Academic literature on the topic 'Clinical EEG data'

Infraslow electroencephalographic (EEG) activity refers to frequencies below the conventional clinical EEG range that starts at about 0.5 Hz. Evidence suggests that salient EEG signals in the infraslow range are essential parts of many physiological and pathological conditions. In addition, brain is known to exhibit multitude of infraslow processes, which may be observed directly as fluctuations in the EEG signal amplitude, as infraslow fluctuations or intermittency in other neurophysiological signals, or as fluctuations in behavioural performance. Both physiological and pathological EEG activity may range from 0.01 Hz to several hundred Hz. In the clinical context, infraslow activity is commonly observed in the neonatal EEG, during and prior to epileptic seizures, and during sleep and arousals. Laboratory studies have demonstrated the presence of spontaneous infraslow EEG fluctuations or very slow event-related potentials in awake and sleeping subjects. Infraslow activity may not only arise in cortical and subcortical networks but is also likely to involve non-neuronal generators such as glial networks. The full, physiologically relevant range of brain mechanisms can be readily recorded with wide dynamic range direct-current (DC)-coupled amplifiers or full-band EEG (FbEEG). Due to the different underlying mechanisms, a single FbEEG recording can even be perceived as a multimodal recording where distinct brain modalities can be studied simultaneously by performing data analysis for different frequency ranges. FbEEG is likely to become the standard approach for a wide range of applications in both basic science and in the clinic.

Electroencephalography (EEG), a dynamic real-time recording of electrical neocortical brain activity, began in the 1600s with the discovery of electrical phenomena and the concept of an “action current.” The galvanometer was introduced in the 1800s and the first bioelectrical observations of human brain signals were made in the 1900s. Certain EEG patterns were associated with brain disorders, increasing the clinical and scientific use of EEG. In the 1980s, technical advances allowed EEGs to be digitized and linked with videotape recording. In the 1990s, digital data storage increased and computer networking enabled remote real-time EEG reading, which made possible continuous EEG (cEEG) monitoring. Manual cEEG analysis became increasingly labor-intensive, calling for methods to assist this process. In the 2000s, complex algorithms enabling quantitative EEG analyses were introduced, with a new focus on shared activity between rhythms, including phase and magnitude synchrony. The automation of spectral analysis enabled studies of spectral content.

Quantitative electroencephalogram (qEEG) is the transformation of the EEG by spectral analysis in which the amount of electrical activity at a particular frequency is determined and compared against a normative data base. EEG findings are specific for different psychiatric problems and help reveal brain abnormalities associated with psychological symptoms. Repetitive transcranial magnetic stimulation (rTMS) is a system of delivering multiple pulses within a short time period that induce changes that outlast the stimulation period. Operant conditioning involves providing a reward to increase the probability of a certain behavior. Neurofeedback involves recording, analyzing, and presenting results of qEEG analyses in near real-time to patients in order to promote changes in brain electrical activity. This chapter reviews how neuromodulation works both clinically and from a neurophysiological perspective. This chapter also reviews current clinical data on the use of neuromodulation approaches for improving mental health and well-being.

Clinical Electromyography in Clinical Practice provides case-based learning of clinical Electromyography (EMG) with a main mission of reducing the gap between theory and practice in the field of electrodiagnostic medicine. The book format includes four introductory chapters that acquaint the discipline and scope of the EMG Examination to the beginners. This include chapters on nerve conduction studies, needle EMG, and specialized testing including late responses, repetitive nerve stimulation and single fiber EMG. Discussion on the electrodiagnostic and clinical EMG findings in the numerous neuromuscular disorders including anterior horn cell disorders, peripheral neuropathies, neuromuscular junction disorders and myopathies. The second part of the book includes comprehensive presentations of 27 cases that encompass the most common disorders encountered in the EMG laboratory and are presented in a similar layout. These are subdivided into (1) focal disorders of the lower extremity, (2) focal disorders of the upper extremity, and (3) generalized neuromuscular disorders. The book focuses on problem solving through analysis of the data obtained on nerve conduction studies and needle EMG. This is meant to be a bedside analysis of data, similar to what occurs in the EMG laboratory on a daily basis. The exact values obtained on nerve conduction studies are examined and the details of the findings on needle EMG are studied. A final diagnosis is then made. This is followed by a detailed discussion of the clinical and electrodiagnostic findings of the disorder. Clinical Electromyography in Clinical Practice is an ideal book for physicians interested in learning and mastering the clinical practice of clinical EMG. This includes specialists in the field of neurology, physical medicine and rehabilitation, orthopedics, hand surgery, neurosurgery, spine, rheumatology and pain management.

Until recently, borderline personality disorder (BPD) has been the stepchild of psychiatric disorders. Many researchers even questioned its existence. Clinicians have been reluctant to reveal the diagnosis to patients because of the stigma attached to it. But individuals with BPD suffer terribly and a significant proportion die by suicide and engage in nonsuicidal self-injury. The aim of this primer on BPD is to fill this void and provide clinicians with an accessible, easy-to-use, clinically oriented, evidenced-based guide for early-stage BPD. We present the most up to date data about BPD by leading experts in the field in a format accessible to trainees and professionals working with individuals with BPD and their family members. The volume is comprehensive and covers the etiology of BPD, its clinical presentation and comorbid disorders, genetics and neurobiology of BPD, effective treatment approaches to BPD, the role of advocacy, and the treatment of special subpopulations (e.g., forensic) in the clinical management of BPD.

Epilepsy syndromes of childhood are a heterogeneous group of disorders that occur at specific neurodevelopmental stages, with a variable prognosis ranging from benign to catastrophic. In clinical practice they are categorized based on seizure type, age of onset, clinical presentation, electroencephalographic (EEG) findings, as well as response to treatment. In addition, recent advancements in neuroimaging and genetic testing have become important diagnostic tools revealing underlying defects for some of these syndromes. This knowledge has consequences for clinical practice, as it opens new perspectives for early diagnosis, prognosis and treatment. Here, we provide an up-to-date overview of the most common pediatric epilepsy syndromes, their clinical findings, associated EEG findings, and clinical management.

In axial spondyloarthritis (axSpA) there is little evidence to support use of classical synthetic disease-modifying antirheumatic drugs (DMARDs), with the majority of studies performed in advanced ankylosing spondylitis. Sulfasalazine is the best investigated DMARD in axSpA. Its positive clinical effect, if any, seems to be more prominent in the presence of peripheral arthritis, although a certain proportion of patients with axial disease might benefit from sulfasalazine therapy. Available data indicate that there is no evidence that methotrexate might be effective in axial disease, and only marginal evidence exists in support of methotrexate use in case of peripheral involvement. No true disease-modifying properties (e.g. retardation of structural damage progression in the spine) have been demonstrated for DMARDs in axSpA to date. Efficacy of a combination therapy (e.g. methotrexate plus sulfasalazine) as well as benefits of methotrexate (or other DMARDs) in addition to tumour necrosis factor α‎ inhibitors in axSpA remain uncertain.

Neurosurgery is a rapidly developing and technically demanding branch of surgery that requires a detailed knowledge of the basic sciences and a thorough clinical approach. The Oxford Textbook of Neurological Surgery is an up-to-date, objective, and readable text that covers the full scope of neurosurgical practice. Each section takes a dual approach with ‘generic surgical management’ chapters that focus on specific clinical problems facing the neurosurgeon (e.g. sellar/suprasellar tumour, intradural spina tumours, and others) and ‘pathology-specific’ chapters (e.g. glioma, meningeal tumours, scoliosis and spinal deformity, aneurysm, and others). Where appropriate, this division provides the reader with easily accessible information for both clinical problems which present in a regional fashion and specific pathologies. The generic chapters cover aspects such as operative approaches, neuroanatomy, and nuances.

AbstractHypoxic-ischemic encephalopathy (HIE) remains a major burden for infants, their families, and society all over the world, while the incidence of HIE has fallen slightly in high-income countries (HICs) that is not the situation in many poorer economic environments. Still, in many cases, a clear cause for and the timing of the insult remains unclear. The introduction of therapeutic cooling in HICs for moderate and severe HIE has resulted in better early recognition of encephalopathy, better monitoring with EEG, and an emphasis on optimal early management with early seizure treatments and outcome prediction. In turn, this has led to significant improvements in outcomes though some infants still have moderate to severe long-term problems affecting all developmental domains and some do not survive. Studies remain in progress as to whether mild HIE should be treated with cooling, whether cooling should be used in different clinical settings, and whether additional neuroprotective agents can further improve outcome.Nowadays most children in HICs survive with good early outcomes, but data from school-age follow-up has allowed much better recognition of more subtle but significant longer-term problems affecting memory, cognition, and minor motor skills, making long-term follow-up essential. MR brain imaging remains the best individual modality for outcome prediction.

AbstractClinical data is often collected and processed as time series: a sequence of data indexed by successive time points. Such time series can be from sources that are sampled over short time intervals to represent continuous biophysical wave-(one word waveforms) forms such as the voltage measurements representing the electrocardiogram, to measurements that are sampled daily, weekly, yearly, etc. such as patient weight, blood triglyceride levels, etc. When analyzing clinical data or designing biomedical systems for measurements, interventions, or diagnostic aids, it is important to represent the information contained within such time series in a more compact or meaningful form (e.g., noise filtering), amenable to interpretation by a human or computer. This process is known as feature extraction. This chapter will discuss some fundamental techniques for extracting features from time series representing general forms of clinical data.

AbstractThe in vitro fertilization procedure called intracytoplasmic sperm injection can be used to help fertilize an egg by injecting a single sperm cell directly into the cytoplasm of the egg. In order to evaluate, refine and improve the method in the fertility clinic, the procedure is usually observed at the clinic. Alternatively, a video of the procedure can be examined and labeled in a time-consuming process. To reduce the time required for the assessment, we propose an unsupervised method that automatically clusters video frames of the intracytoplasmic sperm injection procedure. Deep features are extracted from the video frames and form the basis for a clustering method. The method provides meaningful clusters representing different stages of the intracytoplasmic sperm injection procedure. The clusters can lead to more efficient examinations and possible new insights that can improve clinical practice. Further on, it may also contribute to improved clinical outcomes due to increased understanding about the technical aspects and better results of the procedure. Despite promising results, the proposed method can be further improved by increasing the amount of data and exploring other types of features.

Electrocardiogram (ECG) is the most commonly used diagnostic method for heart diseases such as arrhythmia. However, its inherent complexity, to some extent, reduces the accuracy of diagnosis. To quickly and automatically identify the type of arrhythmia, this paper constructs a clinical ECG classification model based on Convolutional Neural Network (CNN) to assist clinicians in analyzing ECG signals. The MIT-BIH ECG database is used as the research data source, and the heart beats are classified into 5 categories based on AAMI EC57 standard. 95% of the ECG data is randomly divided into training and testing sets, and the remaining 5% is used as the internal testing set. Based on the experimental outcomes, the model's accuracy exceeds 96%, indicating a commendable overall performance.

Background: The Brazilian Surveillance for Prion Disease began in 2005 with compulsory notification of suspected cases. Objective: To determine the diagnosis of reported patients to the Brazilian Surveillance for Prion Disease and evaluate the clinical and genetic data. Methods: Data from the notification sheet were collected and patients were classified according to current clinical and pathological criteria. Results: 757 cases were notified from 2005 to 2019. 51 cases were defined DCJ, 295 probable DCJ, 172 possible DCJ and 38 genetic DCJ. 55 patients had other diagnosis and 146 were unclassified (missing data). The most frequent mutations were E200K, D178N, P102L and V180I. Among defined and probable DCJ: 55% were female, mean age was 62 y.o. and median age was 61.9 y.o.; 51.8% were M129M and 23.2% V129V. CSF 14.3.3 was positive in 69.2%, disease-typical EEG findings were observed in 42.3% and MRI revealed typical findings in 76.9%. No variant CJD were diagnosed. Discussion: considering the Brazilian population and the prevalence of CJD worldwilde, we expected more cases of CJD than were notified. Methionine and valine homozygotes are overrepresented, in agreement with international data. MRI were the more useful subsidiary test for clinical classification.. Conclusion: besides the undernotification, the Brazilian surveillance for prion diseases evaluated 757 suspected cases in the last 15 years. 50.7% were probable, defined CJD or genetic prion disease.

This study focuses on deep learning models for predicting coma outcomes using electroencephalogram (EEG) data, exploring convolutional neural networks (CNNs), particularly Shallow and Deep ConvNets, based on Filter Bank Common Spatial Patterns. A dataset of 121 EEG samples (42 favorable, 79 unfavorable) was analyzed. EEG segments were selected using two strategies and frequencies. Models were trained with 10-fold cross-validation and FTSurrogate for class balance. Shallow ConvNet showed stable performance across frequencies, while Deep ConvNet excelled at 200Hz. Simple segment selection and sampling frequency methods improved CNN performance. The findings offer insights for future research and potential clinical applications.

This paper investigates the feasibility of using non-cerebral, time-series data to detect epileptic seizures. Data were recorded from fifteen patients (7 male, 5 female, 3 not noted, mean age 36.17 yrs), five of whom had a total of seven seizures. Patients were monitored in an inpatient setting using standard video electroencephalography (vEEG), while also wearing sensors monitoring electrocardiography, electrodermal activity, electromyography, accelerometry, and audio signals (vocalizations). A systematic and detailed study was conducted to identify the sensors and the features derived from the non-cerebral sensors that contribute most significantly to separability of data acquired during seizures from non-seizure data. Post-processing of the data using linear discriminant analysis (LDA) shows that seizure data are strongly separable from non-seizure data based on features derived from the signals recorded. The mean area under the receiver operator characteristic (ROC) curve for each individual patient that experienced a seizure during data collection, calculated using LDA, was 0.9682. The features that contribute most significantly to seizure detection differ for each patient. The results show that a multimodal approach to seizure detection using the specified sensor suite is promising in detecting seizures with both sensitivity and specificity. Moreover, the study provides a means to quantify the contribution of each sensor and feature to separability. Development of a non-electroencephalography (EEG) based seizure detection device would give doctors a more accurate seizure count outside of the clinical setting, improving treatment and the quality of life of epilepsy patients.

Review question / Objective: We aim to compare second-generation supraglottic airways with endotracheal tubes for perioperative safety and quality of postoperative recovery as well as for ventilation performance and risk of pulmonary aspiration. Eligibility criteria: Inclusion criteria will be as follows: randomized clinical trials; human patients aged ≥ 16 years undergoing abdominopelvic procedures under general anaesthesia from any population (e.g., general population, pregnant women, obese patients); data available on any outcome related to insertion performance (e.g., failed first attempt, failed insertion, and time to insertion), ventilation efficacy (e.g., leak pressure, leak fraction, and ventilation inadequacy), risk of regurgitation and aspiration (e.g., gastric insufflation, regurgitation, and aspiration), quality of postoperative recovery (e.g., sore throat, hoarseness, and postoperative nausea and vomiting [PONV]), and major complications (e.g., laryngospasm, bronchospasm, and hypoxemia); and comparison between any second-generation SGA and an endotracheal tube. We will exclude: studies reported in a language that prevent us of extracting relevant information; outcomes with no objective data presented (i.e., effect sizes, measures of dispersion, frequency, etc.); and studies with contradictory data.

Review question / Objective: What is the clinical efficacy of combing Chengqi Decoction in the treatment of ARDS/ALI, compared with the conventional treatment of ARDA/ALI with western medicine? Condition being studied: Acute respiratory distress syndrome(ARDS), Acute lung injury(ALI). Eligibility criteria: (1) lacking literature data (e.g., nonpaired studies) (2) duplicate publications; (3) do not have access to the full text (4) conference reports, system reviews, protocols, or abstracts; (5) RCTs with small sample sizes; . (5)The treatment course is less than 6 days (6) Exclude articles with high risk of deviation

The goal of a QIBA Profile is to help achieve a useful level of performance for a given biomarker. The Claim (Section 2) describes the biomarker performance. The Activities (Section 3) contribute to generating the biomarker. Requirements are placed on the Actors that participate in those activities as necessary to achieve the Claim. Assessment Procedures (Section 4) for evaluating specific requirements are defined as needed. This QIBA Profile (MR-based cartilage compositional biomarkers (T1ρ, T2) ) addresses the application of T1ρ and T2 for the quantification of cartilage composition, which can be used as an imaging biomarker to diagnose, predict and monitor early osteoarthritis. It places requirements on Acquisition Devices, Technologists, MRI Physicists, Radiologists, Reconstruction Software and Image Analysis Tools involved in Subject Handling, Image Data Acquisition, Image Data Reconstruction, Image Quality Assurance (QA) and Image Analysis. The requirements are focused on achieving sufficient reproducibility and accuracy for measuring cartilage composition. The clinical performance target is to achieve a reproducibility of 4-5% for measurements of global cartilage composition with T2 and T1ρ relaxation time measurements and a 95% confidence level for a true/critical change in cartilage composition (least significant change) with a precision of 11-14% and 9-12% if only an increase is expected (claim is one-sided). The target applies to 3T MR scanners of one manufacturer with identical scan parameters across different sites. It does not apply to scanners from different manufacturers. This document is intended to help clinicians basing decisions on this biomarker, imaging staff generating this biomarker, vendor staff developing related products, purchasers of such products and investigators designing trials with imaging endpoints. Note that this document only states requirements to achieve the claim, not “requirements on standard of care.” Conformance to this Profile is secondary to properly caring for the patient. Summary for Clinical Trial Use The MR-based cartilage compositional biomarkers profile defines the behavioral performance levels and quality control specifications for T1ρ, T2 scans used in single- and multi-center clinical trials of osteoarthritis and other trials assessing cartilage composition longitudinally with a focus on therapies to treat degenerative joint disease. While the emphasis is on clinical trials, this process is also intended to be applied for clinical practice. The specific claims for accuracy are detailed below in the Claims. The specifications that must be met to achieve conformance with this Profile correspond to acceptable levels specified in the T1ρ, T2 Protocols. The aim of the QIBA Profile specifications is to minimize intra- and inter-subject, intra- and inter-platform, and interinstitutional variability of quantitative scan data due to factors other than the intervention under investigation. T1ρ and T2 studies performed according to the technical specifications of this QIBA Profile in clinical trials can provide quantitative data for single timepoint assessments (e.g. disease burden, investigation of predictive and/or prognostic biomarker(s)) and/or for multi-time-point comparative assessments (e.g., response assessment, investigation of predictive and/or prognostic biomarkers of treatment efficacy). A motivation for the development of this Profile is that while a typical MR T1ρ and T2 measurement may be stable over days or weeks, this stability cannot be expected over the time that it takes to complete a clinical trial. In addition, there are well known differences between scanners and the operation of the same type of scanner at different imaging sites. The intended audiences of this document include: Biopharmaceutical companies, rheumatologists and orthopedic surgeons, and clinical trial scientists designing trials with imaging endpoints. Clinical research professionals. Radiologists, technologists, physicists and administrators at healthcare institutions considering specifications for procuring new MRI equipment for cartilage measurements. Radiologists, technologists, and physicists designing T1ρ and T2 acquisition protocols. Radiologists, and other physicians making quantitative measurements from T1ρ and T2 sequence protocols. Regulators, rheumatologists, orthopedic surgeons, and others making decisions based on quantitative image measurements. Technical staff of software and device manufacturers who create products for this purpose. Note that specifications stated as 'requirements' in this document are only requirements to achieve the claim, not 'requirements on standard of care.' Specifically, meeting the goals of this Profile is secondary to properly caring for the patient.

Background: Major depressive disorder is a common mental disorder. Many pressing questions regarding depression treatment and outcomes exist, and new, efficient research approaches are necessary to address them. The primary objective of this project is to demonstrate the feasibility and value of capturing the harmonized depression outcome measures in the clinical workflow and submitting these data to different registries. Secondary objectives include demonstrating the feasibility of using these data for patient-centered outcomes research and developing a toolkit to support registries interested in sharing data with external researchers. Methods: The harmonized outcome measures for depression were developed through a multi-stakeholder, consensus-based process supported by AHRQ. For this implementation effort, the PRIME Registry, sponsored by the American Board of Family Medicine, and PsychPRO, sponsored by the American Psychiatric Association, each recruited 10 pilot sites from existing registry sites, added the harmonized measures to the registry platform, and submitted the project for institutional review board review Results: The process of preparing each registry to calculate the harmonized measures produced three major findings. First, some clarifications were necessary to make the harmonized definitions operational. Second, some data necessary for the measures are not routinely captured in structured form (e.g., PHQ-9 item 9, adverse events, suicide ideation and behavior, and mortality data). Finally, capture of the PHQ-9 requires operational and technical modifications. The next phase of this project will focus collection of the baseline and follow-up PHQ-9s, as well as other supporting clinical documentation. In parallel to the data collection process, the project team will examine the feasibility of using natural language processing to extract information on PHQ-9 scores, adverse events, and suicidal behaviors from unstructured data. Conclusion: This pilot project represents the first practical implementation of the harmonized outcome measures for depression. Initial results indicate that it is feasible to calculate the measures within the two patient registries, although some challenges were encountered related to the harmonized definition specifications, the availability of the necessary data, and the clinical workflow for collecting the PHQ-9. The ongoing data collection period, combined with an evaluation of the utility of natural language processing for these measures, will produce more information about the practical challenges, value, and burden of using the harmonized measures in the primary care and mental health setting. These findings will be useful to inform future implementations of the harmonized depression outcome measures.

Objectives. To assess the use, effectiveness, and implementation of telehealth-supported provider-to-provider communication and collaboration for the provision of healthcare services to rural populations and to inform a scientific workshop convened by the National Institutes of Health Office of Disease Prevention on October 12–14, 2021. Data sources. We conducted a comprehensive literature search of Ovid MEDLINE®, CINAHL®, Embase®, and Cochrane CENTRAL. We searched for articles published from January 1, 2015, to October 12, 2021, to identify data on use of rural provider-to-provider telehealth (Key Question 1) and the same databases for articles published January 1, 2010, to October 12, 2021, for studies of effectiveness and implementation (Key Questions 2 and 3) and to identify methodological weaknesses in the research (Key Question 4). Additional sources were identified through reference lists, stakeholder suggestions, and responses to a Federal Register notice. Review methods. Our methods followed the Agency for Healthcare Research and Quality Methods Guide (available at https://effectivehealthcare.ahrq.gov/topics/cer-methods-guide/overview) and the PRISMA reporting guidelines. We used predefined criteria and dual review of abstracts and full-text articles to identify research results on (1) regional or national use, (2) effectiveness, (3) barriers and facilitators to implementation, and (4) methodological weakness in studies of provider-to-provider telehealth for rural populations. We assessed the risk of bias of the effectiveness studies using criteria specific to the different study designs and evaluated strength of evidence (SOE) for studies of similar telehealth interventions with similar outcomes. We categorized barriers and facilitators to implementation using the Consolidated Framework for Implementation Research (CFIR) and summarized methodological weaknesses of studies. Results. We included 166 studies reported in 179 publications. Studies on the degree of uptake of provider-to-provider telehealth were limited to specific clinical uses (pharmacy, psychiatry, emergency care, and stroke management) in seven studies using national or regional surveys and claims data. They reported variability across States and regions, but increasing uptake over time. Ninety-seven studies (20 trials and 77 observational studies) evaluated the effectiveness of provider-to-provider telehealth in rural settings, finding that there may be similar rates of transfers and lengths of stay with telehealth for inpatient consultations; similar mortality rates for remote intensive care unit care; similar clinical outcomes and transfer rates for neonates; improvements in medication adherence and treatment response in outpatient care for depression; improvements in some clinical monitoring measures for diabetes with endocrinology or pharmacy outpatient consultations; similar mortality or time to treatment when used to support emergency assessment and management of stroke, heart attack, or chest pain at rural hospitals; and similar rates of appropriate versus inappropriate transfers of critical care and trauma patients with specialist telehealth consultations for rural emergency departments (SOE: low). Studies of telehealth for education and mentoring of rural healthcare providers may result in intended changes in provider behavior and increases in provider knowledge, confidence, and self-efficacy (SOE: low). Patient outcomes were not frequently reported for telehealth provider education, but two studies reported improvement (SOE: low). Evidence for telehealth interventions for other clinical uses and outcomes was insufficient. We identified 67 program evaluations and qualitative studies that identified barriers and facilitators to rural provider-to-provider telehealth. Success was linked to well-functioning technology; sufficient resources, including time, staff, leadership, and equipment; and adequate payment or reimbursement. Some considerations may be unique to implementation of provider-to-provider telehealth in rural areas. These include the need for consultants to better understand the rural context; regional initiatives that pool resources among rural organizations that may not be able to support telehealth individually; and programs that can support care for infrequent as well as frequent clinical situations in rural practices. An assessment of methodological weaknesses found that studies were limited by less rigorous study designs, small sample sizes, and lack of analyses that address risks for bias. A key weakness was that studies did not assess or attempt to adjust for the risk that temporal changes may impact the results in studies that compared outcomes before and after telehealth implementation. Conclusions. While the evidence base is limited, what is available suggests that telehealth supporting provider-to-provider communications and collaboration may be beneficial. Telehealth studies report better patient outcomes in some clinical scenarios (e.g., outpatient care for depression or diabetes, education/mentoring) where telehealth interventions increase access to expertise and high-quality care. In other applications (e.g., inpatient care, emergency care), telehealth results in patient outcomes that are similar to usual care, which may be interpreted as a benefit when the purpose of telehealth is to make equivalent services available locally to rural residents. Most barriers to implementation are common to practice change efforts. Methodological weaknesses stem from weaker study designs, such as before-after studies, and small numbers of participants. The rapid increase in the use of telehealth in response to the Coronavirus disease 2019 (COVID-19) pandemic is likely to produce more data and offer opportunities for more rigorous studies.

Aims. There is uncertainty around the optimal role of percutaneous coronary intervention (PCI) for management of chronic coronary syndrome, specifically when patients have disease in multiple coronary vessels and disease in the proximal portion of the left anterior descending coronary artery. This uncertainty was reflected in 2021 guidance from the American College of Cardiology (ACC)/American Heart Association (AHA) on coronary artery revascularization. The Agency for Healthcare Research and Quality has commissioned this rapid response literature review to meet a Congressional request for a summary of recent evidence on the benefits of angioplasties conducted in nonemergency situations. Methods. This rapid response literature review on the comparative effectiveness of nonemergent PCI followed established best systematic review methods, modified to meet a shortened project timeframe. We searched PubMed®, Embase®, and the Trip© medical database from 2018 through April 2023 for systematic reviews (SRs), clinical practice guidelines, and randomized controlled trials, and summarized the evidence comparing PCI to optimal medical therapy (OMT) for stable ischemic heart disease (SIHD). Our primary outcomes of interest were major objective cardiovascular outcomes, including mortality, myocardial infarction, stroke, urgent revascularization, or composites of one or more of these hard clinical outcomes. Where available, we also abstracted patient reported outcomes (e.g., angina severity and quality of life [QoL]) from included studies. Findings. Key findings from nine SRs and one primary study include: • The body of evidence directly comparing PCI to OMT for SIHD has remained largely unchanged since the 2021 ACC/AHA guidance’s publication. • Most studies of revascularization for coronary artery disease do not focus on direct head-to-head comparisons of PCI versus OMT for SIHD but instead either (1) compare OMT to invasive revascularization (PCI and coronary artery bypass graft [CABG] combined cohort); (2) compare PCI to CABG; or (3) compare different PCI techniques. • Another factor that complicates comparison is that the meta-analyses often included data from CABG and PCI combined cohorts (e.g., the recent landmark ISCHEMIA trial) but reported the outcomes as PCI specific. • In the general SIHD population, our review did not find evidence to support survival benefit or effect on hard clinical outcomes when PCI is added to OMT. • Limited evidence indicates there may be a beneficial effect of PCI on angina symptoms and measures of QoL, but most systematic reviews focused on major objective cardiovascular outcomes and did not consider QoL or freedom from angina. • Both OMT and PCI have evolved significantly during the period of time in which the systematic reviews’ included studies were conducted. It is not clear how these changes may have affected the applicability of past studies to current practice. Conclusions. The evidence directly comparing PCI to OMT for SIHD has remained largely unchanged since publication of the 2021 ACC/AHA guidelines. More research is needed to verify the comparative effectiveness of nonemergent PCI compared to medical treatment for individuals with SIHD, and how the effectiveness varies by certain patient populations and clinical presentation.

Objectives. To examine how Trauma Informed Care (TIC) and its components are defined and operationalized, and to examine the state of the evidence on effectiveness and potential harms of TIC approaches, frameworks, models, and components. Data sources. We searched Medline (Ovid)®, APA PsycInfo® (Ovid), CINAHL® (EBSCOHost), ERIC (EBSCOHost), and Scopus (Elsevier) for peer-reviewed articles published through July 19, 2024. Grey literature was also searched for Contextual Questions regarding TIC definitions and organizational and clinical components. Review methods. We used methods consistent with the Agency for Healthcare Research and Quality’s Evidence-based Practice Center Program Methods Guide. We prepared the review protocol with input from Key Informants, Technical Experts, and a public comment period in April 2023. Using predefined criteria and dual review, we selected intervention studies that enrolled adult or pediatric patients/clients regardless of identified trauma exposure or type of trauma exposure in any healthcare or social service setting in any country. Eligible studies included randomized controlled trials and comparative nonrandomized studies of interventions. We assessed risk of bias and strength of evidence for a prespecified list of patient/client health related outcomes. Results. From 4,379 unique references, we identified 12 eligible studies discussed in 16 publications. Study settings were varied: two studies in adult medical care settings, one in adult mental health service, one in primary prevention for children, one in adolescent medical care, four in residential child welfare, and three in non-residential child welfare. We did not combine data quantitatively due to variability of interventions. All studies were assessed as high risk of bias and evidence was insufficient to determine the effects of TIC on patient/client outcomes for all settings and comparisons. Studies did not collect information on harms, adverse events, or unintended consequences of TIC. TIC models vary considerably in their socioecological components from youth to adult services across settings and disciplines. There was a broad range of organizational and clinical components, with only some overlap within both organizational and clinical domains. A few TIC models described specific elements of cultural competency/humility. Conclusions. Evidence was insufficient to make any clear determinations on the effectiveness of TIC approaches across any patient/client health related outcome, but this does not mean the individual interventions described are not potentially useful. Rather, it means the evidence does not yet provide clear answers. Still, TIC is being widely implemented, and research on its effectiveness and potential harms seems to be neither informing nor keeping pace with related areas (e.g., evidence-based trauma treatments) or practice/implementation.

Objectives. Diagnostic errors are a known patient safety concern across all clinical settings, including the emergency department (ED). We conducted a systematic review to determine the most frequent diseases and clinical presentations associated with diagnostic errors (and resulting harms) in the ED, measure error and harm frequency, as well as assess causal factors. Methods. We searched PubMed®, Cumulative Index to Nursing and Allied Health Literature (CINAHL®), and Embase® from January 2000 through September 2021. We included research studies and targeted grey literature reporting diagnostic errors or misdiagnosis-related harms in EDs in the United States or other developed countries with ED care deemed comparable by a technical expert panel. We applied standard definitions for diagnostic errors, misdiagnosis-related harms (adverse events), and serious harms (permanent disability or death). Preventability was determined by original study authors or differences in harms across groups. Two reviewers independently screened search results for eligibility; serially extracted data regarding common diseases, error/harm rates, and causes/risk factors; and independently assessed risk of bias of included studies. We synthesized results for each question and extrapolated U.S. estimates. We present 95 percent confidence intervals (CIs) or plausible range (PR) bounds, as appropriate. Results. We identified 19,127 citations and included 279 studies. The top 15 clinical conditions associated with serious misdiagnosis-related harms (accounting for 68% [95% CI 66 to 71] of serious harms) were (1) stroke, (2) myocardial infarction, (3) aortic aneurysm and dissection, (4) spinal cord compression and injury, (5) venous thromboembolism, (6/7 – tie) meningitis and encephalitis, (6/7 – tie) sepsis, (8) lung cancer, (9) traumatic brain injury and traumatic intracranial hemorrhage, (10) arterial thromboembolism, (11) spinal and intracranial abscess, (12) cardiac arrhythmia, (13) pneumonia, (14) gastrointestinal perforation and rupture, and (15) intestinal obstruction. Average disease-specific error rates ranged from 1.5 percent (myocardial infarction) to 56 percent (spinal abscess), with additional variation by clinical presentation (e.g., missed stroke average 17%, but 4% for weakness and 40% for dizziness/vertigo). There was also wide, superimposed variation by hospital (e.g., missed myocardial infarction 0% to 29% across hospitals within a single study). An estimated 5.7 percent (95% CI 4.4 to 7.1) of all ED visits had at least one diagnostic error. Estimated preventable adverse event rates were as follows: any harm severity (2.0%, 95% CI 1.0 to 3.6), any serious harms (0.3%, PR 0.1 to 0.7), and deaths (0.2%, PR 0.1 to 0.4). While most disease-specific error rates derived from mainly U.S.-based studies, overall error and harm rates were derived from three prospective studies conducted outside the United States (in Canada, Spain, and Switzerland, with combined n=1,758). If overall rates are generalizable to all U.S. ED visits (130 million, 95% CI 116 to 144), this would translate to 7.4 million (PR 5.1 to 10.2) ED diagnostic errors annually; 2.6 million (PR 1.1 to 5.2) diagnostic adverse events with preventable harms; and 371,000 (PR 142,000 to 909,000) serious misdiagnosis-related harms, including more than 100,000 permanent, high-severity disabilities and 250,000 deaths. Although errors were often multifactorial, 89 percent (95% CI 88 to 90) of diagnostic error malpractice claims involved failures of clinical decision-making or judgment, regardless of the underlying disease present. Key process failures were errors in diagnostic assessment, test ordering, and test interpretation. Most often these were attributed to inadequate knowledge, skills, or reasoning, particularly in “atypical” or otherwise subtle case presentations. Limitations included use of malpractice claims and incident reports for distribution of diseases leading to serious harms, reliance on a small number of non-U.S. studies for overall (disease-agnostic) diagnostic error and harm rates, and methodologic variability across studies in measuring disease-specific rates, determining preventability, and assessing causal factors. Conclusions. Although estimated ED error rates are low (and comparable to those found in other clinical settings), the number of patients potentially impacted is large. Not all diagnostic errors or harms are preventable, but wide variability in diagnostic error rates across diseases, symptoms, and hospitals suggests improvement is possible. With 130 million U.S. ED visits, estimated rates for diagnostic error (5.7%), misdiagnosis-related harms (2.0%), and serious misdiagnosis-related harms (0.3%) could translate to more than 7 million errors, 2.5 million harms, and 350,000 patients suffering potentially preventable permanent disability or death. Over two-thirds of serious harms are attributable to just 15 diseases and linked to cognitive errors, particularly in cases with “atypical” manifestations. Scalable solutions to enhance bedside diagnostic processes are needed, and these should target the most commonly misdiagnosed clinical presentations of key diseases causing serious harms. New studies should confirm overall rates are representative of current U.S.-based ED practice and focus on identified evidence gaps (errors among common diseases with lower-severity harms, pediatric ED errors and harms, dynamic systems factors such as overcrowding, and false positives). Policy changes to consider based on this review include: (1) standardizing measurement and research results reporting to maximize comparability of measures of diagnostic error and misdiagnosis-related harms; (2) creating a National Diagnostic Performance Dashboard to track performance; and (3) using multiple policy levers (e.g., research funding, public accountability, payment reforms) to facilitate the rapid development and deployment of solutions to address this critically important patient safety concern.

Background Lung cancer is the number one cause of cancer death worldwide.(1) It is the fifth most commonly diagnosed cancer in Australia (12,741 cases diagnosed in 2018) and the leading cause of cancer death.(2) The number of years of potential life lost to lung cancer in Australia is estimated to be 58,450, similar to that of colorectal and breast cancer combined.(3) While tobacco control strategies are most effective for disease prevention in the general population, early detection via low dose computed tomography (LDCT) screening in high-risk populations is a viable option for detecting asymptomatic disease in current (13%) and former (24%) Australian smokers.(4) The purpose of this Evidence Check review is to identify and analyse existing and emerging evidence for LDCT lung cancer screening in high-risk individuals to guide future program and policy planning. Evidence Check questions This review aimed to address the following questions: 1. What is the evidence for the effectiveness of lung cancer screening for higher-risk individuals? 2. What is the evidence of potential harms from lung cancer screening for higher-risk individuals? 3. What are the main components of recent major lung cancer screening programs or trials? 4. What is the cost-effectiveness of lung cancer screening programs (include studies of cost–utility)? Summary of methods The authors searched the peer-reviewed literature across three databases (MEDLINE, PsycINFO and Embase) for existing systematic reviews and original studies published between 1 January 2009 and 8 August 2019. Fifteen systematic reviews (of which 8 were contemporary) and 64 original publications met the inclusion criteria set across the four questions. Key findings Question 1: What is the evidence for the effectiveness of lung cancer screening for higher-risk individuals? There is sufficient evidence from systematic reviews and meta-analyses of combined (pooled) data from screening trials (of high-risk individuals) to indicate that LDCT examination is clinically effective in reducing lung cancer mortality. In 2011, the landmark National Lung Cancer Screening Trial (NLST, a large-scale randomised controlled trial [RCT] conducted in the US) reported a 20% (95% CI 6.8% – 26.7%; P=0.004) relative reduction in mortality among long-term heavy smokers over three rounds of annual screening. High-risk eligibility criteria was defined as people aged 55–74 years with a smoking history of ≥30 pack-years (years in which a smoker has consumed 20-plus cigarettes each day) and, for former smokers, ≥30 pack-years and have quit within the past 15 years.(5) All-cause mortality was reduced by 6.7% (95% CI, 1.2% – 13.6%; P=0.02). Initial data from the second landmark RCT, the NEderlands-Leuvens Longkanker Screenings ONderzoek (known as the NELSON trial), have found an even greater reduction of 26% (95% CI, 9% – 41%) in lung cancer mortality, with full trial results yet to be published.(6, 7) Pooled analyses, including several smaller-scale European LDCT screening trials insufficiently powered in their own right, collectively demonstrate a statistically significant reduction in lung cancer mortality (RR 0.82, 95% CI 0.73–0.91).(8) Despite the reduction in all-cause mortality found in the NLST, pooled analyses of seven trials found no statistically significant difference in all-cause mortality (RR 0.95, 95% CI 0.90–1.00).(8) However, cancer-specific mortality is currently the most relevant outcome in cancer screening trials. These seven trials demonstrated a significantly greater proportion of early stage cancers in LDCT groups compared with controls (RR 2.08, 95% CI 1.43–3.03). Thus, when considering results across mortality outcomes and early stage cancers diagnosed, LDCT screening is considered to be clinically effective. Question 2: What is the evidence of potential harms from lung cancer screening for higher-risk individuals? The harms of LDCT lung cancer screening include false positive tests and the consequences of unnecessary invasive follow-up procedures for conditions that are eventually diagnosed as benign. While LDCT screening leads to an increased frequency of invasive procedures, it does not result in greater mortality soon after an invasive procedure (in trial settings when compared with the control arm).(8) Overdiagnosis, exposure to radiation, psychological distress and an impact on quality of life are other known harms. Systematic review evidence indicates the benefits of LDCT screening are likely to outweigh the harms. The potential harms are likely to be reduced as refinements are made to LDCT screening protocols through: i) the application of risk predication models (e.g. the PLCOm2012), which enable a more accurate selection of the high-risk population through the use of specific criteria (beyond age and smoking history); ii) the use of nodule management algorithms (e.g. Lung-RADS, PanCan), which assist in the diagnostic evaluation of screen-detected nodules and cancers (e.g. more precise volumetric assessment of nodules); and, iii) more judicious selection of patients for invasive procedures. Recent evidence suggests a positive LDCT result may transiently increase psychological distress but does not have long-term adverse effects on psychological distress or health-related quality of life (HRQoL). With regards to smoking cessation, there is no evidence to suggest screening participation invokes a false sense of assurance in smokers, nor a reduction in motivation to quit. The NELSON and Danish trials found no difference in smoking cessation rates between LDCT screening and control groups. Higher net cessation rates, compared with general population, suggest those who participate in screening trials may already be motivated to quit. Question 3: What are the main components of recent major lung cancer screening programs or trials? There are no systematic reviews that capture the main components of recent major lung cancer screening trials and programs. We extracted evidence from original studies and clinical guidance documents and organised this into key groups to form a concise set of components for potential implementation of a national lung cancer screening program in Australia: 1. Identifying the high-risk population: recruitment, eligibility, selection and referral 2. Educating the public, people at high risk and healthcare providers; this includes creating awareness of lung cancer, the benefits and harms of LDCT screening, and shared decision-making 3. Components necessary for health services to deliver a screening program: a. Planning phase: e.g. human resources to coordinate the program, electronic data systems that integrate medical records information and link to an established national registry b. Implementation phase: e.g. human and technological resources required to conduct LDCT examinations, interpretation of reports and communication of results to participants c. Monitoring and evaluation phase: e.g. monitoring outcomes across patients, radiological reporting, compliance with established standards and a quality assurance program 4. Data reporting and research, e.g. audit and feedback to multidisciplinary teams, reporting outcomes to enhance international research into LDCT screening 5. Incorporation of smoking cessation interventions, e.g. specific programs designed for LDCT screening or referral to existing community or hospital-based services that deliver cessation interventions. Most original studies are single-institution evaluations that contain descriptive data about the processes required to establish and implement a high-risk population-based screening program. Across all studies there is a consistent message as to the challenges and complexities of establishing LDCT screening programs to attract people at high risk who will receive the greatest benefits from participation. With regards to smoking cessation, evidence from one systematic review indicates the optimal strategy for incorporating smoking cessation interventions into a LDCT screening program is unclear. There is widespread agreement that LDCT screening attendance presents a ‘teachable moment’ for cessation advice, especially among those people who receive a positive scan result. Smoking cessation is an area of significant research investment; for instance, eight US-based clinical trials are now underway that aim to address how best to design and deliver cessation programs within large-scale LDCT screening programs.(9) Question 4: What is the cost-effectiveness of lung cancer screening programs (include studies of cost–utility)? Assessing the value or cost-effectiveness of LDCT screening involves a complex interplay of factors including data on effectiveness and costs, and institutional context. A key input is data about the effectiveness of potential and current screening programs with respect to case detection, and the likely outcomes of treating those cases sooner (in the presence of LDCT screening) as opposed to later (in the absence of LDCT screening). Evidence about the cost-effectiveness of LDCT screening programs has been summarised in two systematic reviews. We identified a further 13 studies—five modelling studies, one discrete choice experiment and seven articles—that used a variety of methods to assess cost-effectiveness. Three modelling studies indicated LDCT screening was cost-effective in the settings of the US and Europe. Two studies—one from Australia and one from New Zealand—reported LDCT screening would not be cost-effective using NLST-like protocols. We anticipate that, following the full publication of the NELSON trial, cost-effectiveness studies will likely be updated with new data that reduce uncertainty about factors that influence modelling outcomes, including the findings of indeterminate nodules. Gaps in the evidence There is a large and accessible body of evidence as to the effectiveness (Q1) and harms (Q2) of LDCT screening for lung cancer. Nevertheless, there are significant gaps in the evidence about the program components that are required to implement an effective LDCT screening program (Q3). Questions about LDCT screening acceptability and feasibility were not explicitly included in the scope. However, as the evidence is based primarily on US programs and UK pilot studies, the relevance to the local setting requires careful consideration. The Queensland Lung Cancer Screening Study provides feasibility data about clinical aspects of LDCT screening but little about program design. The International Lung Screening Trial is still in the recruitment phase and findings are not yet available for inclusion in this Evidence Check. The Australian Population Based Screening Framework was developed to “inform decision-makers on the key issues to be considered when assessing potential screening programs in Australia”.(10) As the Framework is specific to population-based, rather than high-risk, screening programs, there is a lack of clarity about transferability of criteria. However, the Framework criteria do stipulate that a screening program must be acceptable to “important subgroups such as target participants who are from culturally and linguistically diverse backgrounds, Aboriginal and Torres Strait Islander people, people from disadvantaged groups and people with a disability”.(10) An extensive search of the literature highlighted that there is very little information about the acceptability of LDCT screening to these population groups in Australia. Yet they are part of the high-risk population.(10) There are also considerable gaps in the evidence about the cost-effectiveness of LDCT screening in different settings, including Australia. The evidence base in this area is rapidly evolving and is likely to include new data from the NELSON trial and incorporate data about the costs of targeted- and immuno-therapies as these treatments become more widely available in Australia.