Aagaardmccurdy0016

The outbreak of the SARS-CoV-2 virus responsible for the COVID-19 disease has given rise to a new disease whose boundaries are still to be discovered. While the first data suggested a purely respiratory infection, the most recent publications highlight a large pleomorphism of the disease, responsible for multiple organ damage, of which cardiac injury seems to be the most represented. This cardiac injury can present as acute myocarditis. Selleckchem SB-715992 Our aim was to discuss the pathophysiological rationale underlying the existence of SARS-CoV-2 myocarditis and to analyze the literature data regarding the diagnosis and treatment of this particular entity.Vascular access site infections are infrequent and rarely reported as a potential complication of percutaneous cardiac intervention. A case of access site infection is reported with a literature review. Femoral access is mainly concerned in some circumstances delayed sheath withdrawal, vascular complications (hematoma, false-aneurysm, arteriovenous fistula), or use of hemostatic closure device. These infectious complications are always serious requiring medical and surgical treatment and potentially associated with life-threatening complications. Preventive measures should be applied in order to reduce the risks optimisation of femoral punctures with the support of echography guidance, avoid a new puncture in a area with hematoma, femoral angiographic evaluation and strict aseptic precautions with vascular closure devices, and obviously preferential choice of radial access.The COVID-19 pandemic had an unexpected impact on cardiovascular emergencies, particularly STEMI. The France PCI registry and other studies around the world have highlighted a significant decrease in myocardial infarctions arriving at hospital. This decrease is mainly related to patients' fear of coming to the hospital and being contaminated. Although the STEMI revascularisation time targets ( less then 120min) are often difficult to achieve in normal times, they were almost impossible to achieve in periods of lockdown because of the many obstacles. Longer delays and longer total ischemic time have led to excess mortality, especially in the regions most affected by the epidemic. Recommendations for the management of STEMI during the COVID-19 period have thus been issued by the scientific societies. STEMI in patients with COVID-19 often have an uncommon clinical presentation, and the absence of coronary obstruction on angiography is frequent. Their prognosis is very poor. Only public information campaigns and an organisation adapted to the management of coronary emergencies during epidemics can try to limit their effects and avoid aggravating an already fragile health situation in the future.Multiple sclerosis [MS] is a common inflammatory, demyelinating and neurodegenerative disease of the central nervous system that affects both the brain and the spinal cord. In clinical practice, spinal cord MRI is performed far less frequently than brain MRI, mainly owing to technical limitations and time constraints. However, improvements of acquisition techniques, combined with a strong diagnosis and prognostic value, suggest an increasing use of spinal cord MRI in the near future. This review summarizes the current data from the literature on the prognostic value of spinal cord MRI in MS patients in the early and later stages of their disease. Both conventional and quantitative MRI techniques are discussed. The prognostic value of spinal cord lesions is clearly established at the onset of disease, underlining the interest of spinal cord conventional MRI at this stage. However, studies are currently lacking to affirm the prognostic role of spinal cord lesions later in the disease, and therefore the added value of regular follow-up with spinal cord MRI in addition to brain MRI. Besides, spinal cord atrophy, as measured by the loss of cervical spinal cord area, is also associated with disability progression, independently of other clinical and MRI factors including spinal cord lesions. Although potentially interesting, this measurement is not currently performed as a routine clinical procedure. Finally, other measures extracted from quantitative MRI have been established as valuable for a better understanding of the physiopathology of MS, but still remain a field of research.

Occurrence of post-dural puncture headache (PDPH) after diagnostic lumbar puncture (LP) for idiopathic intracranial hypertension (IIH) may seem very unlikely in clinical practice. Nevertheless, it has been suggested by several studies, mainly in sub-group analyses. We aimed to evaluate the prevalence of PDPH in an IIH population and determine any eventual predictive factors of PDPH occurrence.

We conducted a retrospective multiple-center observational study. All newly diagnosed IIH patients who met the International Classification of Headache Disorders (ICHD-3) or the Dandy modified criteria were included from three different French hospitals. They all underwent LP following the same process with the same type of needle. We recorded PDPH occurring within five days after LP, as defined by ICHD-3 criteria.

Seventy-four IIH patients were recruited, of whom 23 (31%) presented with PDPH. Neither classical risk factors for PDPH such as body mass index, age or gender, nor cerebrospinal fluid opening pressure, or specific IIH features were associated with occurrence of PDPH.

PDPH can occur after LP in IIH patients. Clinicians should be aware of this possible event during the IIH diagnosis assessment and should not automatically reconsider IIH diagnosis. PDPH prevention using an atraumatic needle and dedicated PDPH treatment seem relevant in IIH patients.

PDPH can occur after LP in IIH patients. Clinicians should be aware of this possible event during the IIH diagnosis assessment and should not automatically reconsider IIH diagnosis. PDPH prevention using an atraumatic needle and dedicated PDPH treatment seem relevant in IIH patients.

Providing a new tool, based on the point of view of experts in polyhandicap, which assesses the global severity of the health status of polyhandicapped persons is necessary. We present herein the initial validation of the polyhandicap severity scale (PSS).

The initial development of the tool was undertaken in two steps item selection and validation process. The final set included 10 items related to abilities and 17 items related to comorbidities and impairments. The patient selection criteria were as follows age>3 years, age at onset of cerebral lesion under 3 years old, with a combination of motor deficiency and profound intellectual impairment, associated with restricted mobility and everyday life dependence. External validity, reproducibility (20 patients), responsiveness (38 patients), and acceptability were explored.

During the 18-month study period, a total of 875 patients were included. Two scores were calculated an abilities score and a comorbidities/impairments score (higher score, higher severity). The 2 scores were higher for older patients, patients with a progressive etiology, patients with more devices and more medications, patients with higher dependency and lower mobility. link2 Indicators of reproducibility and responsiveness were satisfactory. The mean time duration of fulfilling was 22minutes (standard deviation 5).

Quantifying the health severity of polyhandicapped persons is necessary for both healthcare workers and health decision makers. The polyhandicap severity scale provides the first reliable and valid measure of the health severity status for children and adults.

Quantifying the health severity of polyhandicapped persons is necessary for both healthcare workers and health decision makers. link3 The polyhandicap severity scale provides the first reliable and valid measure of the health severity status for children and adults.

To determine if natural language processing (NLP) with machine learning of unstructured full text documents (a preoperative CT scan) improves the ability to predict postoperative complication and hospital readmission among women with ovarian cancer undergoing surgery when compared with discrete data predictors alone.

Medical records from two institutions were queried to identify women with ovarian cancer and available preoperative CT scan reports who underwent debulking surgery. Machine learning methods using both discrete data predictors (age, comorbidities, preoperative laboratory values) and natural language processing of full text reports (preoperative CT scans) were used to predict postoperative complication and hospital readmission within 30days of surgery. Discrimination was measured using the area under the receiver operating characteristic curve (AUC).

We identified 291 women who underwent debulking surgery for ovarian cancer. Mean age was 59, mean preoperative CA125 value was 610U/ml and albumin was 3.9g/dl. There were 25 patients (8.6%) who were readmitted and 45 patients (15.5%) who developed postoperative complications within 30days. Using discrete features alone, we were able to predict postoperative readmission with an AUC of 0.56 (0.54-0.58, 95% CI); this improved to 0.70 (0.68-0.73, 95% CI) (p<0.001) with the addition of NLP of preoperative CT scans.

Natural language processing with machine learning improved the ability to predict postoperative complication and hospital readmission among women with ovarian cancer undergoing surgery.

Natural language processing with machine learning improved the ability to predict postoperative complication and hospital readmission among women with ovarian cancer undergoing surgery.Only vision-based navigation is the key of cost reduction and widespread application of indoor mobile robot. Consider the unpredictable nature of artificial environments, deep learning techniques can be used to perform navigation with its strong ability to abstract image features. In this paper, we proposed a low-cost way of only vision-based perception to realize indoor mobile robot navigation, converting the problem of visual navigation to scene classification. Existing related research based on deep scene classification network has lower accuracy and brings more computational burden. Additionally, the navigation system has not yet been fully assessed in the previous work. Therefore, we designed a shallow convolutional neural network (CNN) with higher scene classification accuracy and efficiency to process images captured by a monocular camera. Besides, we proposed an adaptive weighted control (AWC) algorithm and combined with regular control (RC) to improve the robot's motion performance. We demonstrated the capability and robustness of the proposed navigation method by performing extensive experiments in both static and dynamic unknown environments. The qualitative and quantitative results showed that the system performs better compared to previous related work in unknown environments.A multi-microgrid system, including several microgrids and distributed energy resources, is always threatened by numbers of faults and attacks as a consequence of which malfunctioning can occur on a large scale. Thus, minimizing the effects of such disruptions is of paramount importance. This paper addresses the problem of mitigating a multi-microgrid system that faces false data injection and replay attacks by considering the multi-microgrid as a multi-agent system in which each microgrid as an agent represents a node in a weighted directed graph. The problem of consensus among normal agents is studied when microgrids and their communications are attacked. The malicious agents become isolated with the help of Weighted Mean Subsequence Reduced (W-MSR) algorithms in which all normal agents neglect the extreme values received from their neighbors. The proposed controller is able to maintain the system's desired performance when false data is injected into the system, or valid data is received with time-delays. Finally, numerical examples and simulation results are provided.