Operational challenges and collaborative solutions in radiology image interpretation: perspectives from imaging departments in a low-resource setting.

INTRODUCTION: Medical imaging's critical role in diagnosis requires prompt and precise image interpretation. Numerous radiology departments, especially in low-resourced settings, encounter challenges such as a shortage of radiologists in their operational setup. This study explored the perceptions of radiographers and radiologists from low-resourced departments in a single country regarding operational challenges and potential solutions in image interpretation. METHODS: A qualitative approach was utilised, involving heads of departments, senior radiographers, and radiologists with a minimum of 5 years of experience, from three major state referral hospitals. Face-to-face, semi-structured interviews were conducted in November 2022, using an interview guide that included questions on the challenges encountered during image interpretation and the proposed solutions. Data analysis was conducted using Atlas.ti version 9.0, following the four-step content analysis method. All participants willingly provided consent to participate in the study. RESULTS: Ten participants, comprising two radiologists and eight radiographers participated in the study. The research identified three main themes: image interpretation pathways, image interpretation operational challenges and proposed solutions for image interpretation. In addition, a total of 10 subthemes were generated from the three main themes. CONCLUSION: The study revealed critical challenges and the need to explore the formal inclusion of radiographers in image interpretation, as a way to improve efficiency. However, a comprehensive assessment of the image interpretation system, encompassing radiographers' knowledge and competence, is recommended for context-specific, empirical-based modifications to enhance service provision.

Setting epidemiological cut-off values relevant to MIC and disc diffusion data for Aeromonas salmonicida generated by a standard method.

The Clinical and Laboratory Standards Institute has published epidemiological cut-off values for susceptibility data generated at 22°°C and read after 44-48 h for florfenicol, oxolinic acid and oxytetracycline against Aeromonas salmonicida. The cut-off values for the minimum inhibitory concentration (MIC) and disc diffusion were derived from data obtained by 1 laboratory and 2 laboratories respectively. The present work reports the generation of susceptibility data from additional laboratories and the calculation of provisional cut-off values from aggregations of these data with previously published data. With respect to MIC data, the provisional cut-off values, derived from aggregations of the data from 4 laboratories, were ≤4 µg ml-1 for florfenicol, ≤0.0625 µg ml-1 for oxolinic acid and ≤1 µg ml-1 for oxytetracycline. For disc diffusion data, the provisional cut-off values derived from aggregations of the data from 5 laboratories were ≥30 mm for florfenicol, ≥32 mm for oxolinic acid and ≥25 mm for oxytetracycline. In addition, a cut-off value of ≥29 mm for ampicillin was derived from the aggregation of data from 4 laboratories.

Associations of state and chronic loneliness with interpretation bias: The role of internalizing symptoms.

Loneliness is common and, while generally transient, persists in up to 22% of the population. The rising prevalence and adverse impacts of chronic loneliness highlight the need to understand its underlying mechanisms. Evolutionary models of loneliness suggest that chronically lonely individuals demonstrate negative interpretation biases towards social information. It may also be that such biases are exacerbated by momentary increases in state loneliness, or elevated anxiety or depression. Yet, little research has tested these possibilities. The current study aimed to advance understandings of loneliness by examining associations of chronic loneliness with individual differences in negative interpretation bias for social (relative to non-social) stimuli, and testing whether these associations change in the context of increased state loneliness and current levels of anxiety and depressive symptoms. These aims were explored in 591 participants who completed an interpretation bias task before and after undergoing a state loneliness induction. Participants also self-reported chronic loneliness, anxiety, and depression. Linear mixed models indicated that only state (but not chronic) loneliness was associated with more positive interpretations of non-social stimuli, with greater anxiety and depressive symptoms predicting more negative interpretations. Implications of these findings for present theoretical models of loneliness are discussed.

MFS-DBF: A trustworthy multichannel feature sieve and decision boundary formulation system for Obstructive Sleep Apnea detection.

The fine identification of sleep apnea events is instrumental in Obstructive Sleep Apnea (OSA) diagnosis. The development of sleep apnea event detection algorithms based on polysomnography is becoming a research hotspot in medical signal processing. In this paper, we propose an Inverse-Projection based Visualization System (IPVS) for sleep apnea event detection algorithms. The IPVS consists of a feature dimensionality reduction module and a feature reconstruction module. First, features of blood oxygen saturation and nasal airflow are extracted and used as input data for event analysis. Then, visual analysis is conducted on the feature distribution for apnea events. Next, dimensionality reduction and reconstruction methods are combined to achieve the dynamic visualization of sleep apnea event feature sets and the visual analysis of classifier decision boundaries. Moreover, the decision-making consistency is explored for various sleep apnea event detection classifiers, which provides researchers and users with an intuitive understanding of the detection algorithm. We applied the IPVS to an OSA detection algorithm with an accuracy of 84% and a diagnostic accuracy of 92% on a publicly available dataset. The experimental results show that the consistency between our visualization results and prior medical knowledge provides strong evidence for the practicality of the proposed system. For clinical practice, the IPVS can guide users to focus on samples with higher uncertainty presented by the OSA detection algorithm, reducing the workload and improving the efficiency of clinical diagnosis, which in turn increases the value of trust.

A novel way to prospectively evaluate of AI-enhanced ECG algorithms.

Significant strides will be made in the field of computerized electrocardiology through the development of artificial intelligence (AI)-enhanced ECG (AI-ECG) algorithms. Yet, the scientific discourse has primarily relied upon on retrospective analyses for deriving and externally validating AI-ECG classification algorithms, an approach that fails to fully judge their real-world effectiveness or reveal potential unintended consequences. Prospective trials and analyses of AI-ECG algorithms will be crucial for assessing real-world diagnostic scenarios and understanding their practical utility and degree influence they confer onto clinicians. However, conducting such studies is challenging due to their resource-intensive nature and associated technical and logistical hurdles. To overcome these challenges, we propose an innovative approach to assess AI-ECG algorithms using a virtual testing environment. This strategy can yield critical insights into the practical utility and clinical implications of novel AI-ECG algorithms. Moreover, such an approach can enable an assessment of the influence of AI-ECG algorithms have their users. Herein, we outline a proposed randomized control trial for evaluating the diagnostic efficacy of new AI-ECG algorithm(s) specifically designed to differentiate between wide complex tachycardias into ventricular tachycardia and supraventricular wide complex tachycardia.

Top Ten Tips Palliative Care Clinicians Should Know About Interpreting a Clinical Trial.

Evidence-based practice is foundational to high-quality palliative care delivery. However, the clinical trials that compose the evidence base are often methodologically imperfect. Applying their conclusions without critical application to the clinical practice context can harm patients. The tips provided can help clinicians infer judiciously from clinical trial results and avoid credulously accepting findings without critique. We suggest that statistical and mathematical expertise is unnecessary, but rather a keen curiosity about investigators' rationale for certain design choices and how these choices can affect results is key. For a more comprehensive understanding of clinical trials, this article can be used with the authors' corresponding ten tips article that focuses on designing a clinical trial.

Giving Back What the Patient Brings: On Winnicott's "Mirror-Role of Mother and Family in Child Development".

The author offers a creative reading of Winnicott's (1967) "Mirror-role of mother and family in child development." Winnicott presents the idea that a pivotal experience in the process of the infant's coming into being as himself is the mother's communicating to the infant, by the look in her eyes, what she sees there when she looks at him. In the absence of the experience of being seen, the infant's capacity to feel real and alive atrophies. The author fleshes out Winnicott's thinking by suggesting that just as the infant comes more fully into being as he sees himself in his mother's eyes, so too, the mother comes more fully into being as a mother as she sees herself in the infant's eyes. The paradigm shift that Winnicott has contributed to psychoanalysis is reflected in the clinical work he presents: (1) the goal of psychoanalysis is no longer the enrichment of the patient's self-understanding; rather, the analytic goal is the patient's coming more fully alive to himself; and (2) the analyst helps the patient achieve this end not by making astute interpretations but by allowing the patient to experience the pleasure of making discoveries of his or her own.

"Not everything that can be counted counts" in ethanol toxicological results: an antemortem and postmortem technical interpretation focusing on driving under the influence.

Ethanol blood analysis is the most common request in forensic toxicology, and some studies point to positive results in approximately one-third of all unnatural deaths. However, distinguishing sober deaths from drunk deaths is not as simple as it may seem. This technical, clinical, and forensic interpretation is proposed to interpret the ethanol toxicological results, discussing several artefacts and pitfalls that must be considered, namely focusing on driving under the influence. This work is presented with a practical and objective approach, aiming to alleviate the complexities associated with clinical, physiological, pathophysiological, and toxicological aspects to enhance comprehension, practicality, and applicability of its content, especially to courts. Particularly the physical integrity of the body, the postmortem interval, putrefactive signs, anatomic place of blood collection, alternative samples such as vitreous humour and urine, the possibility of postmortem redistribution, the inclusion of preservatives in containers, and optimal temperature conditions of shipment are among some of the aspects to pay attention. Although several biomarkers related to postmortem microbial ethanol production have been proposed, their translation into forensic routine is slow to be implemented due to the uncertainties of their application and analytical difficulties. Specifically, in the interpretation of ethanol toxicological results, "not everything that can be counted counts and not everything that counts can be counted" (attributed to Albert Einstein).

Evidence on sulfadoxine-pyrimethamine resistance molecular markers from India: interpret with caution.

BACKGROUND: Sulfadoxine-pyrimethamine (SP), as a partner to artesunate as ACT is the treatment of choice for uncomplicated P. falciparum infections in the majority of India and SP-resistance has a potential to lead to ACT failure. In the lack of robust surveillance of therapeutic efficacy of SP, validate molecular markers of SP-resistance offer a hint of failing SP. However, studies reporting these validated markers often suffer from certain pitfalls that warrant a careful interpretation. MAIN BODY: Critical analyses of the results and their reported interpretations from a recent study and other studies conducted on the WHO-validated molecular markers of SP-resistance in India were analysed and the main problems with studying and reporting of these markers are presented here. It was noted that almost all studies analysed flawed either on the usage, estimation and/or interpretation of the standardized classification of the studies SP mutations. These flaws not only impart spatiotemporal incomparability of the published data but also have the potential of being misunderstood and wrongly translated. CONCLUSION: Based on this universal problem in studying, reporting and interpreting the data from the studies on molecular markers of SP-resistance, it is stressed that the future studies should be conducted with utmost caution so that robust evidence may be generated and correctly translated to policy.

Revisiting the Electrochemical Impedance Spectroscopy of Porous Electrodes in Li-ion Batteries by Employing Reference Electrode.

Electrochemical impedance spectroscopy (EIS), characterized by its non-destructive and in-situ nature, plays a crucial role in comprehending the thermodynamic and kinetic processes occurring with Li-ion batteries. However, there is a lack of consistent and coherent physical interpretations for the EIS of porous electrodes. Therefore, it is imperative to conduct thorough investigations into the underlying physical mechanisms of EIS. Herein, by employing reference electrode in batteries, we revisit the associated physical interpretation of EIS at different frequency. Combining different battery configurations, temperature-dependent experiments, and elaborated distribution of relaxation time analysis, we find that the ion transport in porous electrode channels and pseudo-capacitance behavior dominate the high-frequency and mid-frequency impedance arcs, respectively. This work offers a perspective for the physical interpretation of EIS and also sheds light on the understanding of EIS characteristics in other advanced energy storage systems.

Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors.

Background: Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb). Results: The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past 25 years, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 186 VIPs, resulting in a total of 403 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods. Conclusions: VIPdb version 2 summarizes 403 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. Availability: VIPdb version 2 is available at https://genomeinterpretation.org/vipdb.

Pulmonary Function Tests: Easy Interpretation in Three Steps.

Pulmonary function tests (PFTs) are pivotal in diagnosing and managing a broad spectrum of respiratory disorders. These tests provide critical insights into lung health, guiding diagnoses, assessing disease severity, and shaping patient management strategies. This review addresses the complexities and nuances inherent in interpreting PFT data, particularly in light of recent updates from the European Respiratory Society (ERS) and American Thoracic Society (ATS). These updates have refined interpretive strategies, moving away from definitive diagnostic uses of spirometry to a more probabilistic approach that better accounts for individual variability through the use of Z-scores and lower limits of normal (LLNs). Significantly, this narrative review delves into the philosophical shift in spirometry interpretation, highlighting the transition from direct clinical diagnostics to a more nuanced evaluation geared towards determining the likelihood of disease. It critiques the reliance on fixed ratios and emphasizes the need for reference values that consider demographic variables such as age, sex, height, and ethnicity, in line with the latest Global Lung Function Initiative (GLI) equations. Despite these advances, challenges remain in ensuring uniformity across different predictive models and reference equations, which can affect the accuracy and consistency of interpretations. This paper proposes a streamlined three-step framework for interpreting PFTs, aiming to unify and simplify the process to enhance clarity and reliability across various medical specialties. This approach not only aids in accurate patient assessments but also mitigates the potential for misdiagnosis and ensures more effective patient management. By synthesizing contemporary guidelines and integrating robust physiological principles, this review fosters a standardized yet flexible approach to PFT interpretation that is both scientifically sound and practically feasible.

Mudskipper detects combinatorial RNA binding protein interactions in multiplexed CLIP data.

The uncovering of protein-RNA interactions enables a deeper understanding of RNA processing. Recent multiplexed crosslinking and immunoprecipitation (CLIP) technologies such as antibody-barcoded eCLIP (ABC) dramatically increase the throughput of mapping RNA binding protein (RBP) binding sites. However, multiplex CLIP datasets are multivariate, and each RBP suffers non-uniform signal-to-noise ratio. To address this, we developed Mudskipper, a versatile computational suite comprising two components: a Dirichlet multinomial mixture model to account for the multivariate nature of ABC datasets and a softmasking approach that identifies and removes non-specific protein-RNA interactions in RBPs with low signal-to-noise ratio. Mudskipper demonstrates superior precision and recall over existing tools on multiplex datasets and supports analysis of repetitive elements and small non-coding RNAs. Our findings unravel splicing outcomes and variant-associated disruptions, enabling higher-throughput investigations into diseases and regulation mediated by RBPs.

Machine learning predicts emergency physician specialties from treatment strategies for patients suspected of myocardial infarction.

BACKGROUND: Our investigation aimed to determine how the diverse backgrounds and medical specialties of emergency physicians (Eps) influence the accuracy of diagnoses and the subsequent treatment pathways for patients presenting preclinically with MI symptoms. By scrutinizing the relationships between EPs' specialties and their approaches to patient care, we aimed to unveil potential variances in diagnostic accuracy and treatment choices. METHODS: In this retrospective, monocenter cohort study, we leveraged machine learning techniques to analyze a comprehensive dataset of 2328 patients with suspected MI, encompassing preclinical diagnoses, electrocardiogram (ECG) interpretations, and subsequent treatment strategies by attending EPs. RESULTS: We demonstrated that diagnosis and treatment patterns of different specialties were distinct enough, that machine learning (ML) was able to differentiate between specialties (maximum area under the receiver operating characteristic = 0.80 for general medicine and 0.80 for surgery). In our study, internist demonstrated the highest accuracy for preclinical identification of STEMI (0.96) whereas surgeons showed the highest accuracy for identifying NSTEMI. Our findings highlight significant correlations between EP specialties and the accuracy of both preclinical diagnoses and subsequent treatment pathways for patients with suspected MI. CONCLUSIONS: Our results offer valuable insights into how the diverse backgrounds and specialties of EPs can influence the optimization of patient care in emergency settings. Understanding these patterns can help in the development of tailored training programs and protocols to enhance diagnostic accuracy and treatment efficacy in emergency cardiac care, ultimately optimizing patient treatment and improving outcomes.

Consequences of Data Loss on Clinical Decision-Making in Continuous Glucose Monitoring: Retrospective Cohort Study.

BACKGROUND: The impact of missing data on individual continuous glucose monitoring (CGM) data is unknown but can influence clinical decision-making for patients. OBJECTIVE: We aimed to investigate the consequences of data loss on glucose metrics in individual patient recordings from continuous glucose monitors and assess its implications on clinical decision-making. METHODS: The CGM data were collected from patients with type 1 and 2 diabetes using the FreeStyle Libre sensor (Abbott Diabetes Care). We selected 7-28 days of 24 hours of continuous data without any missing values from each individual patient. To mimic real-world data loss, missing data ranging from 5% to 50% were introduced into the data set. From this modified data set, clinical metrics including time below range (TBR), TBR level 2 (TBR2), and other common glucose metrics were calculated in the data sets with and that without data loss. Recordings in which glucose metrics deviated relevantly due to data loss, as determined by clinical experts, were defined as expert panel boundary error (εEPB). These errors were expressed as a percentage of the total number of recordings. The errors for the recordings with glucose management indicator <53 mmol/mol were investigated. RESULTS: A total of 84 patients contributed to 798 recordings over 28 days. With 5%-50% data loss for 7-28 days recordings, the εEPB varied from 0 out of 798 (0.0%) to 147 out of 736 (20.0%) for TBR and 0 out of 612 (0.0%) to 22 out of 408 (5.4%) recordings for TBR2. In the case of 14-day recordings, TBR and TBR2 episodes completely disappeared due to 30% data loss in 2 out of 786 (0.3%) and 32 out of 522 (6.1%) of the cases, respectively. However, the initial values of the disappeared TBR and TBR2 were relatively small (<0.1%). In the recordings with glucose management indicator <53 mmol/mol the εEPB was 9.6% for 14 days with 30% data loss. CONCLUSIONS: With a maximum of 30% data loss in 14-day CGM recordings, there is minimal impact of missing data on the clinical interpretation of various glucose metrics. TRIAL REGISTRATION: ClinicalTrials.gov NCT05584293; https://clinicaltrials.gov/study/NCT05584293.

pECGreview: Assessment of a Novel Tool to Evaluate the Accuracy of Pediatric ECG Interpretation Skills.

The skill of interpretation of the electrocardiogram (ECG) remains poor despite existing educational initiatives. We sought to evaluate the validity of using a subjective scoring system to assess the accuracy of ECG interpretations submitted by pediatric cardiology fellows, trainees, and faculty to the Pediatric ECG Review (pECGreview), a web-based ECG interpretation training program. We conducted a retrospective, cross-sectional study of responses submitted to pECGreview. ECG interpretations were assessed independently by four individuals with a range of experience. Accuracy was assessed using a 3-point scale: 100% for generally correct interpretations, 50% for over- or underdiagnosis of minor ECG abnormalities, and 0% for over- or underdiagnosis of major ECG abnormalities. Inter-rater agreement was assessed using expanded Bland-Altman plots, Pearson correlation coefficients, and Intraclass Correlation Coefficients (ICC). 1460 ECG interpretations by 192 participants were analyzed. 107 participants interpreted at least five ECGs. The mean accuracy score was 76.6 ± 13.7%. Participants were correct in 66.1 ± 5.1%, had minor over- or underdiagnosis in 21.5 ± 4.6% and major over- or underdiagnosis in 12.3 ± 3.9% of interpretations. Validation of agreement between evaluators demonstrated limits of agreement of 11.3%. Inter-rater agreement exhibited consistent patterns (all correlations ≥ 0.75). Absolute agreement was 0.74 (95% CI 0.69-0.80), and average measures agreement was 0.92 (95% CI 0.89-0.94). Accuracy score analysis of as few as five ECG interpretations submitted to pECGreview yielded good inter-rater reliability for assessing and ranking ECG interpretation skills in pediatric cardiology fellows in training.

Patient-authored medical record II: A not-knowing approach to psychiatric nursing.

A patient-authored medical record (PAMR) is a narrative-based prescription that is written by a psychiatric patient with help from a nurse. It is a tool specifically designed and developed for psychiatric nursing. We have reported its notable therapeutic effects for Japanese patients and found that the patients had accurate views of how to improve their illness. The present paper, which broadens the scope of this examination, includes the entire process of using this tool, including both patient-authored medical records and follow-up dialogue. We aim to demonstrate how a patient's potentials are leveraged and expanded through the interpretation of such texts through dialogue, in which interpretation takes the form of a conversational question based on not-knowing. Follow-up meetings facilitate the therapeutic process and team collaboration for patients, medical staff, and families. We also reaffirm the soundness and legitimacy of psychiatric patients writing their own prescription with help from a nurse.

Ventricular Fibrillation Arrest Triggered by Antiemetics Revealing an Underlying Long QT Syndrome in a Young Woman.

Undiagnosed phenomena such as long QT syndrome can have devastating effects on patients. Our case, involving a woman in her 30s, highlights the serious effects of undiagnosed long QT and how antiemetic medications can precipitate cardiac events that can lead to fatalities. Various medications are known to prolong QT intervals, and clinicians must be aware of the side effects of some of these commonly used medications. While survival was achieved in this case, education and reflection can act as a tool to help improve global standards of care in this subgroup of the population.

The physical basis of analog-to-digital signal processing in the EGFR system-Delving into the role of the endoplasmic reticulum.

Receptor tyrosine kinases exhibit ligand-induced activity and uptake into cells via endocytosis. In the case of epidermal growth factor (EGF) receptor (EGFR), the resulting endosomes are trafficked to the perinuclear region, where dephosphorylation of receptors occurs, which are subsequently directed to degradation. Traveling endosomes bearing phosphorylated EGFRs are subjected to the activity of cytoplasmic phosphatases as well as interactions with the endoplasmic reticulum (ER). The peri-nuclear region harbors ER-embedded phosphatases, a component of the EGFR-bearing endosome-ER contact site. The ER is also emerging as a central player in spatiotemporal control of endosomal motility, positioning, tubulation, and fission. Past studies strongly suggest that the physical interaction between the ER and endosomes forms a reaction "unit" for EGFR dephosphorylation. Independently, endosomes have been implicated to enable quantization of EGFR signals by modulation of the phosphorylation levels. Here, we review the distinct mechanisms by which endosomes form the logistical means for signal quantization and speculate on the role of the ER.