Objective: The objective of this review is to evaluate the measurement properties of multidimensional pain assessment tools for postoperative pain in adults.
Introduction: Effective postoperative pain management increases patient safety and satisfaction, and reduces healthcare costs. The most commonly used postoperative pain assessment tools only evaluate pain intensity, which is only one aspect of the sensory dimension of pain. Pain is a subjective phenomenon, and variability exists among patients. Efforts are underway to incorporate multidimensional assessment tools for postoperative pain assessment in clinical practice.
Inclusion Criteria: Eligible studies will include postoperative patients aged 18 years and older from all surgical disciplines. Studies evaluating multidimensional assessment instruments for the measurement of postoperative pain during the first two weeks following surgery will be considered. Studies will include the following measurement properties of assessment tools as outcomes: reliability, validity and generalizability.
Methods: MEDLINE, CINAHL, Embase, PsycINFO and Cochrane Trials (CENTRAL) will be searched, as well as ClinicalTrials.gov and multiple gray literature sources. There will be no limitations on publication date. Titles and abstracts will be screened by independent reviewers for inclusion. The full text of selected papers will be retrieved and assessed against the inclusion criteria. Two independent reviewers will assess papers for methodological quality using the COSMIN checklist, and papers with poor scores on relevant items will be excluded. Data will be extracted by two independent reviewers using a standardized data extraction tool. Statistical pooling will be performed, if possible.
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http://dx.doi.org/10.11124/JBISRIR-2017-003819 | DOI Listing |
EJNMMI Phys
January 2025
Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Solna, Sweden.
Background: System calibration is essential for accurate SPECT/CT dosimetry. However, count losses due to dead time and pulse pileup may cause calibration errors, in particular for I, where high count rates may be encountered. Calibration at low count rates should also be avoided to minimise detrimental effects from e.
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The expansion of drone-based aerial imagery has facilitated an increase in data obtained from free-ranging marine mammal populations, in particular cetacean species. This non-invasive approach allows for body condition assessments, including nutritional and reproductive health. Yet, existing methods of image analysis are time-consuming and lack the granularity to determine early-stage pregnancies and miscarriage rates.
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January 2025
Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany.
The characteristics of data produced by omics technologies are pivotal, as they critically influence the feasibility and effectiveness of computational methods applied in downstream analyses, such as data harmonization and differential abundance analyses. Furthermore, variability in these data characteristics across datasets plays a crucial role, leading to diverging outcomes in benchmarking studies, which are essential for guiding the selection of appropriate analysis methods in all omics fields. Additionally, downstream analysis tools are often developed and applied within specific omics communities due to the presumed differences in data characteristics attributed to each omics technology.
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January 2025
Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, 04103, Germany.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models.
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