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Brain differences linked to autism spectrum disorder (ASD) can manifest before observable symptoms. Studying these early neural precursors in larger and more diverse cohorts is crucial for advancing our understanding of developmental pathways and potentially facilitating earlier identification. EEG is an ideal tool for investigating early neural differences in ASD, given its scalability and high tolerability in infant populations. In this context, we integrated EEG into an existing multi-site MRI study of infants with a higher familial likelihood of developing ASD. This paper describes the comprehensive protocol established to collect longitudinal, high-density EEG data from infants across five sites as part of the Infant Brain Imaging Study (IBIS) Network and reports interim feasibility and data quality results. We evaluated feasibility by measuring the percentage of infants from whom we successfully collected each EEG paradigm. The quality of task-free data was assessed based on the duration of EEG recordings remaining after artifact removal. Preliminary analyses revealed low data loss, with average in-session loss rates at 4.16 % and quality control loss rates at 11.66 %. Overall, the task-free data retention rate, accounting for both in-session issues and quality control, was 84.16 %, with high consistency across sites. The insights gained from this preliminary analysis highlight key sources of data attrition and provide practical considerations to guide similar research endeavors.

Despite ethical and historical arguments for removing race from clinical algorithms, the consequences of removal remain unclear. Here, we highlight a largely undiscussed consideration in this debate: varying data quality of input features across race groups. For example, family history of cancer is an essential predictor in cancer risk prediction algorithms but is less reliably documented for Black participants and may therefore be less predictive of cancer outcomes. Using data from the Southern Community Cohort Study, we assessed whether race adjustments could allow risk prediction models to capture varying data quality by race, focusing on colorectal cancer risk prediction. We analyzed 77,836 adults with no history of colorectal cancer at baseline. The predictive value of self-reported family history was greater for White participants than for Black participants. We compared two cancer risk prediction algorithms-a race-blind algorithm which included standard colorectal cancer risk factors but not race, and a race-adjusted algorithm which additionally included race. Relative to the race-blind algorithm, the race-adjusted algorithm improved predictive performance, as measured by goodness of fit in a likelihood ratio test (P-value:

In classic semiquantitative metabolomics, metabolite intensities are affected by biological factors and other unwanted variations. A systematic evaluation of the data processing methods is crucial to identify adequate processing procedures for a given experimental setup. Current comparative studies are mostly focused on peak area data but not on absolute concentrations. In this study, we evaluated data processing methods to produce outputs that were most similar to the corresponding absolute quantified data. We examined the data distribution characteristics, fold difference patterns between 2 metabolites, and sample variance. We used 2 metabolomic datasets from a retail milk study and a lupus nephritis cohort as test cases. When studying the impact of data normalization, transformation, scaling, and combinations of these methods, we found that the cross-contribution compensating multiple standard normalization (ccmn) method, followed by square root data transformation, was most appropriate for a well-controlled study such as the milk study dataset. Regarding the lupus nephritis cohort study, only ccmn normalization could slightly improve the data quality of the noisy cohort. Since the assessment accounted for the resemblance between processed data and the corresponding absolute quantified data, our results denote a helpful guideline for processing metabolomic datasets within a similar context (food and clinical metabolomics). Finally, we introduce Metabox 2.0, which enables thorough analysis of metabolomic data, including data processing, biomarker analysis, integrative analysis, and data interpretation. It was successfully used to process and analyze the data in this study. An online web version is available at http://metsysbio.com/metabox.

Data curators play an important role in assessing data quality and take actions that may ultimately lead to better, more valuable data products. This study explores the curation practices of data curators working within US-based data repositories. We performed a survey in January 2021 to benchmark the levels of curation performed by repositories and assess the perceived value and impact of curation on the data sharing process. Our analysis included 95 responses from 59 unique data repositories. Respondents primarily were professionals working within repositories and examined curation performed within a repository setting. A majority 72.6% of respondents reported that data-level curation was performed by their repository and around half reported their repository took steps to ensure interoperability and reproducibility of their repositorys datasets. Curation actions most frequently reported include checking for duplicate files, reviewing documentation, reviewing metadata, minting persistent identifiers, and checking for corrupt/broken files. The most value-add curation action across generalist, institutional, and disciplinary repository respondents was related to reviewing and enhancing documentation. Respondents reported high perceived impact of curation by their repositories on specific data sharing outcomes including usability, findability, understandability, and accessibility of deposited datasets; respondents associated with disciplinary repositories tended to perceive higher impact on most outcomes. Most survey participants strongly agreed that data curation by the repository adds value to the data sharing process and that it outweighs the effort and cost. We found some differences between institutional and disciplinary repositories, both in the reported frequency of specific curation actions as well as the perceived impact of data curation. Interestingly, we also found variation in the perceptions of those working within the same repository regarding the level and frequency of curation actions performed, which exemplifies the complexity of a repository curation work. Our results suggest data curation may be better understood in terms of specific curation actions and outcomes than broadly defined curation levels and that more research is needed to understand the resource implications of performing these activities. We share these results to provide a more nuanced view of curation, and how curation impacts the broader data lifecycle and data sharing behaviors.

Electronic medical records (EMRs) are important for rapidly compiling information to determine disease characteristics (eg, symptoms) and risk factors (eg, underlying comorbidities, medications) for disease-related outcomes. To assess EMR data accuracy, agreement between EMR abstractions and patient interviews was evaluated. Symptoms, medical history, and medication use among patients with COVID-19 collected from EMRs and patient interviews were compared using overall agreement (ie, same answer in EMR and interview), reported agreement (yes answer in both EMR and interview among those who reported yes in either), and κ statistics. Overall, patients reported more symptoms in interviews than in EMR abstractions. Overall agreement was high (≥50% for 20 of 23 symptoms), but only subjective fever and dyspnea had reported agreement of ≥50%. The κ statistics for symptoms were generally low. Reported medical conditions had greater agreement with all condition categories (n = 10 of 10) having ≥50% overall agreement and half (n = 5 of 10) having ≥50% reported agreement. More nonprescription medications were reported in interviews than in EMR abstractions, leading to low reported agreement (28%). Discordance was observed for symptoms, medical history, and medication use between EMR abstractions and patient interviews. Investigations using EMRs to describe clinical characteristics and identify risk factors should consider the potential for incomplete data, particularly for symptoms and medications. [ABSTRACT FROM AUTHOR]

Copyright of HNO is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: In Portugal, trained physicians undertake the clinical coding process, which serves as the basis for hospital reimbursement systems. In 2017, the classification version used for coding of diagnoses and procedures for hospital morbidity changed from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS). Objective: To assess the perceptions of medical coders on the transition of the clinical coding process from ICD-9-CM to ICD-10-CM/PCS in terms of its impact on data quality, as well as the major differences, advantages, and problems they faced. Method: We conducted an observational study using a web-based survey submitted to medical coders in Portugal. Survey questions were based on a literature review and from previous focus group studies. Results: A total of 103 responses were obtained from medical coders with experience in the two versions of the classification system (i.e. ICD-9-CM and ICD-10-CM/PCS). Of these, 82 (79.6%) medical coders preferred the latest version and 76 (73.8%) considered that ICD-10-CM/PCS guaranteed higher quality of the coded data. However, more than half of the respondents (N = 61; 59.2%) believed that more time for the coding process for each episode was needed. Conclusion: Quality of clinical coded data is one of the major priorities that must be ensured. According to the medical coders, the use of ICD-10-CM/PCS appeared to achieve higher quality coded data, but also increased the effort. Implications: According to medical coders, the change off classification systems should improve the quality of coded data. Nevertheless, the extra time invested in this process might also pose a problem in the future. [ABSTRACT FROM AUTHOR]

Background: Population surveys are crucial for public policy planning and provide valuable representative data. In the health sector studies to identify and assess the prevalence of Arterial Hypertension (AH), a chronic non-communicable disease (NCD), along with its associated risk factors have been conducted. Objectives: This study aims to assess the effectiveness of a population health survey in estimating the prevalence of arterial hypertension (AH) in the Sorocaba municipality between August 2021 and June 2023. Methods: The analyzed performance indicator is the precision (design effect - deff) of AH prevalence in adults (≥ 18 years) and their exposure to primary risk factors. The total sample included 1,080 individuals from the urban area, deemed sufficient to estimate a deff of 1.5. This cluster-based study utilized census sectors as clusters, with data collected through household interviews, standardized questionnaires, and measurements of blood pressure and biometric parameters. The deff calculation formula used was weighted variance / raw variance. The Research Ethics Committee approved this study, with registration CAAE 30538520-1-0000-5373. Results: The deff values ranged from 0.44 for chronic obstructive pulmonary disease to 1.63 for asthma, with a deff of 1.00 for AH prevalence. Conclusion: The study demonstrated good precision in its results, with high receptivity and cooperation from participants. The cost-effectiveness of the research deemed appropriate. The technique of selecting households within clusters (census sectors) based on detailed mapping and demographic data from the Instituto Brasileiro de Geografia e Estatística (IBGE) proved to be practical and efficient, suitable for replication in other municipalities and for studying other NCDs. [ABSTRACT FROM AUTHOR]

Background: Vestibular Activities and Participation Measure (VAP) subscales assess the effect of vestibular disorders on activity and participation. This study aimed to perform the cross-cultural adaptation and assess the validity, internal consistency, reliability, and measurement error of the Brazilian version of VAP subscales. Methods: The cross-cultural adaptation followed the translation, synthesis, back-translation, review by a committee of experts, and pretesting phases. Structural validity was assessed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while Spearman's correlation between VAP subscales and the Dizziness Handicap Inventory (DHI) was used to assess construct validity. Cronbach's alpha measured internal consistency. Intraclass correlation coefficient (ICC) assessed intra- and inter-rater reliability, and measurement error was calculated by using the standard error of measurement (SEM) and minimal detectable change (MDC). Results: Additional information was included in the Brazilian version of the Vestibular Activities and Participation measure (VAP-BR) after approval by one of the developers of the instrument to improve the understanding among individuals. One factor was found in the EFA for each subscale with 50% explained variance. Regarding CFA, the subscales 1 (S1) and 2 (S2) presented, respectively, adequate model fit indices (ie, comparative fit index of 0.99 and 0.97, and standardized root mean square residual of 0.04 for both subscales), but a very low factor load in item 6 of S1 (0.08). Chronbach's alpha was 0.80 (S1) and 0.82 (S2). For intra-rater assessment, the S1 and S2 presented an ICC of 0.87 and 0.90, SEM of 0.01 and 1.16, and MDC of 0.39 and 0.46, respectively. When assessed by 2 different raters, SEM values were 1.03 and 1.53, and MDC values were 2.85 and 4.23 for S1 and S2, respectively; both subscales showed an ICC of 0.92. Correlations between DHI and VAP subscales presented coefficients above 0.57. Conclusion: The Brazilian version of VAP subscales presents good measurement properties and may assist health professionals in identifying activity limitations and participation restrictions in individuals with vestibular disorders. [ABSTRACT FROM AUTHOR]

New Adaptive Nano-Scale Sensor Network (ANSN) can quickly feel nanoscale surroundings. ANSN uses data in many scenarios to improve networks, consume less energy, and gain more accurate data. ANSI essentials are covered in detail here. This group has numerous parts. Making service better, collecting data with less energy, sending data with Q-learning, merging sensor data to increase accuracy, controlling power dynamically, and protecting data using AES are examples. Energy collection and sensor use are key to this effort. Academic research has proven that ANSN outperforms other techniques in several areas. Improvements include speed, security, latency, sensor accuracy, and network stability. With these changes, ANSN may be suitable for small wireless sensor networks [ABSTRACT FROM AUTHOR]

Abstract Background Population surveys are crucial for public policy planning and provide valuable representative data. In the health sector studies to identify and assess the prevalence of Arterial Hypertension (AH), a chronic non-communicable disease (NCD), along with its associated risk factors have been conducted. Objectives This study aims to assess the effectiveness of a population health survey in estimating the prevalence of arterial hypertension (AH) in the Sorocaba municipality between August 2021 and June 2023. Methods: The analyzed performance indicator is the precision (design effect - deff) of AH prevalence in adults (≥ 18 years) and their exposure to primary risk factors. The total sample included 1,080 individuals from the urban area, deemed sufficient to estimate a deff of 1.5. This cluster-based study utilized census sectors as clusters, with data collected through household interviews, standardized questionnaires, and measurements of blood pressure and biometric parameters. The deff calculation formula used was weighted variance / raw variance. The Research Ethics Committee approved this study, with registration CAAE 30538520-1-0000-5373. Results The deff values ranged from 0.44 for chronic obstructive pulmonary disease to 1.63 for asthma, with a deff of 1.00 for AH prevalence. Conclusion: The study demonstrated good precision in its results, with high receptivity and cooperation from participants. The cost-effectiveness of the research deemed appropriate. The technique of selecting households within clusters (census sectors) based on detailed mapping and demographic data from the Instituto Brasileiro de Geografia e Estatística (IBGE) proved to be practical and efficient, suitable for replication in other municipalities and for studying other NCDs.

In the banking industry, data accuracy and integrity are paramount for ensuring regulatory compliance, operational efficiency, and risk management. However, manual data validation processes often lead to delays, errors, and inefficiencies, posing challenges for financial institutions. To address these issues, many banks are turning to automation to streamline data validation processes and improve accuracy. Using data automation, banks optimize time-consuming manual tasks such as data entry, validation, and retrieval by creating automated software processes that execute these tasks quickly and accurately. This case study examines how a hypothetical bank uses automation to improve data validation processes, focusing on Albanian Identity Numbers (AINs). By automating validation tasks, the bank enhances accuracy, compliance, and efficiency, mitigating the limitations of manual processes. The study outlines the implementation steps, discusses results, and highlights the importance of automating data validation in the banking sector.

Abstract Aim The study was performed to compare the mandibular resection guide with a directional guidance slot with the conventional guide regarding three-dimensional positional accuracy. Materials and methods Twenty-six patients with lateral segmental mandibular defects were selected, and randomly allocated into two groups. All defects were managed with preoperative virtual surgical planning. Resection in the test group was conducted using a resection guide with a directional guidance slot, while a conventional resection guide design was utilized in the control group. The linear and angular deviation of the osteotomy planes was analyzed for both groups, along with the accuracy of the insertion of the reconstruction bone block in the resected defect. Data were documented, absolute deviation was calculated, statistical analysis was performed and significance was set at the 5% level. Results The cases conducted with a directional guidance templet reported a statistically significant difference when compared to the conventional edge-cutting guide regarding the linear and angular spatial osteotomy plane position (P

Introduction. Choric obstructive pulmonary disease (COPD) is the third mortality cause in the world, and the development of useful diagnostic tools is necessary to improve timely diagnostic rates in primary care settings. Objective. To develop a web application displaying spirometric and clinical information – including respiratory symptoms and risk factors– to facilitate a COPD diagnosis. Materials and methods. In this cross-sectional study, an expert consensus was carried out with three specialists using the Delphi method to choose the relevant variables for COPD diagnosis. We developed a Python-based web application to diagnose COPD, displaying the clinical variables deemed relevant by the experts along the spirometric curve. Results. Twenty-six clinical variables were included in the web application for the diagnosis of COPD. A fourth expert used the web application to classify a cohort of 695 patients who had undergone spirometry in a third-level centre and had answered at least one of five questionnaires for COPD screening. Out of the 695 subjects, 34% had COPD, according to the expert that diagnosed them using the web application. Only 42% of the patients in the COPD group had received a previous COPD diagnosis and 19% of the patients in the no COPD group had been misdiagnosed with the disease. Conclusion. We developed a web application that displays demographic and clinical information, as well as spirometric data, to facilitate the process of diagnosing COPD in primary care settings.

Among the accuracy analysis techniques for orthognathic surgery, regional voxel-based registration (R-VBR) has robust data, but remains unvalidated for smaller jaw segments. The purpose of this study was to validate the angular accuracy of R-VBR for segmental Le Fort I (SLFI) and genioplasty osteotomies. Postoperative cone beam computed tomography (CBCT) of consecutive patients with three-piece SLFI or genioplasties was rotated to a known pitch/roll/yaw (P/R/Y). Using R-VBR, a copy of the raw CBCT was superimposed onto the rotated CBCT at four mutual regions of interest (ROI): anterior, right posterior, and left posterior maxilla, and chin. The P/R/Y of each was subtracted from those of the rotated CBCT to calculate the angular error. The predictor and outcome variables were ROI and absolute angular error, respectively. The accuracy threshold was 0.5°. Ten SLFI and 34 genioplasties were analyzed based on the sample size calculation. The one-sample t -test and Wilcoxon signed rank test were applied in the analysis. The mean absolute error was 0.20–0.54° for the maxillary segments (all P ≤ 0.01) and 0.83–2.51° for the genioplasty segments (all P < 0.001). R-VBR has variable angular accuracy for SLFI osteotomies and may be insufficient for genioplasty. The findings may allow the design and interpretation of studies on SLFI and genioplasty with greater rigor, thereby contributing to minimizing the discrepancy between planned and achieved outcomes. [ABSTRACT FROM AUTHOR]

Purpose: The aims of the present study were (a) to compare the scanning time and image count to complete optical scans of a typodont between augmented‐reality‐assisted intraoral scanning (ARIOS) and intraoral scanning (IOS); (b) to compare the accuracy of the digital casts derived from ARIOS and IOS; (c) to compare participant‐related outcomes between ARIOS and IOS. Materials and Methods: A multi‐session within‐subject experiment was conducted to compare ARIOS and IOS. Thirty‐one dental students participated in the study. Following a trial session, each participant obtained optical scans under ARIOS and IOS conditions. The time required to complete the scan, and the number of images taken were recorded. Participant feedback was collected using entry, exit, and NASA‐Task Load Index (TLX) surveys. The accuracy of the digital casts derived from the optical scans was measured in root mean square error (RMSE). Results: The present study found a 6.8% increase in preference for ARIOS from entry to exit survey. Slightly more participants favored the ARIOS setup compared to IOS; 54.8% of participants favored ARIOS, 9.7% were indifferent, and 35.5% favored IOS. NASA‐TLX subscale ratings were higher for IOS in general apart from mental demand. The accuracy of the digital casts between ARIOS and IOS was comparable in RMSE. Conclusion: ARIOS was advantageous compared to IOS in ergonomics, improved scanner tracking, and ease of scanner orientation. However additional trials, increased field of view, and better superimposition of scanning status to the target site were improvements desired by the study participants. [ABSTRACT FROM AUTHOR]

The current review explores multiple definitions of school shootings used by myriad data collection platforms and by various scholars. Importantly, the impacts of definitional discrepancies on inclusion criteria, data divergence, research, policy, and public perception are discussed at length. The review concludes with a call to Criminologists and school gun violence scholars to better collaborate on what should be considered a "school shooting" and lists five benefits that may result from modifying school gun violence definitions and data collection methodologies. [ABSTRACT FROM AUTHOR]

Purpose: Preoperative planning has become essential in performance of total hip arthroplasty (THA). However, data regarding the effect of the planner's experience on the accuracy of digital preoperative planning is limited. The objective of this study was to assess the accuracy of digital templating in THA based on the surgeon's experience. Materials and Methods: A retrospective study was conducted. An analysis of 98 anteroposterior pelvic radiographs, which were individually templated by four surgeons (two hip surgeons and two orthopaedic residents) using TraumaCad® digital planning, was performed. A comparison of preoperatively planned sizes with implanted sizes was performed to evaluate the accuracy of predicting component size. The results of preoperative planning performed by hip surgeons and orthopaedic residents were compared for testing of the planner's experience. Results: Femoral stem was precisely predicted in 32.4% of cases, acetabular component in 40.3%, and femoral offset in 76.7%. Prediction of cup size showed greater accuracy than femoral size among all observers. No differences in any variable were observed among the four groups (acetabular cup P =0.07, femoral stem P =0.82, femoral offset P =0.06). All measurements showed good reliability (intraclass correlation coefficient [ICC] acetabular cup: 0.76, ICC femoral stem: 0.79). Conclusion: The results of this study might suggest that even though a surgeon's experience supports improved precision during the planning stage, it should not be restricted only to surgeons with a high level of experience. We consider preoperative planning an essential part of the surgery, which should be included in training for orthopaedics residents. [ABSTRACT FROM AUTHOR]

Copyright of Biomédica: Revista del Instituto Nacional de Salud is the property of Instituto Nacional de Salud of Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The integration of the Pencel Pressuremeter (PPMT) model with the Automated Pressuremeter (APMT) software represents a significant advancement in in-situ soil testing. This combination simplifies the process of data reduction and analysis, resulting in substantial time savings. The APMT software efficiently records digital pressure and volume data, performs necessary calibrations, and offers quick access to essential strength and stiffness properties for engineering analysis. Through extensive testing conducted on various soil types, the integration of a linear potentiometer and a digital pressure transducer into the control unit has significantly improved the accuracy of digital volume measurements and pressure readings. Notably, the Stabilization Time (ST) for volume increments, as estimated by the APMT software, ranges from 20 to 70 seconds depending on the specific soil conditions. The APMT system not only enhances data quality but also minimizes the potential for human recording errors. It drastically reduces the time required for data collection and analysis when compared to manual methods, establishing itself as an efficient and precise tool for evaluating soil properties. [ABSTRACT FROM AUTHOR]

Background: The International Classification of Diseases (ICD) is widely used by clinical coders worldwide for clinical coding morbidity data into administrative health databases. Accordingly, hospital data quality largely depends on the coders' skills acquired during ICD training, which varies greatly across countries. Objective: To characterise the current landscape of international ICD clinical coding training. Method: An online questionnaire was created to survey the 194 World Health Organization (WHO) member countries. Questions focused on the training provided to clinical coding professionals. The survey was distributed to potential participants who met specific criteria, and to organisations specialised in the topic, such as WHO Collaborating Centres, to be forwarded to their representatives. Responses were analysed using descriptive statistics. Results: Data from 47 respondents from 26 countries revealed disparities in all inquired topics. However, most participants reported clinical coders as the primary person assigning ICD codes. Although training was available in all countries, some did not mandate training qualifications, and those that did differed in type and duration of training, with college or university degree being most common. Clinical coding certificates most frequently entailed passing a certification exam. Most countries offered continuing training opportunities, and provided a range of support resources for clinical coders. Conclusion: Variability in clinical coder training could affect data collection worldwide, thus potentially hindering international comparability of health data. Implications: These findings could encourage countries to improve their resources and training programs available for clinical coders and will ultimately be valuable to the WHO for the standardisation of ICD training. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to evaluate the diagnostic accuracy, inter-reader agreement, and associated pathologies on MR images of patients with confirmed TC. Methods and materials: In this retrospective study, 168 ankle MRI exams were included, consisting of 56 patients with clinically or surgically confirmed TC and 112 controls without TC, matched for age and sex. Images were analyzed independently by three radiologists blinded to clinical information. The evaluation criteria included the presence, type, and location of TC, as well as associated pathologies. After calculating diagnostic accuracy and the odds ratio of demographic data and anatomic coalition type for associated pathologies, inter-reader agreement was assessed using kappa statistics. Results: The majority of TCs were non-osseous (91.1%) and located at the calcaneonavicular (33.9%) or talocalcaneal joint (66.1%). Associated pathologies included adjacent and distant bone marrow edema (57.1% and 25.0%), osteochondral defect of the talar dome (OCD, 19.6%), and joint effusion (10.7%) and accessory anterolateral talar facet (17.9%). Talar OCD was associated with increased patient age (p = 0.03). MRI exhibited a cumulative sensitivity and specificity of 95.8% and 94.3% with almost perfect inter-reader agreement (κ = 0.895). Conclusion: MRI is a reliable method for detecting tarsal coalition and identifying commonly associated pathologies. Therefore, we recommend the routine use of MRI in the diagnostic workup of patients with foot pain and suspected tarsal coalition. Clinical relevance statement: MRI is an accurate and reliable modality for diagnosing tarsal coalitions and detecting associated pathologies, while improving patient safety compared to computed tomography by avoiding radiation exposure. Key Points: • Despite the technological progress in magnetic resonance imaging (MRI), computed tomography (CT) is still regarded as the gold standard for diagnosing tarsal coalition (TC). • MRI had a cumulative sensitivity of 95.8% and specificity of 94.3% for detecting tarsal coalition with an almost perfect inter-reader agreement. • MRI demonstrates high accuracy and reliability in diagnosing tarsal coalitions and is useful for identifying associated pathologies, while also improving patient safety by avoiding radiation exposure. [ABSTRACT FROM AUTHOR]

Purpose: To compare the results of retinal venous pressure (RVP) measurement performed with contact lens dynamometry (CLD) and with the new IOPstim. Methods: In this cross-sectional study, we included 36 patients with primary open angle glaucoma with a median age (Q25; Q75) of 74 (64; 77) years (m/f = 18/18), baseline intraocular pressure (IOP): 13.9 (12.2; 15.1) mmHg. Median mean defect: − 5.8 (− 11.9; − 2.6) db. Principle of the IOPstim: an empty balloon with a diameter of 8 mm is positioned on the eye, laterally of the limbus. Under observation of the central retinal vein (CRV), the examiner inflates the balloon. As soon as the CRV starts pulsation, the inflation is stopped and the IOP is measured, equaling the RVP at this moment. In the CLD, the pulsation of the CRV is observed with a contact lens. The RVP is calculated from the attachment force applied when pulsation appears. Course of examinations: Three single measurements of RVP in quick succession with both methods. The sequence of the two methods was randomized. The means of the three RVP measurements were compared. Results: Pressures in mmHg. RVP: IOPstim: 19.4 ± 5.4 (mean ± SD), CLD: 20.3 ± 5.9. Range of three single measurements: IOPstim: 2.9 ± 1.5, CLD: 2.2 ± 1.1. The differences were RVPIOPstim − RVPCLD = − 0.94 ± 1.15, and approximately normally distributed. Bland–Altman analysis: only one data point was 0.5 mmHg higher than the upper line of agreement. The confidence interval of this line was 0.65 mmHg. Concordance correlation coefficient according to Lin (CCC): 0.96. Intraclass correlation coefficient: both methods, 0.94. Conclusion: In both methods, the range of the single measurements may be taken as a sign of good reliability, the CCC of 0.96 as a sign of a very good agreement. At the mean, the IOPstim RVP values were 1 mmHg lower than those obtained with the CLD. This difference may be due to the different directions of the prevailing force vectors induced by the instruments. The IOPstim seems applicable in glaucoma diagnostics. [ABSTRACT FROM AUTHOR]

Three-dimensional soft tissue simulation has become a popular tool in the process of virtual orthognathic surgery planning and patient–surgeon communication. To apply 3D soft tissue simulation software in routine clinical practice, both qualitative and quantitative validation of its accuracy are required. The objective of this study was to systematically review the literature on the accuracy of 3D soft tissue simulation in orthognathic surgery. The Web of Science, PubMed, Cochrane, and Embase databases were consulted for the literature search. The systematic review (SR) was conducted according to the PRISMA statement, and 40 articles fulfilled the inclusion and exclusion criteria. The Quadas-2 tool was used for the risk of bias assessment for selected studies. A mean error varying from 0.27 mm to 2.9 mm for 3D soft tissue simulations for the whole face was reported. In the studies evaluating 3D soft tissue simulation accuracy after a Le Fort I osteotomy only, the upper lip and paranasal regions were reported to have the largest error, while after an isolated bilateral sagittal split osteotomy, the largest error was reported for the lower lip and chin regions. In the studies evaluating simulation after bimaxillary osteotomy with or without genioplasty, the highest inaccuracy was reported at the level of the lips, predominantly the lower lip, chin, and, sometimes, the paranasal regions. Due to the variability in the study designs and analysis methods, a direct comparison was not possible. Therefore, based on the results of this SR, guidelines to systematize the workflow for evaluating the accuracy of 3D soft tissue simulations in orthognathic surgery in future studies are proposed. [ABSTRACT FROM AUTHOR]

Nutrient databases are a critical component of nutrition science and the basis of exciting new research in precision nutrition (PN). To identify the most critical components needed for improvement of nutrient databases, food composition data were analyzed for quality, with completeness being the most important measure, and for FAIRness, how well the data conformed with the data science criteria of findable, accessible, interoperable, and reusable (FAIR). Databases were judged complete if they provided data for all 15 nutrition fact panel (NFP) nutrient measures and all 40 National Academies of Sciences, Engineering, and Medicine (NASEM) essential nutrient measures for each food listed. Using the gold standard the USDA standard reference (SR) Legacy database as surrogate, it was found that SR Legacy data were not complete for either NFP or NASEM nutrient measures. In addition, phytonutrient measures in the 4 USDA Special Interest Databases were incomplete. To evaluate data FAIRness, a set of 175 food and nutrient data sources were collected from worldwide. Many opportunities were identified for improving data FAIRness, including creating persistent URLs, prioritizing usable data storage formats, providing Globally Unique Identifiers for all foods and nutrients, and implementing citation standards. This review demonstrates that despite important contributions from the USDA and others, food and nutrient databases in their current forms do not yet provide truly comprehensive food composition data. We propose that to enhance the quality and usage of food and nutrient composition data for research scientists and those fashioning various PN tools, the field of nutrition science must step out of its historical comfort zone and improve the foundational nutrient databases used in research by incorporating data science principles, the most central being data quality and data FAIRness.

Abstract: The Brazilian Unified National Health System (SUS) has incorporated newborn screening for cystic fibrosis since 2001. The protocol involves two samples of immunoreactive trypsinogen (IRT1/IRT2). This study aims to analyze fixed and floating values at the first and second IRT (IRT1/IRT2) cutoff points and assess the accuracy of the IRT/IRT methodology in a population from Northeastern Brazil. Descriptive, individual-level data from the newborn screening reference service data system (2013-2017) were used in this observational population study. The sensitivity, specificity, and positive predictive values (PPV) for the protocol were calculated. The best cutoff point was determined using the Youden’s index. The previous year’s cut-off values for the IRT1 and IRT2 99.4-, 99.5-, 99.6-, and 99.7-percentiles were utilized for the floating cutoff. During the studied period, 840,832 newborns underwent screening for cystic fibrosis, obtaining 49 cystic fibrosis diagnoses: 39 by newborn screening (79.6%) and 10 (20.4%) by clinical suspicion (false negative). The sensitivity, specificity, and PPV of the protocol totaled 79.6%, 99.9%, and 6.1%, respectively. No proposed cutoff for IRT1 performed better than the current one. IRT2 performed similarly to the current protocol at a cutoff point of 90ng/mL, showing the appropriate sensitivity and specificity while reducing the frequency of false positives. The protocol to screen newborns for cystic fibrosis had low sensitivity, a predictive positive value, and a high number of false positives and negatives. A floating cut point for IRT1 or IRT2 seems to constitute no viable option. However, changing the IRT2 cut point from 70ng/mL to 90ng/mL seems to have advantages and should undergo consideration.

Antimicrobial resistance is a major threat to human health. Since the 2000s, computational tools for predicting infectious diseases have been greatly advanced; however, efforts to develop real-time forecasting models for antimicrobial-resistant organisms (AMROs) have been absent. In this perspective, we discuss the utility of AMRO forecasting at different scales, highlight the challenges in this field, and suggest future research priorities. We also discuss challenges in scientific understanding, access to high-quality data, model calibration, and implementation and evaluation of forecasting models. We further highlight the need to initiate research on AMRO forecasting using currently available data and resources to galvanize the research community and address initial practical questions.

Our subjective sense of time is intertwined with a plethora of perceptual, cognitive and motor functions, and likewise, the brain is equipped to expertly filter, weight and combine these signals for seamless interactions with a dynamic world. Until relatively recently, the literature on time perception has excluded the influence of simultaneous motor activity, yet it has been found that motor circuits in the brain are at the core of most timing functions. Several studies have now identified that concurrent movements exert robust effects on perceptual timing estimates, but critically have not assessed how humans consciously judge the duration of their own movements. This creates a gap in our understanding of the mechanisms driving movement-related effects on sensory timing. We sought to address this gap by administering a sensorimotor timing task in which we explicitly compared the timing of isolated auditory tones and arm movements, or both simultaneously. We contextualized our findings within a Bayesian cue combination framework, in which separate sources of temporal information are weighted by their reliability and integrated into a unitary time estimate that is more precise than either unisensory estimate. Our results revealed differences in accuracy between auditory, movement and combined trials, and (crucially) that combined trials were the most accurately timed. Under the Bayesian framework, we found that participants' combined estimates were more precise than isolated estimates, yet were sub-optimal when compared with the model's prediction, on average. These findings elucidate previously unknown qualities of conscious motor timing and propose computational mechanisms that can describe how movements combine with perceptual signals to create unified, multimodal experiences of time.

Background: Surveillance of healthcare-associated infections (HAIs) is an essential component of hospital infection prevention and control systems. We aimed to assess the quality of the data compiled by the Brazilian HAI Surveillance System from pediatric (PICUs) and neonatal intensive care units (NICUs), between 2012 and 2021. Methods: Data Quality Review, including adherence, completeness, internal consistency, consistency over time, and consistency of population trend, were computed at both national and state levels based on quality metrics from World Health Organization Toolkit. Incidence rates (or incidence density) of ventilator-associated pneumonia (VAP) and central line-associated bloodstream infection (CLABSI) were obtained from the Brazilian National Nosocomial Infections Surveillance (NNIS) system. Data on sepsis-related mortality, spanning the period from 2012 to 2021, were extracted from the Brazilian National Health Service database (DATASUS). Additionally, correlations between sepsis-related mortality and incidence rates of VAP or CLABSI were calculated. Results: Throughout the majority of the study period, adherence to VAP reporting remained below 75%, exhibiting a positive trend post-2016. Widespread outliers, as well as inconsistencies over time and in population trends, were evident across all 27 states. Only four states maintained consistent adherence levels above 75% for more than 8 years regarding HAI incidence rates. Notably, CLABSI in NICUs boasted the highest reporting adherence among all HAIs, with 148 periods out of 270 (54.8%) exhibiting reporting adherence surpassing 75%. Three states achieved commendable metrics for CLABSI in PICUs, while five states demonstrated favorable results for CLABSI in NICUs. Conclusions: While adherence to HAI report is improving among Brazilian states, an important room for improvement in the Brazilian NNIS exists. Additional efforts should be made by the Brazilian government to improve the reliability of HAI data, which could serve as valuable guidance for hospital infection prevention and control policies.

Within the realm of printing machine distribution, information technology assumes a critical role in streamlining business operations. This study addresses persistent challenges related to inaccurate inventory data and insufficient knowledge management in IT applications. Utilizing the COBIT 2019 framework to assess IT governance capability, qualitative data was collected through interviews to uncover prevailing issues. The findings underscore specific process objectives—APO11 (Managed Quality), BAI08 (Managed Knowledge), and DSS06 (Managed Business Process Controls)—highlighting the need for improved capability levels. For example, APO11 currently resides at level 3 while aiming for level 4, indicating a one-level discrepancy. Similarly, BAI08 and DSS06 are at level 2, signaling a collective two-level gap. Proposed enhancements center on bolstering IT knowledge management and procedural training to meet quality standards in future IT applications. These measures aim to strengthen organizations, aligning IT practices with business processes to ensure heightened quality and efficiency. Notably, this abstract intentionally omits explicit mention of the evaluated IT process, adhering to the specified guideline.

Electronic health records (EHRs) have been increasingly adopted in clinical practices across the United States, providing a primary source of data for clinical research, particularly observational cohort studies. EHRs are a high-yield, low-maintenance source of longitudinal real-world data for large patient populations and provide a wealth of information and clinical contexts that are useful for clinical research and translation into practice. Despite these strengths, it is important to recognize the multiple limitations and challenges related to the use of EHR data in clinical research. Missing data are a major source of error and biases and can affect the representativeness of the cohort of interest, as well as the accuracy of the outcomes and exposures. Here, we aim to provide a critical understanding of the types of data available in EHRs and describe the impact of data heterogeneity, quality, and generalizability, which should be evaluated prior to and during the analysis of EHR data. We also identify challenges pertaining to data quality, including errors and biases, and examine potential sources of such biases and errors. Finally, we discuss approaches to mitigate and remediate these limitations. A proactive approach to addressing these issues can help ensure the integrity and quality of EHR data and the appropriateness of their use in clinical studies.

Abstract Background Population-based cancer quality registries are of great importance for the improvement of cancer care. However, little is known about the quality of recurrence data in cancer quality registries. The aim of this study was to evaluate data quality in the regional Breast Cancer Quality Registry of Central Sweden, with emphasis on the validity of recorded information on recurrence. Methods Validation by re-abstraction was performed on a random sample of 800 women with primary invasive breast cancer stage I-III diagnosed between 1993 and 2010, of which 400 had at least one registered recurrence and 400 had no registered recurrence. Registry data were compared with data from medical records. Exact agreement, correlation and kappa values, sensitivity and specificity were calculated. Results Seven hundred forty-seven women (93%) were available for analysis. Exact agreement was high for diagnostics, tumor characteristics, surgery, and adjuvant oncological treatment (90% or more for most variables). The registry’s sensitivity was low for regional recurrence (47%), but higher for local and distant recurrence (80% and 75%), whereas specificity was overall high (≥ 95%). Combining all recurrence categories irrespective of localization improved sensitivity to 90% with a specificity of 91%. In 87% of women, the date of first recurrence according to medical records fell within ± 90 days of the date recorded in the registry. Conclusions While the quality of data in the regional Breast Cancer Quality Registry was generally high, data accuracy on recurrences was lower. The overall precision of identifying any recurrence, irrespective of localization, was high. However, the accuracy of classification of recurrences (local, regional or distant) was lower, with evidence of underreporting for each of the recurrence categories. Given the importance of recurrence-related outcomes in the assessment of quality of care, efforts should be made to improve the reporting of recurrences.

Abstract Background The quality of the statistics on causes of death (CoD) does not present consolidated indicators in literature further than the coding group of ill-defined conditions of the International Classification of Diseases. Our objective was to assess the territorial quality of CoD by reliability of the official mortality statistics in Spain over the years 1980–2019. Methods A descriptive epidemiological design of four decades (1980-, 1990-, 2000-, and 2010–2019) by region (18) and sex was implemented. The CoD cases, age-adjusted rates and ratios (to all-cause) were assigned by reliability to unspecific and ill-defined quality categories. The regional mortality rates were contrasted to the Spanish median by decade and sex by the Comparative Mortality Ratio (CMR) in a Bayesian perspective. Statistical significance was considered when the CMR did not contain the value 1 in the 95% credible intervals. Results Unspecific, ill-defined, and all-cause rates by region and sex decreased over 1980–2019, although they scored higher in men than in women. The ratio of ill-defined CoD decreased in both sexes over these decades, but was still prominent in 4 regions. CMR of ill-defined CoD in both sexes exceeded the Spanish median in 3 regions in all decades. In the last decade, women’s CMR significantly exceeded in 5 regions for ill-defined and in 6 regions for unspecific CoD, while men’s CMR exceeded in 4 and 2 of the 18 regions, respectively on quality categories. Conclusions The quality of mortality statistics of causes of death has increased over the 40 years in Spain in both sexes. Quality gaps still remain mostly in Southern regions. Authorities involved might consider to take action and upgrading regional and national death statistics, and developing a systematic medical post-grade training on death certification.

Upon completion of an experiment, if a trend is observed that is "not quite significant," it can be tempting to collect more data in an effort to achieve statistical significance. Such sample augmentation or "N-hacking" is condemned because it can lead to an excess of false positives, which can reduce the reproducibility of results. However, the scenarios used to prove this rule tend to be unrealistic, assuming the addition of unlimited extra samples to achieve statistical significance, or doing so when results are not even close to significant; an unlikely situation for most experiments involving patient samples, cultured cells, or live animals. If we were to examine some more realistic scenarios, could there be any situations where N-hacking might be an acceptable practice? This Essay aims to address this question, using simulations to demonstrate how N-hacking causes false positives and to investigate whether this increase is still relevant when using parameters based on real-life experimental settings.

Purpose: Lumbar spinal stenosis (LSS) is a prevalent disorder, and surgery for LSS is a common procedure. Postoperative complications occur after any surgery and impose costs for society and costs and additional morbidity for patients. Since complications are relatively rare, medical registries of large populations may provide valuable knowledge. However, recording of complications in registries can be incomplete. To better estimate the true prevalence of complications after LSS surgery, we reviewed two different sources of data and recorded complications for a sample of Norwegian LSS patients. Methods: 474 patients treated surgically for LSS during 2015 and 2016 at four hospitals reported to a national spine registry (NORspine). Postoperative complications were recorded by patients in NORspine, and we cross-referenced complications documented in NORspine with the patients´ electronic patient records (EPR) to re-test the complication rates. We performed descriptive statistics of complication rates using the two different data sources above, and analyzed the association between postoperative complications and clinical outcome with logistic regression. Results: The mean (95%CI) patient age was 66.3 (65.3–67.2) years, and 254 (53.6%) were females. All patients were treated with decompression, and 51 (10.7%) received an additional fusion during the index surgery. Combining the two data sources, we found a total rate for postoperative complications of 22.4%, the NORspine registry reported a complication rate of 15.6%, and the EPR review resulted in a complication rate of 16.0%. However, the types of complications were inconsistent across the two data sources. According to NORspine, the frequency of reoperation within 90 days was 0.9% and according to EPR 3.4%. The rates of wound infection were for NORspine 3.1% and EPR review 2.1%. There was no association between postoperative complication and patient reported outcome. Conclusion: Postoperative complications occurred in 22% of LSS patients. The frequency of different postoperative complications differed between the two data sources. [ABSTRACT FROM AUTHOR]

Background: To evaluate the effects of probe positioning on radioactive iodine uptake (RAIU) measurements and 131I quantification in Graves disease (GD) patients. Materials and Methods: We performed a cross-sectional study in GD patients between May 9 and June 27, 2013. 24 hr-RAIU was measured. Measurement A was the reference measurement and was obtained with the probe parallel to the bottom of the thyroid cartilage. Measurements B, C, D, and E were obtained by moving the probe 2.5 cm to the left, 5 cm to the left, 2.5 cm vertically upward, and 5 cm vertically upward, respectively. The 131I doses were calculated. Non-reference measurements were compared with measurement A using the paired t-test or Wilcoxon signed-rank test. Results: A total of 63 GD patients (17 men, 40.3±13.6 years old) were enrolled. Among them, 57 patients had 24 hr-RAIU measurement and 37 patients chose the 131I treatment. Significant changes were observed in 24 hr-RAIU and 131I dose between measurement A (24 hr-RAIU 60.40±12.67% and median 131I dose 8.17 mCi) and measurement E (24 hr-RAIU 48.67±11.74% and median 131I dose 9.50 mCi) (P<0.05). In one patient, the 24 hr-RAIU was 20.3% lower in measurement E compared with that in measurement A, resulting in a 30 mCi increase in the calculated 131I dose. Conclusions: The vertically upward movement by a distance of a radius of the collimator could affect the 24 hr-RAIU measurement and thus cause inaccurate calculation of the 131I dose. [ABSTRACT FROM AUTHOR]

Surveillance of healthcare-associated infections (HAIs) is an essential component of hospital infection prevention and control systems. We aimed to assess the quality of the data compiled by the Brazilian HAI Surveillance System from pediatric (PICUs) and neonatal intensive care units (NICUs), between 2012 and 2021. Data Quality Review, including adherence, completeness, internal consistency, consistency over time, and consistency of population trend, were computed at both national and state levels based on quality metrics from World Health Organization Toolkit. Incidence rates (or incidence density) of ventilator-associated pneumonia (VAP) and central line-associated bloodstream infection (CLABSI) were obtained from the Brazilian National Nosocomial Infections Surveillance (NNIS) system. Data on sepsis-related mortality, spanning the period from 2012 to 2021, were extracted from the Brazilian National Health Service database (DATASUS). Additionally, correlations between sepsis-related mortality and incidence rates of VAP or CLABSI were calculated. Throughout the majority of the study period, adherence to VAP reporting remained below 75%, exhibiting a positive trend post-2016. Widespread outliers, as well as inconsistencies over time and in population trends, were evident across all 27 states. Only four states maintained consistent adherence levels above 75% for more than 8 years regarding HAI incidence rates. Notably, CLABSI in NICUs boasted the highest reporting adherence among all HAIs, with 148 periods out of 270 (54.8%) exhibiting reporting adherence surpassing 75%. Three states achieved commendable metrics for CLABSI in PICUs, while five states demonstrated favorable results for CLABSI in NICUs. While adherence to HAI report is improving among Brazilian states, an important room for improvement in the Brazilian NNIS exists. Additional efforts should be made by the Brazilian government to improve the reliability of HAI data, which could serve as valuable guidance for hospital infection prevention and control policies. [ABSTRACT FROM AUTHOR]

Secure authentication and accurate localization among Internet of Things (IoT) sensors are pivotal for the functionality and integrity of IoT networks. IoT authentication and localization are intricate and symbiotic, impacting both the security and operational functionality of IoT systems. Hence, accurate localization and lightweight authentication on resource-constrained IoT devices pose several challenges. To overcome these challenges, recent approaches have used encryption techniques with well-known key infrastructures. However, these methods are inefficient due to the increasing number of data breaches in their localization approaches. This proposed research efficiently integrates authentication and localization processes in such a way that they complement each other without compromising on security or accuracy. The proposed framework aims to detect active attacks within IoT networks, precisely localize malicious IoT devices participating in these attacks, and establish dynamic implicit authentication mechanisms. This integrated framework proposes a Correlation Composition Awareness (CCA) model, which explores innovative approaches to device correlations, enhancing the accuracy of attack detection and localization. Additionally, this framework introduces the Pair Collaborative Localization (PCL) technique, facilitating precise identification of the exact locations of malicious IoT devices. To address device authentication, a Behavior and Performance Measurement (BPM) scheme is developed, ensuring that only trusted devices gain access to the network. This work has been evaluated across various environments and compared against existing models. The results prove that the proposed methodology attains 96% attack detection accuracy, 84% localization accuracy, and 98% device authentication accuracy. [ABSTRACT FROM AUTHOR]

Background: Medical professionals can use mass-casualty triage systems to assist them in prioritizing patients from mass-casualty incidents (MCIs). Correct triaging of victims will increase their chances of survival. Determining the triage system that has the best performance has proven to be a difficult question to answer. The Advanced Prehospital Triage Model (Modelo Extrahospitalario de Triaje Avanzado; META) and Sort, Assess, Lifesaving Interventions, Treatment/Transport (SALT) algorithms are the most recent triage techniques to be published. The present study aimed to evaluate the META and SALT algorithms' performance and statistical agreement with various standards. The secondary objective was to determine whether these two MCI triage systems predicted patient outcomes, such as mortality, length-of-stay, and intensive care unit (ICU) admission. Methods: This retrospective study used patient data from the trauma registry of an American College of Surgeons Level 1 trauma center, from January 1, 2018 through December 31, 2020. The sensitivity, specificity, and statistical agreement of the META and SALT triage systems to various standards (Revised Trauma Score [RTS]/Sort Triage, Injury Severity Score [ISS], and Lerner criteria) when applied using trauma patients. Statistical analysis was used to assess the relationship between each triage category and the secondary outcomes. Results: A total of 3,097 cases were included in the study. Using Sort triage as the standard, SALT and META showed much higher sensitivity and specificity in the Immediate category than for Delayed (Immediate sensitivity META 91.5%, SALT 94.9%; specificity 60.8%, 72.7% versus Delayed sensitivity 28.9%, 1.3%; specificity 42.4%, 28.9%). With the Lerner criteria, in the Immediate category, META had higher sensitivity (77.1%, SALT 68.6%) but lower specificity (61.1%) than SALT (71.8%). For the Delayed category, SALT showed higher sensitivity (META 61.4%, SALT 72.2%), but lower specificity (META 75.1%, SALT 67.2%). Both systems showed a positive, though modest, correlation with ISS. For SALT and META, triaged Immediate patients tended to have higher mortality and longer ICU and hospital lengths-of-stay. Conclusion: Both META and SALT triage appear to be more accurate with Immediate category patients, as opposed to Delayed category patients. With both systems, patients triaged as Immediate have higher mortality and longer lengths-of-stay when compared to Delayed patients. Further research can help refine MCI triage systems and improve accuracy. [ABSTRACT FROM AUTHOR]

Background: Population-based cancer quality registries are of great importance for the improvement of cancer care. However, little is known about the quality of recurrence data in cancer quality registries. The aim of this study was to evaluate data quality in the regional Breast Cancer Quality Registry of Central Sweden, with emphasis on the validity of recorded information on recurrence. Methods: Validation by re-abstraction was performed on a random sample of 800 women with primary invasive breast cancer stage I-III diagnosed between 1993 and 2010, of which 400 had at least one registered recurrence and 400 had no registered recurrence. Registry data were compared with data from medical records. Exact agreement, correlation and kappa values, sensitivity and specificity were calculated. Results: Seven hundred forty-seven women (93%) were available for analysis. Exact agreement was high for diagnostics, tumor characteristics, surgery, and adjuvant oncological treatment (90% or more for most variables). The registry’s sensitivity was low for regional recurrence (47%), but higher for local and distant recurrence (80% and 75%), whereas specificity was overall high (≥ 95%). Combining all recurrence categories irrespective of localization improved sensitivity to 90% with a specificity of 91%. In 87% of women, the date of first recurrence according to medical records fell within ± 90 days of the date recorded in the registry. Conclusions: While the quality of data in the regional Breast Cancer Quality Registry was generally high, data accuracy on recurrences was lower. The overall precision of identifying any recurrence, irrespective of localization, was high. However, the accuracy of classification of recurrences (local, regional or distant) was lower, with evidence of underreporting for each of the recurrence categories. Given the importance of recurrence-related outcomes in the assessment of quality of care, efforts should be made to improve the reporting of recurrences. [ABSTRACT FROM AUTHOR]

Introduction: Despite being the most used exam today, few studies have evaluated the accuracy of findings on non-contrast magnetic resonance imaging (MRI). The primary objective of the study was to evaluate the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of non-contrast MRI findings in frozen shoulder, isolated and in combination. The secondary objectives were to define the interobserver and intraobserver agreement of the assessments and the odds ratio for frozen shoulder because of the various findings of MRI. Methods: A retrospective diagnostic accuracy study comparing non-contrast MRI findings between the frozen shoulder group and the control group. Sensitivity, specificity, positive and negative predictive value, accuracy, odds ratio, interobserver and intraobserver agreement were calculated for each finding and their possible associations. Results: The hyperintensity on capsule in the axillary recess presented 84% sensitivity, 94% specificity, and 89% accuracy. The obliteration of the subcoracoid fat triangle in the rotator interval had sensitivity 34%, specificity 82% and accuracy 58%. For coracohumeral ligament thickness ≥ 2 mm had specificity 66%, 48% specificity and 57% accuracy. Capsule thickness in the axillary recess ≥ 4 mm resulted in 54% sensitivity, 82% specificity, and 68% accuracy. Regarding interobserver agreement, only the posteroinferior and posterosuperior quadrants showed moderate results, and all the others showed strong reliability. The odds ratio for hyperintensity in the axillary recess was 82.3 for frozen shoulder. The association of these findings increased specificity (95%). Conclusion: The accuracy of non-contrast magnetic resonance imaging is high for diagnosing frozen shoulder, especially when evaluating the hyperintensity of the axillary recess. The exam has high reliability and reproducibility. The presence of an association of signs increases the specificity of the test. Level of evidence: Level III, study of diagnostic test. [ABSTRACT FROM AUTHOR]

Non-Echo-Planar Diffusion Weighed Magnetic Resonance Imaging (non-EPI DW MRI) plays a role in the planning of cholesteatoma surgery. To outline the usage of Non-EPI DW MRI in cholesteatoma diagnostics and to determine its accuracy, using otosurgery diagnostics as reference standard. A retrospective descriptive study. All subjects operated, with suspicion of cholesteatoma as indication, that had a preceding examination with non-EPI DW MRI, between October 2010 and March 2019. Calculating sensitivity, specificity, predicative values, and likelihood ratios, using non-EPI DW MRI as index test and diagnosis from otosurgery as reference standard. Fifty-two subject episodes were included. Non-EPI DW MRI had a sensitivity of 0.50, specificity of 0.75, positive and negative predictive values of 0.74 and 0.52 and, positive and negative likelihood ratios of 2.0 and 0.67 respectively. There is a clear annual trend with increased numbers of executed examinations during the study period. The diagnostic accuracy of non-EPI DW MRI does not reach acceptable levels in the existing everyday routine practice conditions. The accuracy of the examination increases when interpreted by an experienced radiologist and when using the definition of cholesteatoma recommended by EAONO/JOS. [ABSTRACT FROM AUTHOR]

Electronic health records (EHRs) have been increasingly adopted in clinical practices across the United States, providing a primary source of data for clinical research, particularly observational cohort studies. EHRs are a high-yield, low-maintenance source of longitudinal real-world data for large patient populations and provide a wealth of information and clinical contexts that are useful for clinical research and translation into practice. Despite these strengths, it is important to recognize the multiple limitations and challenges related to the use of EHR data in clinical research. Missing data are a major source of error and biases and can affect the representativeness of the cohort of interest, as well as the accuracy of the outcomes and exposures. Here, we aim to provide a critical understanding of the types of data available in EHRs and describe the impact of data heterogeneity, quality, and generalizability, which should be evaluated prior to and during the analysis of EHR data. We also identify challenges pertaining to data quality, including errors and biases, and examine potential sources of such biases and errors. Finally, we discuss approaches to mitigate and remediate these limitations. A proactive approach to addressing these issues can help ensure the integrity and quality of EHR data and the appropriateness of their use in clinical studies. [ABSTRACT FROM AUTHOR]

Background During the pandemic, countries utilized various forms of statistical estimations of coronavirus disease-2019 (COVID-19) impact. Differences between databases make direct comparisons and interpretations of data in different countries a challenge. We evaluated country-specific approaches to COVID-19 data and recommended changes that would improve future international collaborations. Methods We compared the COVID-19 reports presented on official UK (National Health System), Israeli (Department of Health), Latvian (Center for Disease Prevention and Control) and USA (Centers for Disease Control and Prevention) health authorities' websites. Results Our analysis demonstrated critical differences in the ways COVID-19 statistics were made available to the general and scientific communities. Specifically, the differences in approaches were found in the presentation of the number of infected cases and tests, and percentage of positive cases, the number of severe cases, the number of vaccinated, and the number and percent of deaths. Conclusion Findability, Accessibility, Interoperability and Reusability principles could guide the development of essential global standards that provide a basis for communication within and outside of the scientific community. [ABSTRACT FROM AUTHOR]

Background: The quality of the statistics on causes of death (CoD) does not present consolidated indicators in literature further than the coding group of ill-defined conditions of the International Classification of Diseases. Our objective was to assess the territorial quality of CoD by reliability of the official mortality statistics in Spain over the years 1980–2019. Methods: A descriptive epidemiological design of four decades (1980-, 1990-, 2000-, and 2010–2019) by region (18) and sex was implemented. The CoD cases, age-adjusted rates and ratios (to all-cause) were assigned by reliability to unspecific and ill-defined quality categories. The regional mortality rates were contrasted to the Spanish median by decade and sex by the Comparative Mortality Ratio (CMR) in a Bayesian perspective. Statistical significance was considered when the CMR did not contain the value 1 in the 95% credible intervals. Results: Unspecific, ill-defined, and all-cause rates by region and sex decreased over 1980–2019, although they scored higher in men than in women. The ratio of ill-defined CoD decreased in both sexes over these decades, but was still prominent in 4 regions. CMR of ill-defined CoD in both sexes exceeded the Spanish median in 3 regions in all decades. In the last decade, women's CMR significantly exceeded in 5 regions for ill-defined and in 6 regions for unspecific CoD, while men's CMR exceeded in 4 and 2 of the 18 regions, respectively on quality categories. Conclusions: The quality of mortality statistics of causes of death has increased over the 40 years in Spain in both sexes. Quality gaps still remain mostly in Southern regions. Authorities involved might consider to take action and upgrading regional and national death statistics, and developing a systematic medical post-grade training on death certification. [ABSTRACT FROM AUTHOR]