Progression of Overactive Bladder Symptoms in Patients with Prior Sars-Cov-2 Infection

INTRODUCTION AND OBJECTIVE: Infection with SARS-CoV- 2 can result in de novo or worsening genitourinary (GU) symptoms, such as frequency, urgency, nocturia, and pain/pressure, also referred to as COVID-19 associated cystitis (CAC). The aim of this study was to follow progression of OAB symptoms in patients that previously reported new or worsening OAB symptoms after COVID-19 diagnosis. METHOD(S): 19,128 individuals from a Beaumont COVID-19 serology study, were invited to participate in a follow-up study, with 2,137 subsequent respondents. Participants were divided into a COVID-, Ser+ (positive serology test only) or PCR+ (positive PCR test) groups. Initially, patients were asked to score their OAB symptoms retrospectively prior to the pandemic (baseline) and at present time (day 0). Participants were subsequently asked to score their symptoms at 2-, 4-, 8- and 12-months follow-up. Participants that obtained COVID-19 diagnosis during follow-up phase were excluded from the study. GU symptoms were assessed using the ICIQ-OAB. The minimal important difference (MID) of ICIQ-OAB of 1 is considered a significant change. Data was collected between May 2021 and July 2022. RESULT(S): Of 2,137 participants, 564 (26.4%) previously tested positive for COVID, and 1,573 (73.6%) were COVID naive (COVID-). Of these, 592 participants reported a >=1 unit increase in OAB score at study onset (Day 0) compared to pre-pandemic;243 (41%) were COVID-, 129 (21.8%) had positive serology test (Ser+), and 220 (37.2%) were COVID+ based on PCR test (PCR+). OAB score of these three cohorts were similar at pre-pandemic (2.71 vs 2.97 vs 2.53;p=0.193) but significantly higher at start of study (day 0) in PCR+ versus COVID- or Ser+ groups (5.83 vs 5.12 vs 5.33;p=0.019). In prospective follow-up, change in ICIQ-OAB scores from baseline were recorded at 2, 4, 8 and 12 months. At day 0, both Ser+ and PCR+ cohorts had significantly higher change in OAB score than COVID- group (2.8 and 3.11 vs 2.16;p=0.001). However, after 12 months follow-up, change in OAB score was similar between COVID- (1.86), Ser+ (2.15) and PCR+ (2.09). By 12 months, 74% of COVID-, 80.5% of Ser+ and 72.4% of PCR+ participants still reported significant increase in ICIQ-OAB scores from pre-pandemic levels. CONCLUSION(S): We previously demonstrated that COVID-19 infections increases the risk for developing CAC. COVID infected individuals with CAC take up to 12 months to reach levels of COVIDpatients with baseline elevated OAB Symptoms. Elevated ICIQ-OAB scores in COVID- participants may be contributed to other consequences of the pandemic such as elevated stress and depression.

Role of digital twin technology in medical sector-Toward ensuring safe healthcare

In today's scenario, digital technology is gaining prominence in different sectors like business, healthcare, education, security, aerospace, construction, automotive, etc. Digital twin technology is a novel technology. It represents virtually physical objects or process. The basic building block of a digital twin is internet of things (IoT) and the goal of digital twin technology is to create, test, and validate in the virtual environment. In the perspective of the healthcare sector, the digital twin virtually represents physical entity or process. The chapter organization is as follows: introduction to digital twin technology, generic applications of the digital twin, the role of digital twin technology in healthcare, and finally, the conclusion. © 2023 Scrivener Publishing LLC.

THE INCIDENCE OF NEW OR WORSENING OAB SYMPTOMS IN PATIENTS WITH PRIOR SARS COV-2 INFECTION

INTRODUCTION AND OBJECTIVE: Investigators from our institution were the first US group to identify de novo genitourinary symptoms, such as frequency, urgency, nocturia, and pain/pressure, in individuals with prior COVID-19 infection. They termed this condition COVID-19 associated cystitis (CAC). Our study aims to establish the incidence of worsening or de-novo CAC, and to determine the correlation of CAC with serology status and antibody levels. METHODS: After IRB approval, 19,128 individuals from the largest COVID-19 serology study (BLAST COVID Study Group) were invited to participate in a follow-up study, with 1,895 subsequent respondents. Participants were retrospectively asked to score their OAB symptoms at three different time points: prior to the pandemic, 2 months after COVID-19 infection (if applicable), and at the present time. Genitourinary symptoms were assessed using the ICIQ-OAB. RESULTS: Of the 1,895 participants, 81.7% (n=1,548) were female, 16.5% male (n=312), 1.9% other/unknown (n=35). Most were Caucasian (85.8%), followed by African American (4.1%), Asian (3.8%), and Hispanic (1.4%). A third of participants (n=605) were COVID-19 positive as defined by positive serology or PCR test. Of these, 492 had 2 months post infection data with 36.4% (n=179/492) reporting an increase of ≥1 unit on the ICIQ-OAB compared to pre-pandemic. Out of these, 22% (n=40/179) were de novo. Comparing prepandemic to present symptoms, 35.7% (n=219) of participants with prior COVID-19 infection had an increase of ≥1 unit on the ICIQOAB, compared to 15.7% (n=202) of uninfected patients (OR: 2.99, 99.6Cl, 2.21, 4.05, p <0.001). The minimal important difference (MID) of ICIQ-OAB of 1 is considered a significant change. Antibody levels were not correlated with OAB symptoms in those with a positive PCR (ρ==-0.10) and were weakly correlated in those with a positive serology test (ρ= 0.14). CONCLUSIONS: In this study, we demonstrate that patients infected with COVID-19 are at increased risk for developing new or worsening OAB symptoms. No correlation was found between antibody levels and OAB symptoms in patients with prior COVID-19 infection. Participants are being followed prospectively to assess the progression of OAB symptoms in patients with CAC.

Management of breast incidentalomas: A closed loop audit experience at royal surrey foundation trust

Introduction: Breast Incidentalomas occur as an unexpected abnormality demonstrated on imaging performed for unrelated symptoms. Pre-COVID19 pandemic management involved urgent referrals for initial breast team evaluation. Clinical encounters occurred prior to the Multi-Disciplinary Team meeting (MDT). COVID-19 restrictions necessitated streamlining and optimising service provision with clinically appropriate encounters. Our aim was to re-audit (SU-CA-21-22-068) findings and management of breast incidentalomas during the pandemic. Methods: Pre-pandemic analysis of practice (November 2019 - January 2020) led us to the intervention of all referrals straight to MDT without an unnecessary prior clinical encounter, with secondary planned investigations and clinical assessment thereafter. Completion of audit loop and analysis included referral information, MDT outcome, imaging, and clinical correspondence with descriptive analysis. Results: Post-intervention 61 patients were referred to the MDT over an 18-month period (February 2020 - October 2021). 90% of patients were referred following CT scans. Median age 71 (range 32-93), 38% of patients had no additional breast imaging and 74% of patients did not require a tissue biopsy. 15% (n=9) were diagnosed with new breast cancer, 36% were new benign, with 34% already known lesions. 16% of patients required no further intervention. Conclusion: 15% of incidentalomas were diagnosed as malignancies, compared to local 3-4% from one stop clinics. Prompt referral to MDT accelerates triple assessment and tissue diagnosis. Streamlining of patient care optimised appropriate clinical encounters for vulnerable patients. Early senior radiological assessment at the MDT of incidentalomas during COVID-19 provided confirmation of benign features and therefore no further intervention and reassurance for 16% of patients.

Modeling how antibody responses may determine the efficacy of COVID-19 vaccines

Predicting the efficacy of COVID-19 vaccines would aid vaccine development and usage strategies, which is of importance given their limited supplies. Here we develop a multiscale mathematical model that proposes mechanistic links between COVID-19 vaccine efficacies and the neutralizing antibody (NAb) responses they elicit. We hypothesized that the collection of all NAbs would constitute a shape space and that responses of individuals are random samples from this space. We constructed the shape space by analyzing reported in vitro dose–response curves of ~80 NAbs. Sampling NAb subsets from the space, we recapitulated the responses of convalescent patients. We assumed that vaccination would elicit similar NAb responses. We developed a model of within-host SARS-CoV-2 dynamics, applied it to virtual patient populations and, invoking the NAb responses above, predicted vaccine efficacies. Our predictions quantitatively captured the efficacies from clinical trials. Our study thus suggests plausible mechanistic underpinnings of COVID-19 vaccines and generates testable hypotheses for establishing them. © 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.

Non Linear Tensor Diffusion Based Unsharp Masking for Filtering of COVID-19 CT Images

COVID-19 is a dreadful disease caused by coronavirus and it belongs to the family of single-stranded RNA viruses. The Computed Tomography (CT) imaging was found to be a primary diagnostic tool in the screening of COVID-19. Preprocessing is the first stage in image processing operation, it improves segmentation and classification accuracy and hence it gains importance. Preprocessing techniques plays vital role in the improvement of image quality and the objective is to minimize noise, elimination of artifacts and aliasing effects. The improved contrast aids image segmentation and compression algorithms for better diagnosis by physicians. The CT images in general are corrupted by Gaussian and salt and pepper noise. The classical filtering techniques are median, Gaussian, bilateral and anisotropic diffusion. This chapter proposes a novel filtering technique, Non Linear Tensor Diffusion based Unsharp Masking for CT images. The performance validation was done by performance metrics like Just Noticeable Distortion (JND), Discrete Entropy (DE) and average mean brightness error (AMBE) for comparative analysis, classical filtering algorithms are used. The filtering algorithms are implemented in Matlab2015b and tested on real time CT images of COVID-19. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.