X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Statistical biases due to anonymization evaluated in an open clinical dataset from COVID-19 patients
    Springer Science and Business Media LLC ; 2022
    In:  Scientific Data Vol. 9, No. 1 ( 2022-12-21)
    Details
    In: Scientific Data, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2022-12-21)
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2052-4463
    URL: Article
    DOI: 10.1038/s41597-022-01669-9
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2775191-0
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 2
    Online Resource
    Online Resource
    Consistency as a Data Quality Measure for German Corona Consensus Items Mapped from National Pandemic Cohort Network Data Collections
    Georg Thieme Verlag KG ; 2023
    In:  Methods of Information in Medicine Vol. 62, No. S 01 ( 2023-06), p. e47-e56
    Details
    In: Methods of Information in Medicine, Georg Thieme Verlag KG, Vol. 62, No. S 01 ( 2023-06), p. e47-e56
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0026-1270 , 2511-705X
    URL: Article
    DOI: 10.1055/a-2006-1086
    RVK:
    XA 10000
    Language: English
    Publisher: Georg Thieme Verlag KG
    Publication Date: 2023
    detail.hit.zdb_id: 3500-2
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 3
    Online Resource
    Online Resource
    Persistent symptoms and risk factors predicting prolonged time to symptom-free after SARS‑CoV‑2 infection: an analysis of the baseline examination of the German COVIDOM/NAPKON-POP cohort
    Springer Science and Business Media LLC ; 2023
    In:  Infection
    Details
    In: Infection, Springer Science and Business Media LLC
    Abstract: We aimed to assess symptoms in patients after SARS-CoV-2 infection and to identify factors predicting prolonged time to symptom-free. Methods COVIDOM/NAPKON-POP is a population-based prospective cohort of adults whose first on-site visits were scheduled ≥ 6 months after a positive SARS-CoV-2 PCR test. Retrospective data including self-reported symptoms and time to symptom-free were collected during the survey before a site visit. In the survival analyses, being symptom-free served as the event and time to be symptom-free as the time variable. Data were visualized with Kaplan–Meier curves, differences were tested with log-rank tests. A stratified Cox proportional hazard model was used to estimate adjusted hazard ratios (aHRs) of predictors, with aHR  〈  1 indicating a longer time to symptom-free. Results Of 1175 symptomatic participants included in the present analysis, 636 (54.1%) reported persistent symptoms after 280 days (SD 68) post infection. 25% of participants were free from symptoms after 18 days [quartiles: 14, 21]. Factors associated with prolonged time to symptom-free were age 49–59 years compared to  〈  49 years (aHR 0.70, 95% CI 0.56–0.87), female sex (aHR 0.78, 95% CI 0.65–0.93), lower educational level (aHR 0.77, 95% CI 0.64–0.93), living with a partner (aHR 0.81, 95% CI 0.66–0.99), low resilience (aHR 0.65, 95% CI 0.47–0.90), steroid treatment (aHR 0.22, 95% CI 0.05–0.90) and no medication (aHR 0.74, 95% CI 0.62–0.89) during acute infection. Conclusion In the studied population, COVID-19 symptoms had resolved in one-quarter of participants within 18 days, and in 34.5% within 28 days. Over half of the participants reported COVID-19-related symptoms 9 months after infection. Symptom persistence was predominantly determined by participant’s characteristics that are difficult to modify.
    Type of Medium: Online Resource
    ISSN: 0300-8126 , 1439-0973
    URL: Article
    DOI: 10.1007/s15010-023-02043-6
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2006315-5
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 4
    Online Resource
    Online Resource
    Analysis of acute COVID-19 including chronic morbidity: protocol for the deep phenotyping National Pandemic Cohort Network in Germany (NAPKON-HAP)
    Springer Science and Business Media LLC ; 2023
    In:  Infection
    Details
    In: Infection, Springer Science and Business Media LLC
    Abstract: The severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) pandemic causes a high burden of acute and long-term morbidity and mortality worldwide despite global efforts in containment, prophylaxis, and therapy. With unprecedented speed, the global scientific community has generated pivotal insights into the pathogen and the host response evoked by the infection. However, deeper characterization of the pathophysiology and pathology remains a high priority to reduce morbidity and mortality of coronavirus disease 2019 (COVID-19). Methods NAPKON-HAP is a multi‐centered prospective observational study with a long‐term follow‐up phase of up to 36 months post-SARS-CoV-2 infection. It constitutes a central platform for harmonized data and biospecimen for interdisciplinary characterization of acute SARS-CoV-2 infection and long-term outcomes of diverging disease severities of hospitalized patients. Results Primary outcome measures include clinical scores and quality of life assessment captured during hospitalization and at outpatient follow-up visits to assess acute and chronic morbidity. Secondary measures include results of biomolecular and immunological investigations and assessment of organ-specific involvement during and post-COVID-19 infection. NAPKON-HAP constitutes a national platform to provide accessibility and usability of the comprehensive data and biospecimen collection to global research. Conclusion NAPKON-HAP establishes a platform with standardized high-resolution data and biospecimen collection of hospitalized COVID-19 patients of different disease severities in Germany. With this study, we will add significant scientific insights and provide high-quality data to aid researchers to investigate COVID-19 pathophysiology, pathology, and chronic morbidity.
    Type of Medium: Online Resource
    ISSN: 0300-8126 , 1439-0973
    URL: Article
    DOI: 10.1007/s15010-023-02057-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2006315-5
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 5
    Online Resource
    Online Resource
    Population data-based federated machine-learning improves automated echocardiographic quantification of cardiac structure and function – the AVE project
    Oxford University Press (OUP) ; 2023
    In:  European Heart Journal - Digital Health ( 2023-11-15)
    Details
    In: European Heart Journal - Digital Health, Oxford University Press (OUP), ( 2023-11-15)
    Abstract: Machine-learning (ML)-based automated measurement of echocardiography images emerged as an option to reduce observer variability. Objectives To improve the accuracy of a pre-existing automated reading tool (“original detector”) by federated ML-based re-training. Methods AVE (Automatisierte Vermessung der Echokardiographie) was based on the echocardiography images of n = 4,965 participants of the population-based Characteristics and Course of Heart Failure Stages A-B and Determinants of Progression Cohort Study. We implemented federated ML: echocardiography images were read by the Academic CoreLab Ultrasound-based Cardiovascular Imaging at the University Hospital Würzburg (UKW). A random algorithm selected 3,226 participants for re-training of the original detector. According to data protection rules, generation of ground truth and ML training cycles took place within the UKW network. Only non-personal training weights were exchanged with the external cooperation partner for refinement of ML algorithms. Results Both the original detector as the re-trained detector were then applied to the echocardiograms of n = 563 participants not used for training. With regards to the human referent the re-trained detector revealed 1) superior accuracy when contrasted with the original detector´s performance as it arrived at significantly smaller mean differences in all but one parameter, and 2) smaller absolute difference between measurements when compared to a group of different human observers. Conclusions Population data based ML in a federated ML set-up was feasible. The re-trained detector exhibited a much lower measurement variability than human readers. This gain in accuracy and precision strengthens the confidence into automated echocardiographic readings, which carries large potential for applications in various settings.
    Type of Medium: Online Resource
    ISSN: 2634-3916
    URL: Article
    DOI: 10.1093/ehjdh/ztad069
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 3076078-1
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 6
    Online Resource
    Online Resource
    1886. External Validation of the 4C Mortality Score and the qSOFA for Different Variants of Concerns of SARS-CoV-2 Using Data of the NAPKON Cross-Sectoral Cohort Platform (SUEP)
    Oxford University Press (OUP) ; 2022
    In:  Open Forum Infectious Diseases Vol. 9, No. Supplement_2 ( 2022-12-15)
    Details
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 9, No. Supplement_2 ( 2022-12-15)
    Abstract: Numerous predictive clinical scores with varying discriminatory performance have been developed in the context of the current coronavirus disease 2019 (COVID-19) pandemic. To support clinical application, we test the transferability of the frequently applied 4C mortality score (4C score) to the German prospective Cross-Sectoral Platform (SUEP) of the National Pandemic Cohort Network (NAPKON) compared to the non COVID-19 specific quick sequential organ failure assessment score (qSOFA). Our project aims to externally validate these two scores, stratified for the most prevalent variants of concerns (VOCs) of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) in Germany. Methods A total of 685 adults with polymerase chain reaction (PCR)-detected SARS-CoV-2 infection were included from NAPKON-SUEP. Patients were recruited from 11/2020 to 03/2022 at 34 university and non-university hospitals across Germany. Missing values were complemented using multiple imputation. Predictive performance for in-hospital mortality at day of baseline visit was determined by area under the curve (AUC) with 95%-confidence interval (CI) stratified by VOCs of SARS-CoV-2 (alpha, delta, omicron) (Figure 1). Figure 1:Study flow chart with inclusion criteria and methodological workflow. Results Preliminary results suggest a high predictive performance of the 4C score for in-hospital mortality (Table 1). This applies for the overall cohort (AUC 0.813 (95%CI 0.738-0.888)) as well as the VOC-strata (alpha: AUC 0.859 (95%CI 0.748-0.970); delta: AUC 0.769 (95%CI 0.657-0.882); omicron: AUC 0.866 (95%CI 0.724-1.000)). The overall mortality rates across the defined 4C score risk groups are 0.3% (low), 3.2% (intermediate), 11.6% (high), and 49.5% (very high). The 4C score performs significantly better than the qSOFA (Chi2-test: p=0.001) and the qSOFA does not seem to be a suitable tool in this context. Table 1:Discriminatory performance of the 4C Mortality Score and the qSOFA score within the validation cohort NAPKON-SUEP stratified by the Variant of Concerns of SARS-CoV-2. Conclusion Despite its development in the early phase of the pandemic and improved treatment, external validation of the 4C score in NAPKON-SUEP indicates a high predictive performance for in-hospital mortality across all VOCs. However, since the qSOFA was not specifically designed for this predictive issue, it shows low discriminatory performance, as in other validation studies. Any interpretations regarding the omicron stratum are limited due to the sample size. Disclosures Daniel Pape, Dr., Advanz Pharma Germany: Support for attending meetings and/or travel for ECCMID 2021 Martin Hower, n/a, MSD: Advisor/Consultant|Trogarzo: Advisor/Consultant|ViiV Healthcare: Advisor/Consultant Björn-Erik O. Jensen, Dr. med., GILEAD: Advisor/Consultant|GILEAD: Lectures, Travel|GSK: Lectures, Travel Jörg J. Vehreschild, Univ.-Prof. Dr. med., Ärztekammer Nordrhein: Honoraria|Academy for Infectious Medicine, University Manchester: Honoraria|Astellas Pharma: Grant/Research Support|Astellas Pharma: Honoraria|Back Bay Strategies: Honoraria|Basilea: Grant/Research Support|Basilea: Honoraria|Deutsches Zetrum für Luft- und Raumfahrt (DLR): Grant/Research Support|German Centre for Infection Research (DZIF): Grant/Research Support|German Centre for Infection Research (DZIF): Honoraria|German Federal Ministry of Education and Research (BMBF): Grant/Research Support|German Society for Infectious Diseases (DGI): Honoraria|German Society for Internal Medicine (DGIM): Honoraria|GILEAD: Advisor/Consultant|GILEAD: Grant/Research Support|GILEAD: Honoraria|Janssen: Honoraria|Merck / MSD: Grant/Research Support|Merck / MSD: Honoraria|Molecular Health: Honoraria|Netzwerk Universitätsmedizin: Honoraria|NordForsk: Honoraria|Pfizer: Advisor/Consultant|Pfizer: Grant/Research Support|Pfizer: Honoraria|Rigshospitalet Copenhagen: Grant/Research Support|Shionogi: Advisor/Consultant|Shionogi: Honoraria|University Hospital Aachen: Honoraria|University Hospital Freiburg/ Congress and Communication: Honoraria|University of Bristol: Grant/Research Support.
    Type of Medium: Online Resource
    ISSN: 2328-8957
    URL: Article
    DOI: 10.1093/ofid/ofac492.1513
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2757767-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 7
    Online Resource
    Online Resource
    Impact of the coronavirus disease 2019 pandemic on stroke teleconsultations in Germany in the first half of 2020
    Wiley ; 2021
    In:  European Journal of Neurology Vol. 28, No. 10 ( 2021-10), p. 3267-3278
    Details
    In: European Journal of Neurology, Wiley, Vol. 28, No. 10 ( 2021-10), p. 3267-3278
    Abstract: The effects of the coronavirus disease 2019 (COVID‐19) pandemic on telemedical care have not been described on a national level. Thus, we investigated the medical stroke treatment situation before, during, and after the first lockdown in Germany. Methods In this nationwide, multicenter study, data from 14 telemedical networks including 31 network centers and 155 spoke hospitals covering large parts of Germany were analyzed regarding patients' characteristics, stroke type/severity, and acute stroke treatment. A survey focusing on potential shortcomings of in‐hospital and (telemedical) stroke care during the pandemic was conducted. Results Between January 2018 and June 2020, 67,033 telemedical consultations and 38,895 telemedical stroke consultations were conducted. A significant decline of telemedical ( p   〈  0.001) and telemedical stroke consultations ( p   〈  0.001) during the lockdown in March/April 2020 and a reciprocal increase after relaxation of COVID‐19 measures in May/June 2020 were observed. Compared to 2018–2019, neither stroke patients' age ( p  = 0.38), gender ( p  = 0.44), nor severity of ischemic stroke ( p  = 0.32) differed in March/April 2020. Whereas the proportion of ischemic stroke patients for whom endovascular treatment (14.3% vs. 14.6%; p  = 0.85) was recommended remained stable, there was a nonsignificant trend toward a lower proportion of recommendation of intravenous thrombolysis during the lockdown (19.0% vs. 22.1%; p  = 0.052). Despite the majority of participating network centers treating patients with COVID‐19, there were no relevant shortcomings reported regarding in‐hospital stroke treatment or telemedical stroke care. Conclusions Telemedical stroke care in Germany was able to provide full service despite the COVID‐19 pandemic, but telemedical consultations declined abruptly during the lockdown period and normalized after relaxation of COVID‐19 measures in Germany.
    Type of Medium: Online Resource
    ISSN: 1351-5101 , 1468-1331
    URL: Issue
    URL: Article
    DOI: 10.1111/ene.v28.10
    DOI: 10.1111/ene.14787
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2020241-6
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 8
    Online Resource
    Online Resource
    Data_Sheet_1.docx
    Frontiers Media SA ; 2023
    In:  Frontiers in Public Health Vol. 10 ( 2023-1-10)
    Details
    In: Frontiers in Public Health, Frontiers Media SA, Vol. 10 ( 2023-1-10)
    Abstract: Although the vast majority of COVID-19 cases are treated in primary care, patients' experiences during home isolation have been little studied. This study aimed to explore the experiences of patients with acute COVID-19 and to identify challenges after the initial adaptation of the German health system to the pandemic (after first infection wave from February to June 2020). Methods A mixed-method convergent design was used to gain a holistic insight into patients experience. The study consisted of a cross-sectional survey, open survey answers and semi-structured telephone interviews. Descriptive analysis was performed on quantitative survey answers. Between group differences were calculated to explore changes after the first infection wave. Qualitative thematic analysis was conducted on open survey answers and interviews. The results were then compared within a triangulation protocol. Results A total of 1100 participants from all German states were recruited by 145 general practitioners from August 2020 to April 2021, 42 additionally took part in qualitative interviews. Disease onset varied from February 2020 to April 2021. After the first infection wave, more participants were tested positive during the acute disease (88.8%; 95.2%; P & lt; 0.001). Waiting times for tests (mean 4.5 days, SD 4.1; 2.7days, SD 2.6, P & lt; 0.001) and test results (mean 2.4 days, SD 1.9; 1.8 days, SD 1.3, P & lt; 0.001) decreased. Qualitative results indicated that the availability of repeated testing and antigen tests reduced insecurities, transmission and related guilt. Although personal consultations at general practices increased (6.8%; 15.5%, P & lt; 0.001), telephone consultation remained the main mode of consultation (78.5%) and video remained insignificant (1.9%). The course of disease, the living situation and social surroundings during isolation, access to health care, personal resilience, spirituality and feelings of guilt and worries emerged as themes influencing the illness experience. Challenges were contact management and adequate provision of care during home isolation. A constant contact person within the health system helped against feelings of care deprivation, uncertainty and fear. Conclusions Our study highlights that home isolation of individuals with COVID-19 requires a holistic approach that considers all aspects of patient care and effective coordination between different care providers.
    Type of Medium: Online Resource
    ISSN: 2296-2565
    URL: Article
    URL: Article
    DOI: 10.3389/fpubh.2022.1023431
    DOI: 10.3389/fpubh.2022.1023431.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2711781-9
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 9
    Online Resource
    Online Resource
    The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics
    Springer Science and Business Media LLC ; 2022
    In:  European Journal of Epidemiology Vol. 37, No. 8 ( 2022-08), p. 849-870
    Details
    In: European Journal of Epidemiology, Springer Science and Business Media LLC, Vol. 37, No. 8 ( 2022-08), p. 849-870
    Abstract: 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
    Type of Medium: Online Resource
    ISSN: 0393-2990 , 1573-7284
    URL: Article
    DOI: 10.1007/s10654-022-00896-z
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2004992-4
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 10
    Online Resource
    Online Resource
    Severity, predictors and clinical correlates of Post-COVID syndrome (PCS) in Germany: A prospective, multi-centre, population-based cohort study
    Elsevier BV ; 2022
    In:  eClinicalMedicine Vol. 51 ( 2022-09), p. 101549-
    Details
    In: eClinicalMedicine, Elsevier BV, Vol. 51 ( 2022-09), p. 101549-
    Type of Medium: Online Resource
    ISSN: 2589-5370
    URL: Article
    DOI: 10.1016/j.eclinm.2022.101549
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2946413-4
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
Nothing or not found what you are looking for? Please check your search query or use the Interlibrary Loan Search.
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages