Nationwide Electronic Prescription Services in Finland in 2010-2023.

This research aimed to follow up a 14-year period (2010-2023) public and private healthcare service organizations' and community pharmacies' entries to and exits from the centralized, interoperable and shared electronic Prescription Services in Finland. Our material were the official Social Welfare and Healthcare Organization Registry and the official Pharmacy Registry; their data were extracted in January 2024. Outcomes were continuous registration of services or registered exist from the services. In addition, we used information from the Kanta Services for presenting monthly and annual number of electronic prescriptions and medicine dispensations on national level. In 2010-2023, totally 838 community pharmacies' and their subsidiary pharmacies' entries to and 24 exits from the nationwide Prescription Services took place, and in total 814 pharmacy outlets had the Prescription Services in production in 2023. Totally, 1980 public and private healthcare service organizations' entries to and 494 exits from the Prescription Service took place, and 1486 organizations had the Prescription Services in production in 2023. Healthcare service organizations recorded totally 303.8 million electronic prescriptions into the Prescription Services. Recorded numbers were lower during the Covid-19 epidemic in Finland in 2020-2021. We also observed seasonal effects in the time series. Pharmacies recorded totally 660.4 million medicine dispensations (purchases) into the Prescription Services with an increasing trend year after year. We also observed seasonal effects in the dispensation time series.

Facilitators and barriers to monitoring and evaluation at syringe service programs.

BACKGROUND: Syringe services programs (SSPs) provide harm reduction supplies and services to people who use drugs and are often required by funders or partners to collect data from program participants. SSPs can use these data during monitoring and evaluation (M&E) to inform programmatic decision making, however little is known about facilitators and barriers to collecting and using data at SSPs. METHODS: Using the Consolidated Framework for Implementation Research (CFIR), we conducted 12 key informant interviews with SSP staff to describe the overall landscape of data systems at SSPs, understand facilitators and barriers to data collection and use at SSPs, and generate recommendations for best practices for data collection at SSPs. We used 30 CFIR constructs to develop individual interview guides, guide data analysis, and interpret study findings. RESULTS: Four main themes emerged from our analysis: SSP M&E systems are primarily designed to be responsive to perceived SSP client needs and preferences; SSP staffing capacity influences the likelihood of modifying M&E systems; external funding frequently forces changes to M&E systems; and strong M&E systems are often a necessary precursor for accessing funding. CONCLUSIONS: Our findings highlight that SSPs are not resistant to data collection and M&E, but face substantial barriers to implementation, including lack of funding and disjointed data reporting requirements. There is a need to expand M&E-focused funding opportunities, harmonize quantitative indicators collected across funders, and minimize data collection to essential data points for SSPs.

Evaluating Large Language Models for Automated Reporting and Data Systems Categorization: Cross-Sectional Study.

BACKGROUND: Large language models show promise for improving radiology workflows, but their performance on structured radiological tasks such as Reporting and Data Systems (RADS) categorization remains unexplored. OBJECTIVE: This study aims to evaluate 3 large language model chatbots-Claude-2, GPT-3.5, and GPT-4-on assigning RADS categories to radiology reports and assess the impact of different prompting strategies. METHODS: This cross-sectional study compared 3 chatbots using 30 radiology reports (10 per RADS criteria), using a 3-level prompting strategy: zero-shot, few-shot, and guideline PDF-informed prompts. The cases were grounded in Liver Imaging Reporting & Data System (LI-RADS) version 2018, Lung CT (computed tomography) Screening Reporting & Data System (Lung-RADS) version 2022, and Ovarian-Adnexal Reporting & Data System (O-RADS) magnetic resonance imaging, meticulously prepared by board-certified radiologists. Each report underwent 6 assessments. Two blinded reviewers assessed the chatbots' response at patient-level RADS categorization and overall ratings. The agreement across repetitions was assessed using Fleiss κ. RESULTS: Claude-2 achieved the highest accuracy in overall ratings with few-shot prompts and guideline PDFs (prompt-2), attaining 57% (17/30) average accuracy over 6 runs and 50% (15/30) accuracy with k-pass voting. Without prompt engineering, all chatbots performed poorly. The introduction of a structured exemplar prompt (prompt-1) increased the accuracy of overall ratings for all chatbots. Providing prompt-2 further improved Claude-2's performance, an enhancement not replicated by GPT-4. The interrun agreement was substantial for Claude-2 (k=0.66 for overall rating and k=0.69 for RADS categorization), fair for GPT-4 (k=0.39 for both), and fair for GPT-3.5 (k=0.21 for overall rating and k=0.39 for RADS categorization). All chatbots showed significantly higher accuracy with LI-RADS version 2018 than with Lung-RADS version 2022 and O-RADS (P<.05); with prompt-2, Claude-2 achieved the highest overall rating accuracy of 75% (45/60) in LI-RADS version 2018. CONCLUSIONS: When equipped with structured prompts and guideline PDFs, Claude-2 demonstrated potential in assigning RADS categories to radiology cases according to established criteria such as LI-RADS version 2018. However, the current generation of chatbots lags in accurately categorizing cases based on more recent RADS criteria.

Relationship of the Novel Scoring System for Lower Extremity Venous Thrombosis with Pulmonary Embolism.

RATIONALE AND OBJECTIVE: To develop a new scoring system, the "Lower extremity venous Doppler ultrasound scoring system" (LEVDUS), to predict the diagnosis of pulmonary embolism (PE) localization in patients with deep vein thrombosis (DVT). METHODS: This single-center retrospective study included 182 patients aged ≥ 18 years. We used scoring according to thrombosis localization and stage in Doppler US. Patients with PE were divided into three categories based on the pulmonary artery (PA) location on CT pulmonary angiography. LEVDUS values were compared according to the PE classification. The threshold value was determined for the diagnosis of PE in the receiver operating characteristics analysis. Factors affecting the diagnosis of PE were evaluated by logistic regression analysis. RESULTS: A total of 182 patients were included (female patients: 55.5% [101/182]). The median age of the patients was 68 (IQR, 56-77). The rates of DVT and PE were 35.2% (64/182) and 52.7% (96/182), respectively. Although the median LEVDUS and d-dimer values in the subsegmental PE group were higher, LEVDUS was statistically significant but d-dimer was not (p = 0.005 and p = 0.022, respectively). In addition, both LEVDUS and d-dimer median values in the other PE groups were statistically significantly higher than the non-PE group (p < 0.001). The cut-off value for the diagnosis of PE was LEVDUS≥ 2.5. LEVDUS was 1.2-fold higher for the presence of PE. CONCLUSION: LEVDUS provides useful information in predicting the presence of PE in patients and provides a common diagnostic language between radiologists and emergency or clinic physicians.

The Pandemic Response Commons.

Objectives: A data commons is a software platform for managing, curating, analyzing, and sharing data with a community. The Pandemic Response Commons (PRC) is a data commons designed to provide a data platform for researchers studying an epidemic or pandemic. Methods: The PRC was developed using the open source Gen3 data platform and is based upon consortium, data, and platform agreements developed by the not-for-profit Open Commons Consortium. A formal consortium of Chicagoland area organizations was formed to develop and operate the PRC. Results: The consortium developed a general PRC and an instance of it for the Chicagoland region called the Chicagoland COVID-19 Commons. A Gen3 data platform was set up and operated with policies, procedures, and controls for a NIST SP 800-53 revision 4 Moderate system. A consensus data model for the commons was developed, and a variety of datasets were curated, harmonized and ingested, including statistical summary data about COVID cases, patient level clinical data, and SARS-CoV-2 viral variant data. Discussion and conclusions: Given the various legal and data agreements required to operate a data commons, a PRC is designed to be in place and operating at a low level prior to the occurrence of an epidemic, with the activities increasing as required during an epidemic. A regional instance of a PRC can also be part of a broader data ecosystem or data mesh consisting of multiple regional commons supporting pandemic response through sharing regional data.

Rapid assessment of data systems for COVID-19 vaccination in the WHO African Region.

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.

Sawtooth-characteristic-based free matrix integral inequality and its application to sampled-data systems.

The focus of this article is to present a sawtooth-characteristic-based free-matrix integral inequality and to discuss its application to sampled-data systems (SDSs). Firstly, the free matrix, which is associated with the sawtooth characteristic of the input delay, is presented and incorporated into the integral inequality. In the development of inequality techniques, this is the first time that a free matrix has been associated with the sawtooth characteristic. On this basis, a corresponding sawtooth-characteristic-based free-matrix integral inequality is established, enabling estimation of the integral quadratic terms of the Lyapunov-Krasovskii functional (LKF) derivative. To overcome the challenges posed by second-order terms resulting from the proposed integral inequality, augmented system variables associated with the sawtooth characteristic are also introduced. Thus, the complicated calculation arising from second-order terms and the conservatism caused by the quadratic estimation of the LKF can be avoided. Finally, through the utilization of the sawtooth-characteristic-based free-matrix integral inequality, stability criteria with less conservatism are derived for the SDSs in the form of linear matrix inequalities. The superiority of the proposed approach is illustrated through two numerical examples and a simplified sampled-data based power market.

A Multifunctional, Low Cost and Sustainable Neonatal Database System.

Continuous improvement in the clinical performance of neonatal intensive care units (NICU) depends on the use of locally relevant, reliable data. However, neonatal databases with these characteristics are typically unavailable in NICUs using paper-based records, while in those using electronic records, the inaccuracy of data and the inability to customize commercial data systems limit their usability for quality improvement or research purposes. We describe the characteristics and uses of a simple, neonatologist-centered data system that has been successfully maintained for 30 years, with minimal resources and serving multiple purposes, including quality improvement, administrative, research support and educational functions. Structurally, our system comprises customized paper and electronic components, while key functional aspects include the attending-based recording of diagnoses, integration into clinical workflows, multilevel data accuracy and validation checks, and periodic reporting on both data quality and NICU performance results. We provide examples of data validation methods and trends observed over three decades, and discuss essential elements for the successful implementation of this system. This database is reliable and easily maintained; it can be developed from simple paper-based forms or used to supplement the functionality and end-user customizability of existing electronic medical records. This system should be readily adaptable to NICUs in either high- or limited-resource environments.

Thyroid Imaging Reporting and Data Systems: Applicability of the "Taller than Wide" Criterium in Primary/Secondary Care Units and the Role of Thyroid Scintigraphy.

BACKGROUND: To examine the applicability of the "taller than wide" (ttw) criterium for risk assessment of thyroid nodules (TNs) in primary/secondary care units and the role of thyroid scintigraphy therein. METHODS: German bicenter study performed in a setting of primary/secondary care. Patient recruitment and analysis in center A was conducted in a prospective manner. In center B, patient data were retrieved from a database that was originally generated by prospective data collection. TNs were assessed by ultrasound and thyroid scans, mostly fine needle biopsy and occasionally surgery and others. In center A, only patients who presented for the first time were included. The inclusion criterion was any TN ≥ 10 mm that had at least the following two sonographic risk features: solidity and a ttw shape. In center B, consecutive patients who had at least ttw and hypofunctioning nodules ≥ 10 mm were retrieved from the above-mentioned database. The risk of malignancy was determined according to a mixed reference standard and compared with literature data. RESULTS: In center A, 223 patients with 259 TNs were included into the study. For further analysis, 200 nodules with a reference standard were available. The overall malignancy rate was 2.5% (upper limit of the 95% CI: 5.1%). After the exclusion of scintigraphically hyperfunctioning nodules, the malignancy rate increased slightly to 2.8% (upper limit of the 95% CI: 5.7%). Malignant nodules exhibited sonographic risk features additional to solidity and ttw shape more often than benign ones. In addition to the exclusion of hyperfunctioning nodules, when considering only nodules without additional US risk features, i.e., exclusively solid and ttw-nodules, the malignancy rate decreased to 0.9% (upper limit 95% CI: 3.7%). In center B, from 58 patients, 58 ttw and hypofunctioning TNs on thyroid scans with a reference standard were available. Malignant nodules from center B were always solid and hypoechoic. The overall malignancy rate of hypofunctioning and ttw nodules was 21%, with the lower limit of the 95% CI (one-sided) being 12%. CONCLUSIONS: In primary/secondary care units, the lowest TIRADS categories for indicating FNB, e.g., applying one out of five sonographic risk features, may not be appropriate owing to the much lower a priori malignancy risk in TNs compared to tertiary/quaternary care units. Even the combination of two sonographic risk features, "solidity" and "ttw", may only be appropriate in a limited fashion. In contrast, the preselection of TNs according to hypofunctioning findings on thyroid scans clearly warranted FNB, even when applying only one sonographic risk criterion ("ttw"). For this reason, thyroid scans in TNs may not only be indicated to rule out hyperfunctioning nodules from FNB but also to rule in hypofunctioning ones.

Can we identify the prevalence of perinatal mental health using routinely collected health data?: A review of publicly available perinatal mental health data sources in England.

Introduction: Perinatal mental health (PMH) conditions affect around one in four women, and may be even higher in women from some ethnic minority groups and those living in low socioeconomic circumstances. Poor PMH causes significant distress and can have lifelong adverse impacts for some children. In England, current prevalence rates are estimated using mental health data of the general population and do not take sociodemographic variance of geographical areas into account. Services cannot plan their capacity and ensure appropriate and timely support using these estimates. Our aim was to see if PMH prevalence rates could be identified using existing publicly available sources of routine health data. Methods: A review of data sources was completed by searching NHS Digital (now NHS England), Public Health England and other national PMH resources, performing keyword searches online, and research team knowledge of the field. The sources were screened for routine data that could be used to produce prevalence of PMH conditions by sociodemographic variation. Included sources were reviewed for their utility in accessibility, data relevance and technical specification relating to PMH and sociodemographic data items. Results: We found a PMH data 'blind spot' with significant inadequacies in the utility of all identified data sources, making it impossible to provide information on the prevalence of PMH in England and understand variation by sociodemographic differences. Conclusions: To enhance the utility of publicly available routine data to provide PMH prevalence rates requires improved mandatory PMH data capture in universal services, available publicly via one platform and including assessment outcomes and sociodemographic data.

District health management and stillbirth recording and reporting: a qualitative study in the Ashanti Region of Ghana.

BACKGROUND: Despite global efforts to reduce maternal and neonatal mortality, stillbirths remain a significant public health challenge in many low- and middle-income countries. District health systems, largely seen as the backbone of health systems, are pivotal in addressing the data gaps reported for stillbirths. Available, accurate and complete data is essential for District Health Management Teams (DHMTs) to understand the burden of stillbirths, evaluate interventions and tailor health facility support to address the complex challenges that contribute to stillbirths. This study aims to understand stillbirth recording and reporting in the Ashanti Region of Ghana from the perspective of DHMTs. METHODS: The study was conducted in the Ashanti Region of Ghana. 15 members of the regional and district health directorates (RHD/DHD) participated in semi-structured interviews. Sampling was purposive, focusing on RHD/DHD members who interact with maternity services or stillbirth data. Thematic analyses were informed by an a priori framework, including theme 1) experiences, perceptions and attitudes; theme 2) stillbirth data use; and theme 3) leadership and support mechanisms, for stillbirth recording and reporting. RESULTS: Under theme 1, stillbirth definitions varied among respondents, with 20 and 28 weeks commonly used. Fresh and macerated skin appearance was used to classify timing with limited knowledge of antepartum and intrapartum stillbirths. For theme 2, data quality checks, audits, and the district health information management system (DHIMS-2) data entry and review are functions played by the DHD. Midwives were blamed for data quality issues on omissions and misclassifications. Manual entry of data, data transfer from the facility to the DHD, limited knowledge of stillbirth terminology and periodic closure of the DHIMS-2 were seen to proliferate gaps in stillbirth recording and reporting. Under theme 3, perinatal audits were acknowledged as an enabler for stillbirth recording and reporting by the DHD, though audits are mandated for only late-gestational stillbirths (> 28 weeks). Engagement of other sectors, e.g., civil/vital registration and private health facilities, was seen as key in understanding the true population-level burden of stillbirths. CONCLUSION: Effective district health management ensures that every stillbirth is accurately recorded, reported, and acted upon to drive improvements. A large need exists for capacity building on stillbirth definitions and data use. Recommendations are made, for example, terminology standardization and private sector engagement, aimed at reducing stillbirth rates in high-mortality settings such as Ghana.

The role of gadolinium-based contrast agents in magnetic resonance imaging structured reporting and data systems (RADS).

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.

C-TIRADS combined with contrast-enhanced ultrasound for evaluation of category 4 nodules in Hashimoto's thyroiditis / 中国现代医生

Objective Evaluation of Chinese-thyroid imaging reporting and data system(C-TIRADS)combined with contrast-enhanced ultrasound(CEUS)for the assessment of category 4 nodules in the setting of Hashimoto's thyroiditis.Methods Retrospective analysis of 120 C-TIRADS category 4 thyroid nodules from 79 patients with confirmed Hashimoto's thyroiditis who attended the Yiyang Central Hospital from June to December 2022.Thyroid nodules exhibiting one or more benign or malignant features that were suspicious on CEUS were treated as downgraded or upgraded one level.Using the final surgical pathology results as the gold standard,working characteristic(ROC)curves of subjects based on C-TIRADS grading before and after CEUS adjustment were plotted to compare diagnostic efficacy.Results The sensitivity,specificity,and accuracy of the CEUS-adjusted C-TIRADS were 93.0％,87.8％and 90.8％,respectively(P<0.05).The area under the ROC curve was 0.811 and 0.904,respectively(P<0.05).Conclusion C-TIRADS combined with CEUS has better diagnostic efficacy in evaluating category 4 nodules in Hashimoto's thyroiditis.

ICPUTRD: Image Cloud Platform for use in tagging and research on decomposition.

Human decomposition studies aim to understand the various factors influencing human decay to assess the deceased and develop postmortem interval (PMI) estimation methods. These types of studies are typically conducted through physical experiments examining the deceased; however, big data systems have the potential to transform how large-scale forensic anthropology research questions can be addressed with curated images of donors with known demographic, climatic, and postmortem historical data. This study introduces ICPUTRD (Image Cloud Platform for Use in Tagging and Research on Decomposition), a web-based software system, which enables forensic scientists to easily access, enhance (or curate), and analyze very large photographic collections documenting the longitudinal process of human decomposition. ICPUTRD, a JavaScript-based application, was designed and built through a combination of the Waterfall and Agile software development life-cycle methods and provides an image search and tagging features with a predefined nomenclature of forensic-related keywords. To evaluate the system, a user study was conducted, involving 27 participants who completed pre- and post-study surveys and three research tasks. Analysis of the study results confirmed the feasibility and practicality of ICPUTRD to facilitate aspects of forensic research and casework involving large collections of digital photographs of human decomposition. It was observed that the nomenclature lacked certain law enforcement keywords, so future work will focus on expanding it to ensure ICPUTRD is suited for all its intended users.

Reducing fall injuries with better data.

BACKGROUND: Fall deaths in the USA almost tripled in the twenty-first century. While various interventions have been effective in reducing fall deaths, they have failed to make a substantial impact at a population level. MAIN BODY: An overarching factor that has been relatively neglected in fall injury prevention is the need for more and better data. We need better data on the causes and circumstances of older adult fall deaths. While there are excellent national surveillance systems on the circumstances of other injury deaths (e.g., motor vehicle crashes, suicides, and homicides), such a system is lacking for fall deaths. These other data systems have been instrumental in indicating and evaluating policies that will reduce injury. It is also important to provide consumers with better information concerning the many products that affect the likelihood of fall injury (e.g., flooring, hip protectors, footwear). Automotive buyers are provided with relevant up-to-date make-model safety information from crash tests and real-world performance. Such information not only helps protect buyers from purchasing dangerous products, but it provides producers with the incentive to make ever safer products over time. CONCLUSION: We believe that creation of a national surveillance system on the circumstances of fall deaths, and increased testing/certifying of fall-related products, are two steps that would help create the conditions for continuous reductions in fall fatalities. Fall prevention should apply some of the same basic strategies that have proved effective in addressing other injuries.

The role of iodinated contrast media in computed tomography structured Reporting and Data Systems (RADS): a narrative review.

Background and Objective: In recent years, there has been a large-scale dissemination of guidelines in radiology in the form of Reporting & Data Systems (RADS). The use of iodinated contrast media (ICM) has a fundamental role in enhancing the diagnostic capabilities of computed tomography (CT) but poses certain risks. The scope of the present review is to summarize the current role of ICM only in clinical reporting guidelines for CT that have adopted the "RADS" approach, focusing on three specific questions per each RADS: (I) what is the scope of the scoring system; (II) how is ICM used in the scoring system; (III) what is the impact of ICM enhancement on the scoring. Methods: We analyzed the original articles for each of the latest versions of RADS that can be used in CT [PubMed articles between January, 2005 and March, 2023 in English and American College of Radiology (ACR) official website]. Key Content and Findings: We found 14 RADS suitable for use in CT out of 28 RADS described in the literature. Four RADS were validated by the ACR: Colonography-RADS (C-RADS), Liver Imaging-RADS (LI-RADS), Lung CT Screening-RADS (Lung-RADS), and Neck Imaging-RADS (NI-RADS). One RADS was validated by the ACR in collaboration with other cardiovascular scientific societies: Coronary Artery Disease-RADS 2.0 (CAD-RADS). Nine RADS were proposed by other scientific groups: Bone Tumor Imaging-RADS (BTI-RADS), Bone­RADS, Coronary Artery Calcium Data & Reporting System (CAC-DRS), Coronavirus Disease 2019 Imaging-RADS (COVID-RADS), COVID-19-RADS (CO-RADS), Interstitial Lung Fibrosis Imaging-RADS (ILF-RADS), Lung-RADS (LU-RADS), Node-RADS, and Viral Pneumonia Imaging-RADS (VP-RADS). Conclusions: This overview suggests that ICM is not strictly necessary for the study of bones and calcifications (CAC-DRS, BTI-RADS, Bone-RADS), lung parenchyma (Lung-RADS, LU-RADS, COVID-RADS, CO-RADS, VP-RADS and ILF-RADS), and in CT colonography (C-RADS). On the other hand, ICM plays a key role in CT angiography (CAD-RADS), in the study of liver parenchyma (LI-RADS), and in the evaluation of soft tissues and lymph nodes (NI-RADS, Node-RADS). Future studies are needed in order to evaluate the impact of the new iodinated and non-iodinate contrast media, artificial intelligence tools and dual energy CT in the assignment of RADS scores.

Making the case for lead safe housing: Downstream effects of lead exposure on outcomes for children and youth.

Lead based paint is a predominate source of lead exposure in children, which has a documented negative effect on their health and development. Despite public health efforts, the housing stock in disinvested neighborhoods in many cities continues to present significant risk of childhood lead exposure. In this article, we describe how a multi-agency integrated data system was used to document the impact of lead exposure on indicators of child and youth development as recorded in educational and human service systems. By tracking administrative data for two cohorts of Cleveland, Ohio children from birth to early adulthood and using rigorous matching methods to reduce confounders when comparing those with and without elevated blood lead levels, we document negative effects on developmental, behavioral and socio-economic outcomes due to early childhood lead exposure. The magnitude of disparities between individuals who had elevated blood lead levels (≥5 µg/dL) in early childhood, compared to their matched counterparts, is in the ranges of 20-40%. The analysis is framed by clarifying the context, assumptions and limitations associated with the use of administrative data. This type of information has been useful in illuminating the burden of lead exposure for children, families and youth serving agencies and engaging public officials, landlords and residents in initiatives to bring housing up to lead safe standards.

Signal processing and machine learning algorithm to classify anaesthesia depth.

BACKGROUND: Poor assessment of anaesthetic depth (AD) has led to overdosing or underdosing of the anaesthetic agent, which requires continuous monitoring to avoid complications. The evaluation of the central nervous system activity and autonomic nervous system could provide additional information on the monitoring of AD during surgical procedures. METHODS: Observational analytical single-centre study, information on biological signals was collected during a surgical procedure under general anaesthesia for signal preprocessing, processing and postprocessing to feed a pattern classifier and determine AD status of patients. The development of the electroencephalography index was carried out through data processing and algorithm development using MATLAB V.8.1. RESULTS: A total of 25 men and 35 women were included, with a total time of procedure average of 109.62 min. The results show a high Pearson correlation between the Complexity Brainwave Index and the indices of the entropy module. A greater dispersion is observed in the state entropy and response entropy indices, a partial overlap can also be seen in the boxes associated with deep anaesthesia and general anaesthesia in these indices. A high Pearson correlation might be explained by the coinciding values corresponding to the awake and general anaesthesia states. A high Pearson correlation might be explained by the coinciding values corresponding to the awake and general anaesthesia states. CONCLUSION: Biological signal filtering and a machine learning algorithm may be used to classify AD during a surgical procedure. Further studies will be needed to confirm these results and improve the decision-making of anaesthesiologists in general anaesthesia.