Integrase strand transfer inhibitor (INSTI) related changes in BMI and risk of diabetes: a prospective study from the RESPOND cohort consortium.

BACKGROUND: With integrase strand transfer inhibitor (INSTI) use associated with increased body mass index (BMI) and BMI increases associated with higher diabetes mellitus (DM) risk, this study explored the relationship between INSTI/non-INSTI regimens, BMI changes, and DM risk. METHODS: RESPOND participants were included if they had CD4, HIV RNA, and ≥ 2 BMI measurements during follow up. Those with prior DM were excluded. DM was defined as a random blood glucose ≥ 11·1 mmol/L, HbA1c ≥ 6·5%/48 mmol/mol, use of antidiabetic medication, or site reported clinical diagnosis. Poisson regression assessed the association between natural log (ln) of time-updated BMI, current INSTI/non-INSTI, and their interactions, on DM risk. RESULTS: Among 20,865 people with HIV included, most were male (74%) and White (73%). Baseline median age was 45 years (IQR 37-52), with a median BMI of 24 kg/m2 (IQR 22-26). There were 785 DM diagnoses with a crude rate of 0·73 (95%CI 0·68-0·78)/100 PYFU. Ln(BMI) was strongly associated with DM (adjusted incidence rate ratio (aIRR) 16·54 per log increase, 95%CI 11·33-24·13; p<0·001). Current INSTI use associated with increased DM risk (IRR 1·58, 95%CI 1·37-1·82; p<0·001) in univariate analyses, only partially attenuated when adjusted for variables including ln(BMI) (aIRR 1·48, 95%CI 1·29-1·71; p<0·001). There was no interaction between ln(BMI), INSTI and non-INSTI use, and DM (p=0·130). CONCLUSIONS: In RESPOND, compared with non-INSTIs, current use of INSTIs was associated with an increased DM risk, which partially attenuated when adjusted for BMI changes and other variables.

Incidence and risk factors for HIV-tuberculosis coinfection in the Cologne-Bonn region: a retrospective cohort study.

PURPOSE: The risk of developing active tuberculosis (TB) is considerably increased in people living with HIV/AIDS (PLWH). However, incidence of HIV/TB coinfection is difficult to assess as surveillance data are lacking in many countries. Here, we aimed to perform a quantitative analysis of HIV/TB coinfections within the Cologne/Bonn HIV cohort and to determine risk factors for active TB. METHODS: We systematically evaluated data of patients with HIV/TB coinfection between 2006 and 2017. In this retrospective analysis, we compared HIV/TB-coinfected patients with a cohort of HIV-positive patients. The incidence density rate (IDR) was calculated for active TB cases at different time points. RESULTS: During 2006-2017, 60 out of 4673 PLWH were diagnosed with active TB. Overall IDR was 0.181 cases/100 patient-years and ranged from 0.266 in 2006-2009 to 0.133 in 2014-2017. Patients originating from Sub-Saharan Africa had a significantly (p < 0.001) higher IDR (0.694/100 patient-years of observation, 95% CI [0.435-1.050]) in comparison to patients of German origin (0.053/100 patient-years of observation, 95% CI [0.028-0.091]). In terms of TB-free survival, individuals originating from countries with a TB incidence higher than 10/100,000 exhibited a markedly reduced TB-free survival compared to those originating from regions with lower incidence (p < 0.001). In 22 patients, TB and HIV infection were diagnosed simultaneously. CONCLUSION: Overall, we observed a decline in the incidence density rate (IDR) of HIV/TB coinfections between 2006 and 2017. Patients originating from regions with high incidence bear a higher risk of falling ill with active TB. For PLWH born in Germany, the observed risk of active TB appears to be lower compared to other groups within the cohort. These findings should be considered when developing TB containment and screening strategies for PLWH in low-incidence countries.

Role and benefits of infectious diseases specialists in the COVID-19 pandemic: Multilevel analysis of care provision in German hospitals using data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) cohort.

PURPOSE: This study investigates the care provision and the role of infectious disease (ID) specialists during the coronavirus disease-2019 (COVID-19) pandemic. METHODS: A survey was conducted at German study sites participating in the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS). Hospitals certified by the German Society of Infectious diseases (DGI) were identified as ID centers. We compared care provision and the involvement of ID specialists between ID and non-ID hospitals. Then we applied a multivariable regression model to analyse how clinical ID care influenced the mortality of COVID-19 patients in the LEOSS cohort. RESULTS: Of the 40 participating hospitals in the study, 35% (14/40) were identified as ID centers. Among those, clinical ID care structures were more commonly established, and ID specialists were always involved in pandemic management and the care of COVID-19 patients. Overall, 68% (27/40) of the hospitals involved ID specialists in the crisis management team, 78% (31/40) in normal inpatient care, and 80% (28/35) in intensive care. Multivariable analysis revealed that COVID-19 patients in ID centers had a lower mortality risk compared to those in non-ID centers (odds ratio: 0.61 (95% CI 0.40-0.93), p = 0.021). CONCLUSION: ID specialists played a crucial role in pandemic management and inpatient care.

Estimating vaccine effectiveness against COVID-19 using cause-specific sick leave as an indicator: a nationwide population-based cohort study, Norway, July 2021 - December 2022.

BACKGROUND: Due to changes in testing policy and increased use of rapid tests, other indicators for SARS-CoV-2 infections are needed to monitor vaccine effectiveness (VE). We aimed to estimate VE against COVID-19 sick leave (> 3 days, certified by a medical professional) among employed individuals (25-64-years-old) in Norway. METHODS: We performed a nationwide cohort study by collating data from the Emergency preparedness register for COVID-19. We used adjusted Cox proportional hazard models with vaccine status as a time-varying covariate and presented results as adjusted hazard ratios (aHRs) with corresponding 95% confidence intervals. Separate models were run against sick leave and against SARS-CoV-2 infections during the Delta period (June-December 2021), and against sick leave during the Omicron period (January-December 2022) when SARS-CoV-2 PCR-testing was replaced by rapid self-tests and infections were underreported. RESULTS: We included 2,236,419 individuals during the Delta period, of whom 73,776 (3.3%) had a reported infection and 54,334 (2.4%) were registered with sick leave. Of the 2,206,952 included individuals in the Omicron period, 300,140 (13.6%) were registered with sick leave. During the Delta period, 55% (26,611) of individuals who had registered sick leave also had a positive test, compared to 32% (96,445) during the Omicron period. The VE against sick leave during the Delta period followed a similar waning pattern to that against SARS-CoV-2 infections. After the second and third dose, the lowest aHRs were estimated for 2-7 days after vaccination for both sick leave (0.25; 95%CI 0.24-0.26 and 0.26; 95% CI 0.24-0.29) and infection ( 0.16; 95% CI 0.15-0.17 and 0.18; 95% CI 0.16-0.19) respectively. During the Omicron period, aHRs for sick leave were higher than during the Delta period, but the lowest aHRs were still found in 2-7 weeks after receiving the second (0.61; 95% CI 0.59-0.64) or third dose (0.63; 95% CI 0.62-0.64). CONCLUSION: Our results showed that sick leave could be a relevant indicator for VE in the surveillance of COVID-19 and a finding that may be important in the surveillance of other respiratory infection.

[Integration of Inventory Data from Cohort and Registry Studies into an Existing Research Network: National Pandemic Cohort Network (NAPKON)]. / Integration von Bestandsdaten aus Kohorten- und Registerstudien in ein existierendes Forschungsnetzwerk: Nationales Pandemie Kohorten Netz (NAPKON).

In the early phase of the COVID-19 pandemic, many local collections of clinical data on patients infected with SARS-CoV-2 were initiated in Germany. As part of the National Pandemic Cohort Network (NAPKON) of the University Medicine Network, the "Integration Core" was established to design the legal, technical and organisational requirements for the integration of inventory data into ongoing prospective data collections and to test the feasibility of the newly developed solutions using use cases (UCs). Detailed study documents of the data collections were obtained. After structured document analysis, a review board evaluated the integrability of the data in NAPKON according to defined criteria. Of 30 university hospitals contacted, 20 responded to the request. Patient information and consent showed a heterogeneous picture with regard to the pseudonymised transfer of data to third parties and re-contact. The majority of the data collections (n=13) met the criteria for integration into NAPKON; four studies would require adjustments to the regulatory documents. Three cohorts were not suitable for inclusion in NAPKON. The legal framework for retrospective data integration and consent-free data use via research clauses (§27 BDSG) was elaborated by a legal opinion by TMF - Technology, Methods and Infrastructure for Networked Medical Research, Berlin. Two UCs selected by the NAPKON steering committee (CORKUM, LMU Munich; Pa-COVID-19, Charité- Universitätsmedizin Berlin) were used to demonstrate the feasibility of data integration in NAPKON by the end of 2021. Quality assurance and performance-based reimbursement of the cases were carried out according to the specifications. Based on the results, recommendations can be formulated for various contexts in order to create technical-operational prerequisites such as interoperability, interfaces and data models for data integration and to fulfil regulatory requirements on ethics, data protection, medical confidentiality and data access when integrating existing cohort data. The possible integration of data into research networks and their secondary use should be taken into account as early as the planning phase of a study - particularly with regard to informed consent - in order to maximise the benefits of the data collected.

Plasma Human Immunodeficiency Virus 1 RNA and CD4+ T-Cell Counts Are Determinants of Virological Nonsuppression Outcomes With Initial Integrase Inhibitor-Based Regimens: A Prospective RESPOND Cohort Study.

BACKGROUND: There are conflicting data regarding baseline determinants of virological nonsuppression outcomes in persons with human immunodeficiency virus (HIV) starting antiretroviral treatment (ART). We evaluated the impact of different baseline variables in the RESPOND cohort. METHODS: We included treatment-naive participants aged ≥18 who initiated 3-drug ART, in 2014-2020. We assessed the odds of virological suppression (VS) at weeks 48 and 96 using logistic regression. Viral blips, low-level viremia (LLV), residual viremia (RV), and virological failure (VF) rates were assessed using Cox regression. RESULTS: Of 4310 eligible participants, 72% started integrase strand transfer inhibitor (INSTI)-based regimens. At 48 and 96 weeks, 91.0% and 93.3% achieved VS, respectively. At 48 weeks, Kaplan-Meier estimates of rates were 9.6% for viral blips, 2.1% for LLV, 22.2% for RV, and 2.1% for VF. Baseline HIV-1 RNA levels >100 000 copies/mL and CD4+ T-cell counts ≤200/µL were negatively associated with VS at weeks 48 (adjusted odds ratio, 0.51 [95% confidence interval, .39-.68] and .40 [.27-.58], respectively) and 96 and with significantly higher rates of blips, LLV, and RV. CD4+ T-cell counts ≤200/µL were associated with higher risk of VF (adjusted hazard ratio, 3.12 [95% confidence interval, 2.02-4.83]). Results were consistent in those starting INSTIs versus other regimens and those starting dolutegravir versus other INSTIs. CONCLUSIONS: Initial high HIV-1 RNA and low CD4+ T-cell counts are associated with lower rates of VS at 48 and 96 weeks and higher rates of viral blips, LLV, and RV. Low baseline CD4+ T-cell counts are associated with higher VF rates. These associations remain with INSTI-based and specifically with dolutegravir-based regimens. These findings suggest that the impact of these baseline determinants is independent of the ART regimen initiated.

SARS-CoV-2 infection in chronic kidney disease patients with pre-existing dialysis: description across different pandemic intervals and effect on disease course (mortality).

PURPOSE: Patients suffering from chronic kidney disease (CKD) are in general at high risk for severe coronavirus disease (COVID-19) but dialysis-dependency (CKD5D) is poorly understood. We aimed to describe CKD5D patients in the different intervals of the pandemic and to evaluate pre-existing dialysis dependency as a potential risk factor for mortality. METHODS: In this multicentre cohort study, data from German study sites of the Lean European Open Survey on SARS-CoV-2-infected patients (LEOSS) were used. We multiply imputed missing data, performed subsequent analyses in each of the imputed data sets and pooled the results. Cases (CKD5D) and controls (CKD not requiring dialysis) were matched 1:1 by propensity-scoring. Effects on fatal outcome were calculated by multivariable logistic regression. RESULTS: The cohort consisted of 207 patients suffering from CKD5D and 964 potential controls. Multivariable regression of the whole cohort identified age (> 85 years adjusted odds ratio (aOR) 7.34, 95% CI 2.45-21.99), chronic heart failure (aOR 1.67, 95% CI 1.25-2.23), coronary artery disease (aOR 1.41, 95% CI 1.05-1.89) and active oncological disease (aOR 1.73, 95% CI 1.07-2.80) as risk factors for fatal outcome. Dialysis-dependency was not associated with a fatal outcome-neither in this analysis (aOR 1.08, 95% CI 0.75-1.54) nor in the conditional multivariable regression after matching (aOR 1.34, 95% CI 0.70-2.59). CONCLUSIONS: In the present multicentre German cohort, dialysis dependency is not linked to fatal outcome in SARS-CoV-2-infected CKD patients. However, the mortality rate of 26% demonstrates that CKD patients are an extreme vulnerable population, irrespective of pre-existing dialysis-dependency.

Use and effectiveness of remdesivir for the treatment of patients with covid-19 using data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS): a multicentre cohort study.

OBJECTIVES: The use of remdesivir (RDV) as the first drug approved for coronavirus disease 2019 (COVID-19) remains controversial. Based on the Lean European Open Survey on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infected patients (LEOSS), we aim to contribute timing-focused complementary real-world insights to its evaluation. METHODS: SARS-CoV-2 infected patients between January 2020 and December 2021 treated with RDV were matched 1:1 to controls considering sociodemographics, comorbidities and clinical status. Multiple imputations were used to account for missing data. Effects on fatal outcome were estimated using uni- and multivariable Cox regression models. RESULTS: We included 9,687 patients. For those starting RDV administration in the complicated phase, Cox regression for fatal outcome showed an adjusted hazard ratio (aHR) of 0.59 (95%CI 0.41-0.83). Positive trends could be obtained for further scenarios: an aHR of 0.51 (95%CI 0.16-1.68) when RDV was initiated in uncomplicated and of 0.76 (95% CI 0.55-1.04) in a critical phase of disease. Patients receiving RDV with concomitant steroids exhibited a further reduction in aHR in both, the complicated (aHR 0.50, 95%CI 0.29-0.88) and critical phase (aHR 0.63, 95%CI 0.39-1.02). CONCLUSION: Our study results elucidate that RDV use, in particular when initiated in the complicated phase and accompanied by steroids is associated with improved mortality. However, given the limitations of non-randomized trials in estimating the magnitude of the benefit of an intervention, further randomized trials focusing on the timing of therapy initiation seem warranted.

Disease severity in hospitalized COVID-19 patients: comparing routine surveillance with cohort data from the LEOSS study in 2020 in Germany.

INTRODUCTION: Studies investigating risk factors for severe COVID-19 often lack information on the representativeness of the study population. Here, we investigate factors associated with severe COVID-19 and compare the representativeness of the dataset to the general population. METHODS: We used data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) of hospitalized COVID-19 patients diagnosed in 2020 in Germany to identify associated factors for severe COVID-19, defined as progressing to a critical disease stage or death. To assess the representativeness, we compared the LEOSS cohort to cases of hospitalized patients in the German statutory notification data of the same time period. Descriptive methods and Poisson regression models were used. RESULTS: Overall, 6672 hospitalized patients from LEOSS and 132,943 hospitalized cases from the German statutory notification data were included. In LEOSS, patients above 76 years were less likely represented (34.3% vs. 44.1%). Moreover, mortality was lower (14.3% vs. 21.5%) especially among age groups above 66 years. Factors associated with a severe COVID-19 disease course in LEOSS included increasing age, male sex (adjusted risk ratio (aRR) 1.69, 95% confidence interval (CI) 1.53-1.86), prior stem cell transplantation (aRR 2.27, 95% CI 1.53-3.38), and an elevated C-reactive protein at day of diagnosis (aRR 2.30, 95% CI 2.03-2.62). CONCLUSION: We identified a broad range of factors associated with severe COVID-19 progression. However, the results may be less applicable for persons above 66 years since they experienced lower mortality in the LEOSS dataset compared to the statutory notification data.

Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways.

The Covid-19 pandemic has pushed many hospitals to their capacity limits. Therefore, a triage of patients has been discussed controversially primarily through an ethical perspective. The term triage contains many aspects such as urgency of treatment, severity of the disease and pre-existing conditions, access to critical care, or the classification of patients regarding subsequent clinical pathways starting from the emergency department. The determination of the pathways is important not only for patient care, but also for capacity planning in hospitals. We examine the performance of a human-made triage algorithm for clinical pathways which is considered a guideline for emergency departments in Germany based on a large multicenter dataset with over 4,000 European Covid-19 patients from the LEOSS registry. We find an accuracy of 28 percent and approximately 15 percent sensitivity for the ward class. The results serve as a benchmark for our extensions including an additional category of palliative care as a new label, analytics, AI, XAI, and interactive techniques. We find significant potential of analytics and AI in Covid-19 triage regarding accuracy, sensitivity, and other performance metrics whilst our interactive human-AI algorithm shows superior performance with approximately 73 percent accuracy and up to 76 percent sensitivity. The results are independent of the data preparation process regarding the imputation of missing values or grouping of comorbidities. In addition, we find that the consideration of an additional label palliative care does not improve the results.