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Objectives: Due to the association between COVID-19 and adverse pregnancy outcomes, pregnant women are considered to be a vulnerable patient group. Studies have shown that low socioeconomic status (SES) is a risk factor for SARS-CoV-2 infection. COVID-19 and low SES are likely to have a synergistic adverse effect. This study aimed to evaluate the socioeconomic background, indicated by self-reported SES, educational level, and financial situation, in pregnant women who were positive for SARS-CoV-2., Methods: A case-control study was conducted, including all pregnant women with positive SARS-CoV-2 PCR tests at Kepler University Hospital Linz between May 2020 and August 2021 (n=150) and a control group matched 1:1 relative to gestational age at birth (n=150). Data were collected using written questionnaires and medical records from the hospital information system., Results: Lower self-reported socioeconomic status (p=0.029) and lower education level (p=0.003) were detected in the COVID group. Mothers in the COVID group were significantly younger (p=0.024). However, after adjustment for educational attainment, younger age was not confirmed as a risk factor for SARS-CoV-2 infection during pregnancy (p=0.326). The social gradient was not explained by the assumed mediators and confounders., Conclusions: These findings confirm an association between lower socioeconomic status and the risk of SARS-CoV-2 infection during pregnancy. Since both socioeconomic factors and COVID-19 impose negative effects on pregnancy outcomes, health inequalities should be taken into consideration when implementing SARS-CoV-2 prevention measures and when providing health care for pregnant women from disadvantaged communities., (© 2024 the author(s), published by De Gruyter, Berlin/Boston.)

Background: Pregnant people are particularly vulnerable to SARS-CoV-2 infection and to ensuing severe illness. Predicting adverse maternal and perinatal outcomes could aid clinicians in deciding on hospital admission and early initiation of treatment in affected individuals, streamlining the triaging processes., Methods: An international repository of 1501 SARS-CoV-2-positive cases in pregnancy was created, consisting of demographic variables, patient comorbidities, laboratory markers, respiratory parameters, and COVID-19-related symptoms. Data were filtered, preprocessed, and feature selection methods were used to obtain the optimal feature subset for training a variety of machine learning models to predict maternal or fetal/neonatal death or critical illness., Results: The Random Forest model demonstrated the best performance among the trained models, correctly identifying 83.3% of the high-risk patients and 92.5% of the low-risk patients, with an overall accuracy of 89.0%, an AUC of 0.90 (95% Confidence Interval 0.83 to 0.95), and a recall, precision, and F1 score of 0.85, 0.94, and 0.89, respectively. This was achieved using a feature subset of 25 features containing patient characteristics, symptoms, clinical signs, and laboratory markers. These included maternal BMI, gravidity, parity, existence of pre-existing conditions, nicotine exposure, anti-hypertensive medication administration, fetal malformations, antenatal corticosteroid administration, presence of dyspnea, sore throat, fever, fatigue, duration of symptom phase, existence of COVID-19-related pneumonia, need for maternal oxygen administration, disease-related inpatient treatment, and lab markers including sFLT-1/PlGF ratio, platelet count, and LDH., Conclusions: We present the first COVID-19 prognostication pipeline specifically for pregnant patients while utilizing a large SARS-CoV-2 in pregnancy data repository. Our model accurately identifies those at risk of severe illness or clinical deterioration, presenting a promising tool for advancing personalized medicine in pregnant patients with COVID-19., (© 2023. The Author(s).)

Background: Using data from the German CRONOS registry, we assessed the risk of a complicated course of COVID-19 in women with a SARS-CoV-2-infection during pregnancy, with particular consideration of gestational age, vaccination status, and pandemic dynamics., Methods: Data acquired in two separate periods (March 2020 to August 2021; January to June 2022) for CRONOS, a prospective, hospital-based observational study (DRKS00021208), were studied with logistic regression models. Odds ratios comparing 32 with 22 weeks of gestation were calculated for relevant COVID-19-specific events occurring within 4 weeks of a positive test result., Results: Data from 3481 women were evaluated. The risk of all of the defined COVID-19-specific events was low among women who became ill with COVID-19 during the first trimester and rose with increasing gestational age into the early third trimester. For example, the odds ratio for hospitalization because of a COVID-19 infection, comparing 32 versus 22 weeks of gestation, was 1.4 (95% confidence interval [1.2; 1.7]). This risk was lower in the second period of data acquisition than in the first (OR 0.66; 95% CI [0.50; 0.88]), and it was even lower if the pregnant patient had been vaccinated against COVID-19 (OR 0.27; 95% CI [0.18; 0.41])., Conclusion: These findings can serve as a basis for counseling about prophylactic or therapeutic measures, such as the administration of monoclonal antibodies. They underscore the efficacy of vaccination for pregnant women even during the omicron phase of the pandemic.

Aim: This observational study investigated the association between remdesivir treatment during hospitalization for COVID-19 and 30-day COVID-19-related and all-cause readmission across different variants time periods. Patients & methods: Hospitalization records for adult patients discharged from a COVID-19 hospitalization between 1 May 2020 to 30 April 2022 were extracted from the US PINC AI Healthcare Database. Likelihood of 30-day readmission was compared among remdesivir-treated and nonremdesivir-treated patients using multivariable logistic regression models adjusted for age, corticosteroid treatment, Charlson comorbidity index and intensive care unit stay during the COVID-19 hospitalization. Analyses were stratified by maximum supplemental oxygen requirement and variant time period (pre-Delta, Delta and Omicron). Results: Of the 440,601 patients discharged alive after a COVID-19 hospitalization, 248,785 (56.5%) patients received remdesivir. Overall, remdesivir patients had a 30-day COVID-19-related readmission rate of 3.0% and all-cause readmission rate of 6.3% compared with 5.4% and 9.1%, respectively, for patients who did not receive remdesivir during their COVID-19 hospitalization. After adjusting for demographics and clinical characteristics, remdesivir treatment was associated with significantly lower odds of 30-day COVID-19-related readmission (odds ratio 0.60 [95% confidence interval: 0.58-0.62]), and all-cause readmission (0.73 [0.72-0.75]). Significantly lower odds of 30-day readmission in remdesivir-treated patients was observed across all variant time periods. Conclusion: Treating patients hospitalized for COVID-19 with remdesivir is associated with a statistically significant reduction in 30-day COVID-19-related and all-cause readmission across variant time periods. These findings indicate that the clinical benefit of remdesivir may extend beyond the COVID-19 hospitalization.

Abstract Despite the wide availability of effective vaccines, COVID-19 continues to be an infectious disease of global importance. Remdesivir is a broad-spectrum antiviral and was the first US Food and Drug Administration-approved treatment for COVID-19. In clinical guidelines, remdesivir is currently the only recommended antiviral for use in hospitalized patients with COVID-19, with or without a supplemental oxygen requirement. It is also recommended for nonhospitalized patients with COVID-19 and hospitalized patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection who are at high risk of progression to severe disease. This narrative review explores the evidence for remdesivir across various clinical outcomes and evolution of clinical guidelines through a survey over time of randomized controlled trials, observational studies, and meta-analyses. Remdesivir, compared to standard of care, appears to improve survival and disease progression in a variety of patient populations with COVID-19 across a spectrum of disease severity and SARS-CoV-2 variant periods. Remdesivir also appears to improve time to clinical recovery, increase rate of recovery, and reduce time on supplemental oxygen and readmission rates. More recent large, real-world studies further support the early use of remdesivir in a range of patient populations, including those with immunocompromising conditions.

Abstract Background Pregnant people are particularly vulnerable to SARS-CoV-2 infection and to ensuing severe illness. Predicting adverse maternal and perinatal outcomes could aid clinicians in deciding on hospital admission and early initiation of treatment in affected individuals, streamlining the triaging processes. Methods An international repository of 1501 SARS-CoV-2-positive cases in pregnancy was created, consisting of demographic variables, patient comorbidities, laboratory markers, respiratory parameters, and COVID-19-related symptoms. Data were filtered, preprocessed, and feature selection methods were used to obtain the optimal feature subset for training a variety of machine learning models to predict maternal or fetal/neonatal death or critical illness. Results The Random Forest model demonstrated the best performance among the trained models, correctly identifying 83.3% of the high-risk patients and 92.5% of the low-risk patients, with an overall accuracy of 89.0%, an AUC of 0.90 (95% Confidence Interval 0.83 to 0.95), and a recall, precision, and F1 score of 0.85, 0.94, and 0.89, respectively. This was achieved using a feature subset of 25 features containing patient characteristics, symptoms, clinical signs, and laboratory markers. These included maternal BMI, gravidity, parity, existence of pre-existing conditions, nicotine exposure, anti-hypertensive medication administration, fetal malformations, antenatal corticosteroid administration, presence of dyspnea, sore throat, fever, fatigue, duration of symptom phase, existence of COVID-19-related pneumonia, need for maternal oxygen administration, disease-related inpatient treatment, and lab markers including sFLT-1/PlGF ratio, platelet count, and LDH. Conclusions We present the first COVID-19 prognostication pipeline specifically for pregnant patients while utilizing a large SARS-CoV-2 in pregnancy data repository. Our model accurately identifies those at risk of severe illness or clinical deterioration, presenting a promising tool for advancing personalized medicine in pregnant patients with COVID-19.

Aim: This observational study investigated the association between remdesivir treatment during hospitalization for COVID-19 and 30-day COVID-19-related and all-cause readmission across different variants time periods. Patients & methods: Hospitalization records for adult patients discharged from a COVID-19 hospitalization between 1 May 2020 to 30 April 2022 were extracted from the US PINC AI Healthcare Database. Likelihood of 30-day readmission was compared among remdesivir-treated and nonremdesivir-treated patients using multivariable logistic regression models adjusted for age, corticosteroid treatment, Charlson comorbidity index and intensive care unit stay during the COVID-19 hospitalization. Analyses were stratified by maximum supplemental oxygen requirement and variant time period (pre-Delta, Delta and Omicron). Results: Of the 440,601 patients discharged alive after a COVID-19 hospitalization, 248,785 (56.5%) patients received remdesivir. Overall, remdesivir patients had a 30-day COVID-19-related readmission rate of 3.0% and all-cause readmission rate of 6.3% compared with 5.4% and 9.1%, respectively, for patients who did not receive remdesivir during their COVID-19 hospitalization. After adjusting for demographics and clinical characteristics, remdesivir treatment was associated with significantly lower odds of 30-day COVID-19-related readmission (odds ratio 0.60 [95% confidence interval: 0.58–0.62]), and all-cause readmission (0.73 [0.72–0.75]). Significantly lower odds of 30-day readmission in remdesivir-treated patients was observed across all variant time periods. Conclusion: Treating patients hospitalized for COVID-19 with remdesivir is associated with a statistically significant reduction in 30- day COVID-19-related and all-cause readmission across variant time periods. These findings indicate that the clinical benefit of remdesivir may extend beyond the COVID-19 hospitalization.

Este artigo é resultado do “I Encontro da Fisioterapia da UFPel”, que ocorreu junto ao tradicional Simpósio Nacional de Educação Física da Universidade Federal de Pelotas, e tem o objetivo de apresentar experiências vividas por profissionais fisioterapeutas sobre o momento pandêmico, o cenário apresentado, as dificuldades enfrentadas e os aprendizados. Foi relatada a experiência de profissionais que atuaram durante a pandemia nas áreas de terapia intensiva, unidade de tratamento intensivo neonatal e na clínica, após a alta hospitalar. Identificamos que as experiências vivenciadas na atuação do profissional fisioterapeuta foi marcada pela adaptação ao novo cenário e pelo enfrentamento de diferentes situações com protagonismo, o que possibilitou mostrar o quanto esses profissionais estão prontos para agir, junto aos demais membros da equipe de saúde, nas diversas situações em saúde que podem se apresentar.

Coronavirus disease 19 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first emerged in late 2019 and has since rapidly become a global pandemic. SARS-CoV-2 infection causes damages to the lung and other organs. The clinical manifestations of COVID-19 range widely from asymptomatic infection, mild respiratory illness to severe pneumonia with respiratory failure and death. Autopsy studies demonstrate that diffuse alveolar damage, inflammatory cell infiltration, edema, proteinaceous exudates, and vascular thromboembolism in the lung as well as extrapulmonary injuries in other organs represent key pathological findings. Herein, we hypothesize that GPR4 plays an integral role in COVID-19 pathophysiology and is a potential therapeutic target for the treatment of COVID-19. GPR4 is a pro-inflammatory G protein-coupled receptor (GPCR) highly expressed in vascular endothelial cells and serves as a “gatekeeper” to regulate endothelium-blood cell interaction and leukocyte infiltration. GPR4 also regulates vascular permeability and tissue edema under inflammatory conditions. Therefore, we hypothesize that GPR4 antagonism can potentially be exploited to mitigate the hyper-inflammatory response, vessel hyper-permeability, pulmonary edema, exudate formation, vascular thromboembolism and tissue injury associated with COVID-19.

Abstract Background The SARS-CoV-2 pandemic is still ongoing and a major challenge for health care services worldwide. In the first WSES COVID-19 emergency surgery survey, a strong negative impact on emergency surgery (ES) had been described already early in the pandemic situation. However, the knowledge is limited about current effects of the pandemic on patient flow through emergency rooms, daily routine and decision making in ES as well as their changes over time during the last two pandemic years. This second WSES COVID-19 emergency surgery survey investigates the impact of the SARS-CoV-2 pandemic on ES during the course of the pandemic. Methods A web survey had been distributed to medical specialists in ES during a four-week period from January 2022, investigating the impact of the pandemic on patients and septic diseases both requiring ES, structural problems due to the pandemic and time-to-intervention in ES routine. Results 367 collaborators from 59 countries responded to the survey. The majority indicated that the pandemic still significantly impacts on treatment and outcome of surgical emergency patients (83.1% and 78.5%, respectively). As reasons, the collaborators reported decreased case load in ES (44.7%), but patients presenting with more prolonged and severe diseases, especially concerning perforated appendicitis (62.1%) and diverticulitis (57.5%). Otherwise, approximately 50% of the participants still observe a delay in time-to-intervention in ES compared with the situation before the pandemic. Relevant causes leading to enlarged time-to-intervention in ES during the pandemic are persistent problems with in-hospital logistics, lacks in medical staff as well as operating room and intensive care capacities during the pandemic. This leads not only to the need for triage or transferring of ES patients to other hospitals, reported by 64.0% and 48.8% of the collaborators, respectively, but also to paradigm shifts in treatment modalities to non-operative approaches reported by 67.3% of the participants, especially in uncomplicated appendicitis, cholecystitis and multiple-recurrent diverticulitis. Conclusions The SARS-CoV-2 pandemic still significantly impacts on care and outcome of patients in ES. Well-known problems with in-hospital logistics are not sufficiently resolved by now; however, medical staff shortages and reduced capacities have been dramatically aggravated over last two pandemic years.