Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stages.

COVID-19 has been spreading widely since January 2020, prompting the implementation of non-pharmaceutical interventions and vaccinations to prevent overwhelming the healthcare system. Our study models four waves of the epidemic in Munich over two years using a deterministic, biology-based mathematical model of SEIR type that incorporates both non-pharmaceutical interventions and vaccinations. We analyzed incidence and hospitalization data from Munich hospitals and used a two-step approach to fit the model parameters: first, we modeled incidence without hospitalization, and then we extended the model to include hospitalization compartments using the previous estimates as a starting point. For the first two waves, changes in key parameters, such as contact reduction and increasing vaccinations, were enough to represent the data. For wave three, the introduction of vaccination compartments was essential. In wave four, reducing contacts and increasing vaccinations were critical parameters for controlling infections. The importance of hospitalization data was highlighted, as it should have been included as a crucial parameter from the outset, along with incidence, to avoid miscommunication with the public. The emergence of milder variants like Omicron and a significant proportion of vaccinated people has made this fact even more evident.

Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contacts.

Mathematical models have been widely used during the ongoing SARS-CoV-2 pandemic for data interpretation, forecasting, and policy making. However, most models are based on officially reported case numbers, which depend on test availability and test strategies. The time dependence of these factors renders interpretation difficult and might even result in estimation biases. Here, we present a computational modelling framework that allows for the integration of reported case numbers with seroprevalence estimates obtained from representative population cohorts. To account for the time dependence of infection and testing rates, we embed flexible splines in an epidemiological model. The parameters of these splines are estimated, along with the other parameters, from the available data using a Bayesian approach. The application of this approach to the official case numbers reported for Munich (Germany) and the seroprevalence reported by the prospective COVID-19 Cohort Munich (KoCo19) provides first estimates for the time dependence of the under-reporting factor. Furthermore, we estimate how the effectiveness of non-pharmaceutical interventions and of the testing strategy evolves over time. Overall, our results show that the integration of temporally highly resolved and representative data is beneficial for accurate epidemiological analyses.

[Treatment of sepsis-induced coagulopathy : Results of a Germany-wide survey in intensive care units]. / Therapie der sepsisinduzierten Koagulopathie : Ergebnisse einer deutschlandweiten Umfrage auf Intensivstationen.

BACKGROUND: In the context of sepsis and septic shock, coagulopathy often occurs due to the close relationship between coagulation and inflammation. Sepsis-induced coagulopathy (SIC) is the most severe and potentially fatal form. Anticoagulants used in prophylactic or therapeutic doses are discussed to potentially exert beneficial effects in patients with sepsis and/or SIC; however, due to the lack of evidence recent guidelines are limited to recommendations for drug prophylaxis of venous thromboembolism (VTE), while treatment of SIC has not been addressed. METHODS: In order to determine the status quo of VTE prophylaxis as well as treatment of SIC in German intensive care units (ICU), we conducted a Germany-wide online survey among heads of ICUs from October 2019 to May 2020. In April 2020, the survey was supplemented by an additional block of questions on VTE prophylaxis and SIC treatment in coronavirus disease 2019 (COVID-19) patients. RESULTS: A total of 67 senior doctors took part in the survey. The majority (n = 50; 74.6%) of the responses were from ICU under the direction of an anesthesiologist and/or a department of anesthesiology. Most of the participants worked either at a university hospital (n = 31; 47.8%) or an academic teaching hospital (n = 27; 40.3%). The survey results show a pronounced heterogeneity in clinical practice with respect to the prophylaxis of VTE as well as SIC treatment. In an exemplary case of pneumogenic sepsis, low molecular weight heparins (LMWH) were by far the most frequently mentioned group of medications (n = 51; 76.1% of the responding ITS). In the majority of cases (n = 43; 64.2%), anti-FXa activity is not monitored with the use of LMWH in prophylaxis doses. Unfractionated heparin (UFH) was listed as a strategy for VTE prophylaxis in 37.3% of the responses (n = 25). In an exemplary case of abdominal sepsis 54.5% of the participants (n = 36; multiple answers possible) stated the use of UFH or LMWH and UFH with dosage controlled by PTT is used on two participating ICUs. The anti-FXa activity under prophylactic anticoagulation with LMWH is monitored in 7 participating clinics (10.6%) in abdominal sepsis. Systematic screening for sepsis-associated coagulation disorders does not take place in most hospitals and patterns in the use of anticoagulants show significant variability between ICUs. In the case of COVID-19 patients, it is particularly noticeable that in three quarters of the participating ICUs the practice of drug-based VTE prophylaxis and SIC treatment does not differ from that of non-COVID-19 patients. CONCLUSION: The heterogeneity of answers collected in the survey suggests that a systematic approach to this topic via clinical trials is urgently needed to underline individualized patient care with the necessary evidence.

Anthropometric analysis of body habitus and outcomes in critically ill COVID-19 patients.

AIMS: This study aimed to determine whether anthropometric markers of thoracic skeletal muscle and abdominal visceral fat tissue correlate with outcome parameters in critically ill COVID-19 patients. METHODS: We retrospectively analysed thoracic CT-scans of 67 patients in four ICUs at a university hospital. Thoracic skeletal muscle (total cross-sectional area (CSA); pectoralis muscle area (PMA)) and abdominal visceral fat tissue (VAT) were quantified using a semi-automated method. Point-biserial-correlation-coefficient, Spearman-correlation-coefficient, Wilcoxon rank-sum test and logistic regression were used to assess the correlation and test for differences between anthropometric parameters and death, ventilator- and ICU-free days and initial inflammatory laboratory values. RESULTS: Deceased patients had lower CSA and PMA values, but higher VAT values (p < 0.001). Male patients with higher CSA values had more ventilator-free days (p = 0.047) and ICU-free days (p = 0.017). Higher VAT/CSA and VAT/PMA values were associated with higher mortality (p < 0.001), but were negatively correlated with ICU length of stay in female patients only (p < 0.016). There was no association between anthropometric parameters and initial inflammatory biomarker levels. Logistic regression revealed no significant independent predictor for death. CONCLUSION: Our study suggests that pathologic body composition assessed by planimetric measurements using thoracic CT-scans is associated with worse outcome in critically ill COVID-19 patients.

Repurposing existing medications for coronavirus disease 2019: protocol for a rapid and living systematic review.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has no confirmed specific treatments. However, there might be in vitro and early clinical data as well as evidence from severe acute respiratory syndrome and Middle Eastern respiratory syndrome that could inform clinicians and researchers. This systematic review aims to create priorities for future research of drugs repurposed for COVID-19. METHODS: This systematic review will include in vitro, animal, and clinical studies evaluating the efficacy of a list of 34 specific compounds and 4 groups of drugs identified in a previous scoping review. Studies will be identified both from traditional literature databases and pre-print servers. Outcomes assessed will include time to clinical improvement, time to viral clearance, mortality, length of hospital stay, and proportions transferred to the intensive care unit and intubated, respectively. We will use the GRADE methodology to assess the quality of the evidence. DISCUSSION: The challenge posed by COVID-19 requires not just a rapid review of drugs that can be repurposed but also a sustained effort to integrate new evidence into a living systematic review. TRIAL REGISTRATION: PROSPERO 2020 CRD42020175648.