Treatments at ultra-high dose rate (UHDR) have the potential to improve the therapeutic index of radiation therapy (RT) by sparing normal tissues compared to conventional dose rate irradiations. Insufficient and inconsistent reporting in physics and dosimetry of preclinical and translational studies may have contributed to a reproducibility crisis of radiobiological data in the field. Consequently, the development of a common terminology, as well as common recording, reporting, dosimetry, and metrology standards is required. In the context of UHDR irradiations, the temporal dose delivery parameters are of importance, and under-reporting of these parameters is also a concern.This work proposes a standardization of terminology, recording, and reporting to enhance comparability of both preclinical and clinical UHDR studies and and to allow retrospective analyses to aid the understanding of the conditions which give rise to the FLASH effect.

UNASSIGNED: Healthcare workers face a high risk of blood-borne infections due to needlestick injuries, especially in developing countries like Pakistan.
UNASSIGNED: This study aims to evaluate the prevalence of needlestick injuries, reporting practices, and post-exposure prophylaxis measures among healthcare personnel in tertiary care hospitals in Punjab.
UNASSIGNED: A cross-sectional study was conducted from May to July 2019. Data were collected from healthcare personnel working in teaching hospitals across six randomly selected cities of Punjab. Data were collected from 600 healthcare personnel using a pretested, self-administered questionnaire, employing stratified random sampling to ensure representative sampling. Descriptive statistics were applied, and differences in needlestick injuries across demographic segments were assessed using the Mann-Whitney U and Kruskal-Wallis H tests.
UNASSIGNED: Among the 600 respondents, 533 returned the complete questionnaire, yielding a response rate of 88.8%. The majority of respondents were female (n = 341, 64.2%). The mean years of service was 5.58 (±5.78), with most participants falling in the 0.5-5 years category (n = 338, 66.4%). The prevalence of self-reported needlestick injuries in the last six months was 35.25%. Most injuries occurred during sampling (n = 95, 35.85%), followed by recapping (n = 63, 23.77%). Reporting of needlestick injuries to the respective department was poor, with only 82 (21.87%) injuries reported. The frequency of needlestick injuries differed significantly across profession, working department, and education categories (p < 0.05). Sanitary staff were more likely to sustain needlestick injuries during garbage collection and waste handling. Post-exposure screening for blood-borne infections was received by 79 (42.93%) individuals, and post-exposure prophylaxis (PEP) was administered to 67 (36.41%).
UNASSIGNED: The high prevalence of needlestick injuries among healthcare personnel occurred primarily during sampling and recapping. Reporting of NSIs was inadequate, and post-exposure testing and prophylaxis practices were substandard. Enhanced policies and protocols are necessary for effective NSI surveillance and the administration of pre- and post-exposure prophylaxis.

Parents vary in conversational goals and style when discussing events with their children-two aspects of parent socialization that may be related, or exert opposing influence on the development of young children\'s report accuracy (a critical factor in children\'s eyewitness reports). In a sample of 116 parent-child dyads (M age = 53.17 months, range: 36-72 months), we examined the roles of parent social conversation goals (parent-reported and experimentally manipulated) and parent cognitive elaboration in children\'s ability to accurately report about a laboratory event. Parent cognitive elaboration varied by conversation goal and was positively associated with child accuracy across age but only when parents strongly endorsed social conversation goals. Parent questioning strategies and children\'s response accuracy varied with age. This work has implications for how we understand short- and long-term impacts caregivers exert on children\'s event reporting and suggests that even very young children are sensitive to variations in parent questioning practices.

Background/Objective: We sought to characterize the proportion of peripheral zone lesions \"upgraded\" within the PI-RADS v2.1 protocol using DCE imaging sequences in a large patient population undergoing multiparametric prostate MRI. Methods: A retrospective review of radiologist reports for 2742 prostate MRI exams at 2 large Alberta teaching hospitals between January 2017 and January 2022 was conducted. Prostate specific antigen (PSA), prostate volume, sequence specific and overall PI-RADS scores, and lesion positivity for DCE were collected if present in the accompanying radiology report. Further, pathology reports of biopsies of the upgraded lesions within upgraded patients were reviewed to see if upgraded lesions were deemed clinically significant by gleason score/grade group. Results: The median age was 63 years, with a median PSA and PSA density of 7.5 ng/mL and 0.13 ng/mL2 respectively. A total of 1809 lesions were reported, with 69.4% of all lesions being DCE positive. Of the lesions within the peripheral zone, 548 were overall PI-RADS 4. A total of 87/2742 (3.2%) of patients were upgraded to a PI-RADS 4 by DCE imaging. Within these patients, 65 had pathology reports available, of which 18 had a clinically significant lesion at the upgrade site. Conclusion: Contrast enhancement is only beneficial for a very small portion of patients undergoing prostate MRI. Given the invasive nature of contrast enhanced studies, potential contrast induced side effects, added imaging time, and the cost of contrast agent, routine use of contrast for prostate MRI is questioned. Further studies are necessary to determine if it should be part of routine prostate MRI imaging protocols.

UNASSIGNED: The National Disaster Management Agency (Badan Nasional Penanggulangan Bencana) handles disaster management in Indonesia as a health cluster by collecting, storing, and reporting information on the state of survivors and their health from various sources during disasters. Data were collected on paper and transferred to Microsoft Excel spreadsheets. These activities are challenging because there are no standards for data collection. The World Health Organization (WHO) introduced a standard for health data collection during disasters for emergency medical teams (EMTs) in the form of a minimum dataset (MDS). Meanwhile, the Ministry of Health of Indonesia launched the SATUSEHAT platform to integrate all electronic medical records in Indonesia based on Fast Healthcare Interoperability Resources (FHIR).
UNASSIGNED: This study aims to implement the WHO EMT MDS to create a disaster profile for the SATUSEHAT platform using FHIR.
UNASSIGNED: We extracted variables from 2 EMT MDS medical records-the WHO and Association of Southeast Asian Nations (ASEAN) versions-and the daily reporting form. We then performed a mapping process to match these variables with the FHIR resources and analyzed the gaps between the variables and base resources. Next, we conducted profiling to see if there were any changes in the selected resources and created extensions to fill the gap using the Forge application. Subsequently, the profile was implemented using an open-source FHIR server.
UNASSIGNED: The total numbers of variables extracted from the WHO EMT MDS, ASEAN EMT MDS, and daily reporting forms were 30, 32, and 46, with the percentage of variables matching FHIR resources being 100% (30/30), 97% (31/32), and 85% (39/46), respectively. From the 40 resources available in the FHIR ID core, we used 10, 14, and 9 for the WHO EMT MDS, ASEAN EMT MDS, and daily reporting form, respectively. Based on the gap analysis, we found 4 variables in the daily reporting form that were not covered by the resources. Thus, we created extensions to address this gap.
UNASSIGNED: We successfully created a disaster profile that can be used as a disaster case for the SATUSEHAT platform. This profile may standardize health data collection during disasters.

BACKGROUND: Workplace violence is a pervasive, perpetual, and underreported problem in the emergency department. Nurses experience devastating physical and psychological consequences owing to workplace violence exposure. Understanding workplace violence is challenging due to nurse underreporting. Improvement in capturing workplace violence cases can help drive data-informed, sustainable solutions to workplace violence prevention. The purpose of this project was to better capture the full extent of workplace violence in the emergency department through enhanced nurse workplace violence reporting.
METHODS: In collaboration with emergency nurses and management, the project team used a multi-interventional approach and designed a feasible electronic reporting instrument to capture workplace violence events in real time by reducing nurse reporting barriers. Participating nurses accessed the instrument by scanning a quick-response code with their mobile phones. This code was strategically located on wall flyers and individual name badge stickers. Data were collected using Qualtrics software and analyzed using SPSS Statistics, which summarized the descriptive statistics.
RESULTS: Two months after implementation, the electronic reporting instrument recorded 94 quick response code scans and 59 workplace violence reports, resulting in a 1080% increase in ED workplace violence reporting compared with the 2 months prior to implementation. The 59 workplace violence reports comprised 78% registered nurses, 19% emergency medical technicians, and 3% other health care workers. Workplace violence events were most frequent from 12:01 pm to 6:00 pm in treatment rooms (37%), triage (29%), waiting room (19%), behavioral health section (15%), and hallway (12%).
CONCLUSIONS: A multi-interventional approach, coupled with a feasible, readily available electronic reporting instrument, enhanced ED workplace violence reporting and facilitated a better capture of ED workplace violence. Although nurse underreporting is still likely occurring, an emergence of workplace violence data trends can provide data-driven solutions in workplace violence prevention. Continued efforts to reduce the barriers that inhibit reporting are needed to foster a safe and supportive culture surrounding workplace violence reporting.

OBJECTIVE: To assess the capabilities of large language models (LLMs), including Open AI (GPT-4.0) and Microsoft Bing (GPT-4), in generating structured reports, the Breast Imaging Reporting and Data System (BI-RADS) categories, and management recommendations from free-text breast ultrasound reports.
METHODS: In this retrospective study, 100 free-text breast ultrasound reports from patients who underwent surgery between January and May 2023 were gathered. The capabilities of Open AI (GPT-4.0) and Microsoft Bing (GPT-4) to convert these unstructured reports into structured ultrasound reports were studied. The quality of structured reports, BI-RADS categories, and management recommendations generated by GPT-4.0 and Bing were evaluated by senior radiologists based on the guidelines.
RESULTS: Open AI (GPT-4.0) was better than Microsoft Bing (GPT-4) in terms of performance in generating structured reports (88% vs. 55%; p < 0.001), giving correct BI-RADS categories (54% vs. 47%; p = 0.013) and providing reasonable management recommendations (81% vs. 63%; p < 0.001). As the ability to predict benign and malignant characteristics, GPT-4.0 performed significantly better than Bing (AUC, 0.9317 vs. 0.8177; p < 0.001), while both performed significantly inferior to senior radiologists (AUC, 0.9763; both p < 0.001).
CONCLUSIONS: This study highlights the potential of LLMs, specifically Open AI (GPT-4.0), in converting unstructured breast ultrasound reports into structured ones, offering accurate diagnoses and providing reasonable recommendations.

Double-blind, placebo-controlled, randomized controlled trials are the gold standard for clinical trials in nutrition science. For trials of whole diets, dietary counseling is advantageous as they offer clinical translatability although can vary in the fidelity of the intended intervention from participant to participant and across studies. Feeding trials, in which most or all food is provided, offer high precision and can provide proof-of-concept evidence that a dietary intervention is efficacious and can also better evaluate the effect of known quantities of foods and nutrients on physiology. However, they come with additional methodological complexities. Feeding trials also call for a variety of unique methodological considerations, not least of which relate to the design and delivery of diets to participants. This review aims to provide a comprehensive summary of recommendations for design and conduct of feeding trials, encompassing domiciled and nondomiciled feeding trials. Several pertinent aspects of trial design and methodology are discussed, including defining the study population to maximize retention, safety, and generalizability of findings, recommendations for design of control interventions and optimizing blinding, and specific considerations for clinical populations. A detailed stepwise process for menu design, development, validation, and delivery are also presented. These recommendations aim to facilitate methodologic consistency and execution of high-quality feeding trials, ultimately facilitating improved understanding of the role of diet in treating disease and the underpinning mechanisms.

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Statistical regression models are used for predicting outcomes based on the values of some predictor variables or for describing the association of an outcome with predictors. With a data set at hand, a regression model can be easily fit with standard software packages. This bears the risk that data analysts may rush to perform sophisticated analyses without sufficient knowledge of basic properties, associations in and errors of their data, leading to wrong interpretation and presentation of the modeling results that lacks clarity. Ignorance about special features of the data such as redundancies or particular distributions may even invalidate the chosen analysis strategy. Initial data analysis (IDA) is prerequisite to regression analyses as it provides knowledge about the data needed to confirm the appropriateness of or to refine a chosen model building strategy, to interpret the modeling results correctly, and to guide the presentation of modeling results. In order to facilitate reproducibility, IDA needs to be preplanned, an IDA plan should be included in the general statistical analysis plan of a research project, and results should be well documented. Biased statistical inference of the final regression model can be minimized if IDA abstains from evaluating associations of outcome and predictors, a key principle of IDA. We give advice on which aspects to consider in an IDA plan for data screening in the context of regression modeling to supplement the statistical analysis plan. We illustrate this IDA plan for data screening in an example of a typical diagnostic modeling project and give recommendations for data visualizations.