A precise performance-based reimbursement model for the multi-centre NAPKON cohorts - development and evaluation.

Fair allocation of funding in multi-centre clinical studies is challenging. Models commonly used in Germany - the case fees ("fixed-rate model", FRM) and up-front staffing and consumables ("up-front allocation model", UFAM) lack transparency and fail to suitably accommodate variations in centre performance. We developed a performance-based reimbursement model (PBRM) with automated calculation of conducted activities and applied it to the cohorts of the National Pandemic Cohort Network (NAPKON) within the Network of University Medicine (NUM). The study protocol activities, which were derived from data management systems, underwent validation through standardized quality checks by multiple stakeholders. The PBRM output (first funding period) was compared among centres and cohorts, and the cost-efficiency of the models was evaluated. Cases per centre varied from one to 164. The mean case reimbursement differed among the cohorts (1173.21€ [95% CI 645.68-1700.73] to 3863.43€ [95% CI 1468.89-6257.96]) and centres and mostly fell short of the expected amount. Model comparisons revealed higher cost-efficiency of the PBRM compared to FRM and UFAM, especially for low recruitment outliers. In conclusion, we have developed a reimbursement model that is transparent, accurate, and flexible. In multi-centre collaborations where heterogeneity between centres is expected, a PBRM could be used as a model to address performance discrepancies.Trial registration: https://clinicaltrials.gov/ct2/show/NCT04768998 ; https://clinicaltrials.gov/ct2/show/NCT04747366 ; https://clinicaltrials.gov/ct2/show/NCT04679584 .

Definition of the Post-COVID syndrome using a symptom-based Post-COVID score in a prospective, multi-center, cross-sectoral cohort of the German National Pandemic Cohort Network (NAPKON).

PURPOSE: The objective examination of the Post-COVID syndrome (PCS) remains difficult due to heterogeneous definitions and clinical phenotypes. The aim of the study was to verify the functionality and correlates of a recently developed PCS score. METHODS: The PCS score was applied to the prospective, multi-center cross-sectoral cohort (in- and outpatients with SARS-CoV-2 infection) of the "National Pandemic Cohort Network (NAPKON, Germany)". Symptom assessment and patient-reported outcome measure questionnaires were analyzed at 3 and 12 months (3/12MFU) after diagnosis. Scores indicative of PCS severity were compared and correlated to demographic and clinical characteristics as well as quality of life (QoL, EQ-5D-5L). RESULTS: Six hundred three patients (mean 54.0 years, 60.6% male, 82.0% hospitalized) were included. Among those, 35.7% (215) had no and 64.3% (388) had mild, moderate, or severe PCS. PCS severity groups differed considering sex and pre-existing respiratory diseases. 3MFU PCS worsened with clinical severity of acute infection (p = .011), and number of comorbidities (p = .004). PCS severity was associated with poor QoL at the 3MFU and 12MFU (p < .001). CONCLUSION: The PCS score correlated with patients' QoL and demonstrated to be instructive for clinical characterization and stratification across health care settings. Further studies should critically address the high prevalence, clinical relevance, and the role of comorbidities. TRAIL REGISTRATION NUMBER: The cohort is registered at www. CLINICALTRIALS: gov under NCT04768998.

Depression and fatigue six months post-COVID-19 disease are associated with overlapping symptom constellations: A prospective, multi-center, population-based cohort study.

BACKGROUND: Depression and fatigue are commonly observed sequelae following viral diseases such as COVID-19. Identifying symptom constellations that differentially classify post-COVID depression and fatigue may be helpful to individualize treatment strategies. Here, we investigated whether self-reported post-COVID depression and post-COVID fatigue are associated with the same or different symptom constellations. METHODS: To address this question, we used data from COVIDOM, a population-based cohort study conducted as part of the NAPKON-POP platform. Data were collected in three different German regions (Kiel, Berlin, Würzburg). We analyzed data from >2000 individuals at least six months past a PCR-confirmed COVID-19 disease, using elastic net regression and cluster analysis. The regression model was developed in the Kiel data set, and externally validated using data sets from Berlin and Würzburg. RESULTS: Our results revealed that post-COVID depression and fatigue are associated with overlapping symptom constellations consisting of difficulties with daily activities, perceived health-related quality of life, chronic exhaustion, unrestful sleep, and impaired concentration. Confirming the overlap in symptom constellations, a follow-up cluster analysis could categorize individuals as scoring high or low on depression and fatigue but could not differentiate between both dimensions. LIMITATIONS: The data presented are cross-sectional, consisting primarily of self-reported questionnaire or medical records rather than biometric data. CONCLUSIONS: In summary, our results suggest a strong link between post-COVID depression and fatigue, highlighting the need for integrative treatment approaches.

Estimates of protection levels against SARS-CoV-2 infection and severe COVID-19 in Germany before the 2022/2023 winter season: the IMMUNEBRIDGE project.

PURPOSE: Despite the need to generate valid and reliable estimates of protection levels against SARS-CoV-2 infection and severe course of COVID-19 for the German population in summer 2022, there was a lack of systematically collected population-based data allowing for the assessment of the protection level in real time. METHODS: In the IMMUNEBRIDGE project, we harmonised data and biosamples for nine population-/hospital-based studies (total number of participants n = 33,637) to provide estimates for protection levels against SARS-CoV-2 infection and severe COVID-19 between June and November 2022. Based on evidence synthesis, we formed a combined endpoint of protection levels based on the number of self-reported infections/vaccinations in combination with nucleocapsid/spike antibody responses ("confirmed exposures"). Four confirmed exposures represented the highest protection level, and no exposure represented the lowest. RESULTS: Most participants were seropositive against the spike antigen; 37% of the participants ≥ 79 years had less than four confirmed exposures (highest level of protection) and 5% less than three. In the subgroup of participants with comorbidities, 46-56% had less than four confirmed exposures. We found major heterogeneity across federal states, with 4-28% of participants having less than three confirmed exposures. CONCLUSION: Using serological analyses, literature synthesis and infection dynamics during the survey period, we observed moderate to high levels of protection against severe COVID-19, whereas the protection against SARS-CoV-2 infection was low across all age groups. We found relevant protection gaps in the oldest age group and amongst individuals with comorbidities, indicating a need for additional protective measures in these groups.

Differential network interactions between psychosocial factors, mental health, and health-related quality of life in women and men.

Psychosocial factors affect mental health and health-related quality of life (HRQL) in a complex manner, yet gender differences in these interactions remain poorly understood. We investigated whether psychosocial factors such as social support and personal and work-related concerns impact mental health and HRQL differentially in women and men during the first year of the COVID-19 pandemic. Between June and October 2020, the first part of a COVID-19-specific program was conducted within the "Characteristics and Course of Heart Failure Stages A-B and Determinants of Progression (STAAB)" cohort study, a representative age- and gender-stratified sample of the general population of Würzburg, Germany. Using psychometric networks, we first established the complex relations between personal social support, personal and work-related concerns, and their interactions with anxiety, depression, and HRQL. Second, we tested for gender differences by comparing expected influence, edge weight differences, and stability of the networks. The network comparison revealed a significant difference in the overall network structure. The male (N = 1370) but not the female network (N = 1520) showed a positive link between work-related concern and anxiety. In both networks, anxiety was the most central variable. These findings provide further evidence that the complex interplay of psychosocial factors with mental health and HRQL decisively depends on gender. Our results are relevant for the development of gender-specific interventions to increase resilience in times of pandemic crisis.

Consistency as a Data Quality Measure for German Corona Consensus Items Mapped from National Pandemic Cohort Network Data Collections.

BACKGROUND: As a national effort to better understand the current pandemic, three cohorts collect sociodemographic and clinical data from coronavirus disease 2019 (COVID-19) patients from different target populations within the German National Pandemic Cohort Network (NAPKON). Furthermore, the German Corona Consensus Dataset (GECCO) was introduced as a harmonized basic information model for COVID-19 patients in clinical routine. To compare the cohort data with other GECCO-based studies, data items are mapped to GECCO. As mapping from one information model to another is complex, an additional consistency evaluation of the mapped items is recommended to detect possible mapping issues or source data inconsistencies. OBJECTIVES: The goal of this work is to assure high consistency of research data mapped to the GECCO data model. In particular, it aims at identifying contradictions within interdependent GECCO data items of the German national COVID-19 cohorts to allow investigation of possible reasons for identified contradictions. We furthermore aim at enabling other researchers to easily perform data quality evaluation on GECCO-based datasets and adapt to similar data models. METHODS: All suitable data items from each of the three NAPKON cohorts are mapped to the GECCO items. A consistency assessment tool (dqGecco) is implemented, following the design of an existing quality assessment framework, retaining their-defined consistency taxonomies, including logical and empirical contradictions. Results of the assessment are verified independently on the primary data source. RESULTS: Our consistency assessment tool helped in correcting the mapping procedure and reveals remaining contradictory value combinations within COVID-19 symptoms, vital signs, and COVID-19 severity. Consistency rates differ between the different indicators and cohorts ranging from 95.84% up to 100%. CONCLUSION: An efficient and portable tool capable of discovering inconsistencies in the COVID-19 domain has been developed and applied to three different cohorts. As the GECCO dataset is employed in different platforms and studies, the tool can be directly applied there or adapted to similar information models.

Statistical biases due to anonymization evaluated in an open clinical dataset from COVID-19 patients.

Anonymization has the potential to foster the sharing of medical data. State-of-the-art methods use mathematical models to modify data to reduce privacy risks. However, the degree of protection must be balanced against the impact on statistical properties. We studied an extreme case of this trade-off: the statistical validity of an open medical dataset based on the German National Pandemic Cohort Network (NAPKON), which was prepared for publication using a strong anonymization procedure. Descriptive statistics and results of regression analyses were compared before and after anonymization of multiple variants of the original dataset. Despite significant differences in value distributions, the statistical bias was found to be small in all cases. In the regression analyses, the median absolute deviations of the estimated adjusted odds ratios for different sample sizes ranged from 0.01 [minimum = 0, maximum = 0.58] to 0.52 [minimum = 0.25, maximum = 0.91]. Disproportionate impact on the statistical properties of data is a common argument against the use of anonymization. Our analysis demonstrates that anonymization can actually preserve validity of statistical results in relatively low-dimensional data.

[Post COVID - Just a matter of definition?] / Post-COVID: Alles eine Frage der Definition?

The prevalence of post-COVID syndrome (PCS) has not yet been conclusively clarified. The existing definitions primarily reflect temporal aspects, but disregard functional deficits as well as the objectification of symptoms. This leads to diagnostic as well as therapeutic ambiguities. Pubmed was searched for systematic reviews dealing with the impact of SARS-CoV-2 infection. The underlying definitions as well as temporal inclusion criteria were extracted. 16 systematic reviews were included, 11 of which included a definition of PCS. In 58 % of the individual studies analyzed, patients with symptomatology > 12 weeks and thus according to the definition of PCS were included. CONCLUSION:: Further clarification of the definition of PCS is necessary to facilitate diagnosis and multimodal treatment and to use the scarce therapeutic resources accordingly.

Severity, predictors and clinical correlates of Post-COVID syndrome (PCS) in Germany: A prospective, multi-centre, population-based cohort study.

Background: Post-COVID syndrome (PCS) is an important sequela of COVID-19, characterised by symptom persistence for >3 months, post-acute symptom development, and worsening of pre-existing comorbidities. The causes and public health impact of PCS are still unclear, not least for the lack of efficient means to assess the presence and severity of PCS. Methods: COVIDOM is a population-based cohort study of polymerase chain reaction (PCR) confirmed cases of SARS-CoV-2 infection, recruited through public health authorities in three German regions (Kiel, Berlin, Würzburg) between November 15, 2020 and September 29, 2021. Main inclusion criteria were (i) a PCR confirmed SARS-CoV-2 infection and (ii) a period of at least 6 months between the infection and the visit to the COVIDOM study site. Other inclusion criteria were written informed consent and age ≥18 years. Key exclusion criterion was an acute reinfection with SARS-CoV-2. Study site visits included standardised interviews, in-depth examination, and biomaterial procurement. In sub-cohort Kiel-I, a PCS (severity) score was developed based upon 12 long-term symptom complexes. Two validation sub-cohorts (Würzburg/Berlin, Kiel-II) were used for PCS score replication and identification of clinically meaningful predictors. This study is registered at clinicaltrials.gov (NCT04679584) and at the German Registry for Clinical Studies (DRKS, DRKS00023742). Findings: In Kiel-I (n = 667, 57% women), 90% of participants had received outpatient treatment for acute COVID-19. Neurological ailments (61·5%), fatigue (57·1%), and sleep disturbance (57·0%) were the most frequent persisting symptoms at 6-12 months after infection. Across sub-cohorts (Würzburg/Berlin, n = 316, 52% women; Kiel-II, n = 459, 56% women), higher PCS scores were associated with lower health-related quality of life (EQ-5D-5L-VAS/-index: r = -0·54/ -0·56, all p < 0·0001). Severe, moderate, and mild/no PCS according to the individual participant's PCS score occurred in 18·8%, 48·2%, and 32·9%, respectively, of the Kiel-I sub-cohort. In both validation sub-cohorts, statistically significant predictors of the PCS score included the intensity of acute phase symptoms and the level of personal resilience. Interpretation: PCS severity can be quantified by an easy-to-use symptom-based score reflecting acute phase disease burden and general psychological predisposition. The PCS score thus holds promise to facilitate the clinical diagnosis of PCS, scientific studies of its natural course, and the development of therapeutic interventions. Funding: The COVIDOM study is funded by the Network University Medicine (NUM) as part of the National Pandemic Cohort Network (NAPKON).

The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics.

The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON's goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany. Within NAPKON, adult and pediatric patients are observed in three complementary cohort platforms (Cross-Sectoral, High-Resolution and Population-Based) from the initial infection until up to three years of follow-up. Study procedures comprise comprehensive clinical and imaging diagnostics, quality-of-life assessment, patient-reported outcomes and biosampling. The three cohort platforms build on four infrastructure core units (Interaction, Biosampling, Epidemiology, and Integration) and collaborations with NUM projects. Key components of the data capture, regulatory, and data privacy are based on the German Centre for Cardiovascular Research. By April 01, 2022, 34 university and 40 non-university hospitals have enrolled 5298 patients with local data quality reviews performed on 4727 (89%). 47% were female, the median age was 52 (IQR 36-62-) and 50 pediatric cases were included. 44% of patients were hospitalized, 15% admitted to an intensive care unit, and 12% of patients deceased while enrolled. 8845 visits with biosampling in 4349 patients were conducted by April 03, 2022. In this overview article, we summarize NAPKON's design, relevant milestones including first study population characteristics, and outline the potential of NAPKON for German and international research activities.Trial registration https://clinicaltrials.gov/ct2/show/NCT04768998 . https://clinicaltrials.gov/ct2/show/NCT04747366 . https://clinicaltrials.gov/ct2/show/NCT04679584.

Key characteristics impacting survival of COVID-19 extracorporeal membrane oxygenation.

BACKGROUND: Severe COVID-19 induced acute respiratory distress syndrome (ARDS) often requires extracorporeal membrane oxygenation (ECMO). Recent German health insurance data revealed low ICU survival rates. Patient characteristics and experience of the ECMO center may determine intensive care unit (ICU) survival. The current study aimed to identify factors affecting ICU survival of COVID-19 ECMO patients. METHODS: 673 COVID-19 ARDS ECMO patients treated in 26 centers between January 1st 2020 and March 22nd 2021 were included. Data on clinical characteristics, adjunct therapies, complications, and outcome were documented. Block wise logistic regression analysis was applied to identify variables associated with ICU-survival. RESULTS: Most patients were between 50 and 70 years of age. PaO2/FiO2 ratio prior to ECMO was 72 mmHg (IQR: 58-99). ICU survival was 31.4%. Survival was significantly lower during the 2nd wave of the COVID-19 pandemic. A subgroup of 284 (42%) patients fulfilling modified EOLIA criteria had a higher survival (38%) (p = 0.0014, OR 0.64 (CI 0.41-0.99)). Survival differed between low, intermediate, and high-volume centers with 20%, 30%, and 38%, respectively (p = 0.0024). Treatment in high volume centers resulted in an odds ratio of 0.55 (CI 0.28-1.02) compared to low volume centers. Additional factors associated with survival were younger age, shorter time between intubation and ECMO initiation, BMI > 35 (compared to < 25), absence of renal replacement therapy or major bleeding/thromboembolic events. CONCLUSIONS: Structural and patient-related factors, including age, comorbidities and ECMO case volume, determined the survival of COVID-19 ECMO. These factors combined with a more liberal ECMO indication during the 2nd wave may explain the reasonably overall low survival rate. Careful selection of patients and treatment in high volume ECMO centers was associated with higher odds of ICU survival. TRIAL REGISTRATION: Registered in the German Clinical Trials Register (study ID: DRKS00022964, retrospectively registered, September 7th 2020, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00022964 .

Impact of cumulative body mass index and cardiometabolic diseases on survival among patients with colorectal and breast cancer: a multi-centre cohort study.

BACKGROUND: Body mass index (BMI) and cardiometabolic comorbidities such as cardiovascular disease and type 2 diabetes have been studied as negative prognostic factors in cancer survival, but possible dependencies in the mechanisms underlying these associations remain largely unexplored. We analysed these associations in colorectal and breast cancer patients. METHODS: Based on repeated BMI assessments of cancer-free participants from four European countries in the European Prospective Investigation into Cancer and nutrition (EPIC) study, individual BMI-trajectories reflecting predicted mean BMI between ages 20 to 50 years were estimated using a growth curve model. Participants with incident colorectal or breast cancer after the age of 50 years were included in the survival analysis to study the prognostic effect of mean BMI and cardiometabolic diseases (CMD) prior to cancer. CMD were defined as one or more chronic conditions among stroke, myocardial infarction, and type 2 diabetes. Hazard ratios (HRs) and confidence intervals (CIs) of mean BMI and CMD were derived using multivariable-adjusted Cox proportional hazard regression for mean BMI and CMD separately and both exposures combined, in subgroups of localised and advanced disease. RESULTS: In the total cohort of 159,045 participants, there were 1,045 and 1,620 eligible patients of colorectal and breast cancer. In colorectal cancer patients, a higher BMI (by 1 kg/m2) was associated with a 6% increase in risk of death (95% CI of HR: 1.02-1.10). The HR for CMD was 1.25 (95% CI: 0.97-1.61). The associations for both exposures were stronger in patients with localised colorectal cancer. In breast cancer patients, a higher BMI was associated with a 4% increase in risk of death (95% CI: 1.00-1.08). CMDs were associated with a 46% increase in risk of death (95% CI: 1.01-2.09). The estimates and CIs for BMI remained similar after adjustment for CMD and vice versa. CONCLUSIONS: Our results suggest that cumulative exposure to higher BMI during early to mid-adulthood was associated with poorer survival in patients with breast and colorectal cancer, independent of CMD prior to cancer diagnosis. The association between a CMD diagnosis prior to cancer and survival in patients with breast and colorectal cancer was independent of BMI.

Identifying key environmental barriers experienced by persons with mild, moderate, or severe disability in Bankim Health District, Cameroon: a policy-targeted secondary analysis of data obtained with the World Bank and WHO model disability survey.

BACKGROUND: Comprehensive data is key for evidence-informed policy aiming to improve the lives of persons experiencing different levels of disability. The objective of this paper was to identify the environmental barriers - including physical, social, attitudinal, and political barriers - that might become priorities for cross-cutting policies and policies tailored to the needs of persons experiencing severe disability in Cameroon. METHODS: A secondary analysis of data obtained with the WHO Model Disability Survey was completed in the Bankim Health District (N = 559) using random forest regression to determine and compare the impact of the environmental factors on the experience of disability. RESULTS: The physical environment had by far the highest influence on disability, with transportation, toilet of the dwelling, and the dwelling itself being the most important factors. Factors inside one's own home (toilet of the dwelling, and the dwelling itself) were the most important for persons with moderate and severe disability, followed by attitudes of others and issues with accessing health care. CONCLUSION: Our study provides country policy makers with evidence for setting priorities and for the development of evidence-informed policies for the Bankim Health District in Cameroon.