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Filename: drivers/Session_files_driver.php
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File: /var/www/html/index.php
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Function: require_once
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Filename: Session/Session.php
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File: /var/www/html/index.php
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Function: require_once
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Message: Undefined array key "choices"
Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
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Function: require_once
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Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
Line Number: 249
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File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
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Function: require_once
Severity: Warning
Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
Line Number: 249
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File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
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Function: require_once
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Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
Line Number: 249
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File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
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Function: require_once
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Filename: models/Detail_model.php
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File: /var/www/html/application/models/Detail_model.php
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Function: strpos
File: /var/www/html/application/controllers/Detail.php
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Function: insertAPISummary
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Function: require_once
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Filename: helpers/my_audit_helper.php
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File: /var/www/html/application/helpers/my_audit_helper.php
Line: 8919
Function: str_replace
File: /var/www/html/application/controllers/Detail.php
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Function: formatAIDetailSummary
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
Line: 256
Function: _error_handler
File: /var/www/html/index.php
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Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
Line Number: 256
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File: /var/www/html/application/controllers/Detail.php
Line: 256
Function: _error_handler
File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Function: require_once
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Filename: controllers/Detail.php
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Backtrace:
File: /var/www/html/application/controllers/Detail.php
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Function: require_once
Background: Multi-centre studies generally cost more than single-centre studies because of larger sample sizes and the need for multiple ethical approvals. Multi-centre studies include clinical trials, clinical quality registries, observational studies and implementation studies. We examined the costs of two large Australian multi-centre studies in obtaining ethical and site-specific approvals.
Methods: We collected data on staff time spent on approvals and expressed the overall cost as a percent of the total budget.
Results: The total costs of gaining approval were 38 % of the budget for a study of 50 centres (mean cost AUD $6960 per site) and 2 % for a study of 11 centres (mean cost AUD $2300 per site). Seventy-five and 90 % of time was spent on repeated tasks, respectively, and many time-consuming tasks, such as reformatting documents, did nothing to improve the study design or participant safety.
Conclusions: Improvements have been made to the ethical approval application system, but more gains could be made without increasing risks of harm to research participants. We propose that ethical review bodies and individual sites publish statistics on how long they take to process approvals which could then be nationally benchmarked.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5803625 | PMC |
http://dx.doi.org/10.1186/s41073-016-0023-6 | DOI Listing |
Front Oncol
December 2024
Personalised Oncology Division, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia.
Prostate cancer is a common malignancy with an increasing incidence in ageing populations. However, older patients with prostate cancer are often underrepresented in traditional clinical trials. The electronic Prostate Cancer Australian and Asian Database (ePAD) is a multi-centre, multi-national prospective clinical registry, that records real world data from a broader population.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
December 2024
The Research Center for Women's, Family and Child Health, Faculty of Health and Social Sciences, University of South-Eastern Norway, Kongsberg, Buskerud, Norway.
Background: Migrant women face an increased risk of poor obstetric and neonatal outcomes. Norway implemented a multicultural doula (MCD) program in 2018, which was designed to improve pregnancy care for this group in vulnerable circumstances. This study aimed to assess the impact of MCD support, provided in addition to standard care, on obstetric and neonatal outcomes for selected newly arrived migrants.
View Article and Find Full Text PDFCancer Imaging
December 2024
Department of Translational Imaging in Oncology, National Center for Tumor Diseases (NCT/UCC) Dresden, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Fetscherstraße 74, Dresden, 01307, Germany.
Purpose: Staging of non-small cell lung cancer (NSCLC) is commonly based on [F]FDG PET/CT, in particular to exclude distant metastases and guide local therapy approaches like resection and radiotherapy. Although it is hoped that PET/CT will increase the value of primary staging compared to conventional imaging, it is generally limited to the characterization of TNM. The first aim of this study was to evaluate the PET parameter metabolic tumor volume (MTV) above liver background uptake as a prognostic marker in lung cancer.
View Article and Find Full Text PDFBMC Infect Dis
December 2024
Department of Intensive Care Medicine, Affiliated Hospital of Chengdu University, Chengdu, Sichuan, China.
Background: Predicting mortality in sepsis-related acute kidney injury facilitates early data-driven treatment decisions. Machine learning is predicting mortality in S-AKI in a growing number of studies. Therefore, we conducted this systematic review and meta-analysis to investigate the predictive value of machine learning for mortality in patients with septic acute kidney injury.
View Article and Find Full Text PDFBackground: Recovery after severe injury may be impacted by a range of psychological factors. This multi-site study investigated the prevalence and impact of anxiety and depression at one year after trauma critical care admission.
Methods: Adult trauma patients admitted to four Level 1 Critical Care Units were prospectively enrolled over 18 months.
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