Identifying Facilitators and Inhibitors of Shared Understanding: An Ethnography of Diagnosis Communication in Acute Medical Settings.

BACKGROUND AND AIMS: Communication is important in determining how patients understand the diagnostic process. Empirical studies involving direct observation of communication within diagnostic processes are relatively limited. This ethnographic study aimed to identify communicative practices facilitating or inhibiting shared understanding between patients and doctors in UK acute secondary care settings. METHODS: Data were collected in acute medical sectors of three English hospitals. Researchers observed doctors as they assessed patients; semistructured interviews were undertaken with doctors and patients directly afterwards. Patients were also interviewed 2-4 weeks later. Case studies of individual encounters (consisting of these interviews and observational notes) were created, and were cross-examined by an interdisciplinary team to identify divergence and convergence between doctors' and patients' narratives. These data were analysed thematically. RESULTS: We conducted 228 h of observation, 24 doctor interviews, 32 patient interviews and 15 patient follow-up interviews. Doctors varied in their communication. Patient diagnostic understanding was sometimes misaligned with that of their doctors; interviews revealed that they often made incorrect assumptions to make sense of the fragmented information received. Thematic analysis identified communicative practices that seemed to facilitate, or inhibit, shared diagnostic understanding between patient and doctor, revealing three themes: (1) communicating what has been understood from the medical record, (2) sharing the thought process and diagnostic reasoning and (3) closing the loop and discharge communication. Shared understanding was best fostered by clear communication about the diagnostic process, what had already been done and what was achievable in acute settings. Written information presents an underutilised tool in such communication. CONCLUSIONS: In UK acute secondary settings, the provision of more information about the diagnostic process often fostered shared understanding between doctor and patient, helping to minimise the confusion and dissatisfaction that can result from misaligned expectations or conclusions about the diagnosis, and the uncertainty therein. PATIENT/PUBLIC CONTRIBUTION: A patient and public involvement group (of a range of ages and backgrounds) was consulted. They contributed to the design of the protocol, including the timing of interviews, the acceptability of a follow-up telephone interview, the development of the interview guides and the participant information sheets.

Diagnosis: What Is the Structure of Its Reasoning?

How does the diagnosis process work? This essay traces the philosophical underpinnings of diagnosis from Hume through Kant, Peirce, and Popper, analyzing how pathologists amalgamate sensibility, intuition, and imagination to form new hypotheses that can be tested by evidence and experience.

[The multi-professional alliance in the diagnostic process]. / L'alliance pluriprofessionnelle dans la démarche diagnostique.

Professional support for elderly people suffering from cognitive impairment needs to be comprehensive, and requires the active involvement of a wide range of professionals. Two clinical cases show how the combined support of a therapeutic day-care center and medical specialists can improve the quality of life of patients and their families, by helping to refine diagnoses or adjust treatment.

How to Critically Appraise and Interpret Systematic Reviews and Meta-Analyses of Diagnostic Accuracy: A User Guide.

Systematic reviews of diagnostic accuracy studies can provide the best available evidence to inform decisions regarding the use of a diagnostic test. In this guide, the authors provide a practical approach for clinicians to appraise diagnostic accuracy systematic reviews and apply their results to patient care. The first step is to identify an appropriate systematic review with a research question matching the clinical scenario. The user should evaluate the rigor of the review methods to evaluate its credibility (Did the review use clearly defined eligibility criteria, a comprehensive search strategy, structured data collection, risk of bias and applicability appraisal, and appropriate meta-analysis methods?). If the review is credible, the next step is to decide whether the diagnostic performance is adequate for clinical use (Do sensitivity and specificity estimates exceed the threshold that makes them useful in clinical practice? Are these estimates sufficiently precise? Is variability in the estimates of diagnostic accuracy across studies explained?). Diagnostic accuracy systematic reviews that are judged to be credible and provide diagnostic accuracy estimates with sufficient certainty and relevance are the most useful to inform patient care. This review discusses comparative, noncomparative, and emerging approaches to systematic reviews of diagnostic accuracy using a clinical scenario and examples based on recent publications.

Principles of ideal diagnostic regulation and the IVDR.

This article discusses principles and concepts for ideal regulatory frameworks for diagnostics, and the expression of those principles in the EU IVDR. The authors present the benefits of regulatory frameworks and implementation approaches for diagnostics that are risk-based, globally convergent, connected, nimble and efficient, under the IVDR and with a future outlook. While many expressions of these principles can already be found in the EU IVDR text, and in its implementation approaches, their further embrace is needed in future EU diagnostic regulation. In the long term outlook, risk-based approaches can be extended to comprise entity-based excellence appraisals. Globally convergent approaches can be more explicit in e.g. qualification and classification of products. This will also help further reliance models. Better connections and cooperation between regulators across the healthcare spectrum including pharmaceuticals should be fostered. Nimble approaches such as Emergency Use Authorisations for pandemics are essential in highly regulated schemes like the IVDR and beyond. Finally, regulatory efficiency as in timely availability of IT infrastructure and oversight mechanisms is a distinguishing attribute of globally competitive diagnostic regulatory schemes. All the above needs consideration in the long term efforts to modernize the EU regulatory system, so that diagnostics can play their important role in clinical research as well as along the entire care continuum in the EU.

Development and evaluation of a customized checklist to assess the quality control of disease registry systems of Tehran, the capital of Iran in 2021.

BACKGROUND: Clinical registries facilitate medical research by providing 'real data'. In the past decade, an increasing number of disease registry systems (DRS) have been initiated in Iran. Here, we assessed the quality control (QC) of the data recorded in the DRS established by Shahid Beheshti University of Medical Sciences in Tehran, the capital city of Iran, in 2021. METHODS: The present study was conducted in two consecutive qualitative and quantitative phases and employed a mixed-method design. A checklist containing 23 questions was developed based on a consensus reached following several panel group discussions, whose face content and construct validities were confirmed. Cronbach's alpha was calculated to verify the tool's internal consistency. Overall, the QC of 49 DRS was assessed in six dimensions, including completeness, timeliness, accessibility, validity, comparability, and interpretability. The seventy percent of the mean score was considered a cut-point for desirable domains. RESULTS: The total content validity index (CVI) was obtained as 0.79, which is a reasonable level. Cronbach's alpha coefficients obtained showed acceptable internal consistency for all of the six QC domains. The data recorded in the registries included different aspects of diagnosis/treatment (81.6%) and treatment quality requirements outcomes (12.2%). According to the acceptable quality cut-point, out of 49 evaluated registries, 48(98%), 46(94%), 41(84%), and 38(77.5%), fulfilled desirable quality scores in terms of interpretability, accessibility, completeness, and comparability, however, 36(73.5%) and 32(65.3%) of registries obtained the quality requirement for timeliness and validity, respectively. CONCLUSION: The checklist developed here, containing customized questions to assess six QC domains of DRSs, provided a valid and reliable tool that could be considered as a proof-of-concept for future investigations. The clinical data available in the studied DRSs fulfilled desirable levels in terms of interpretability, accessibility, comparability, and completeness; however, timeliness and validity of these registries needed to be improved.

Improving rural health care reduces illegal logging and conserves carbon in a tropical forest.

Tropical forest loss currently exceeds forest gain, leading to a net greenhouse gas emission that exacerbates global climate change. This has sparked scientific debate on how to achieve natural climate solutions. Central to this debate is whether sustainably managing forests and protected areas will deliver global climate mitigation benefits, while ensuring local peoples' health and well-being. Here, we evaluate the 10-y impact of a human-centered solution to achieve natural climate mitigation through reductions in illegal logging in rural Borneo: an intervention aimed at expanding health care access and use for communities living near a national park, with clinic discounts offsetting costs historically met through illegal logging. Conservation, education, and alternative livelihood programs were also offered. We hypothesized that this would lead to improved health and well-being, while also alleviating illegal logging activity within the protected forest. We estimated that 27.4 km2 of deforestation was averted in the national park over a decade (∼70% reduction in deforestation compared to a synthetic control, permuted P = 0.038). Concurrently, the intervention provided health care access to more than 28,400 unique patients, with clinic usage and patient visitation frequency highest in communities participating in the intervention. Finally, we observed a dose-response in forest change rate to intervention engagement (person-contacts with intervention activities) across communities bordering the park: The greatest logging reductions were adjacent to the most highly engaged villages. Results suggest that this community-derived solution simultaneously improved health care access for local and indigenous communities and sustainably conserved carbon stocks in a protected tropical forest.

A universal diagnosis syntax.

BACKGROUND: Diagnoses are crucial assets of clinical work and provide the foundation for treatment and follow up. They should be informative and customized to the patient's problem. Common prefixes, morphemes, and suffixes may aid the implementation of expressions that generate diagnoses. RESULTS: Apt choices of symbols plays a major role in science. In this study, the variables e, o, and p are assigned to names of an etiological agent, a disorder, and a pathogenetic mechanism, respectively. The suffix -itis designates infections, allergies, inflammation, and/or immune reactions. Diagnoses (d) are generated by the formula d:= e&o&p where '&' means concatenation and ':= ' means assignment. Thus, with e:= 'Staphylococcus aureus ', o:= 'endocard', and p:= 'itis', d:= e&o&p generates the diagnosis d = 'Staphylococcus aureus endocarditis'. Diagnoses formed this way comply with common clinical diagnoses. Certain extensions generate complete, systematic medical diagnoses that are applicable to all medical specialties. For example, common medical prefixes, morphemes, and suffixes give rise to o = 'hypothyroidism', o = 'tachycardia', and o = 'hypophagocytosis'. The formula scales well with the developments in clinical medicine, systems biology, molecular biology, and microbiology. The diagnosis generating formula d:= e&o&p requires meticulous analysis of the components of diagnoses plus the introduction of appropriate variables and terms. Terms partition on established clinical categories and adhere to established clinical nomenclature. The syntax generates universal medical diagnoses. CONCLUSIONS: The present study concerns a universal diagnosis syntax (UDS) that generates diagnoses using the formula d:= e&o&p with several extensions described in the study. The formula is easy to learn and covers diagnoses in all medical specialties. The present work succeeded in creating diagnoses from the formula. The fundamental insight is that no matter how complicated a diagnosis is it can be generated by a systematic process, which adds terms one by one. UDS may have implications for medical education and classifications. The formula lays a foundation for structured clinical decision-making. Formulas are hallmarks of hard science. So, d:= e&o&p anticipates a scientific medical revolution.

Measuring the Impact of AI in the Diagnosis of Hospitalized Patients: A Randomized Clinical Vignette Survey Study.

Importance: Artificial intelligence (AI) could support clinicians when diagnosing hospitalized patients; however, systematic bias in AI models could worsen clinician diagnostic accuracy. Recent regulatory guidance has called for AI models to include explanations to mitigate errors made by models, but the effectiveness of this strategy has not been established. Objectives: To evaluate the impact of systematically biased AI on clinician diagnostic accuracy and to determine if image-based AI model explanations can mitigate model errors. Design, Setting, and Participants: Randomized clinical vignette survey study administered between April 2022 and January 2023 across 13 US states involving hospitalist physicians, nurse practitioners, and physician assistants. Interventions: Clinicians were shown 9 clinical vignettes of patients hospitalized with acute respiratory failure, including their presenting symptoms, physical examination, laboratory results, and chest radiographs. Clinicians were then asked to determine the likelihood of pneumonia, heart failure, or chronic obstructive pulmonary disease as the underlying cause(s) of each patient's acute respiratory failure. To establish baseline diagnostic accuracy, clinicians were shown 2 vignettes without AI model input. Clinicians were then randomized to see 6 vignettes with AI model input with or without AI model explanations. Among these 6 vignettes, 3 vignettes included standard-model predictions, and 3 vignettes included systematically biased model predictions. Main Outcomes and Measures: Clinician diagnostic accuracy for pneumonia, heart failure, and chronic obstructive pulmonary disease. Results: Median participant age was 34 years (IQR, 31-39) and 241 (57.7%) were female. Four hundred fifty-seven clinicians were randomized and completed at least 1 vignette, with 231 randomized to AI model predictions without explanations, and 226 randomized to AI model predictions with explanations. Clinicians' baseline diagnostic accuracy was 73.0% (95% CI, 68.3% to 77.8%) for the 3 diagnoses. When shown a standard AI model without explanations, clinician accuracy increased over baseline by 2.9 percentage points (95% CI, 0.5 to 5.2) and by 4.4 percentage points (95% CI, 2.0 to 6.9) when clinicians were also shown AI model explanations. Systematically biased AI model predictions decreased clinician accuracy by 11.3 percentage points (95% CI, 7.2 to 15.5) compared with baseline and providing biased AI model predictions with explanations decreased clinician accuracy by 9.1 percentage points (95% CI, 4.9 to 13.2) compared with baseline, representing a nonsignificant improvement of 2.3 percentage points (95% CI, -2.7 to 7.2) compared with the systematically biased AI model. Conclusions and Relevance: Although standard AI models improve diagnostic accuracy, systematically biased AI models reduced diagnostic accuracy, and commonly used image-based AI model explanations did not mitigate this harmful effect. Trial Registration: ClinicalTrials.gov Identifier: NCT06098950.

On the Ethics of Withholding and Withdrawing Unwarranted Diagnoses.

The number of diagnoses and the number of persons having diagnoses have increased substantially, and studies indicate that diagnoses are given or upheld even if they are unwarranted, that is, that they do not satisfy professionally accepted diagnostic criteria. In this article, the authors investigate the ethics of withholding and withdrawing unwarranted diagnoses. First, they investigate ethical aspects that make it difficult to withhold and to withdraw such diagnoses. Second, they scrutinize whether there are psychological factors, both in persons/patients and healthcare professionals, making it difficult to withdraw and withhold unwarranted diagnoses. Lastly, they use recent elements of the withholding-versus-withdrawing treatment debate in medical ethics to investigate whether there are any differences between withholding and withdrawing treatment and withdrawing and withholding unwarranted diagnoses. The authors conclude that it is crucial to acknowledge and address all these issues to reduce and avoid unwarranted diagnoses.

A multi-objective optimization method for identification of module biomarkers for disease diagnosis.

Biomarker identification aims at finding a set of biological indicators that best discriminate biological samples of different phenotypes. In this paper, we take the module containing the significant disease-related genes and their interactions from biological networks as a module biomarker, and propose an evolutionary multi-objective optimization method to identify module biomarkers for disease diagnosis. To be specific, we take the classification accuracy on control and disease samples, the association with disease and the intra-link density in the module as the optimization objectives. To achieve the best performance, a novel population initiation strategy is tailored to generate dense-connected initial solutions, and a specific population update strategy is employed to direct the evolution towards the global optimums with abundant diversity. Experimental results show that our method outperforms the previous state-of-the-art disease diagnosis methods. Meantime, the detected biomarker module can reflect the basic and significant biological functions and has a great correlation with a disease phenotype.

QUADAS-C: A Tool for Assessing Risk of Bias in Comparative Diagnostic Accuracy Studies.

Comparative diagnostic test accuracy studies assess and compare the accuracy of 2 or more tests in the same study. Although these studies have the potential to yield reliable evidence regarding comparative accuracy, shortcomings in the design, conduct, and analysis may bias their results. The currently recommended quality assessment tool for diagnostic test accuracy studies, QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2), is not designed for the assessment of test comparisons. The QUADAS-C (Quality Assessment of Diagnostic Accuracy Studies-Comparative) tool was developed as an extension of QUADAS-2 to assess the risk of bias in comparative diagnostic test accuracy studies. Through a 4-round Delphi study involving 24 international experts in test evaluation and a face-to-face consensus meeting, an initial version of the tool was developed that was revised and finalized following a pilot study among potential users. The QUADAS-C tool retains the same 4-domain structure of QUADAS-2 (Patient Selection, Index Test, Reference Standard, and Flow and Timing) and comprises additional questions to each QUADAS-2 domain. A risk-of-bias judgment for comparative accuracy requires a risk-of-bias judgment for the accuracy of each test (resulting from QUADAS-2) and additional criteria specific to test comparisons. Examples of such additional criteria include whether participants either received all index tests or were randomly assigned to index tests, and whether index tests were interpreted with blinding to the results of other index tests. The QUADAS-C tool will be useful for systematic reviews of diagnostic test accuracy addressing comparative questions. Furthermore, researchers may use this tool to identify and avoid risk of bias when designing a comparative diagnostic test accuracy study.

Rapid screening of engineered microbial therapies in a 3D multicellular model.

Synthetic biology is transforming therapeutic paradigms by engineering living cells and microbes to intelligently sense and respond to diseases including inflammation, infections, metabolic disorders, and cancer. However, the ability to rapidly engineer new therapies far outpaces the throughput of animal-based testing regimes, creating a major bottleneck for clinical translation. In vitro approaches to address this challenge have been limited in scalability and broad applicability. Here, we present a bacteria-in-spheroid coculture (BSCC) platform that simultaneously tests host species, therapeutic payloads, and synthetic gene circuits of engineered bacteria within multicellular spheroids over a timescale of weeks. Long-term monitoring of bacterial dynamics and disease progression enables quantitative comparison of critical therapeutic parameters such as efficacy and biocontainment. Specifically, we screen Salmonella typhimurium strains expressing and delivering a library of antitumor therapeutic molecules via several synthetic gene circuits. We identify candidates exhibiting significant tumor reduction and demonstrate high similarity in their efficacies, using a syngeneic mouse model. Last, we show that our platform can be expanded to dynamically profile diverse microbial species including Listeria monocytogenes, Proteus mirabilis, and Escherichia coli in various host cell types. This high-throughput framework may serve to accelerate synthetic biology for clinical applications and for understanding the host-microbe interactions in disease sites.

CRISPR Approaches for the Diagnosis of Human Diseases.

CRISPR/Cas is a prokaryotic self-defense system, widely known for its use as a gene-editing tool. Because of their high specificity to detect DNA and RNA sequences, different CRISPR systems have been adapted for nucleic acid detection. CRISPR detection technologies differ highly among them, since they are based on four of the six major subtypes of CRISPR systems. In just 5 years, the CRISPR diagnostic field has rapidly expanded, growing from a set of specific molecular biology discoveries to multiple FDA-authorized COVID-19 tests and the establishment of several companies. CRISPR-based detection methods are coupled with pre-existing preamplification and readout technologies, achieving sensitivity and reproducibility comparable to the current gold standard nucleic acid detection methods. Moreover, they are very versatile, can be easily implemented to detect emerging pathogens and new clinically relevant mutations, and offer multiplexing capability. The advantages of the CRISPR-based diagnostic approaches are a short sample-to-answer time and no requirement of laboratory settings; they are also much more affordable than current nucleic acid detection procedures. In this review, we summarize the applications and development trends of the CRISPR/Cas13 system in the identification of particular pathogens and mutations and discuss the challenges and future prospects of CRISPR-based diagnostic platforms in biomedicine.

Regional Lipid Expression Abnormalities Identified Using MALDI IMS Correspond to MRI-Defined White Matter Hyperintensities within Post-mortem Human Brain Tissues.

Periventricular white matter hyperintensities (pvWMHs) are a neurological feature detected with magnetic resonance imaging that are clinically associated with an increased risk of stroke and dementia. pvWMHs represent white matter lesions characterized by regions of myelin and axon rarefaction and as such likely involve changes in lipid composition; however, these alterations remain unknown. Lipids are critical in determining cell function and survival. Perturbations in lipid expression have previously been associated with neurological disorders. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is an emerging technique for untargeted, high-throughput investigation of lipid expression and spatial distribution in situ; however, the use of MALDI IMS has been previously been limited by the need for non-embedded, non-fixed, fresh-frozen samples. In the current study, we demonstrate the novel use of MALDI IMS to distinguish regional lipid abnormalities that correlate with magnetic resonance imaging (MRI) defined pvWMHs within ammonium formate washed, formalin-fixed human archival samples. MALDI IMS scans were conducted in positive or negative ion detection mode on tissues sublimated with 2,5-dihydroxybenzoic acid or 1,5-diaminonaphthalene matrices, respectively. Using a broad, untargeted approach to lipid analysis, we consistently detected 116 lipid ion species in 21 tissue blocks from 11 different post-mortem formalin-fixed human brains. Comparing the monoisotopic mass peaks of these lipid ions elucidated significant differences in lipid expression between pvWMHs and NAWM for 31 lipid ion species. Expanding our understanding of alterations in lipid composition will provide greater knowledge of molecular mechanisms underpinning ischemic white matter lesions and provides the potential for novel therapeutic interventions targeting lipid composition abnormalities.

A method to remove the influence of fixative concentration on postmortem T2 maps using a kinetic tensor model.

Formalin fixation has been shown to substantially reduce T2 estimates, primarily driven by the presence of fixative in tissue. Prior to scanning, post-mortem samples are often placed into a fluid that has more favourable imaging properties. This study investigates whether there is evidence for a change in T2 in regions close to the tissue surface due to fixative outflux into this surrounding fluid. Furthermore, we investigate whether a simulated spatial map of fixative concentration can be used as a confound regressor to reduce T2 inhomogeneity. To achieve this, T2 maps and diffusion tensor estimates were obtained in 14 whole, formalin-fixed post-mortem brains placed in Fluorinert approximately 48 hr prior to scanning. Seven brains were fixed with 10% formalin and seven brains were fixed with 10% neutral buffered formalin (NBF). Fixative outflux was modelled using a proposed kinetic tensor (KT) model, which incorporates voxelwise diffusion tensor estimates to account for diffusion anisotropy and tissue-specific diffusion coefficients. Brains fixed with 10% NBF revealed a spatial T2 pattern consistent with modelled fixative outflux. Confound regression of fixative concentration reduced T2 inhomogeneity across both white and grey matter, with the greatest reduction attributed to the KT model versus simpler models of fixative outflux. No such effect was observed in brains fixed with 10% formalin. Correlations between the transverse relaxation rate R2 and ferritin/myelin proteolipid protein (PLP) histology lead to an increased similarity for the relationship between R2 and PLP for the two fixative types after KT correction.

Diagnostic methods for uncovering outcome dependent visit processes.

With the advent of electronic health records, information collected in the course of regular health care is increasingly being used for clinical research. The hope is that the wealth of clinical data and the realistic setting (compared with information derived from highly controlled experiments like randomized trials) will aid in the investigation of determinants of disease and understanding of which treatments are effective in regular practice and for which patients. The availability of information in such databases is often driven by how a patient feels and may therefore be associated with the health outcomes being considered. We call this an outcome dependent visit process and recent work has shown that ignoring the outcome dependence can produce significant bias in the regression coefficients when fitting longitudinal data models. It is therefore important to have tools to recognize datasets exhibiting outcome dependence. We develop a score statistic to motivate the form of diagnostic test statistics, suggest a variety of approaches for diagnosing such situations, and evaluate their performance. Simple diagnostic tests achieve high power for diagnosing outcome dependent visit processes. This occurs when generalized estimating equations methods begin to be exhibit bias in estimating regression coefficients and before likelihood based methods are substantially biased.

The characteristic signs and symptoms of mania and depression according to Kraepelin circa 1905: a comparison with DSM-III.

Although the rise of operationalized diagnostic criteria and the creation of DSM-III were influenced in the USA by a neo-Kraepelinian 'revival' of interest in psychiatric nosology, Kraepelin was only a distal influence on the specific diagnostic criteria proposed. The historical origins of the DSM-III criteria for mania and major depression (MD) are traceable back to the 1950s and contain no direct link to Kraepelin's writings. George Dreyfus, a student and assistant to Kraepelin, authored in 1907 a monograph on Involutional Melancholia which reviewed cases seen by Kraepelin in Heidelberg. In this monograph, Dreyfus presents the 'characteristic' symptoms for mania and depression 'as described by Kraepelin.' This historical finding provides the unprecedented opportunity to examine the resemblance between the criteria proposed for mania and depression in DSM-III, inspired by Kraepelin's nosologic vision, and those specifically suggested by Kraepelin 73 years earlier. Kraepelin's symptoms and signs for mania paralleled seven of the eight DSM-III criteria (except the decreased need for sleep), with two not included in DSM-III (increased mental activity and short bursts of sadness). Kraepelin's signs and symptoms paralleled six of the nine DSM-III criteria for MD, lacking suicidal ideation and changes in appetite/weight and sleep but including obsessions, reduced expressive movements, and decreased mood responsiveness. Although Kraepelin's overall approach to mania and depression emphasized their close inter-relationship in the cyclic course of manic-depressive illness, it is noteworthy Kraepelin's 'characteristic' symptoms for mania and depression as described by Dreyfus, bear substantial but incomplete resemblance to the criteria proposed in DSM-III.