Implementing remote monitoring for COVID-19 patients in primary care (preprint)

Background: In Germany, most patients with coronavirus disease 2019 (COVID-19) are treated in an outpatient setting. To improve assessments of the health status of COVID-19 outpatients, various remote monitoring models have been developed. However, little information exists on experiences acquired with remote monitoring in an outpatient setting, particularly from a patient perspective. The aim of our 'COVID-19@home' study was therefore to implement and evaluate an app-based remote monitoring concept for acute and post-acute COVID-19-patients in primary care. In this paper, we focus on the patients' evaluation of our remote monitoring approach. Methods Patients with acute COVID-19 measured heart rate, blood pressure, oxygen saturation, and body temperature daily for 28 days. Patients with post-acute COVID-19 determined the same parameters for 12 weeks, supplemented by lung parameters and daily step count. The data were documented using the 'SaniQ' smartphone app. COVID-19 symptoms were assessed daily using an app-based questionnaire. Patients' GPs could access the data on the 'SaniQ Praxis' telemedicine platform. We used an app-based questionnaire consisting of 11 questions presented with a 4-point Likert scale to evaluate patient satisfaction. Data were analyzed descriptively. Results Of the 51 patients aged 19-77 years that participated in the study, 42 completed the questionnaire. All patients rated home monitoring as 'very good' or 'rather good' and were able to integrate the measuring processes into their daily routines. Overall, 93% would recommend the app and the measuring devices to their family and friends. About 60% felt that their COVID-19 treatment had benefited from home monitoring. Only few patients were unsettled by the app and use of the measuring devices. During the course of the study, the implementation process was optimized. Conclusions The use of remote monitoring in COVID-19 patients is feasible and was evaluated positively by most study patients. However, it is difficult to imagine how general practices could cope with monitoring patients with acute diseases without any further organizational support. Future research should address cost-effectiveness and changes in such clinical outcomes as hospitalization and mortality.

Post-viral symptoms and conditions are more frequent in COVID-19 than influenza, but not more persistent (preprint)

Post-viral symptoms have long been known in the medical community but have received more public attention during the COVID-19 pandemic. Many post-viral symptoms were reported as particularly frequent after SARS-CoV-2 infection. However, there is still a lack of evidence regarding the specificity, frequency and persistence of these symptoms in comparison to other viral infectious diseases such as Influenza. We addressed this topic by investigating a large population-based cohort based on German routine healthcare data. We matched 573,791 individuals with a PCR-test confirmed SARS-CoV-2 infection from the year 2020 to contemporary controls without SARS-CoV-2 infection and controls from the last Influenza outbreak in 2018 and followed them up to 18 months. We found that post-viral symptoms as defined for COVID-19 by the WHO as well as tissue damage were more frequent among the COVID-19 cohort than the Influenza cohort. Persistence of post-viral symptoms was however similar between COVID-19 and Influenza. We conclude that post-viral symptoms following SARS-CoV-2 infection constitute a substantial disease burden as they are frequent and often persist for many months. As COVID-19 is becoming endemic, the disease must not be trivialized. Research should focus on the development of effective treatments for post-viral symptoms.

Neuropathological assessment of the olfactory bulb and tract in individuals with COVID-19 (preprint)

The majority of patients with Parkinson disease (PD) experience a loss in their sense of smell and accumulate insoluble alpha-synuclein aggregates in their olfactory bulbs (OB). Subjects affected by a SARS-CoV-2-linked illness (COVID-19) frequently experience hyposmia. We previously hypothesized that alpha-synuclein and tau misprocessing could occur following host responses to microbial triggers. Using semiquantitative measurements of immunohistochemical signals, we examined OB and olfactory tract specimens collected serially at autopsies between 2020 and 2023. Deceased subjects comprised 50 adults, which included COVID19+ patients (n=22), individuals with Lewy body disease (e.g., PD and dementia with Lewy bodies (DLB; n=6)), Alzheimer disease (AD; n=3), other non-synucleinopathy-linked degenerative diseases (e.g., progressive supranuclear palsy (PSP; n=2) and multisystem atrophy (MSA; n=1)). Further, we included neurologically healthy controls (HCO; n=9) and those with an inflammation-rich brain disorder as neurological controls (NCO; n=7). When probing for inflammatory changes focusing on anterior olfactory nuclei (AON) using anti-CD68 immunostaining, scores were consistently elevated in NCO and AD cases. In contrast, inflammation on average was not significantly altered in COVID19+ patients relative to controls, although anti-CD68 reactivity in their OB and tracts declined with progression in age. Mild-to-moderate increases in phospho-alpha-Syn and phospho-tau signals were detected in the AON of tauopathy- and synucleinopathy-afflicted brains, respectively, consistent with mixed pathology, as described by others. Lastly, when both sides were available for comparison in our case series, we saw no asymmetry in the degree of pathology of the left versus right OB and tracts. We concluded from our autopsy series that after a fatal course of COVID-19, microscopic changes, when present, in the rostral, intracranial portion of the olfactory circuitry generally reflected neurodegenerative processes seen elsewhere in the brain. In general, inflammation correlated best with the degree of Alzheimer's-linked tauopathy and declined with progression of age in COVID19+ patients.

Wisdom and prosocial behavior (preprint)

Prosocial behavior is crucial for tackling global challenges such as climate change, poverty, and conflict, yet people often prioritize personal benefits over the common good. A classic philosophical proposition is that prosocial behavior benefits from psychological wisdom — a concept characterized by cognitive and behavioral scientists by expression of intellectual humility, open-mindedness towards different ways in which events may unfold, as well as consideration and integration of diverse viewpoints. We investigate the relationship between these features of wisdom and prosocial behavior in an incentivized donation experiment, as well as self-reported real-world behaviors such as blood and charity donations across 13,500 households in nine European countries. Our findings reveal that greater expression of wisdom was systematically aligned with contributions to climate change mitigation, donating blood and money to charitable causes, compliance with rules and behaviors to contain the spread of the COVID-19 virus, voting in parliamentary elections, volunteering and being a member of an environmental group. These results were robust across experimental conditions varying vantage point (self-focused or other-focused), when examining wisdom in reflections specific to climate donation decisions, or reflections on one’s personal life experiences, or when accounting for effect socioeconomic characteristics, personality, and values of prosocial behavior. Finally, the association was observed in each of the country samples, albeit with varying strengths.

Learning COVID-19 Regional Transmission Using Universal Differential Equations in a SIR model (preprint)

Highly-interconnected societies difficult to model the spread of infectious diseases such as COVID-19. Single-region SIR models fail to account for incoming forces of infection and expanding them to a large number of interacting regions involves many assumptions that do not hold in the real world. We propose using Universal Differential Equations (UDEs) to capture the influence of neighboring regions and improve the model's predictions in a combined SIR+UDE model. UDEs are differential equations totally or partially defined by a deep neural network (DNN). We include an additive term to the SIR equations composed by a DNN that learns the incoming force of infection from the other regions. The learning is performed using automatic differentiation and gradient descent to approach the change in the target system caused by the state of the neighboring regions. We compared the proposed model using a simulated COVID-19 outbreak against a single-region SIR and a fully data-driven model composed only of a DNN. The proposed UDE+SIR model generates predictions that capture the outbreak dynamic more accurately, but a decay in performance is observed at the last stages of the outbreak. The single-area SIR and the fully data-driven approach do not capture the proper dynamics accurately. Once the predictions were obtained, we employed the SINDy algorithm to substitute the DNN with a regression, removing the black box element of the model with no considerable increase in the error levels.

An Empirical Analysis for Zero-Shot Multi-Label Classification on COVID-19 CT Scans and Uncurated Reports (preprint)

The pandemic resulted in vast repositories of unstructured data, including radiology reports, due to increased medical examinations. Previous research on automated diagnosis of COVID-19 primarily focuses on X-ray images, despite their lower precision compared to computed tomography (CT) scans. In this work, we leverage unstructured data from a hospital and harness the fine-grained details offered by CT scans to perform zero-shot multi-label classification based on contrastive visual language learning. In collaboration with human experts, we investigate the effectiveness of multiple zero-shot models that aid radiologists in detecting pulmonary embolisms and identifying intricate lung details like ground glass opacities and consolidations. Our empirical analysis provides an overview of the possible solutions to target such fine-grained tasks, so far overlooked in the medical multimodal pretraining literature. Our investigation promises future advancements in the medical image analysis community by addressing some challenges associated with unstructured data and fine-grained multi-label classification.

A Remote Sim2real Aerial Competition: Fostering Reproducibility and Solutions' Diversity in Robotics Challenges (preprint)

Shared benchmark problems have historically been a fundamental driver of progress for scientific communities. In the context of academic conferences, competitions offer the opportunity to researchers with different origins, backgrounds, and levels of seniority to quantitatively compare their ideas. In robotics, a hot and challenging topic is sim2real-porting approaches that work well in simulation to real robot hardware. In our case, creating a hybrid competition with both simulation and real robot components was also dictated by the uncertainties around travel and logistics in the post-COVID-19 world. Hence, this article motivates and describes an aerial sim2real robot competition that ran during the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, from the specification of the competition task, to the details of the software infrastructure supporting simulation and real-life experiments, to the approaches of the top-placed teams and the lessons learned by participants and organizers.

Examination of Influenza A Infection Rate, Its Determinants, and Seasonal Influenza Vaccine Effectiveness in the Post-COVID-19 Pandemic Era (preprint)

BackgroundIn the context of the COVID-19 pandemic, a pronounced wave of Influenza A occurred in the 2022/23 winter season under generally relaxed post-pandemic non-pharmaceutical preventive measures. AimThis study aimed to investigate the Influenza A infection rate, factors influencing its occurrence and seasonal Influenza vaccine effectiveness on seroconversion in the post-COVID-19 pandemic era. MethodsThe seroconversion of Anti-Influenza-A-Nucleoprotein/Matrix IgG was investigated in 402 healthcare workers (HCWs) during the winter season of 2022/2023 (23 May 2022 to 11 May 2023). The participants provided a serum sample and completed a study questionnaire both before and after the seasonal Influenza A wave (24 October 2022 to 8 January 2023). The levels of a vaccine-independent Anti-Influenza-A-Nucleoprotein/Matrix IgG were measured using the SERION ELISA classic Influenza A IgG assay, with a 2-fold increase as indicative of seroconversion after asymptomatic or symptomatic influenza infection. ResultsAmong the participants, 20.6% (95% CI 17.0-24.9%; 83/402) showed seroconversion. The multivariate logistic regression analysis revealed that the age category of [≥] 45 years (p=0.03) and regular patient contact (p=0.02) significantly influenced seroconversion. However, the factors male gender, BMI, smoking, household size, seasonal Influenza vaccination, and SARS-CoV-2 infection during the Influenza A season were not significantly associated with seroconversion. The effectiveness of the 2022/23 seasonal Influenza vaccine on seroconversion induced by Influenza infection was 22.6% (95% CI -17.1-50.6%). ConclusionDuring the initial Influenza A season following the COVID-19 pandemic, approximately 20% of HCWs contracted an Influenza A infection. This highlights a potential risk and a significant asymptomatic or symptomatic infection rate posing a theoretical risk for intrahospital transmission chains and nosocomial infections.

Isolation and characterization of neutralizing monoclonal antibodies from a large panel of murine antibodies against RBD of the SARS-CoV-2 Spike protein (preprint)

Background Coronavirus disease 2019 (COVID-19) emerged in late December 2019 and was declared pandemic in March 2020 by the World Health Organization, causing clinically acute respiratory manifestations and corresponding symptoms, pathological inflammation and multi-organ dysfunctions. The total commitment of the scientific community to develop therapeutics to deal with this global emergency in the shortest possible period was unprecedented. In a very short time, several vaccines were approved by the EMA (European Medicines Agency) and the FDA (Food and Drug Administration). Despite this, it is conceivable that COVID-19 will continue to spread globally through evolving variants in more or less cyclic waves. With these perspectives, it is essential to quickly develop additional therapeutic tools to deal with the next wave of infection.  Methods In the present study we describe the development and characterization of neutralizing mouse monoclonal antibodies (mAbs) against the receptor binding domain (RBD) of the SARS-CoV-2 Spike (S) protein.  Results The mAbs identified are able to specifically detect the RBD of SARS-CoV-2 Spike protein in all tested applications, including enzyme-linked immunosorbent assay (ELISA), flow cytometry (FACS) and bio-layer interferometry. In addition, we show that these mAbs efficiently block entry of both SARS-CoV-2 pseudoparticles carrying the spike protein of the original SARS-CoV-2 strain and a broad set of variants of concern (VOC). Conclusions Here we report a panel of monoclonal antibodies that target RBD and inhibit SARS-CoV-2 variants  infection and enable the isolation of novel therapeutic tools to neutralize SARS-CoV-2 virus

Attitudes toward children: Distinguishing affection and stress.

BACKGROUND: Adults' views and behaviors toward children can vary from being supportive to shockingly abusive, and there are significant unanswered questions about the psychological factors underpinning this variability. OBJECTIVE: The present research examined the content of adults' attitudes toward children to address these questions. METHOD: Ten studies (N = 4702) identified the factor structure of adults' descriptions of babies, toddlers, and school-age children and examined how the resulting factors related to a range of external variables. RESULTS: Two factors emerged-affection toward children and stress elicited by them-and this factor structure was invariant across the United Kingdom, the United States, and South Africa. Affection uniquely captures emotional approach tendencies, concern for others, and broad positivity in evaluations, experiences, motivations, and donation behavior. Stress relates to emotional instability, emotional avoidance, and concern about disruptions to a self-oriented, structured life. The factors also predict distinct experiences in a challenging situation-home-parenting during COVID-19 lockdown-with affection explaining greater enjoyment and stress explaining greater perceived difficulty. Affection further predicts mentally visualizing children as pleasant and confident, whereas stress predicts mentally visualizing children as less innocent. CONCLUSIONS: These findings offer fundamental new insights about social cognitive processes in adults that impact adult-child relationships and children's well-being.

Work fatigue during COVID-19 lockdown teleworking: the role of psychosocial, environmental, and social working conditions.

Background: During national lockdowns in response to the COVID-19 pandemic, previously office-based workers who transitioned to home-based teleworking faced additional demands (e.g., childcare, inadequate homeworking spaces) likely resulting in poor work privacy fit. Previous office research suggests poor work privacy fit is associated with lower wellbeing and higher work fatigue. Emerging evidence suggests a relationship between childcare duties during pandemic teleworking and work fatigue. In addition to psychosocial working conditions (job demand, job control, and job change management), which are acknowledged predictors of work fatigue, this poses a significant threat to occupational health during pandemic teleworking. However, the relative effects of aspects of the psychosocial environment (job demands and resources), the home office environment (including privacy fit), and the social environment (childcare) on work fatigue as well as their interactions are under-explored. Objective: This study examined the relationships between the psychosocial, environmental, and social working conditions of teleworking during the first COVID-19 lockdown and work fatigue. Specifically, the study examined teleworkers' physical work environment (e.g., if and how home office space is shared, crowding, and noise perceptions) as predictors of privacy fit and the relationship between privacy fit, childcare, psychosocial working conditions (job demand, job control, and job change management), and work fatigue. Work privacy fit was hypothesized to mediate the relationship between childcare and work fatigue. Methods: An online cross-sectional survey was conducted with teleworkers (n = 300) during the first COVID-19 lockdown in April and May 2020; most participants were in Germany, Switzerland, and the United Kingdom. Results: Path analysis was used to examine the hypothesized relationships. Privacy fit was lower for those reporting greater levels of noise in home-working spaces and those feeling crowded at home. Work fatigue was lower amongst those with greater privacy fit and higher amongst those with high levels of job demand. An indirect relationship was observed between childcare and work fatigue with privacy fit mediating this relationship. Conclusion: The influence of privacy fit has so far been largely neglected in research on teleworking, especially during the pandemic. However, its contribution to workers' wellbeing should be acknowledged in occupational health strategies.

An integrated cell atlas of the lung in health and disease.

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas.

Assessing the heterogeneity in the transmission of infectious diseases from time series of epidemiological data.

Structural features and the heterogeneity of disease transmissions play an essential role in the dynamics of epidemic spread. But these aspects can not completely be assessed from aggregate data or macroscopic indicators such as the effective reproduction number. We propose in this paper an index of effective aggregate dispersion (EffDI) that indicates the significance of infection clusters and superspreading events in the progression of outbreaks by carefully measuring the level of relative stochasticity in time series of reported case numbers using a specially crafted statistical model for reproduction. This allows to detect potential transitions from predominantly clustered spreading to a diffusive regime with diminishing significance of singular clusters, which can be a decisive turning point in the progression of outbreaks and relevant in the planning of containment measures. We evaluate EffDI for SARS-CoV-2 case data in different countries and compare the results with a quantifier for the socio-demographic heterogeneity in disease transmissions in a case study to substantiate that EffDI qualifies as a measure for the heterogeneity in transmission dynamics.

Prevalence of New-Onset Tinnitus after COVID-19 Vaccination with Comparison to Other Vaccinations.

OBJECTIVE: To investigate how often patients are diagnosed with new-onset tinnitus within 21 days after COVID-19 vaccination in comparison to after three other common vaccinations: influenza, Tdap (tetanus, diphtheria, and acellular pertussis), and polysaccharide pneumococcus. METHODS: The TriNetX Analytics Network, a federated health research network that aggregates the de-identified electronic health record (EHR) data of over 78 million patients, was queried for patients receiving each vaccination. Instances of new-onset tinnitus within 21 days of vaccination were recorded and reported. RESULTS: Out of 2,575,235 patients receiving a first dose of the mRNA COVID-19 vaccine without any prior tinnitus diagnosis, 0.038% (95% CI: 0.036%-0.041%) of patients had a new diagnosis of tinnitus within 21 days. There was a higher risk of a new tinnitus diagnosis after the influenza vaccine (RR: 1.95, 95% CI: 1.72-2.21), Tdap vaccine (RR: 2.36, 95% CI: 1.93-2.89), and pneumococcal vaccine (RR: 1.97, 95% CI: 1.48-2.64) than after the first dose of the COVID-19 vaccine. There was a lower risk of a new tinnitus diagnosis after the second dose of COVID-19 than after the first dose (RR: 0.80, 95% CI: 0.71-0.91). CONCLUSION: The rate of newly diagnosed tinnitus acutely after the first dose of the COVID-19 vaccine is very low. There was a higher risk of newly diagnosed tinnitus after influenza, Tdap, and pneumococcal vaccinations than after the COVID-19 vaccine. The present findings can help to address COVID-19 vaccine hesitancy during the ongoing pandemic. LEVEL OF EVIDENCE: Level 3 Laryngoscope, 2022.

Uncoupling of platelet granule release and integrin activation suggests GPIIb/IIIa as therapeutic target in COVID-19.

Thromboembolic events are frequent and life-threating complications of COVID 19, but are also observed in patients with sepsis. Disseminated thrombosis can occur despite anticoagulation, suggesting that platelets play a direct, but yet incompletely understood role. Several studies demonstrated altered platelet function in COVID 19 with in part controversial findings, while underlying disease-specific mechanisms remain ill-defined. We performed a comprehensive cohort study with 111 patients, comprising 37 with COVID-19, 46 with sepsis, and 28 with infection, compared to controls. Platelet phenotype and function were assessed under static and flow conditions, revealing unexpected disease-specific differences. From hospital admission on, platelets in COVID-19 failed to activate integrin GPIIb/IIIa in response to multiple agonists. Dense granule release was markedly impaired due to virtually missing granules, also demonstrated by whole mount electron microscopy. In contrast, alpha-granule marker CD62P exposure was only mildly affected, revealing a subpopulation of PAC-1-/CD62P+ platelets, independently confirmed by automated clustering. This uncoupling of alpha-granule release was not observed in sepsis patients, despite a similar disease severity. We found overall unaltered thrombus formation in COVID 19 and sepsis samples under venous shear rates, which was dependent on the presence of tissue factor. Unexpectedly, under arterial shear rates thrombus formation was virtually abrogated in sepsis, while we detected overall normal-sized and stable thrombi in blood from COVID-19 patients. These thrombi were susceptible to subthreshold levels of GPIIb/IIIa blockers eptifibatide or tirofiban that had only a minor effect in control blood. We provide evidence that low dose GPIIb/IIIa blockade could be a therapeutic approach in COVID-19.

Virus-Like Particles Are Efficient Tools for Boosting mRNA-Induced Antibodies.

mRNA based vaccines against COVID-19 have proven most successful at keeping SARS-CoV-2 pandemic at bay in many countries. Recently, there is an increased interest in heterologous prime-boost vaccination strategies for COVID-19 to maintain antibody responses for the control of continuously emerging SARS-CoV-2 variants of concern (VoCs) and to overcome other obstacles such as supply shortage, costs and reduced safety issues or inadequatly induced immune-responses. In this study, we investigated the antibody responses induced by heterologous prime-boost with vaccines based on mRNA and virus-like particles (VLPs). The VLP-based mCuMVTT-RBM vaccine candidate and the approved mRNA-1273 vaccine were used for this purpose. We find that homologous prime boost regimens with either mRNA or VLP induced high levels of high avidity antibodies. Optimal antibody responses were, however, induced by heterologous regimens both for priming with mRNA and boosting with VLP and vice versa, priming with VLP and boosting with mRNA. Thus, heterologous prime boost strategies may be able to optimize efficacy and economics of novel vaccine strategies.

Vagus nerve inflammation contributes to dysautonomia in COVID-19 (preprint)

Dysautonomia has substantially impacted acute COVID-19 severity as well as symptom burden after recovery from COVID-19 (long COVID), yet the underlying causes remain unknown. Here, we show that SARS-CoV-2 is detectable in postmortem vagus nerve specimen together with inflammatory cell infiltration derived primarily from monocytes. This is associated with a decreased respiratory rate in non-survivors of critical COVID-19. Our data suggest that SARS-CoV-2 induces vagus nerve inflammation followed by autonomic dysfunction.

The impact of the COVID-19 pandemic on the health and working conditions of nurses and its implications for policies: a cross-sectional study in Slovakia.

BACKGROUND: Increased workload and of the health workforce (HW) strained the capacity to maintain essential health services (EHS) during the Coronavirus Disease 2019 (COVID-19) pandemic, while putting them at increased risk of COVID-19 and other consequences to their health. The aim of this study was to assess the impact of COVID-19 on the health, wellbeing, and working conditions of nurses in Slovakia and to identify gaps in policies to be addressed to increase preparedness of the HW for future emergencies. METHODS: A nation-wide cross-sectional study was conducted among nurses during November-December 2021, referring to the period of January 2021 to November 2021. To assess the differences between impact on HW on various levels of care, respondents were grouped by type of facility: hospital-COVID-19 wards; Hospital-non-covid ward; Outpatient or ER; Other care facilities. RESULTS: 1170 nurses participated, about 1/3 of them tested positive for COVID-19 by November 2021, mostly developing mild disease. Almost 2/3 reported long-covid symptoms and about 13% reported that they do not plan to get vaccinated against COVID-19. The median of the score of the impact of workload on health was 2.8 (56% of the maximum 5), the median score of mental health-wellbeing was 1.9 (63% of a maximum of 3). The studied impacts in all domains were highest in nurses working in COVID-19 hospital wards. Significant disruptions of health care were reported, with relatively high use of telemedicine to mitigate them. Overall, about 70% of the respondents thought of leaving their job, mostly due to working stress or inadequate pay. CONCLUSIONS: Our study showed that the COVID-19 pandemic poses a substantial burden on the health, wellbeing and working conditions of nurses in Slovakia and that a large proportion of nurses considered leaving their jobs because of work overload or low salaries. Human resource strategies should be adopted to attract, retain and continuously invest in HW development including in emergency preparedness and response. Such an approach may improve the resilience and preparedness of the health system in Slovakia for future emergencies.

New-Onset Atrial Fibrillation in the Setting of COVID-19 Infection Is a Predictor of Mortality in Hospitalized Patients: CovAF-Study.

Recent studies show that hospitalized COVID-19 patients have an increased incidence of arrhythmia, especially atrial fibrillation (AF). This single-center study included 383 hospitalized patients with positive polymerase chain reaction tests for COVID-19 from March 2020 to April 2021. Patient characteristics were documented, and data were analyzed for episodes of AF on admission or during the hospital stay, intrahospital mortality, need for intensive care and/or invasive ventilation, inflammatory parameters (hs-CRP, IL-6, and procalcitonin), and differential blood count. We demonstrated that in the setting of hospitalized cases of COVID-19 infection, there is an incidence of 9.8% (n = 36) for the occurrence of new-onset AF. Furthermore, it was shown that a total of 21% (n = 77) had a history of episodes of paroxysmal/persistent AF. However, only about one-third of patients with pre-existing AF had relevant documented tachycardic episodes during the hospital stay. Patients with new-onset AF had a significantly increased intrahospital mortality compared to the control and the pre-existing AF without rapid ventricular rate (RVR) group. Patients with new-onset AF required intensive care and invasive ventilation more frequently. Further analysis examined patients with episodes of RVR and demonstrated that they had significantly elevated CRP (p < 0.05) and PCT (p < 0.05) levels on the day of hospital admission compared to patients without RVR.