ABSTRACT
PURPOSE: The Prostate Imaging Reporting and Data System (PI-RADS) score is standard of care for clinically significant prostate cancer (csPCa) diagnosis. The PRIMARY score (prostate-specific membrane antigen [PSMA]-positron emission tomography [PET]/CT) also has high diagnostic accuracy for csPCa. This study aimed to develop an easily calculated combined (P) score for csPCa detection (International Society of Urological Pathology [ISUP] ≥2) incorporating separately read PI-RADS and PRIMARY scores, with external validation. MATERIALS AND METHODS: Two datasets of men with suspected PCa, no prior biopsy, recent MRI and 68Ga-PSMA-11-PET/CT, and subsequent transperineal biopsy were evaluated. These included the development sample (n = 291, 56% csPCa) a prospective trial and the validation sample (n = 227, 67% csPCa) a multicenter retrospective database. Primary outcome was detection of csPCa (ISUP ≥2), with ISUP ≥ 3 cancer detection a secondary outcome. Score performance was evaluated by area under the curve, sensitivity, specificity, and decision curve analysis. RESULTS: The 5-point combined (P) score was developed in a prospective dataset. In the validation dataset, csPCa was identified in 0%, 20%, 52%, 96%, and 100% for P score 1 to 5. The area under the curve was 0.93 (95% CI: 0.90-0.96), higher than PI-RADS 0.89 (95% CI: 0.85-0.93, P = .039) and PRIMARY score alone 0.84 (95% CI: 0.79-0.89, P < .001). Splitting scores at 1/2 (negative) vs 3/4/5 (positive), P score sensitivity was 94% (95% CI: 89-97) compared to PI-RADS 89% (95% CI: 83-93) and PRIMARY score 86% (95% CI: 79-91). For ISUP ≥ 3, P score sensitivity was 99% (95% CI: 95-100) vs 94% (95% CI: 88-98) and 92% (95% CI: 85-97) for PI-RADS and PRIMARY scores respectively. A maximum standardized uptake value > 12 (P score 5) was ISUP ≥ 2 in all cases with 93% ISUP ≥ 3. CONCLUSIONS: The P score is easily calculated and improves accuracy for csPCa over both PI-RADS and PRIMARY scores. It should be considered when PSMA-PET is undertaken for diagnosis.
Subject(s)
Magnetic Resonance Imaging , Positron Emission Tomography Computed Tomography , Prostatic Neoplasms , Humans , Male , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/pathology , Positron Emission Tomography Computed Tomography/methods , Magnetic Resonance Imaging/methods , Aged , Middle Aged , Retrospective Studies , Prospective Studies , Data Systems , Prostate/diagnostic imaging , Prostate/pathologyABSTRACT
Data access committees (DAC) gatekeep access to secured genomic and related health datasets yet are challenged to keep pace with the rising volume and complexity of data generation. Automated decision support (ADS) systems have been shown to support consistency, compliance, and coordination of data access review decisions. However, we lack understanding of how DAC members perceive the value add of ADS, if any, on the quality and effectiveness of their reviews. In this qualitative study, we report findings from 13 semi-structured interviews with DAC members from around the world to identify relevant barriers and facilitators to implementing ADS for genomic data access management. Participants generally supported pilot studies that test ADS performance, for example in cataloging data types, verifying user credentials and tagging datasets for use terms. Concerns related to over-automation, lack of human oversight, low prioritization, and misalignment with institutional missions tempered enthusiasm for ADS among the DAC members we engaged. Tensions for change in institutional settings within which DACs operated was a powerful motivator for why DAC members considered the implementation of ADS into their access workflows, as well as perceptions of the relative advantage of ADS over the status quo. Future research is needed to build the evidence base around the comparative effectiveness and decisional outcomes of institutions that do/not use ADS into their workflows.
Subject(s)
Datasets as Topic , Decision Support Techniques , Genomics , Software , Automation , Workflow , Interviews as Topic , Data Systems , Datasets as Topic/legislation & jurisprudence , HumansABSTRACT
Most countries in Africa deployed digital solutions to monitor progress in rolling out COVID-19 vaccines. A rapid assessment of existing data systems for COVID-19 vaccines in the African region was conducted between May and July 2022, in 23 countries. Data were collected through interviews with key informants, identified among senior staff within Ministries of Health, using a semi-structured electronic questionnaire. At vaccination sites, individual data were collected in paper-based registers in five countries (21.7%), in an electronic registry in two countries (8.7%), and in the remaining 16 countries (69.6%) using a combination of paper-based and electronic registries. Of the 18 countries using client-based digital registries, 11 (61%) deployed the District Health Information System 2 Tracker, and seven (39%), a locally developed platform. The mean percentage of individual data transcribed in the electronic registries was 61% ± 36% standard deviation. Unreliable Internet coverage (100% of countries), non-payment of data clerks' incentives (89%), and lack of electronic devices (89%) were the main reasons for the suboptimal functioning of digital systems quoted by key informants. It is critical for investments made and experience acquired in deploying electronic platforms for COVID-19 vaccines to be leveraged to strengthen routine immunization data management.
Subject(s)
COVID-19 Vaccines , COVID-19 , Humans , Data Systems , COVID-19/epidemiology , COVID-19/prevention & control , Immunization Programs , Vaccination , Surveys and Questionnaires , World Health OrganizationABSTRACT
This policy document provides key concepts, recommended lines of action, and indicators for monitoring, with the aim of advancing interoperability as one of the eight guiding principles for the digital transformation of the health sector, as promoted by the Pan American Health Organization.
Subject(s)
Information Systems , Integrated Advanced Information Management Systems , Data Systems , Health Knowledge, Attitudes, PracticeABSTRACT
OBJECTIVE: Generation of reliable data underpins the effectiveness of Occupational Health and Safety (OHS) surveillance systems. Despite the importance of understanding OHS data systems, there are few papers that provide overviews of their structure and/or content. This paper introduces a basic framework for assessing OHS data systems that will be of use to researchers internationally. We applied this approach to assess the Irish OHS data system by undertaking a data mapping exercise. METHOD: We developed a checklist based on recommendations of monitoring and measurement of OHS proposed by the National Academies of Sciences, Engineering, and Medicine (USA). An assessment of published reports that present systematic OHS surveillance data was undertaken to identify the institutions or organisations responsible for collecting and curating the data, their remit, and, associated with this, their respective case definitions. We then provide an overview of the variables collected and these are then mapped against the checklist. RESULTS: The assessment highlights that whilst the farm fatalities dataset provides complete coverage of all fatalities, regardless of age or employment status, the same is not true of the three non-fatal injuries datasets reviewed. There are important differences in the data collection methods and, associated with this, which populations are covered. PRACTICAL APPLICATION: The assessment approach provides valuable insights into the strengths and weaknesses of a critical element of OHS surveillance systems, namely the production of datasets. This knowledge is important for researchers as understanding the data that informs their research is fundamental to good science. It is critical for policy-makers and other stakeholders to understand the strengths and weaknesses on which OHS policy, strategies, or education and training interventions are developed.
Subject(s)
Occupational Health , Occupational Injuries , Humans , Farms , Data Systems , Occupational Injuries/epidemiologyABSTRACT
AIM: To retrospectively explored whether systematic training in the use of Liver Imaging Reporting and Data System (LI-RADS) v2018 on computed tomography (CT) can improve the interobserver agreements and performances in LR categorization for focal liver lesions (FLLs) among different radiologists. MATERIALS AND METHODS: A total of 18 visiting radiologists and the liver multiphase CT images of 70 hepatic observations in 63 patients at high risk of HCC were included in this study. The LI-RADS v2018 training procedure included three thematic lectures, with an interval of 1 month. After each seminar, the radiologists had 1 month to adopt the algorithm into their daily work. The interobserver agreements and performances in LR categorization for FLLs among the radiologists before and after training were compared. RESULTS: After training, the interobserver agreements in classifying the LR categories for all radiologists were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.053). After systematic training, the areas under the curve (AUCs) for LR categorization performance for all participants were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.062). CONCLUSION: Systematic training in the use of the LI-RADS can improve the interobserver agreements and performances in LR categorization for FLLs among radiologists with different levels of experience.
Subject(s)
Liver , Radiologists , Humans , Liver/diagnostic imaging , Tomography, X-Ray Computed , Radiologists/education , Data Systems , Liver Neoplasms/diagnostic imaging , Observer Variation , Male , Female , Adult , Middle Aged , Aged , Aged, 80 and overABSTRACT
Health management information systems (HMISs) are essential in programme planning, budgeting, monitoring and evidence-informed decision-making. This paper focuses on donor transitions in two upper-middle-income countries, China and Georgia, and explores how national HMIS adaptations were made and what facilitated or limited successful and sustainable transitions. This comparative analytical case study uses a policy triangle framework and a mixed-methods approach to explore how and why adaptations in the HMIS occurred under the Gavi Alliance and the Global Fund-supported programmes in China and Georgia. A review of published and grey literature, key informant interviews and administrative data analysis informed the study findings. Contextual factors such as the global and country context, and health system and programme needs drove HMIS developments. Other factors included accountability on a national and international level; improvements in HMIS governance by establishing national regulations for clear mandates of data collection and reporting rules and creating institutional spaces for data use; investing in hardware, software and human resources to ensure regular and reliable data generation; and capacitating national players to use data in evidence-based decision-making for programme and transition planning, budgeting and outcome monitoring. Not all the HMIS initiatives supported by donors were sustained and transitioned. For the successful adaptation and sustainable transition, five interlinked and closely coordinated support areas need to be considered: (1) coupling programme design with a good understanding of the country context while considering domestic and external demands for information, (2) regulating appropriate governance and management arrangements enhancing country ownership, (3) avoiding silo HMIS solutions and taking integrative approach, (4) ensuring the transition of funding onto domestic budget and enforcing fulfilment of the government's financial commitments and finally (5) investing in technologies and skilled human resources for the HMIS throughout all levels of the health system. Neglecting any of these elements risks not delivering sustainable outcomes.
Subject(s)
Budgets , Data Systems , Humans , China , Data Collection , Georgia (Republic)ABSTRACT
INTRODUCTION: The aim of our study is to determine the value of Thyroid Imaging Reporting and Data Systems (TIRADS) scoring in predicting malignancy in thyroid nodules by examining its relationship with fine needle aspiration biopsy and postoperative histopathological results. MATERIALS AND METHODS: In this study, patients who underwent surgery after ultrasonographic examination and fine needle aspiration biopsy for thyroid nodules at the General Surgery Clinic of Çukurova University Faculty of Medicine between January 2014 and November 2021 were retrospectively analyzed. The thyroid ultrasonography and fine needle aspiration biopsy of the included patients were performed by a clinician with 15 years of experience. The ultrasonographic features of the nodules were re-evaluated by the same clinician, and the American College of Radiology (ACR) TIRADS score was determined. Fine needle aspiration biopsy results were grouped according to Bethesda criteria. Postoperative histopathological examination results were divided into two groups: benign and malignant. The ACR TIRADS score was compared with fine needle aspiration biopsy and histopathological results. The performance of the ACR TIRADS score in predicting malignancy was determined. RESULTS: 79.8% of the 397 patients were female, and the mean age was 50.9 ± 12.8 years. The mean diameter of the nodules was 27.4 ± 15.8 mm. There was a significant, positive, but weak correlation between ACR TIRADS and Bethesda (p < 0.001) (r = 0.33). When the ACR TIRADS score was compared with histopathological results, it was found that the rate of malignancy increased as the TIRADS score increased (p < 0.001). The rates of malignancy diagnosis were 0% for TR1, 13.2% for TR2, 21.7% for TR3, 50.3% for TR4, and 72.4% for TR5. The area under the receiver operating characteristic curve for TIRADS in predicting malignancy was 0.747 (95% CI: 0.699-0.796, p < 0.001). TIRADS can distinguish malignancy with 75% accuracy. The optimal cutoff point was determined as TR4 with 80.3% sensitivity and 60.8% specificity. CONCLUSION: The ACR TIRADS scoring system is an effective risk classification system for thyroid nodules, providing 75% accuracy in predicting malignancy, with 80.3% sensitivity and 60.8% specificity values.
Subject(s)
Thyroid Neoplasms , Thyroid Nodule , Humans , Female , Adult , Middle Aged , Male , Thyroid Nodule/diagnostic imaging , Thyroid Nodule/surgery , Thyroid Neoplasms/diagnostic imaging , Thyroid Neoplasms/surgery , Retrospective Studies , Biopsy, Fine-Needle/methods , Data Systems , Ultrasonography/methodsABSTRACT
Among the 28 reporting and data systems (RADS) available in the literature, we identified 15 RADS that can be used in Magnetic Resonance Imaging (MRI). Performing examinations without using gadolinium-based contrast agents (GBCA) has benefits, but GBCA administration is often required to achieve an early and accurate diagnosis. The aim of the present review is to summarize the current role of GBCA in MRI RADS. This overview suggests that GBCA are today required in most of the current RADS and are expected to be used in most MRIs performed in patients with cancer. Dynamic contrast enhancement is required for correct scores calculation in PI-RADS and VI-RADS, although scientific evidence may lead in the future to avoid the GBCA administration in these two RADS. In Bone-RADS, contrast enhancement can be required to classify an aggressive lesion. In RADS scoring on whole body-MRI datasets (MET-RADS-P, MY-RADS and ONCO-RADS), in NS-RADS and in Node-RADS, GBCA administration is optional thanks to the intrinsic high contrast resolution of MRI. Future studies are needed to evaluate the impact of the high T1 relaxivity GBCA on the assignment of RADS scores.
Subject(s)
Magnetic Resonance Imaging , Prostatic Neoplasms , Male , Humans , Magnetic Resonance Imaging/methods , Contrast Media , Gadolinium , Data Systems , Retrospective StudiesABSTRACT
Background: Risk stratification systems for thyroid nodules are limited by low specificity. The fine-needle aspiration (FNA) biopsy size thresholds and stratification criteria are based on evidence from the literature and expert consensus. Our aims were to investigate the optimal FNA biopsy size thresholds in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and artificial intelligence (AI) TI-RADS and to revise the stratification criteria in AI TI-RADS. Methods: A total of 2596 thyroid nodules (in 2511 patients) on ultrasound examination with definite pathological diagnoses were retrospectively identified from January 2017 to September 2021 in 6 participating Chinese hospitals. The modified criteria for ACR TI-RADS were as follows: (1) no FNA for TR3; (2) FNA threshold for TR4 increased to 2.5 cm. The modified criteria for AI TI-RADS were as follows: (1) 6-point nodules upgraded to TR5; (2) no FNA for TR3; (3) FNA threshold for TR4 increased to 2.5 cm. The diagnostic performance and the unnecessary FNA rate (UFR) of modified versions were compared with the original ACR TI-RADS. Results: Compared with the original ACR TI-RADS, the modified ACR (mACR) TI-RADS yielded higher specificity (73% vs. 46%), accuracy (74% vs. 51%), area under the receiver operating characteristic curve (AUC; 0.80 vs. 0.70), and lower UFR (25% vs. 48%; all p < 0.001), although the sensitivity was slightly decreased (87% vs. 93%, p = 0.057). Compared with the original ACR TI-RADS, the modified AI (mAI) TI-RADS yielded higher specificity (73% vs. 46%), accuracy (75% vs. 51%), AUC (0.81 vs. 0.70), and lower UFR (24% vs. 48%; all p < 0.001), although the sensitivity tended to be slightly decreased (89% vs. 93%, p = 0.13). There was no significant difference between the mACR TI-RADS and mAI TI-RADS in the diagnostic performance and UFR (all p > 0.05). Conclusions: The revised FNA thresholds and the stratification criteria of the mACR TI-RADS and mAI TI-RADS may be associated with improvements in specificity and accuracy, without significantly sacrificing sensitivity for malignancy detection.
Subject(s)
Radiology , Thyroid Nodule , Humans , United States , Thyroid Nodule/diagnostic imaging , Thyroid Nodule/pathology , Retrospective Studies , Data Systems , Artificial Intelligence , Ultrasonography/methodsABSTRACT
OBJECTIVE: To compare biopsy recommendation rates and accuracy of the Prostate Imaging-Reporting and Data System, version 2 (PI-RADSv2) with the Likert scale for detection of clinically significant and insignificant prostate cancer in men screened within the Imperial Prostate 1 Prostate Cancer Screening Trial Using Imaging (IP1-PROSTAGRAM). PATIENTS AND METHODS: Men aged 50-69 years were screened with Prostagram MRI. Scans were prospectively reported using both PI-RADSv2 (excluding dynamic contrast-enhanced sequence score) and 5-point Likert scores by expert uro-radiologists. Systematic and targeted transperineal biopsy was recommended if the scan was scored ≥ 3, based on either reporting system. The proportion of patients recommended for biopsy and detection rates for Grade Groups (GGs) 1 and ≥ 2 were compared. Receiver operating characteristic (ROC) analysis was performed to compare performance. RESULTS: A total of 406 men underwent Prostagram MRI. The median (interquartile range) age and prostate-specific antigen level were 57 (53-61) years and 0.91 (0.56-1.74) ng/mL, respectively. At MRI score ≥ 3, more patients were recommended for biopsy based on Likert criteria (94/406; 23%, 95% confidence interval [CI] 19.2%-27.6%) compared to PI-RADSv2 (72/406; 18%, 95% CI 14.2%-21.9%; P = 0.03). For MRI scores ≥ 4, PI-RADSv2 and Likert scales led to 43/406 (11%, 95% CI 7.9%-14.1%) and 35/406 (9%, 95% CI 6.2%-11.9%) men recommended for biopsy (P = 0.40). For GG ≥ 2 detection, PIRADSv2 and Likert detected 22% (95% CI 11.4%-30.8%, 14/72) and 16% (95% CI 9.5%-25.3%, 15/94), respectively (P = 0.56). For GG1 cancers detection these were 11% (95% CI 4.3%-19.6%, seven of 72) vs 11% (95% CI 4.7%-17.8%, nine of 94; P = 1.00). The accuracy of PI-RADSv2 and Likert scale was similar (area under the ROC curve 0.64 vs 0.65, P = 0.95). CONCLUSIONS: In reporting non-contrast-enhanced Prostagram MRI in a screening population, the PI-RADSv2 and Likert scoring systems were equally accurate; however, Likert scale use led to more men undergoing biopsy without a subsequent increase in significant cancer detection rates. To improve reporting of Prostagram MRI, either the PI-RADSv2 or a modified Likert scale or a standalone scoring system should be developed.
Subject(s)
Prostate , Prostatic Neoplasms , Male , Humans , Prostate/pathology , Prostatic Neoplasms/pathology , Data Systems , Early Detection of Cancer , Prostate-Specific Antigen , Magnetic Resonance Imaging/methods , Retrospective StudiesABSTRACT
BACKGROUND: In 2021, Nigeria developed a novel Electronic Management of Immunization Data (EMID) system to address COVID-19 data management challenges and ensure the successful implementation of its COVID-19 vaccine deployment plan. The EMID system was envisioned to be interoperable with the DHIS2 national data management system and serve as a gateway into the integration of other primary health care (PHC) service data management. However, the EMID system faced challenges, including inability to filter reports, missing or loss of data, and difficulties with data synchronization, which curtailed its potential to meet the country's needs for COVID-19 data management and negatively impacted system scalability to enable integration with other PHC data systems. METHODS: Multilayered stakeholder interviews were conducted to determine the optimal functionality requirements for the EMID system. Based on these findings, an optimization plan was designed and implemented to address identified gaps and create a more stable and scalable system to enable further system integrations. Following optimization, a routine immunization module was developed and integrated with the EMID system as a first step to achieving an integrated data management system for PHC services in Nigeria. RESULTS: The integrated system currently provides an opportunity to address data fragmentation and strengthen PHC service delivery in Nigeria. By allowing 1 health care worker to deliver both vaccinations, there is also potential for reduction in cost and redundancies, informing redistribution of the health workforce and overall system strengthening. CONCLUSION: The journey from the initial challenges faced by the EMID system to the development of an integrated system for PHC services in Nigeria has been a transformative one. Through a thorough optimization process, training and capacity-building, stakeholder-driven improvements, and an elicitation exercise, the EMID system has evolved into a powerful tool for addressing data fragmentation and enhancing public health service delivery in the country.
Subject(s)
COVID-19 Vaccines , COVID-19 , Humans , Nigeria , Data Systems , Systems Integration , COVID-19/epidemiology , COVID-19/prevention & control , Immunization , VaccinationABSTRACT
BACKGROUND: The Neck Imaging Reporting and Data System (NI-RADS) is a reporting template used in head and neck cancer posttreatment follow-up imaging. PURPOSE: Our aim was to evaluate the pooled detection rates of the recurrence of head and neck squamous cell carcinoma based on each NI-RADS category and to compare the diagnostic accuracy between NI-RADS 2 and 3 cutoffs. DATA SOURCES: The MEDLINE, Scopus, and EMBASE databases were searched. STUDY SELECTION: This systematic review identified 7 studies with a total of 694 patients (1233 lesions) that were eligible for the meta-analysis. DATA ANALYSIS: The meta-analysis of pooled recurrence detection rate estimates for each NI-RADS category and the diagnostic accuracy of recurrence with NI-RADS 3 or 2 as the cutoff was performed. DATA SYNTHESIS: The estimated recurrence rates in each category for primary lesions were 74.4% for NI-RADS 3, 29.0% for NI-RADS 2, and 4.2% for NI-RADS 1. The estimated recurrence rates in each category for cervical lymph nodes were 73.3% for NI-RADS 3, 14.3% for NI-RADS 2, and 3.5% for NI-RADS 1. The area under the curve of the summary receiver operating characteristic for recurrence detection with NI-RADS 3 as the cutoff was 0.887 and 0.983, respectively, higher than 0.869 and 0.919 for the primary sites and cervical lymph nodes, respectively, with NI-RADS 2 as the cutoff. LIMITATIONS: Given the heterogeneity of the data of the studies, the conclusions should be interpreted with caution. CONCLUSIONS: This meta-analysis revealed estimated recurrence rates for each NI-RADS category for primary lesions and cervical lymph nodes and showed that NI-RADS 3 has a high diagnostic performance for detecting recurrence.
Subject(s)
Head and Neck Neoplasms , Humans , Squamous Cell Carcinoma of Head and Neck/diagnostic imaging , Head and Neck Neoplasms/diagnostic imaging , ROC Curve , Research Design , Data Systems , Magnetic Resonance Imaging/methodsABSTRACT
OBJECTIVE: The aim of this study was to compare the capacity of American Thyroid Association and Thyroid Imaging Reporting and Data System developed by the American College of Radiology in predicting malignancy risk of thyroid nodules and to verify which one is better at avoiding unnecessary fine needle aspiration. METHODS: This was a cross-sectional study with 565 thyroid nodules, followed at a tertiary care hospital, in an iodine-replete area. Those were classified as American Thyroid Association and Thyroid Imaging Reporting and Data System developed by the American College of Radiology systems and stratified according to the Bethesda classification of fine needle aspiration. The values of sensibility, specificity, positive predictive value, and negative predictive value accuracy were calculated. Also, the percentage of unnecessary biopsies was presented. RESULTS: The mean age of the individuals was 58.2±13.5 [26-90] years for benign nodules and 41.7±15.6 [23-66] years for malignant nodules (p=0.002). Regarding gender, 92.6% (n=150) of the individuals with benign nodules and 85.7% (n=06) with malignant nodules were females (p=0.601). For American Thyroid Association, 90.9% of sensibility, 51.4% of specificity, 52.6% of accuracy, 10.2% of positive predictive value, and 98.9% of negative predictive value were found. For Thyroid Imaging Reporting and Data System developed by the American College of Radiology, 90.9% of sensibility, 49.7% of specificity, 52.1% of accuracy, 9.9% of positive predictive value, and 98.9% of negative predictive value were found. .Notably, 12.3% of unnecessary fine needle aspiration were found in American Thyroid Association and 44.4% were found in Thyroid Imaging Reporting and Data System developed by the American College of Radiology. CONCLUSION: Both Thyroid Imaging Reporting and Data System developed by the American College of Radiology and American Thyroid Association are able to predict the malignancy risk of thyroid nodules. Thyroid Imaging Reporting and Data System developed by the American College of Radiology was better at avoiding unnecessary fine needle aspiration.
Subject(s)
Radiology , Thyroid Nodule , Female , Humans , Adult , Middle Aged , Aged , Aged, 80 and over , Male , Thyroid Nodule/diagnostic imaging , Data Systems , Cross-Sectional Studies , Biopsy, Fine-NeedleABSTRACT
The aim of this study was to validate the performance of the Ovarian-Adnexal Reporting and Data Systems (O-RADS) series models proposed by the American College of Radiology (ACR) in the preoperative diagnosis of adnexal masses (AMs). Two experienced sonologists examined 218 patients with AMs and gave the assessment results after the examination. Pathological findings were used as a reference standard. Of the 218 lesions, 166 were benign and 52 were malignant. Based on the receiver operating characteristic (ROC) curve, we defined a malignant lesion as O-RADS > 3 (i.e., lesions in O-RADS categories 4 and 5 were malignant). The area under the curve (AUC) of O-RADS (v2022) was 0.970 (95% CI 0.938-0.988), which wasn't statistically significantly different from the O-RADS (v1) combined Simple Rules Risk (SRR) assessment model with the largest AUC of 0.976 (95% CI 0.946-0.992) (p = 0.1534), but was significantly higher than the O-RADS (v1) (AUC = 0.959, p = 0.0133) and subjective assessment (AUC = 0.918, p = 0.0255). The O-RADS series models have good diagnostic performance for AMs. Where, O-RADS (v2022) has higher accuracy and specificity than O-RADS (v1). The accuracy and specificity of O-RADS (v1), however, can be further improved when combined with SRR assessment.
Subject(s)
Data Systems , Ovary , Female , Humans , Area Under Curve , ExtremitiesABSTRACT
CONTEXT: Lacrimators are used by individuals for personal defense and by police for crowd control during periods of civil unrest. Increased public awareness about their use has raised concerns about their application and safety. OBJECTIVE: To characterize patterns of lacrimator exposures in the United States, we describe temporal trends of calls to poison centers by demographics, substances, medical outcomes, exposure sites, and scenarios. METHODS: A retrospective data analysis was performed for all single-substance lacrimator exposures in the United States reported to the National Poison Data System between 2000 and 2021. Descriptive analyses were performed to examine demographic characteristics, geographic distribution, product types and medical outcomes associated with lacrimator exposures. RESULTS: A total of 107,149 lacrimator exposure calls were identified. There was an overall decrease in calls per year, from 6,521 calls in 2000 to 2,520 in 2020, followed by an increase to 3,311 calls in 2021. A declining trend was observed independent of total poison center call volume. Oleoresin capsicum was the most commonly reported substance (81,990, 76.5%). Individuals ages 19 years and younger accounted for 62% of calls, but adults ages 20 and over were more likely to develop major clinical effects (odds ratio 3.03; 95% confidence interval 1.91-4.81; P < 0.0001). The most common exposure site was "own residence," followed by schools. School exposures accounted for 15.8% of exposures in children ages 6-12 years and 37.7% in adolescents. Among calls with documented scenarios, 19.7% involved unintentional exposures due to children accessing lacrimators. CONCLUSION: Lacrimator exposure calls to United States poison centers decreased from 2000 to 2021. Most calls pertain to oleoresin capsicum and individuals ages 19 and younger. Improper storage allowing children to have access to these chemicals, is a common scenario. Public safety interventions such as education about safe storage and use of lacrimators, improved product design, or regulatory changes may prevent unintentional exposures.
Subject(s)
Poisons , Child , Adult , Adolescent , Humans , United States/epidemiology , Retrospective Studies , Poison Control Centers , Databases, Factual , Data Systems , GasesABSTRACT
Wireless sensor networks are widely used in sports training, medical and health care, smart home, environmental monitoring, cloud data and other fields because of their large scale, self-organization, reliability, dynamic, integration and data centralization. Based on this point, this article conducts a comprehensive analysis and research on cloud computing data systems, and designs and implements a dynamic replication strategy. Since different users have different demands for different data at different times, it is necessary to record and analyze recent users' data access, so as to actively adjust the number and location of data blocks. Subsequently, a multi-source blockchain transmission method was proposed and implemented, which can significantly reduce the time cost of data migration and improve the overall performance of cloud storage data systems. Finally, the article provides an in-depth analysis of long-distance running fatigue. This study will design a simulated specialized exercise load experiment to reproduce the load characteristics of excellent athletes during mid to long distance running, in order to induce exercise fatigue in the main muscles of different parts of their bodies. At the same time, the amplitude frequency joint analysis of the surface changes of EMG signal in this process is carried out. This article conducts research on sensor based cloud computing data systems and long-distance running fatigue assessment, promoting the development of cloud computing data systems and improving long-distance running fatigue assessment methods.
Subject(s)
Cloud Computing , Running , Humans , Reproducibility of Results , Data SystemsABSTRACT
The Ovarian-Adnexal Reporting and Data System (O-RADS) MRI risk stratification system provides a standardized lexicon and evidence-based risk score for evaluation of adnexal lesions. The goals of the lexicon and risk score are to improve report quality and communication between radiologists and clinicians, reduce variability in the reporting language, and optimize management of adnexal lesions. The O-RADS MRI risk score is based on the presence or absence of specific imaging features, including the lipid content, enhancing solid tissue, number of loculi, and fluid type. The probability of malignancy ranges from less than 0.5% when there are benign features to approximately 90% when there is solid tissue with a high-risk time-intensity curve. This information can aid in optimizing management of patients with adnexal lesions. The authors present an algorithmic approach to the O-RADS MRI risk stratification system and highlight key teaching points and common pitfalls. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.