Rapid Assessment of COVID-19 Mortality Risk with GASS Classifiers.

Risk prediction models are fundamental to effectively triage incoming COVID-19 patients. However, current triaging methods often have poor predictive performance, are based on variables that are expensive to measure, and often lead to hard-to-interpret decisions. We introduce two new classification methods that can predict COVID-19 mortality risk from the automatic analysis of routine clinical variables with high accuracy and interpretability. SVM22-GASS and Clinical-GASS classifiers leverage machine learning methods and clinical expertise, respectively. Both were developed using a derivation cohort of 499 patients from the first wave of the pandemic and were validated with an independent validation cohort of 250 patients from the second pandemic phase. The Clinical-GASS classifier is a threshold-based classifier that leverages the General Assessment of SARS-CoV-2 Severity (GASS) score, a COVID-19-specific clinical score that recently showed its effectiveness in predicting the COVID-19 mortality risk. The SVM22-GASS model is a binary classifier that non-linearly processes clinical data using a Support Vector Machine (SVM). In this study, we show that SMV22-GASS was able to predict the mortality risk of the validation cohort with an AUC of 0.87 and an accuracy of 0.88, better than most scores previously developed. Similarly, the Clinical-GASS classifier predicted the mortality risk of the validation cohort with an AUC of 0.77 and an accuracy of 0.78, on par with other established and emerging machine-learning-based methods. Our results demonstrate the feasibility of accurate COVID-19 mortality risk prediction using only routine clinical variables, readily collected in the early stages of hospital admission.

IS PSORIATIC ARTHRITIS A RISK FACTOR for SEVERE COVID-19 INFECTION? DATA from the ARGENTINIAN REGISTRY SAR-COVID

Background: Comorbidities, particularly cardio-metabolic disorders, are highly prevalent in patients with psoriatic arthritis (PsA) and they were associated with an increased risk of atherosclerotic cardiovascular disease, which have been associated with higher morbidity and mortality. Whether PsA enhances the risk of SARS-CoV-2 infection or affects the disease outcome remains to be ascertained. Objectives: To describe the sociodemographic, clinical and treatment characteristics of patients with PsA with confrmed SARS-CoV-2 infection from the SAR-COVID registry and to identify the variables associated with poor COVID-19 outcomes, comparing them with those with rheumatoid arthritis (RA). Methods: Cross-sectional observational study including patients ≥18 years old, with diagnosis of PsA (CASPAR criteria) and RA (ACR/EULAR 2010 criteria), who had confrmed SARS-CoV-2 infection (RT-PCR or serology) from the SAR-COVID registry. Recruitment period was between August 13, 2020 and July 31, 2021. Sociodemographic variables, comorbidities, and treatments were analyzed. To assess the severity of the infection, the ordinal scale of the National Institute of Allergy and Infectious Diseases (NIAID)1 was used, and it was considered that a patient met the primary outcome, if they presented criteria of categories 5 or higher on the severity scale. For this analysis, Chi2 test, Fisher's test, Student's test or Wilcoxon test, and binomial logistic regression using NIAID>=5 as dependent variable were performed. Results: A total of 129 PsA patients and 808 with RA were included. Clinical characteristics are shown in Table 1. Regarding PsA treatment, 12.4% of PsA were receiving IL-17 inhibitors, 5.4% IL12-23 inhibitors, one patient apremilast and one abatacept. The frequency of NIAID≥5 was comparable between groups (PsA 19.5% vs RA 20.1%;p=0.976). (Figure 1). PsA patients with NIAID≥5 in comparison with NIAID<5 were older (58.6±11.4 vs 50±12.5;p=0.002), had more frequently hypertension (52.2% vs 23%;p=0.011) and dyslipidemia (39.1% vs 15%;p=0.017). In the multivariate analysis, age (OR 1.06;95% CI 1.02-1.11) was associated with a worse outcome of the COVID-19 (NIAID≥5) in patients with PsA, while those who received methotrexate (OR 0.34;95% CI 0.11-0.92) and biological DMARDs (OR 0.28;95% CI 0.09-0.78) had a better outcome. Conclusion: Although PsA patients have a higher frequency of cardiovascular and metabolic comorbidities than those with RA, the COVID-19 severity was similar. Most of the patients had mild SARS-CoV-2 infection and a low death rate.

Abstracts of the BSG Annual Meeting

The proceedings contain 374 papers. The topics discussed include: optical biopsy with linked color imaging accurately predicts inflammation in ulcerative colitis;predicting use of opiates in patients with inoperable pancreatic cancer: a retrospective cohort study;unbiased clustering of breath signature in NAFLD identifies disease progression high-risk patient phenotype - 5 year study;prevalence of malnutrition screening;the association between IBD and mental ill health: a retrospective primary care cohort study;the interleukin 22//neutrophil axis is associated with treatment resistance in ulcerative colitis;neuromuscular dysfunction in patients with nausea and vomiting syndrome defined by body surface gastric mapping;two-tiered liver fibrosis assessment in primary care annual diabetic screening 3 year follow up;can an algorithm help in the difficult dilemma of upper gastrointestinal bleed and anticoagulant COVID-19 pandemic and alcohol-specific hospital admissions;and upper gastrointestinal hemorrhages and COVID-19: a nationwide cohort study of the pandemic's impact on hospitalizations.

Polycystic ovary syndrome as a predictor of metabolic syndrome in women of reproductive age

Relevance: Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women of reproductive age. The prevalence rates of PCOS depend on the diagnostic criteria used and the characteristics of the population sample, and in the general population of women of reproductive age, the prevalence of the syndrome ranges from 6-9% to 19.9% [1,2]. According to modern criteria adopted by the consensus in Rotterdam, then systematically updated by ESHRE / ASRM (2014), the presence of two of the three criteria in a patient simultaneously allows to diagnose PCOS if other pathological conditions are excluded (thyroid pathology, congenital adrenal hyperplasia, adrenogenitalsyndrome, androgen-secreting tumors, Itsenko-Cushing syndrome). Modern international diagnostic criteria include the following signs: (1) signs of polycystic ovaries according to information from pelvic ultrasound investigation (the presence of more than 10 follicles in each ovary);(2) oligo-anovulation;(3) clinical (presence of hirsutism) or biochemical (increased androgen levels) development of ovarian hyperandrogenism [3, 4]. Polycystic ovary syndrome is closely related to many diseases, including metabolic syndrome. Although insulin resistance is an important risk factor for metabolic syndrome and other diseases associated with PCOS, hyperandrogenismmay also be an independent risk factor for type 2 diabetes, obesity, cardiovascular disease (CVD), and metabolic syndrome in female patients. Obesity is the most common symptom in PCOS patients (33-88%), which has a large impact on fertility and can lead to adverse effects such as menstrual irregularities, anovulation, infertility and abortion. Therefore, weight management in early PCOS is essential to improve fertility and quality of life. Hyperandrogenism plays a decisive role in abdominal obesity in obese women during adolescence, adulthood and menopause [5]. Although some studies have shown a negative association between plasma androgen levels (A4, DHEA and DHEAS) and obesity [6,7]. But the mechanism of how androgens affect fat cells in women is poorly understood. A number of observations show that among obese women with PCOS, metabolic disorders associated with insulin resistance and obesity, in many cases, play a more important role in the mechanism of anovulation in PCOS than excess androgens. In recent years, it has been established that in PCOS there is a frequent combination of hyperandrogenism and insulin resistance. With insulin resistance, there is a decrease in the response of insulin-sensitive tissues to the hormone insulin with its sufficient level in the blood. Insulin resistance is found in 30-70% of patients with PCOS who are overweight or obese, and in patients with normal body weight it occurs in 20-25% of cases. The above facts, as well as our own observations, prompted us to analyze the studied women of fertile age with impaired reproductive system against the background of overweight and obesity. Considering the above, the aim of this study was to identify the relationship between insulin resistance and reproductive disorders in women with overweight and obesity. Material and research methods. The study included 123 women with clinical development of HA and impaired reproductive function, who consulted the consultative clinic of the RSSPMC of Obstetrics and Gynecology of the Ministry of Health of the Republic of Uzbekistan. The criteria for inclusion in the main group were: age of women from 18 to 35 years (average age was 25.8 .. 3.28 years), absence of pregnancy, body mass index over 25 kg / m2. Exclusion criteria from the main group: type 1 and 2 diabetes, pituitary tumors, hypogonadotropichypogonadism, congenital adrenal hyperplasia, hypothyroidism, severe somatic pathology. All patients who applied for the consultation underwent: (1) Collection of anamnestic information. (2) Measurement of anthropometric indicators (height, weight, waist and hip circumference) and assessment of body hair growth using the Ferriman-Hallway scale. (3) Body mass index was

Human ACE2 and TMPRSS2 interaction with SARS-CoV-2 in COVID-19 patient: a review on male reproductive disorders

Since its inception in 2019 from China, the novel Coronavirus has caused an unprecedented havoc in the economic and public health sector. Many countries were forced to close their borders and cross-border interactions in order to limit the spread of the disease. Furthermore, many economic and commercial activities were adversely affected as many businesses had to close. The only ones that the pandemic spared were the ones providing essential services. By March 2020, many public healthcare facilities had already been overrun. Other governments devised alternative means of managing significant cases of COVID-19, such as introducing home-based care to give room for more critical cases to be taken care of in intensive care units. It is imperative to identify the disease's risk factors to mitigate the unexpected devastation caused by the SARS-CoV-2. Global epidemiological results indicate that men, especially the elderly, are more susceptible to Coronavirus infection. The number of reported Coronavirus cases varies by gender, and this disparity continues to grow in favor of male participants until they reach the age of 60. Other studies have also established that men more than women are susceptible to coronavirus infection. Further, male patients diagnosed with coronavirus infection were shown to have an elevated mortality rate. SARS-CoV-2 is the Covid-19 pathogen that is transmitted via respiratory globules, through indirect or direct interaction. Evaluation of the genome has revealed that SARS-CoV-2 is 79% similar to SARS-CoV-2;they employ ACE2 receptors to attack cells, meanwhile it has been established that TMPRSS2 promotes ACE2, therefore causing more severe reactions in comparison to the other types of coronaviruses. Studies describe ACE2 as a gateway for viruses to enter cells. It is directly associated with the COVID-19 clinical symptoms. Research has shown that TMPRSS2 and ACE2 are expressed in the male reproductive system tract and testis and are controlled by testosterone. Thus, the male reproductive system has all the mechanism needed to bid SARs-CoV-2, and these possibilities raise the capability of ACE2 and TMPRSS2 as potential vectors of COVID-19. This review examines how the novel Coronavirus find its way into the human cells through known receptors such as ACE2, antibody Fcy R, etc. The examination is also done on the mechanisms of its spike proteins transition with the help of proteases such as cathepsins, Furin, and TMPRSS2. The study reviewed six articles selected based on PRISMA criteria.