Bush animal attacks: management of complex injuries in a resource-limited setting

Though animal-related injuries and fatalities have been documented throughout the world, the variety of attacks by wild animals native to rural East Africa are less commonly described. Given the proximity of our northwestern Tanzania hospital to Lake Victoria, Lake Tanganyika, and the Serengeti National Park, and presentation of several patients attacked by bush animals and suffering a variety of complex injuries, we sought to report the pattern of attacks and surgical management in a resource-limited setting. Four patients who were admitted to the northwestern Tanzania tertiary referral hospital, Bugando Medical Centre (BMC), in 2010-2011 suffered attacks by different bush animals: hyena, elephant, crocodile, and vervet monkey. These patients were triaged as trauma patients in the Casualty Ward, then admitted for inpatient monitoring and treatment. Their outcomes were followed to discharge. The age and gender of the patients attacked was variable, though all but the pediatric patient were participating in food gathering or guarding activities in rural locations at the time of the attacks. All patients required surgical management of their injuries, which included debridement and closure of wounds, chest tube insertion, amputation, and external fixation of an extremity fracture. All patients survived and were discharged home. Though human injuries secondary to encounters with undomesticated animals such as cows, moose, and camel are reported, they often are indirect traumas resulting from road traffic collisions. Snake attacks are well documented and common. However, this series of unique bush animal attacks describes the initial and surgical management of human injuries in the resource-limited setting of the developing world. Animal attacks are common throughout the world, but their pattern may vary in Africa throughout jungle and bush environmental settings. It is important to understand the management of these attacks in resource-limited health care environment. Further, the growing population and human encroachment on previously wild habitats such as the northwestern Tanzania bush argues for increased community awareness to assist in prevention of human injuries by animals

Improved Otsu and Kapur approach for white blood cells segmentation based on LebTLBO optimization for the detection of Leukemia.

The diagnosis of leukemia involves the detection of the abnormal characteristics of blood cells by a trained pathologist. Currently, this is done manually by observing the morphological characteristics of white blood cells in the microscopic images. Though there are some equipment- based and chemical-based tests available, the use and adaptation of the automated computer vision-based system is still an issue. There are certain software frameworks available in the literature; however, they are still not being adopted commercially. So there is a need for an automated and software- based framework for the detection of leukemia. In software-based detection, segmentation is the first critical stage that outputs the region of interest for further accurate diagnosis. Therefore, this paper explores an efficient and hybrid segmentation that proposes a more efficient and effective system for leukemia diagnosis. A very popular publicly available database, the acute lymphoblastic leukemia image database (ALL-IDB), is used in this research. First, the images are pre-processed and segmentation is done using Multilevel thresholding with Otsu and Kapur methods. To further optimize the segmentation performance, the Learning enthusiasm-based teaching-learning-based optimization (LebTLBO) algorithm is employed. Different metrics are used for measuring the system performance. A comparative analysis of the proposed methodology is done with existing benchmarks methods. The proposed approach has proven to be better than earlier techniques with measuring parameters of PSNR and Similarity index. The result shows a significant improvement in the performance measures with optimizing threshold algorithms and the LebTLBO technique

Temporal Trends in Incidence, Prevalence, and Mortality of Atrial Fibrillation in Primary Care

Background Incidence and prevalence of atrial fibrillation ( AF ) are expected to increase dramatically; however, we currently lack comprehensive data on temporal trends in unselected clinical populations. Methods and Results Analysis of the UK Clinical Practice Research Datalink ( CPRD ) from 1998 to 2010 of patients with incident AF , excluding major valvular disease, linked to hospital admission data and national statistics. Fifty‐seven thousand eight hundred eighteen adults were identified with mean age 74.2 ( SD , 11.7) years and 48.3% women. Overall age‐adjusted incidence of AF per 1000 person years was 1.11 (95% CI , 1.09–1.13) in 1998–2001, 1.33 (1.31–1.34) in 2002–2006, and 1.33 (1.31–1.35) in 2007–2010. Ongoing increases in incidence were noted for patients aged ≥75 years, with similar temporal patterns in women and men. Associated comorbidities varied over time, with a constant prevalence of previous stroke, increases in hypertension and diabetes mellitus, and decreases in ischemic heart disease. Among patients aged 55 to 74 years, there was a significant reduction in mortality over time ( P &lt;0.001), but mortality rates in patients aged ≥75 years remained static at 14% to 15% per year ( P =0.84). Projections of AF prevalence demonstrated a constant yearly rise, increasing from 700 000 patients in 2010 to between 1.3 and 1.8 million patients with AF in the United Kingdom by 2060. Conclusions In a large general practice population, incident AF increased and then plateaued overall, with a continued increase in patients aged ≥75 years. The large projected increase in AF prevalence associated with temporal changes in AF ‐related comorbidities suggests the need for comprehensive implementation of AF prevention and management strategies. </jats:sec

Behavior prediction of traffic actors for intelligent vehicle using artificial intelligence techniques: A review

Intelligent vehicle technology has made tremendous progress due to Artificial Intelligence (AI) techniques. Accurate behavior prediction of surrounding traffic actors is essential for the safe and secure navigation of the intelligent vehicle. Minor misbehavior of these vehicles on the busy roads may lead to an accident. Due to this, there is a need for vehicle behavior research work in today's era. This research article reviews traffic actors' behavior prediction techniques for intelligent vehicles to perceive, infer, and anticipate other vehicles' intentions and future actions. It identifies the key strategies and methods for AI, emerging trends, datasets, and ongoing research issues in these fields. As per the authors' knowledge, this is the first systematic literature review dedicated to the vehicle behavior study examining existing academic literature published by peer review venues between 2011 and 2021. A systematic review was undertaken to examine these papers, and five primary research questions have been addressed. The findings show that using sophisticated input representation that includes traffic rules and road geometry, artificial intelligence-based solutions applied to behavior prediction of traffic actors for intelligent vehicles have shown promising success, particularly in complex driving scenarios. Finally, the paper summarizes the most widely used approaches in behavior prediction of traffic actors for intelligent vehicles, which the authors believe serves as a foundation for future research in behavior prediction of surrounding traffic actors for secure and accurate intelligent vehicle navigation

ADMT: Advanced driver's movement tracking system using spatio-temporal interest points and maneuver anticipation using deep neural networks

Assistive driving is a complex engineering problem and is influenced by several factors such as the sporadic nature of the quality of the environment, the response of the driver, and the standard of the roads on which the vehicle is being driven. The authors track the driver's anticipation based on his head movements using Spatio-Temporal Interest Point (STIP) extraction and enhance the anticipation of action accuracy well before using the RNN-LSTM framework. This research tackles a fundamental problem of lane change assistance by developing a novel model called Advanced Driver's Movement Tracking (ADMT). ADMT uses customized convolution-based deep learning networks by using Recurrent Convolutional Neural Network (RCNN). STIP with eye gaze extraction and RCNN performed in ADMT on brain4cars dataset for driver movement tracking. Its performance is compared with the traditional machine learning and deep learning models, namely Support Vector Machines (SVM), Hidden Markov Model (HMM), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and provided an increment of almost 12% in the prediction accuracy and 44% in the anticipation time. Furthermore, ADMT systems outperformed all of the models in terms of both the accuracy of the system and the previously mentioned time of anticipation that is discussed at length in the paper. Thus it assists the driver with additional anticipation time to access the typical reaction time for better preparedness to respond to undesired future behavior. The driver is then assured of a safe and assisted driving experience with the proposed system

Glaucoma detection: the content of optometric eye examinations for a presbyopic patient of African racial descent

Aims: Standardised patient (SP) methodology is the gold standard for evaluating clinical practice. We investigated the content of optometric eyecare for an early presbyopic SP of African racial descent, an “at-risk” patient group for primary open-angle glaucoma (POAG). Methods: A trained actor presented unannounced as a 44-year-old patient of African racial descent, complaining of recent near vision difficulties, to 100 community optometrists for an audio-recorded eye examination. The eye examinations were subsequently assessed via a checklist based on evidence-based POAG reviews, clinical guidelines and expert panel opinion. Results: Ninety-five per cent of optometrists carried out optic disc assessment and tonometry, which conforms to the UK College of Optometrists’ advice that those patients aged >40 years should receive at least two of the following tests: tonometry, optic disc assessment, visual field testing. Thirty-five per cent of optometrists carried out all of these tests and 6% advised the SP of increased POAG risk in those of African racial descent. Conclusion: SP encounters are an effective measure of optometric clinical practice. As in other healthcare disciplines, there are substantial differences between optometrists in the depth of their clinical investigations, challenging the concept of a “standard sight test”. There is a need for continuing professional development (CPD) in glaucoma screening, in which the increased risk of POAG in those of African racial descent should be emphasised

Impact of Renal Impairment on Beta-Blocker Efficacy in Patients With Heart Failure.

BACKGROUND: Moderate and moderately severe renal impairment are common in patients with heart failure and reduced ejection fraction, but whether beta-blockers are effective is unclear, leading to underuse of life-saving therapy. OBJECTIVES: This study sought to investigate patient prognosis and the efficacy of beta-blockers according to renal function using estimated glomerular filtration rate (eGFR). METHODS: Analysis of 16,740 individual patients with left ventricular ejection fraction <50% from 10 double-blind, placebo-controlled trials was performed. The authors report all-cause mortality on an intention-to-treat basis, adjusted for baseline covariates and stratified by heart rhythm. RESULTS: Median eGFR at baseline was 63 (interquartile range: 50 to 77) ml/min/1.73 m2; 4,584 patients (27.4%) had eGFR 45 to 59 ml/min/1.73 m2, and 2,286 (13.7%) 30 to 44 ml/min/1.73 m2. Over a median follow-up of 1.3 years, eGFR was independently associated with mortality, with a 12% higher risk of death for every 10 ml/min/1.73 m2 lower eGFR (95% confidence interval [CI]: 10% to 15%; p < 0.001). In 13,861 patients in sinus rhythm, beta-blockers reduced mortality versus placebo; adjusted hazard ratio (HR): 0.73 for eGFR 45 to 59 ml/min/1.73 m2 (95% CI: 0.62 to 0.86; p < 0.001) and 0.71 for eGFR 30 to 44 ml/min/1.73 m2 (95% CI: 0.58 to 0.87; p = 0.001). The authors observed no deterioration in renal function over time in patients with moderate or moderately severe renal impairment, no difference in adverse events comparing beta-blockers with placebo, and higher mortality in patients with worsening renal function on follow-up. Due to exclusion criteria, there were insufficient patients with severe renal dysfunction (eGFR <30 ml/min/1.73 m2) to draw conclusions. In 2,879 patients with atrial fibrillation, there was no reduction in mortality with beta-blockers at any level of eGFR. CONCLUSIONS: Patients with heart failure, left ventricular ejection fraction <50% and sinus rhythm should receive beta-blocker therapy even with moderate or moderately severe renal dysfunction

Gender differences in clinical presentation and 1-year outcomes in atrial fibrillation

Objectives Our objective was to examine gender differences in clinical presentation, management and prognosis of atrial fibrillation (AF) in a contemporary cohort. Methods In 6412 patients, 39.7% women, of the PREvention oF thromboembolic events – European Registry in Atrial Fibrillation, we examined gender differences in symptoms, risk factors, therapies and 1-year incidence of adverse outcomes. Results Men with AF were on average younger than women (mean±SD: 70.1±10.7 vs 74.1±9.7 years, p&lt;0.0001). Women more frequently had at least one AF-related symptom at least occasionally compared with men (95.4% in women, 89.8% in men, p&lt;0.0001). Prescription of oral anticoagulation was similar, with an increase of non-vitamin K antagonist oral anticoagulants from 5.9% to 12.6% in women and from 6.2% to 12.6% in men, p&lt;0.0001 for both. Men were more frequently treated with electrical cardioversion and ablation (20.6% and 6.3%, respectively) than women (14.9% and 3.3%, respectively), p&lt;0.0001. Women had 65% (OR: 0.35; 95% CI (0.22 to 0.56)) lower age-adjusted and country-adjusted odds of coronary revascularisation, 40% (OR: 0.60; (0.38 to 0.93)) lower odds of acute coronary syndrome and 20% (OR: 0.80; (0.68 to 0.96)) lower odds of heart failure at 1 year. There were no statistically significant gender differences in 1-year stroke/transient ischaemic attack/arterial thromboembolism and major bleeding events. Conclusion In a ‘real-world’ European AF registry, women were more symptomatic but less likely to receive invasive rhythm control therapy such as electrical cardioversion or ablation. Further study is needed to confirm that these differences do not disadvantage women with AF

A population-based study of 92 clinically recognised risk factors for heart failure: co-occurrence, prognosis and preventive potential

BACKGROUND: Primary prevention strategies for heart failure(HF) have had limited success, possibly due to a wide range of underlying risk factors(RFs). Systematic evaluations of the prognostic burden and preventive potential across this wide range of risk factors are lacking. OBJECTIVE: To estimate evidence, prevalence and co-occurrence for primary prevention and impact on prognosis of RFs for incident HF. METHODS: We systematically reviewed trials and observational evidence of primary HF prevention across 92 putative aetiologic RFs for HF identified from US and European clinical practice guidelines. We identified 170 885 individuals aged ≥30 years with incident HF from 1997-2017, using linked primary and secondary care UK electronic health records(EHR) and rule-based phenotypes(ICD-10, Read Version 2, OPCS-4 procedure and medication codes) for each of 92 RFs. RESULTS: Only 10/92 factors had high quality observational evidence for association with incident HF; 7 had effective RCT-based interventions for HF prevention(RCT-HF), and 6 for CVD prevention, but not HF(RCT-CVD), and the remainder had no RCT-based preventive interventions(RCT-0). We were able to map 91/92 risk factors to EHR using 5961 terms, and 88/91 factors were represented by at least one patient. In the 5 years prior to HF diagnosis, 44.3% had ≥4 RFs. By RCT evidence, the most common RCT-HF RFs were hypertension(48.5%), stable angina(34.9%), unstable angina(16.8%), myocardial infarction(15.8%), and diabetes(15.1%); RCT-CVD RFs were smoking(46.4%) and obesity(29.9%); and RCT-0 RFs were atrial arrhythmias(17.2%), cancer(16.5%),), heavy alcohol intake(14.9%). Mortality at 1 year varied across all 91 factors(lowest: pregnancy-related hormonal disorder 4.2%; highest: phaeochromocytoma 73.7%). Among new HF cases, 28.5% had no RCT-HF RFs and 38.6% had no RCT-CVD RFs. 15.6% had either no RF or only RCT-0 RFs. CONCLUSION: 1 in 6 individuals with HF have no recorded RFs or RFs without trials. We provide a systematic map of primary preventive opportunities across a wide range of RFs for HF, demonstrating a high burden of co-occurrence and the need for trials tackling multiple RFs