Understanding diagnostic test accuracy studies and systematic reviews: A primer for medical radiation technologists

PRIDASE 2024 guidelines for reporting diagnostic accuracy studies in endodontics: A consensus-based development

Studies investigating the accuracy of diagnostic tests should provide data on how effectively they identify or exclude disease in order to inform clinicians responsible for managing patients. This consensus-based project was undertaken to develop reporting guidelines for authors submitting manuscripts, which describe studies that have evaluated the accuracy of diagnostic tests in endodontics. These guidelines are known as the Preferred Reporting Items for Diagnostic Accuracy Studies in Endodontics (PRIDASE) 2024 guidelines. A nine-member steering committee created an initial checklist by integrating and modifying items from the Standards for Reporting of Diagnostic Accuracy (STARD) 2015 checklist and the Clinical and Laboratory Images in Publications (CLIP) principles, as well as adding a number of new items specific to the specialty of endodontics. Thereafter, the steering committee formed the PRIDASE Delphi Group (PDG) and the PRIDASE Online Meeting Group (POMG) in order to collect expert feedback on the preliminary draft checklist. Members of the Delphi group engaged in an online Delphi process to reach consensus on the clarity and suitability of the items in the checklist. The online meeting group then held an in-depth discussion on the online Delphi-generated items via the Zoom platform on 20 October 2023. According to the feedback obtained, the steering committee revised the PRIDASE checklist, which was then piloted by several authors when preparing manuscripts describing diagnostic accuracy studies in endodontics. Feedback from this process resulted in the final version of the PRIDASE 2024 checklist, which has 11 sections and 66 items. Authors are encouraged to use the PRIDASE 2024 guidelines when developing manuscripts on diagnostic accuracy in endodontics in order to improve the quality of reporting in this area. Editors of relevant journals will be invited to include these guidelines in their instructions to authors.

Validation of Two Screening Tools for Detecting Delirium in Older Patients in the Post-Anaesthetic Care Unit: A Diagnostic Test Accuracy Study

(1) Background: Delirium is a common complication among surgical patients after major surgery, but it is often underdiagnosed in the post-anaesthetic care unit (PACU). Valid and reliable tools are required for improving diagnoses of delirium. The objective of this study was to evaluate the diagnostic test accuracy of the Three-Minute Diagnostic Interview for Confusion Assessment Method (3D-CAM) and the 4A's Test (4AT) as screening tools for detection of delirium in older people in the PACU. (2) Methods: A prospective diagnostic test accuracy study was conducted in the PACU and surgical wards of a university-affiliated tertiary care hospital in Victoria, Australia. A consecutive prospective cohort of elective and emergency patients (aged 65 years or older) admitted to the PACU were recruited between July 2021 and December 2021 following a surgical procedure performed under general anaesthesia and expected to stay in the hospital for at least 24 h following surgery. The outcome measures were sensitivity, specificity positive predictive value and negative predictive value for 3D-CAM and 4AT. (3) Results: A total of 271 patients were recruited: 16.2% (44/271) had definite delirium. For a diagnosis of definite delirium, the 3D-CAM (area under curve (AUC) = 0.96) had a sensitivity of 100% (95% CI 92.0 to 100.0) in the PACU and during the first 5 days post-operatively. Specificity ranged from 93% (95% CI 87.8 to 95.2) to 91% (95% CI 85.9 to 95.2) in the PACU and during the first 5 days post-operatively. The 4AT (AUC = 0.92) had a sensitivity of 93% (95% CI 81.7 to 98.6) in the PACU and during the first 5 days post-operatively, and specificity ranged from 89% (95% CI 84.6 to 93.1) to 87% (95%CI 80.9 to 91.8) in the PACU and during the first 5 days post-operatively. (4) Conclusions: The 3D-CAM and the 4AT are sensitive and specific screening tools that can be used to detect delirium in older people in the PACU. Screening with either tool could have an important clinical impact by improving the accuracy of delirium detection in the PACU and hence preventing adverse outcomes associated with delirium.

Toward insights on antimicrobial selectivity of host defense peptides via machine learning model interpretation

Host defense peptides are promising candidates for the development of novel antibiotics. To realize their therapeutic potential, high levels of target selectivity is essential. This study aims to identify factors governing selectivity via the use of the random forest algorithm for correlating peptide sequence information with their bioactivity data. Satisfactory predictive models were achieved from out-of-bag prediction that yielded accuracies and Matthew's correlation coefficients in excess of 0.80 and 0.57, respectively. Model interpretation through the use of variable importance metrics and partial dependence plots indicated that the selectivity was heavily influenced by the composition and distribution patterns of molecular charge and solubility related parameters. Furthermore, the three investigated bacterial target species (Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus) likely had a significant influence on how selectivity was realized as there appears to be a similar underlying selectivity mechanism on the basis of charge-solubility properties (i.e. but which is tailored according to the target in question).