Query: medical  attention

title: Medical Attention Seeking After Transient Ischemic Attack and Minor Stroke Before and After the UK Face, Arm, Speech, Time (FAST) Public Education Campaign
abstract: Importance Risk of major stroke is high during the hours and days after transient ischemic attack (TIA) and minor stroke but is substantially reduced by urgent medical treatment. Public education campaigns have improved the response after major stroke, but their association with behavior after TIA and minor stroke is uncertain. The number of potentially preventable early recurrent strokes in patients who delay or fail to seek medical attention is unknown.  To investigate the association of public education with delays and failure in seeking medical attention after TIA and minor stroke.  Prospective population based study of all patients with TIA or stroke who sought medical attention between April 1, 2002, and March 31, 2014, registered at 9 general practices in Oxfordshire, United Kingdom. Data analysis took place from July 1, 2013, to March 2, 2015.  Face, Arm, Speech, Time (FAST) public education campaign in the United Kingdom.  Number of early recurrent strokes in patients who delayed or failed to seek medical attention, as well as the odds of seeking urgent attention after TIA and minor stroke before vs after initiation of the public education campaign.  Among 2243 consecutive patients with first TIA or stroke (mean [SD] age, 73.6 [13.4] years; 1126 [50.2% female; 96.3% of white race/ethnicity) 1656 (73.8% had a minor stroke or TIA. After the FAST campaign, patients with major stroke more often sought medical attention within 3 hours (odds ratio [OR] 2.56; 95% CI, 1.11 5.90; P .03) For TIA and minor stroke, there was no improvement in use of emergency medical services (OR, 0.79; 95% CI, 0.50 1.23; P for interaction .03 vs major stroke) or time to first seeking medical attention within 24 hours (OR, 0.75; 95% CI, 0.48 1.19; P for interaction .006 vs major stroke) Patient perception of symptoms after TIA and minor stroke was associated with more urgent behavior, but correct perception declined after the FAST campaign (from 37.3% [289 of 774] to 27.6% [178 of 645] OR, 0.64; 95% CI, 0.51 0.80; P .001) One hundred eighty eight patients had a stroke within 90 days of their initial TIA or stroke, of whom 93 (49.5% followed unheeded TIAs for which no medical attention was sought, similar before and after the FAST campaign (43 of 538 [8.0% before vs 50 of 615 [8.1% after, P .93)  This study suggests that in contrast to major stroke, extensive FAST based public education has not improved the response to TIA and minor stroke in the United Kingdom, emphasizing the need for campaigns that are tailored to transient and less severe symptoms.

title: Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images
abstract: We propose a novel attention gate (AG) model for medical image analysis that automatically learns to focus on target structures of varying shapes and sizes. Models trained with AGs implicitly learn to suppress irrelevant regions in an input image while highlighting salient features useful for a specific task. This enables us to eliminate the necessity of using explicit external tissue/organ localisation modules when using convolutional neural networks (CNNs) AGs can be easily integrated into standard CNN models such as VGG or U Net architectures with minimal computational overhead while increasing the model sensitivity and prediction accuracy. The proposed AG models are evaluated on a variety of tasks, including medical image classification and segmentation. For classification, we demonstrate the use case of AGs in scan plane detection for fetal ultrasound screening. We show that the proposed attention mechanism can provide efficient object localisation while improving the overall prediction performance by reducing false positives. For segmentation, the proposed architecture is evaluated on two large 3D CT abdominal datasets with manual annotations for multiple organs. Experimental results show that AG models consistently improve the prediction performance of the base architectures across different datasets and training sizes while preserving computational efficiency. Moreover, AGs guide the model activations to be focused around salient regions, which provides better insights into how model predictions are made. The source code for the proposed AG models is publicly available.

title: A Prospective Analysis of Patients Presenting for Medical Attention at a Large Electronic Dance Music Festival
abstract: Mass Gathering Medicine studies have identified variables that predict greater patient presentation rates (PPRs) and transport to hospital rates (TTHRs) This is a descriptive report of patients who presented for medical attention at an annual electronic dance music festival (EDMF) At this large, single EDMF in New York City (NYC; New York, USA) the frequency of patient presentation, the range of presentations, and interventions performed were identified. This descriptive report examined consecutive patients who presented to the medical tent of a summertime EDMF held at an outdoor venue with an active, mobile, bounded crowd. Alcohol was available for sale. Entry was restricted to persons 18 years and older. The festival occurred on three consecutive days with a total cumulative attendance of 58,000. Medical staffing included two Emergency Medicine physicians, four registered nurses, and 86 Emergency Medical Services (EMS) providers. Data collected included demographics, past medical history, vital signs, physical exam, drug and alcohol use, interventions performed, and transport decisions. Eighty four patients were enrolled over 2.5 days. Six were transported and zero died. The ages of the subjects ranged from 17 to 61 years. Forty three (51% were male. Thirty eight (45% initially presented with abnormal vital signs; four (5% were hyperthermic. Of these latter patients, 34 (90% reported ingestions with 3,4 methylenedioxymethamphetamine (MDMA) or other drugs. Eleven (65% patients were diaphoretic or mydriatic. The most common prehospital interventions were intravenous normal saline (8/84; 10% ondansetron (6/84; 7% and midazolam (3/84; 4% Electronic dance music festivals are a growing trend and a new challenge for Mass Gathering Medicine as new strategies must be employed to decrease TTHR and mortality. Addressing common and expected medical emergencies at mass gathering events through awareness, preparation, and early, focused medical interventions may decrease PPR, TTHR, and overall mortality. FriedmanMS, PlockiA, LikourezosA, PushkarI, BazosAN, FrommC, FriedmanBW. A prospective analysis of patients presenting for medical attention at a large electronic dance music festival.  2017; 32(1):78 82.

title: Factors Associated With Delays in Seeking Medical Attention in Patients With ST segment Elevation Acute Coronary Syndrome.
abstract: Prompt coronary reperfusion is crucial in patients with ST segment elevation acute coronary syndrome. The aim of this study was to determine factors associated with a delay in seeking medical attention after the onset of symptoms in patients with this condition.  Prospective cohort study in consecutive patients with ST segment elevation infarction. Multiple logistic regression analysis was used to identify factors independently associated with a longer delay in requesting medical help.  In total, 444 consecutive patients were included (mean age, 63 years; 76% men, 20% with diabetes) Median total ischemia time was 225 (160 317) minutes; median delay in seeking medical attention was 110 (51 190) minutes. Older patients (age 75 years; odds ratio 11.6) women (odds ratio 3.4) individuals with diabetes (odds ratio 2.3) and those requesting medical care from home (odds ratio 2.2) showed the longest delays in seeking medical attention. Lengthy delay was associated with higher in hospital mortality (9.8% vs 2.7% P<.005) and 1 year mortality (7.3% vs 2.9% P<.05) than when attention was promptly solicited.  Elderly patients, women, and diabetic individuals with ST segment elevation myocardial infarction show longer delays in seeking medical attention for their condition. Delays in seeking medical attention are associated with greater in hospital and 1 year mortality.

title: Incidence and risk factors of postpericardiotomy syndrome requiring medical attention: The Finland postpericardiotomy syndrome study.
abstract: Postpericardiotomy syndrome is a well known complication after cardiac surgery. Nevertheless, little is known about the incidence and predictors of postpericardiotomy syndrome requiring medical attention or hospitalization in a contemporary set of patients undergoing isolated coronary bypass.  This retrospective analysis included 688 patients from 2008 to 2010. The median follow up time was 5.3 [4.5 6.0] years.  The incidence of postpericardiotomy syndrome was 61 of 688 patients (8.9% and the median time to diagnosis was 21 [11 52] days, but only 13 patients (22% required pleural drainage and 3 patients (4.9% required pericardiocentesis. Patients with postpericardiotomy syndrome more often had 1 or more red blood cell units transfused (61% vs 43% P .008) after surgery and less often had diabetes (12% vs 31% P .002) or metformin medication (3.3% vs 20% P .001) compared with those without postpericardiotomy syndrome. In multivariable Cox regression model, renal insufficiency and 1 or more red blood cell units transfused remained as independent predictors of postpericardiotomy syndrome and diabetes remained as a protective factor. Incidence of recurrences was high (38% and increasing body mass index was the only predictor of relapse.  The incidence of symptomatic postpericardiotomy syndrome leading to medical care contact was markedly lower compared with that reported in older clinical studies. Postpericardiotomy syndrome was associated with the use of red blood cell units and was less common in patients with medically treated diabetes.

title: Medical Attention Injuries in Community Australian Football: A Review of 30 Years of Surveillance Data From Treatment Sources
abstract: In recent reports, Australian football has outranked other team sports in the frequency of hospitalizations and emergency department (ED) presentations. Understanding the profile of these and other "medical attention" injuries is vital for developing preventive strategies that can reduce health costs. The objective of this review was to describe the frequency and profile of Australian football injuries presenting for medical attention. A systematic search was carried out to identify peer reviewed articles and reports presenting original data about Australian football injuries from treatment sources (hospitals, EDs, and health care clinics) Data extracted included injury frequency and rate, body region, and nature and mechanism of injury. Following literature search and review, 12 publications were included. In most studies, Australian football contributed the greatest number of injuries out of any sport or recreation activity. Hospitals and EDs reported a higher proportion of upper limb than lower limb injuries, whereas the opposite was true for sports medicine clinics. In hospitals, fractures and dislocations were most prevalent out of all injuries. In EDs and clinics, sprains/strains were most common in adults and superficial injuries were predominant in children. Most injuries resulted from contact with other players or falling. The upper limb was the most commonly injured body region for Australian football presentations to hospitals and EDs. Strategies to prevent upper limb injuries could reduce associated public health costs. However, to understand the full extent of the injury problem in football, treatment source surveillance systems should be supplemented with other datasets, including community club based collections.

title: Multi scale guided attention for medical image segmentation
abstract: Even though convolutional neural networks (CNNs) are driving progress in medical image segmentation, standard models still have some drawbacks. First, the use of multi scale approaches, i.e. encoder decoder architectures, leads to a redundant use of information, where similar low level features are extracted multiple times at multiple scales. Second, long range feature dependencies are not efficiently modeled, resulting in nonoptimal discriminative feature representations associated with each semantic class. In this paper we attempt to overcome these limitations with the proposed architecture, by capturing richer contextual dependencies based on the use of guided self attention mechanisms. This approach is able to integrate local features with their corresponding global dependencies, as well as highlight interdependent channel maps in an adaptive manner. Further, the additional loss between different modules guides the attention mechanisms to neglect irrelevant information and focus on more discriminant regions of the image by emphasizing relevant feature associations. We evaluate the proposed model in the context of abdominal organ segmentation on magnetic resonance imaging (MRI) A series of ablation experiments support the importance of these attention modules in the proposed architecture. In addition, compared to other state of the art segmentation networks our model yields better segmentation performance, increasing the accuracy of the predictions while reducing the standard deviation. This demonstrates the efficiency of our approach to generate precise and reliable automatic segmentations of medical images. Our code and the trained model are made publicly available at: https:/github.com/sinAshish/Multi Scale Attention

title: Association between childhood allergic disease, psychological comorbidity, and injury requiring medical attention.
abstract: Children with allergic disease have multiple risk factors for accidental injuries.  To determine the prevalence of injuries requiring medical treatment in US children with allergic disease.  The authors analyzed data from the 2007 to 2008 National Survey of Children's Health, including a nationally representative sample of 27,556 children 0 to 5 years old.  The prevalence (95% confidence interval [CI] of at least 1 allergic disease was 29.4% (28.0 30.8) 6.6% (5.8 7.4) were diagnosed with asthma, 15.0% (14.0 16.0) with eczema, 11.6% (10.6 12.6) with hay fever, and 6.1% (5.4 6.9) with food allergy. Children with allergic disorders had higher odds of at least 1 comorbid psychiatric and behavioral disorder (PBD; survey logistic regression; odds ratio 2.93, 95% CI 2.13 4.03) including attention deficit/hyperactivity disorder (4.75, 2.89 7.80) depression (6.03, 1.29 28.27) anxiety (5.54, 2.70 11.37) conduct/oppositional defiant disorder (2.97, 1.88 4.70) and learning delay (2.49, 1.70 3.66) but not autism/Asperger disorder (1.89, 0.98 3.64) The prevalence of injury in the past year requiring medical attention was 10.5% (95% CI 9.5 11.4) The association between allergic disease and injury requiring medical attention was mediated in part by a PBD (Sobel test 0.0021, 95% CI 0.0014 0.0029, P .0001; bootstrapping approach, indirect effects, odds ratio 1.005, 95% CI 1.003 1.007; Baron Kenny b(yx,m) 0.04, P .0001, R(2) 0.002) However, children with at least 1 allergic disorder (1.74, 1.23 2.46) including eczema (1.59, 1.01 2.50) asthma (1.91, 1.10 3.31) hay fever (2.05, 1.24 3.39) and food allergies (2.00, 1.10 3.67) had higher odds of sustaining injuries even after controlling for comorbid PBDs and medical disorders.  The results suggest that the association between allergic disease and injury is multifactorial, including being secondary to PBD.

title: Heart attack detection and Medical attention using Motion Sensing Device Kinect
abstract: The main aim of this research paper is to illustrate the use of a device which can perform the dual function of detecting a heart attack without the intervention of any specialist for potential victim and also notify the emergency services. Stroke can be tackled if It is detected and appropriate measures are taken instantly. The research paper illustrates how a device called 'Kinect' can used to detect a heart attack and the symptoms experienced along with it. A step by step guide to its working in an event of heart attack and the how the use of GSM system and Skype feature can be used for sending an alert sms to relatives and emergency services. As well as, provides video conferencing option with doctor. Which is explained in the paper .In all the best chance for survival of a patient who experiences a heart attack and quickest medical attention can be ensured.

title: ASDNet: Attention Based Semi supervised Deep Networks for Medical Image Segmentation
abstract: Segmentation is a key step for various medical image analysis tasks. Recently, deep neural networks could provide promising solutions for automatic image segmentation. The network training usually involves a large scale of training data with corresponding ground truth label maps. However, it is very challenging to obtain the ground truth label maps due to the requirement of expertise knowledge and also intensive labor work. To address such challenges, we propose a novel semi supervised deep learning framework, called "Attention based Semi supervised Deep Networks" (ASDNet) to fulfill the segmentation tasks in an end to end fashion. Specifically, we propose a fully convolutional confidence network to adversarially train the segmentation network. Based on the confidence map from the confidence network, we then propose a region attention based semi supervised learning strategy to include the unlabeled data for training. Besides, sample attention mechanism is also explored to improve the network training. Experimental results on real clinical datasets show that our ASDNet can achieve state of the art segmentation accuracy. Further analysis also indicates that our proposed network components contribute most to the improvement of performance.