatal occurrence of cerebral edema and the excessive use of fluid boluses that may or may not be related to it. Guidelines for managing DKA in adults should not be applied to children and adolescents. The diagnosis of DKA is based on clinical suspicion and subsequent laboratory confirmation: Hyperglycemia (sugar level greater than 11 mmol/L): diabetes warning sign. pH 7.3 and 15 mmol/L of bicarbonate indicate metabolic acidosis. Ketosis, which may include ketonuria or ketonaemia. The severity of DKA depends on the acidity level: Mild: pH 7.3 and/or 15 mmol/L of bicarbonate; Moderate: pH 7.2 and/or 10 mmol/L of bicarbonate. Ketoacidosis associated with diabetes (DKA) Extremely severe: pH 7.1 and/or 5 mmol/L of bicarbonate. DKA can have various deadly consequences. Acute hypoglycemia (during treatment or as a result of utilizing an excessive amount of insulin pump) Cerebral edema, Acute hypokalemia, Acute hypoglycemia, Spontaneous pneumonia. A, B, and C for initial CPR If at all possible, weigh the patient and then use that weight in all calculations. Use an estimated weight from a centile chart or a weight from a recent medical visit as an alternative. Make sure the airway is open. Insert an airway if a child is unconscious (Glasgow Coma Scale Score of 8). In the event that the patient is vomiting or has a reduced level of awareness, insert NGT, aspirate, and place on free drainage. B. An oxygen-only face mask. Draw blood when an IV cannula is in place. Only if the patient is shocked (poor peripheral pulses, poor capillary filling with tachycardia, and/or hypotension) should you provide a bolus of 10 ml/kg 0.9% sodium chloride. Repeat the fluid bolus only after contacting a doctor or pediatric endocrinologist if shock symptoms continue.

Trend of traffic on inland waterways of Port Harcourt urban coastal environment: a comparative safety imperative for a Ghanaian coastal regional province

The purpose of the study is to compare mobility and access in Sub- Saharan Africa urban cities of Nigeria and Ghana by analysing trends and accident probabilities on the inland waterways to improve safety standards. Primary data from100 respondents through structured data and interview from boat and ferry operators were used. The responses were ranked on a four-point scale based on the selected routes’ average accident probabilities in percent: Very Safe {0-20}, Fairy Safe {21- 50}, Unsafe {51- 80}, and Very Unsafe {81- 100}. Secondary data from the National Inland Waterways Authority (NIWA) and Ghana Maritime Authority (GMA) and the Volta Lake Transport Company (VLTC) were subjected to probability, percentage and trend analysis. Results indicate that in the Niger delta for every journey there is approximately 59% likelihood of fatal accident; while on the Volta Lake there is a likelihood of 7% fatal accident occurrence. The trend of traffic was high in the Niger delta noticeably in the routes of Akwa- Ibom. Cross Rivers and Rivers State. The Volta Lake recorded high traffic volumes on the routes of Yeji,Tapa Abo and Bidi on market days while on non-market days, Makango. Kwamekrom and Kpechu had high passenger volumes. Estimated annual passenger traffic on the Niger delta routes outweighed that on the Volta Lake routes on a ratio of 4:1. Safety analysis further reveals that the water ways of Port Harcourt in Rivers state were unsafe for travel while the water ways of the Volta Lake were relatively safe as revealed by the average probability ratio of 8:1 in comparative terms. The log linear regression analysis reveals a price elasticity of demand for boat transport of 1.00 and 0.97 for the selected route of Port Harcourt Nigeria and Volta Lake, Ghana respectively. It further supports the fact that more passengers were responsive to travel by waterways in Nigeria than Ghana. The study concludes that waterways of Niger delta basin have high risk indices and likelihood of accident occurrence than the Volta basin; and recommends that VLTC and NIWA should invest optimally and partner with the private sector to enforce and regulate the waterways operations so as to increase safety and mobility of users of the waterways.

Rare Occipital Artery Pseudoaneurysm After Radical Neck Dissection.

Pseudoaneurysm formation in the occipital artery, post radical neck dissection, leading to a bulging mass, is a rare but potentially fatal occurrence. The authors treated a patient with pseudoaneurysm of occipital artery, post radical neck dissection, presenting with pain and swelling after 17 days of surgery. A pseudoaneurysm involving occipital artery was revealed by digital subtraction angiography and treated by endovascular micro-coil embolization.

A hybrid approach of random forest and random parameters logit model of injury severity modeling of vulnerable road users involved crashes

Vulnerable road users (VRUs) involved crashes are a major road safety concern due to the high likelihood of fatal and severe injury. The use of data-driven methods and heterogeneity models separately have limitations in crash data analysis. This study develops a hybrid approach of Random Forest based SHAP algorithm (RF-SHAP) and random parameters logit modeling framework to explore significant factors and identify the underlying interaction effects on injury severity of VRUs-involved crashes in Shenyang (China) from 2015 to 2017. The results show that the hybrid approach can uncover more underlying causality, which not only quantifies the impact of individual factors on injury severity, but also finds the interaction effects between the factors with random parameters and fixed parameters. Seven factors are found to have significant effect on crash injury severity. Two factors, including primary roads and rural areas produce random parameters. The interaction effects reveal interesting combination features. For example, even though rural areas and primary roads increase the likelihood of fatal crash occurrence individually, the interaction effect of the two factors decreases the likelihood of being fatal. The findings form the foundation for developing safety countermeasures targeted at specific crash groups for reducing fatalities in future crashes.