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FAST and Stroke-112 are two campaigns to reduce the emergency room arrival time of stroke patients. No study has compared the effectiveness of these campaigns. This study aimed to compare recalling capacity of people in these two campaigns.

A prospective, open-label randomized study was conducted in 2019. Recall ability for the items of the two campaigns on the 5th and 30th days post-education was compared using non-parametric methods. Subject characteristics including age, education level, presence of stroke in co-residents, and habitual language were evaluated using multiple ordered logistic regression.

There were 202 participants in FAST group and 193 participants in Stroke-112 group who completed the study. No differences were observed between the two groups in recall ability, either on day 5 or day 30 after receiving education. For both campaigns, recall ability was better for signs in the face (FAST 87.1%, Stroke-112 86.5%) and the arm (FAST 87.1%, Stroke-112 88.1%) than for abnormality in speech (FAST 78.7%, Stroke-112 76.7%) on day 5. Recall ability on day 30 remained the same only for the arm item (FAST 86.1%, Stroke-112 88.6%). The recall ability was correlated to education level equal or more than 7 years in FAST group, and was inversely correlated to age and being a stroke patient in Stroke-112 group.

We found no difference in recall ability between the 2 campaigns. Education level was associated with recallability of FAST, and age and stroke history were associated with recallability of Stroke-112.

We found no difference in recall ability between the 2 campaigns. Education level was associated with recallability of FAST, and age and stroke history were associated with recallability of Stroke-112.Phylodynamic methods have been essential to understand the interplay between the evolution and epidemiology of infectious diseases. To date, the field has centered on viruses. Bacterial pathogens are seldom analyzed under such phylodynamic frameworks, due to their complex genome evolution and, until recently, a paucity of whole-genome sequence data sets with rich associated metadata. We posit that the increasing availability of bacterial genomes and epidemiological data means that the field is now ripe to lay the foundations for applying phylodynamics to bacterial pathogens. The development of new methods that integrate more complex genomic and ecological data will help to inform public heath surveillance and control strategies for bacterial pathogens that represent serious threats to human health.

By analyzing the epidemic characteristics of pediatric burns in a burn center serving large areas of Hubei Provence and partly surrounding provinces around Wuhan City, the aim of this study is to provide better strategies for the prevention and care for pediatric burns.

Pediatric burn patients who were younger than 13 years old in Wuhan Third Hospital from 2004 to 2018 were included. Demographic and clinical data were collected, analyzed and compared among groups.

12,661 pediatric burns, mean aged 2.37 ± 2.30 y, were admitted during the 15 years, with 7973 boys (62.97%) and 4688 girls (37.03%). By age groups, infant (<3y), preschool (>3-6y) and school children (>6-13y) accounted for 81.12% (10,270 cases), 12.08% (1530 cases) and 6.80% (861 cases) respectively. The most cause of injury was scalds (11,232, 88.71%), followed by flame burns (917, 7.24%), electric burns (201, 1.59%), contact burns (127, 1.00%), firework or firecracker (124, 0.98%), chemical burns (40, 0.32%) and hot crush injury (20point to decrease pediatric burns.

Pediatric burns in central China was still common and even increasing. Majority of the pediatric burn victims were boys under three years old, while the mean ages of different etiologies varied from about 2-6 years old. Education and prevention aiming the high risks are the key point to decrease pediatric burns.

Although two-stage exchange for chronic periprosthetic hip infections remains an effective option for infection eradication, long-term outcome reporting remains scarce. Compiling outcomes data for this standard of care is necessary to characterize long-term reinfection risk and identify bacteria associated with reinfection. The purpose of our study was to perform a systematic review to determine the long-term risk of reinfection after two-stage reimplantation. The second purpose was to identify the proportion of reinfections caused by the same or different organism(s) relative to the index infection.

We performed a systematic review of two-stage reimplantation randomized control trials, cohort studies, and case series for the treatment of periprosthetic joint infections, yielding 320 unique citations for abstract review, of which 138 were reviewed in full. We collected reinfection data including the timing of reinfection after successful reimplantation and the bacteria identified at reinfection. Meeting illow-up are needed to identify factors associated with late infections.

While the majority of two stage reimplantation literature follows patients for two years, there is significant risk of reinfection into the long term. Further studies with detailed outcomes and long-term follow-up are needed to identify factors associated with late infections.

Total hip arthroplasty (THA) for femoral neck fracture (FNF) appears to provide superior functional outcomes compared to hemiarthroplasty in selected active, elderly patients; however, the historical tradeoff has been higher risk of complications including dislocation. We aimed to describe implant survivorship and reasons for failure after THA for FNFs.

We identified 217 FNFs treated with THA from 2000 to 2017 from our institutional total joint registry (during the same time period 2039 FNFs were treated with hemiarthroplasty). Mean age was 70 years, and 65% were female. Cemented femoral components were utilized in 41%. Approach was anterolateral in 71%, posterior in 21%, and direct anterior in 8%. Dual-mobility constructs were utilized in 3%. A competing risk model accounting for death was used to analyze revisions and complications. Mean follow-up was 6 years.

The 5-year cumulative incidence of any revision was 8%. Nineteen hips were revised for the following indications postoperative periprosthetic femur fracture (6 3 uncemented stems and 3 cemented), infection (5), aseptic loosening of the femoral component (3 2 cemented and 1 uncemented), dislocation (3), iliopsoas impingement (1), and liner dissociation (1). The 5-year cumulative incidence of periprosthetic femur fractures was 7%, including 7 intraoperative fractures and 11 postoperative fractures. The 5-year cumulative incidence of dislocation was 1.4%.

The 5-year cumulative incidence of any revision after THA for FNFs was 8%, mostly attributed to periprosthetic fracture and infection. Hip instability was not as common after FNF with contemporary patient selection, techniques, and implants compared to previous series.

Prognostic, level III.

Prognostic, level III.

Periprosthetic femur fracture (PFF) remains a common reason for failure after total hip arthroplasty (THA). For over 10 years, our institution has performed both anterior approach (AA) and posterolateral (PL) approaches for primary THA with multiple stem designs. The aim of this study is to determine the 90-day relative risk of PFF with regard to approach and stem design.

A retrospective review of our institutional database was performed on all patients undergoing primary THA from 2007 to 2018 using AA or PL approaches. Five surgeons performing 6309 THAs (AA= 4510; PL= 1799) using single-wedge taper (n= 2417) or fit-and-fill (n= 3892) stems were included. PFF occurring within 90 days of the index procedure were analyzed. Differences in PFF rates, fracture location, stem type, and treatment method were assessed. PRI724 Comparisons were made using a Cox regression analysis.

The 90-day revision rate for fracture was 0.3%. Clinically significant fractures requiring cerclage cabling, stem change, revision, or open ture rates.

Our single-center experience demonstrates the risk of periprosthetic fracture within 90 days of surgery is significantly lower with collared stems and fit-and-fill stem designs. Female sex, age over 65, and body mass index below 25 nearly double the PFF risk. Surgical approach did not influence fracture rates.Looking at the urine for diagnostic purposes, once performed by ancient Egyptians, can still provide some valuable clues in modern medicine. Several diseases have been named after their associated urine color and this underlines the clinical value of visual urine inspection blue diaper disease, purple urine bag syndrome, black urine disease or porphyria. Abnormal urine color could be challenging for the clinician it may reveal neoplastic disease (urologic cancer; melanoma), cell lysis (rhabdomyolysis; hemolysis), infection (lymphatic filariasis; malaria), enzyme deficiency (porphyria; alkaptonuria), medication or food intake. In this article, we present the diagnostic approach, the mechanisms involved and the main causes of abnormal urine color.We investigate the spatiotemporal dynamics and control of an epidemic using a partial differential equation (PDE) based Susceptible-Latent-Infected-Recovered (SLIR) model. We first validate the model using empirical COVID-19 data corresponding to a period of 45 days from the state of Ohio, United States. Upon optimizing the model parameters in the learning phase of the analysis using actual infection data from a period of the first 30 days, we then find that the model output closely tracks the actual data for the next 15 days. Next, we introduce a control input into the model to represent the Non-Pharmaceutical Intervention of social distancing. Implementing the control using two distinct schemes, we find that in both cases the control input is able to significantly mitigate the infection spread. In addition to opening a novel pathway towards the characterization, analysis and implementation of Non-Pharmaceutical Interventions across multiple geographical scales using Control frameworks, our results highlight the importance of first-principles based PDE models in understanding the spatiotemporal dynamics of epidemics triggered by novel pathogens.The research on intelligent fault diagnosis has yielded remarkable achievements based on artificial intelligence-related technologies. In engineering scenarios, machines usually work in a normal condition, which means limited fault data can be collected. Intelligent fault diagnosis with small & imbalanced data (S&I-IFD), which refers to build intelligent diagnosis models using limited machine faulty samples to achieve accurate fault identification, has been attracting the attention of researchers. Nowadays, the research on S&I-IFD has achieved fruitful results, but a review of the latest achievements is still lacking, and the future research directions are not clear enough. To address this, we review the research results on S&I-IFD and provides some future perspectives in this paper. The existing research results are divided into three categories the data augmentation-based, the feature learning-based, and the classifier design-based. Data augmentation-based strategy improves the performance of diagnosis models by augmenting training data.