Assessment of Jordanian physicians' knowledge about venous thromboembolism risk and management among COVID-19 patients

Objectives: The aim of this study was to assess Jordanian physicians' awareness about venous thromboembolism (VTE) risk among COVID-19 patients and its treatment protocol. Method(s): This was a cross-sectional-based survey that was conducted in Jordan in 2020. During the study period, a convenience sample of physicians working in various Jordanian hospitals were invited to participate in this study. Physicians' knowledge was evaluated and physicians gained one point for each correct answer. Then, a knowledge score out of 23 was calculated for each. Key Findings: In this study, 102 physicians were recruited. Results from this study showed that most of the physicians realize that all COVID-19 patients need VTE risk assessment (n = 69, 67.6%). Regarding VTE prophylaxis, the majority of physicians (n = 91, 89.2%) agreed that low molecular weight heparin (LMWH) is the best prophylactic option for mild-moderate COVID-19 patients with high VTE risk. Regarding severe/critically ill COVID-19 patients, 75.5% of physicians (n = 77) recognized that LMWH is the correct prophylactic option in this case, while 80.4% of them (n = 82) knew that mechanical prevention is the preferred prophylactic option for severe/critically ill COVID-19 patients with high bleeding risk. Moreover, 77.5% of physicians (n = 79) knew that LMWH is the treatment of choice for COVID-19 patients diagnosed with VTE. Finally, linear regression analysis showed that consultants had an overall higher knowledge score about VTE prevention and treatment in COVID-19 patients compared with residents (P = 0.009). Conclusion(s): All physicians knew about VTE risk factors for COVID-19 patients. However, consultants showed better awareness of VTE prophylaxis and treatment compared with residents. We recommend educational workshops be conducted to enhance physicians' knowledge and awareness about VTE thromboprophylaxis and management in COVID-19 patients.Copyright © 2022 The Author(s). Published by Oxford University Press on behalf of the Royal Pharmaceutical Society. All rights reserved.

Time is not the same for everyone. How covid-19 changed social acceleration in neoliberal society

This paper is a personal attempt to rethink critically the social impact of the Covid-19 pandemic, trying to discuss about some changes, which came out in that tragic period, in the way of living time and space. There are several ways in which the COVID-19 pandemic has affected these two main structural dimensions of society and the response strategies used by people, groups, and social organizations, depending on the geographical area. There are trends that have had a highly differentiated impact, which have shown that the concept of time is not the same for everyone. Other trends have had a transversal impact, reconfiguring the ideas of present and future. Precariousness and uncertainty, that coincide with an existential specific condition of our contemporary, now take on a new meaning. Before the pandemic, the neoliberal development model seemed to have no alternative. Now, the possibility of an alternative model is imaginable, not only for the critics of it, but also for a large part of public opinion, which now even considers it necessary. The possibility of an alternative becomes concrete and achievable due to the impact that the Covid-19 pandemic has had on the structural dimensions of time and space in social life.

COVID-19-Related Encephalitis in a Child with PIK3CD Defect

Introduction: COVID-19 related encephalitis has been reported in pediatric patients;however, there are no reports in patients with inborn errors of immunity (IEI). Activated PI3K Delta Syndrome (APDS) is a disease of immune dysregulation with immunodeficiency, autoimmunity, and abnormal lymphoproliferation resulting from autosomal dominant gain-offunction variants in PIK3CD or PIK3R1 genes. We investigate a family with APDS, one mother and three children, one of whom developed COVID-19 related encephalitis. Method(s): Patients were consented to an IRB-approved protocol at our institution. Medical records and detailed immunophenotyping were reviewed. Family members were sequenced for IEI with a targeted gene panel. Result(s): The index case is a 10-year-old female with a known pathogenic variant in PIK3CD (c.3061 G > A, p.Glu1021Lys), who contracted SARS-COV-2 despite one COVID-19 vaccination in the series. Her disease course included COVID-related encephalitis with cerebellitis and compression of the pons, resulting in lasting truncal ataxia and cerebellar mutism. At that time, the patient was not on immunoglobulin replacement therapy (IgRT), but was receiving Sirolimus. Besides the index case, 3 family members (2 brothers, 1 mother) also share the same PIK3CD variant with variable clinical and immunological phenotypes. All children exhibited high transitional B-cells, consistent with developmental block to follicular B cell stage. Increased non-class switched IgM+ memory B cells and skewing towards CD21lo B cell subset, which is considered autoreactive-like, was observed in all patients. Of note, the patient had low plasmablasts, but normal immunoglobulins. Of her family members, only one was receiving both sirolimus and IgRT. Conclusion(s): We describe a rare case of COVID-19-related encephalitis in a patient with inborn error of immunity while not on IgRT. This may indicate infection susceptibility because of a lack of sufficient immunity to SARS-CoV-2, unlike the rest of her family with the same PIK3CD variant.Copyright © 2023 Elsevier Inc.

Orchestrating Image Retrieval and Storage Over a Cloud System

Since massive numbers of images are now being communicated from, and stored in different cloud systems, faster retrieval has become extremely important. This is more relevant, especially after COVID-19 in bandwidth-constrained environments. However, to the best of our knowledge, a coherent solution to overcome this problem is yet to be investigated in the literature. In this article, by customizing the Progressive JPEG method, we propose a new Scan Script to ensure Faster Image Retrieval. Furthermore, we also propose a new lossy PJPEG architecture to reduce the file size as a solution to overcome our Scan Script's drawback. In order to achieve an orchestration between them, we improve the scanning of Progressive JPEG's picture payloads to ensure Faster Image Retrieval using the change in bit pixels of distinct Luma and Chroma components ([Formula Omitted], [Formula Omitted], and [Formula Omitted]). The orchestration improves user experience even in bandwidth-constrained cases. We evaluate our proposed orchestration in a real-world setting across two continents encompassing a private cloud. Compared to existing alternatives, our proposed orchestration can improve user waiting time by up to 54% and decrease image size by up to 27%. Our proposed work is tested in cutting-edge cloud apps, ensuring up to 69% quicker loading time.

One-Year Long-Term Follow up for Post-Acute Sequelae of Covid-19 Pots Patients

Background: Persistence of orthostatic tachycardia, palpitations, and fatigue beyond 4 weeks of an acute COVID-19 infection has been termed Post-Acute Sequelae of COVID-19 (PASC) POTS. We have previously reported 6-month outcomes of PASC POTS. Long-term management and outcomes of these patients is unknown. Objective(s): To examine the long-term management and outcomes of PASC POTS patients. Method(s): We conducted a retrospective study of all patients who were diagnosed with POTS at Cardiology, Neurology, and Rehabilitation Post-COVID clinic after a COVID-19 infection between March 1, 2020, and November 1, 2022, at the University of Texas Health San Antonio. We examined COVID history, POTS diagnosis, management, and one-year outcomes of post-COVID POTS patients. Result(s): In 42 patients that were diagnosed with PASC POTS, 33 had a one-year follow-up. 100% were female, 60.6% were Caucasian. Average age was 40.6 + 11 years while the average BMI was 31.9 + 10.4 kg/m2. The most common symptoms were fatigue (87.9%), palpitations (75.7%), brain fog (72.7%), orthostatic tachycardia, exercise intolerance, and dyspnea (70%). The mean heart rate change with 10-minute standing test was 42.68 + 26.73 beats per minute. At 12-months follow-up, the most common symptom was still fatigue (66.7%), palpitations (45.5%), orthostatic tachycardia, and orthostatic intolerance (42.4%). All patients were managed with increased salt and fluid intake, lower compression stockings and rehabilitation. Fifty five percent of patients were treated with Enhanced External Counter Pulsation (EECP), 42% were treated with beta blockers, 18% with fludrocortisone, 15% with midodrine, and 15% with Pyridostigmine. At 1 year follow-up, 33% of patients reported improvement in their symptoms, 33% reported worsening of symptoms, 24% reported stable symptoms, and 9% had resolution. Conclusion(s): PASC POTS patients continue to experience adverse symptoms even at one year. Physical therapy and rehabilitation and pharmacological therapy appear improve symptoms in a minority of patients.Copyright © 2023

Efficient intelligent compression and recognition system-based vision computing for computed tomography COVID images

Computed tomography (CT) image-based medical recognition is extensively used for COVID recognition as it improves recognition and scanning rate. A method for intelligent compression and recognition system-based vision computing for CT COVID (ICRS-VC-COVID) was developed. The proposed system first preprocesses lung CT COVID images. Segmentation is then used to split the image into two regions: nonregion of interest (NROI) with fractal lossy compression and region of interest with context tree weighting lossless. Subsequently, a fast discrete curvelet transform (FDCT) is applied. Finally, vector quantization is implemented through the encoder, channel, and decoder. Two experiments were conducted to test the proposed ICRS-VC-COVID. The first evaluated the segmentation compression, FDCT, wavelet transform, and discrete curvelet transform (DCT). The second evaluated the FDCT, wavelet transform, and DCT with segmentation. It demonstrates a significant improvement in performance parameters, such as mean square error, peak signal-to-noise ratio, and compression ratio. At similar computational complexity, the proposed ICRS-VC-COVID is superior to some existing techniques. Moreover, at the same bit rate, it significantly improves the quality of the image. Thus, the proposed method can enable lung CT COVID images to be applied for disease recognition with low computational power and space. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. [DOI: 10.1117/1.JEI.32.2.021404] © 2023 SPIE. All rights reserved.

Prevalence of impaired upper extremity neural mobility among smart device users during the COVID-19 pandemic.

BACKGROUND: Both the development of various countries and people's health were impacted by the unforeseen global COVID-19 outbreak. Many countries prefer to do their daily business online. Although it was incredibly useful at the time, it still had a problem that was not properly addressed, especially among the student population. OBJECTIVE: The objective of this study was to examine the prevalence of upper extremity neural mobility among students who were using smart devices during the COVID-19 pandemic. METHODS: 458 students who had previously taken home-based online classes during the COVID-19 pandemic and used a smart device for more than six hours were included in this study. The study was conducted in three phases. After being examined in the first two stages of the study, a total of 72 people were chosen for the final phase. Peripheral nerve mobility tests were performed on these 72 subjects. RESULTS: This study observed that 15.72% of smart device users have been affected by forward neck posture and impaired peripheral nerve mobility in the cervical spine. CONCLUSION: The study concludes that forward neck posture is associated with impaired peripheral nerve mobility among smart device users who were in home-based online classes during the COVID-19 pandemic lockdown. Hence, we suggest an appropriate treatment strategy focusing on preventing the forward neck posture through timely analysis and self-care therapies.

Impact of COVID-19-adapted guidelines using different airway management strategies on resuscitation quality in out-of-hospital-cardiac-arrest - a randomised manikin study.

BACKGROUND: Although airway management for paramedics has moved away from endotracheal intubation towards extraglottic airway devices in recent years, in the context of COVID-19, endotracheal intubation has seen a revival. Endotracheal intubation has been recommended again under the assumption that it provides better protection against aerosol liberation and infection risk for care providers than extraglottic airway devices accepting an increase in no-flow time and possibly worsen patient outcomes. METHODS: In this manikin study paramedics performed advanced cardiac life support with non-shockable (Non-VF) and shockable rhythms (VF) in four settings: ERC guidelines 2021 (control), COVID-19-guidelines using videolaryngoscopic intubation (COVID-19-intubation), laryngeal mask (COVID-19-Laryngeal-Mask) or a modified laryngeal mask modified with a shower cap (COVID-19-showercap) to reduce aerosol liberation simulated by a fog machine. Primary endpoint was no-flow-time, secondary endpoints included data on airway management as well as the participants' subjective assessment of aerosol release using a Likert-scale (0 = no release-10 = maximum release) were collected and statistically compared. Continuous Data was presented as mean ± standard deviation. Interval-scaled Data were presented as median and Q1 and Q3. RESULTS: A total of 120 resuscitation scenarios were completed. Compared to control (Non-VF:11 ± 3 s, VF:12 ± 3 s) application of COVID-19-adapted guidelines lead to prolonged no-flow times in all groups (COVID-19-Intubation: Non-VF:17 ± 11 s, VF:19 ± 5 s;p ≤ 0.001; COVID-19-laryngeal-mask: VF:15 ± 5 s,p ≤ 0.01; COVID-19-showercap: VF:15 ± 3 s,p ≤ 0.01). Compared to COVID-19-Intubation, the use of the laryngeal mask and its modification with a showercap both led to a reduction of no-flow-time(COVID-19-laryngeal-mask: Non-VF:p = 0.002;VF:p ≤ 0.001; COVID-19-Showercap: Non-VF:p ≤ 0.001;VF:p = 0.002) due to a reduced duration of intubation (COVID-19-Intubation: Non-VF:40 ± 19 s;VF:33 ± 17 s; both p ≤ 0.01 vs. control, COVID-19-Laryngeal-Mask (Non-VF:15 ± 7 s;VF:13 ± 5 s;p > 0.05) and COVID-19-Shower-cap (Non-VF:15 ± 5 s;VF:17 ± 5 s;p > 0.05). The participants rated aerosol liberation lowest in COVID-19-intubation (median:0;Q1:0,Q3:2;p < 0.001vs.COVID-19-laryngeal-mask and COVID-19-showercap) compared to COVID-19-shower-cap (median:3;Q1:1,Q3:3 p < 0.001vs.COVID-19-laryngeal-mask) or COVID-19-laryngeal-mask (median:9;Q1:6,Q3:8). CONCLUSIONS: COVID-19-adapted guidelines using videolaryngoscopic intubation lead to a prolongation of no-flow time. The use of a modified laryngeal mask with a shower cap seems to be a suitable compromise combining minimal impact on no-flowtime and reduced aerosol exposure for the involved providers.

An effective ECG signal compression algorithm with self controlled reconstruction quality.

Electrocardiogram (ECG) signals are frequently used in the continuous monitoring of heart patients. These recordings generate huge data, which is difficult to store or transmit in telehealth applications. In the above context, this work proposes an efficient novel compression algorithm by integrating the tunable-Q wavelet transform (TQWT) with coronavirus herd immunity optimizer (CHIO). Additionally, this algorithm facilitates the self-adaptive nature to regulate the reconstruction quality by limiting the error parameter. CHIO is a human perception-based algorithm, used to select optimum TQWT parameters, where decomposition level of TQWT is optimized for the first time in the field of ECG compression. The obtained transform coefficients are then thresholded, quantized, and encoded to improve the compression further. The proposed work is tested on MIT-BIH arrhythmia database. The compression and optimization performance using CHIO is also compared with well-established optimization algorithms. The compression performance is measured in terms of compression ratio, signal-to-noise ratio, percent root mean square difference, quality score, and correlation coefficient.

Different weathering conditions affect the release of microplastics by masks.

A generation of microplastics caused by improper disposal of disposable masks has become a non-negligible environmental concern. In order to investigate the degradation mechanisms of masks and the release of microplastics under different environmental conditions, the masks are placed in 4 common environments. After 30 days of weathering, the total amount and release kinetics of microplastics released from different layers of the mask were studied. The chemical and mechanical properties of the mask were also discussed. The results showed that the mask released 25141±3543 particles/mask into the soil, which is much more than the sea and river water. The release kinetics of microplastics fit the Elovich model better. All samples correspond to the release rate of microplastics from fast to slow. Experiments show that the middle layer of the mask is released more than the other layers, and the amount of release was highest in the soil. And the tensile capacity of the mask is negatively correlated with its ability to release microplastics in the following order, which are soil > seawater > river > air > new masks. In addition, during the weathering process, the C-C/C-H bond of the mask was broken.

Anti-IL17A, Ixekizumab, for treatment-resistant chronic venous leg ulcers: A phase II randomized, double-blind, placebo-controlled pilot trial

Chronic venous leg ulcers cause significant morbidity in patients and the majority reoccur after resolution. The current standard of care, double layer compression, is not effective in all patients. Interleukin 17A (IL17) antagonist therapy has been shown to promote healing in murine models of chronic wounds. This has not previously been explored in humans. Therefore, we aim to undertake a phase II randomized, double-blinded, placebo-controlled pilot trial to assess whether Ixekizumab, an anti-IL17A therapy, is effective at reducing chronic venous ulcer size. In addition, to determine the feasibility and safety of undertaking a randomized control trial. Patients with a venous leg ulcer not responsive to 4 weeks of compression therapy were recruited. Participant were randomized to receive either Ixekizumab (80mg) or placebo injected subcutaneously every fortnight for 12 weeks while continuing standard of care. From 30 eligible, 4 patients consented, were enrolled and randomized. Initially, COVID-19 risk, medical history and distance from recruiting site were the main causes of exclusion or refusal to participate. All participants completed the 12-week treatment period. At completion, two participants in the Ixekizumab group reduced by >40% and one completely resolved their ulcer. Ulcers in the Ixekizumab group reduced by an average size of 955mm2 to 529mm2at baseline to final review respectively (p-value 0.12). The placebo group reduced in size by <5%.There were no adverse events related to the intervention. This pilot clinical trial investigated a novel treatment for chronic venous ulcers and showed IL17 inhibition does not impede and may improve chronic wound healing. It also showed a lack of major safety issues in using anti-IL17A therapy in this population. Moreover, the findings reinforce the feasibility of a larger trial to more accurately evaluate anti-inflammatory strategies in chronic wounds.Copyright © 2023

Urban Rehabilitation and Tourism: Lessons from Porto (2010–2020)

Cities experience rapid growth and transformation. Over the past decades, change has been particularly intense and complex, associated to globalization, spatial compression and temporal acceleration. Within this context, the EU funds introduced new urban rehabilitation dynamics that made a city center more and more attractive. This, alongside the growth of international tourism, has increased the number of city users, which has furthered the discussion on the relation between the physical, economic, social and environmental intervention of the city, as well as the debates on the positive and negative impacts of tourism in cities. With that in mind, we look at the intense change that occurred in the city of Porto, Portugal, in the period from an intense economic crisis to the COVID-19 confinement. We consider changes in buildings, retail and policies to conclude that a neoliberal attitude favoured a tourism-led and sustainability blind gentrification. Based on a survey and analysis of 50 urban rehabilitation initiatives in downtown Porto and on the analysis of recent public policies, we discuss the relation between urban rehabilitation and tourism in Porto, and therefore the effectiveness of public policies and its contribution to sustainable urban development.

Video Compression using Deep Neural Networks

Advanced video compression is required due to the rise of online video content. A strong compression method can help convey video data effectively over a constrained bandwidth. We observed how more internet usage for video conferences, online gaming, and education led to decreased video quality from Netflix, YouTube, and other streaming services in Europe and other regions, particularly during the COVID-19 epidemic. They are represented in standard video compression algorithms as a succession of reference frames after residual frames, and these approaches are limited in their application. Deep learning's introduction and current advancements have the potential to overcome such problems. This study provides a deep learning-based video compression model that meets or exceeds current H.264 standards. © 2022 IEEE.

Compression of Bio-Signals Using Block-Based Haar Wavelet Transform and COVIDOA for IoMT Systems.

BACKGROUND: Bio-signals are the essential data that smart healthcare systems require for diagnosing and treating common diseases. However, the amount of these signals that need to be processed and analyzed by healthcare systems is huge. Dealing with such a vast amount of data presents difficulties, such as the need for high storage and transmission capabilities. In addition, retaining the most useful clinical information in the input signal is essential while applying compression. METHODS: This paper proposes an algorithm for the efficient compression of bio-signals for IoMT applications. This algorithm extracts the features of the input signal using block-based HWT and then selects the most important features for reconstruction using the novel COVIDOA. RESULTS: We utilized two different public datasets for evaluation: MIT-BIH arrhythmia and EEG Motor Movement/Imagery, for ECG and EEG signals, respectively. The proposed algorithm's average values for CR, PRD, NCC, and QS are 18.06, 0.2470, 0.9467, and 85.366 for ECG signals and 12.6668, 0.4014, 0.9187, and 32.4809 for EEG signals. Further, the proposed algorithm shows its efficiency over other existing techniques regarding processing time. CONCLUSIONS: Experiments show that the proposed method successfully achieved a high CR while maintaining an excellent level of signal reconstruction in addition to its reduced processing time compared with the existing techniques.

Privacy preserving via multi-key homomorphic encryption in cloud computing

As the world grapples with the COVID-19 and its variants, multi-user collaboration by means of cloud computing is ubiquitous. How to make better use of cloud resources while preventing user privacy leakage has become particularly important. Multi-key homomorphic encryption(MKHE) can effectively deal with the privacy disclosure issue during the multi-user collaboration in the cloud computing setting. Firstly, we improve the DGHV homomorphic scheme by modifying the selection of key and the coefficients in encryption, so as to eliminate the restriction on the parity of the ciphertext modulus in the public key. On this basis, we further propose a DGHV-type MKHE scheme based on the number theory. In our scheme, an extended key is introduced for ciphertext extension, and we prove that it is efficient in performance analysis. The semantic security of our schemes is proved under the assumption of error-free approximate greatest common divisor and the difficulty of large integer factorization. Furthermore, the simulation experiments show the availability and computational efficiency of our MKHE scheme. Therefore, our scheme is suitable for the multi-user scenario in cloud environment. © 2023 Elsevier Ltd

Grisel's Syndrome and Covid Infection in Children: Report of Two Cases

Introduction: Grisel syndrome is a rare condition of rotator subluxation of the atlantoaxial joint that is not associated with trauma or bone lesion. It is characterized by acute and painful torticollis with fever, which is a consequence of complicated pharyngitis and tonsillitis. Material(s) and Method(s): We present two girls, aged 5 and 6 years, who developed atlantoaxial subluxation and torticollis during or after infection with COVID. As part of this, a pararetropharyngeal abscess developed. Based on clinical signs, radiological findings, and the course of the disease, Grisel's syndrome was confirmed. One patient had an asymptomatic COVID infection, before the development of Grisel's syndrome, and the other patient had an active COVID infection, during which Grisel's syndrome developed. Result(s): Both patients were treated multidisciplinary: conservatively with antibiotics and surgically, and then physical therapy was introduced along with the Philadelphia orthosis. Both were in constant clinical improvement and did not develop further complications. According to the literature, the Fielding-Hawkins classification describes 4 degrees of this subluxation, and our patients had type 3 at the time of diagnosis. Conclusion(s): Grisel's syndrome is a rare condition and should be suspected in children with painful torticollis after infections or head and neck surgery. The importance of this syndrome for maxillofacial surgeons is in early differential diagnosis, to avoid early and late consequences of undiagnosed pararetropharyngeal abscess and atlantoaxial subluxation and compression of vital structures. Grisel's syndrome needs to be treated multidisciplinary and immediately.

Removing Zero Variance Units of Deep Models for COVID-19 Detection

Deep Learning has been used for several applications including the analysis of medical images. Some transfer learning works show that an improvement in performance is obtained if a pre-trained model on ImageNet is transferred to a new task. Taking into account this, we propose a method that uses a pre-trained model on ImageNet to fine-tune it for Covid-19 detection. After the fine-tuning process, the units that produce a variance equal to zero are removed from the model. Finally, we test the features of the penultimate layer in different classifiers removing those that are less important according to the f-test. The results produce models with fewer units than the transferred model. Also, we study the attention of the neural network for classification. Noise and metadata printed in medical images can bias the performance of the neural network and it obtains poor performance when the model is tested on new data. We study the bias of medical images when raw and masked images are used for training deep models using a transfer learning strategy. Additionally, we test the performance on novel data in both models: raw and masked data. Author

Segmental lung anatomy for ultrasound assessment for post-COVID conditions

Introduction: Ultrasound (US) has become a more reliable method for lung parenchyma assessment. Precise detecting localization and effective monitoring treatment is crucial in respiratory medicine patients. The aim was to evaluate the accuracy of the US to detect and monitor lung lesions in compliance with lung segmental anatomy in post-COVID patients with associated comorbid respiratory conditions. Materials: We did an evaluation of 30 consecutive patients (25-74?years), who suffered from various chronic respiratory conditions and underwent COVID-19 during the last 3 months. All patients underwent first line lung ultrasound followed by CT and bronchoscopy where needed. Result(s): US can detect correctly in 28/30 cases to verify lesion and segmental localization as confirmed on CT and/or endoscopy. The US was effective to monitor treatment in 24/30 cases without need for follow up CT, including 5 patients after bronchoscopic lavage. Various specific conditions were detected and monitored on US: segmental atelectasis, pneumonia (22 cases);right middle lobe atelectasis (3);bronchiectatic disease (3);lung cirrhosis, post tuberculosis changes (2). Lung compression / atelectasis due to severe scoliosis and thoracic deformities detected in 2 patients. In some cases US was more effective vs CT due to possibility of real time ventilation observation, detecting tissue movement;dorsal areas ventilation was underdetected on CT due to patients'position. Conclusion(s): US can be used for detecting peripheral lung lesions, precise determination of segmental localization, is important for early diagnosis and monitoring.

SAME DAY DISCHARGE VIA A DEDICATED RADIAL LOUNGE-RESULTS of 1-YEAR EXPERIENCE during the COVID-19 PANDEMIC

Background: Same day discharge (SDD) is a validated option for selected patients (pts) undergoing coronary angiography (CAG) and percutaneous coronary interventions (PCI). We analyzed how the COVID-19 pandemic influenced patients' admissions to and discharges from our SDD radial lounge. We focused on safety and complications. Method(s): In 2021, 817 pts (age 65+/-11 years, 28% female) were admitted to the lounge. CAG was performed in 729 pts, and 176 (24%) underwent ad hoc PCI. Furthermore, 88 pts were admitted for implantable device replacement procedures. Result(s): Out of 729 transradial CAGs 621 were performed by using the proximal radial approach (PRA) and 108 (15%) via the distal radial approach (DRA). Ninety % of all these procedures (n = 655) were performed from the nondominant left hand. PRA was associated with one radial artery occlusion (RAO) and longer compression time (92+/-24 min vs 75+/-26 min, p <0.05). In the PRA group 23 postprocedural local hematomas <5 cm (3%) and 17 hematomas <10 cm (2%) were observed but did not require specific treatment. DRA was associated with only 4 super-ficial hematomas <2 cm and no RAO. No other relevant complications occurred in the rest of pts. Ninety % of all pts (n = 732) were discharged home on the same day (<=6 hours after procedures) and none of them was readmitted within the next 24 hours. The remaining 10% of the patients (n = 85) were hospitalized after CAG and PCI, mostly because of severe coronary artery disease findings. Conclusion(s): During COVID-19 pandemic, CAG and PCI together with device replacement procedures in our SDD program were associated with a one-year saving of more than 700 overnight stays, minimal complications and 0,1% RAO rate. Supported by the Charles University Research program "Cooperatio-Cardiovascular Science" and by MH CZ-DRO (Faculty Hospital in Pilsen-FNPl, 00669806).

Feature Adaptation Predictive Coding for Quantized Block Compressive Sensing of COVID-19 X-Ray Images

With the development of remote X-ray detection for Corona Virus Disease 2019 (COVID-19), the quantized block compressive sensing technology plays an important role when remotely acquiring the chest X-ray images of COVID-19 infected people and significantly promoting the portable telemedicine imaging applications. In order to improve the encoding performance of quantized block compressive sensing, a feature adaptation predictive coding (FAPC) method is proposed for the remote transmission of COVID-19 X-ray images. The proposed FAPC method can adaptively calculate the block-wise prediction coefficients according to the main features of COVID-19 X-ray images, and thus provide the optimal prediction candidate from the feature-guided candidate set. The proposed method can implement the high-efficiency encoding of X-ray images, and then swiftly transmit the telemedicine-oriented chest images. The experimental results show that compared with the state-of-the-art predictive coding methods, both rate-distortion and complexity performance of our FAPC method have enough competitive advantages. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.