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We discuss how to diversify the reference iPSC line concept. We highlight workflows for generating diverse iPSC lines. We ask whether reference lines can act as inclusive sources of human diversity for use in benchmarking controls for disease models or drug screens, or as clinical grade lines for cell therapies.
Mutual information (MI)-based approaches have increasingly been applied to cancer genomics; however, their use for genome-wide prognostic biomarker discovery remains relatively underexplored. The present article summarizes the conceptual workflow of Mutual Information-based Prognostic Omics Gene (MI-POG) based on previously published applications in breast cancer, lower-grade glioma, and other cancer datasets. The framework consists of clinical endpoint discretization, genome-wide MI-based screening, candidate ranking, and downstream validation using conventional survival-analysis approaches. Previous MI-POG applications identified solute carrier family 20 member 1 (SLC20A1) as a prognostic biomarker in hormone receptor-positive breast cancer. Elevated SLC20A1 expression was associated with unfavorable survival outcomes and was independently validated in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. Methodological analyses demonstrated how survival endpoints can be integrated into an information-theoretic framework through fixed-time outcome discretization, enabling model-independent assessment of molecular-clinical dependencies. Applications across multiple cancer datasets suggested the potential applicability of the framework across biologically distinct tumor types, although further validation will be required to establish its robustness and generalizability. In conclusion, MI-POG can be formalized as an information-theoretic framework for genome-wide identification of prognostic biomarkers by quantifying molecular-clinical dependencies using mutual information. Representative applications from previously published studies suggest that MI-POG may complement conventional survival-analysis approaches and provide a useful strategy for biomarker discovery, although additional benchmarking and prospective validation will be required.
An automated environment for implementing and monitoring care plans and practice guidelines is very important to the reduction of hospital costs and optimization of medical care. The goal of our research effort is to design a general system architecture that facilitates the implementation of (potentially) numerous care plans. Our approach is unique in that we apply the principles and technologies of Oz a multi-user collaborative workflow system that has been used as a software engineering environment framework, to hospital care planning. We utilize not only the workflow modeling and execution facilities of Oz, but also its open-system architecture to interface it with the World Wide Web, the Medical Logic Module server, and other components of the clinical information system. Our initial proof-of-concept system, OzCare, is constructed on top of the existing Oz system. Through several experiments in which we used this system to implement some Columbia-Presbyterian Medical Center care plans, we demonstrated that our system is capable and flexible for care plan automation.
OBJECTIVE: To identify types of clinical unintended adverse consequences resulting from computerized provider order entry (CPOE) implementation. DESIGN: An expert panel provided initial examples of adverse unintended consequences of CPOE. The authors, using qualitative methods, gathered and analyzed additional examples from five successful CPOE sites. METHODS: Using a card sort method, the authors developed a categorization scheme for the 79 unintended consequences initially identified and then iteratively modified the scheme to categorize 245 additional adverse consequences resulting from fieldwork. Because the focus centered on consequences requiring prevention or remedial action, the authors did not further analyze reported unintended beneficial (positive) consequences. RESULTS: Unintended adverse consequences (UACs) fell into nine major categories (in order of decreasing frequency): 1) more/new work for clinicians; 2) unfavorable workflow issues; 3) never ending system demands; 4) problems related to paper persistence; 5) untoward changes in communication patterns and practices; 6) negative emotions; 7) generation of new kinds of errors; 8) unexpected changes in the power structure; and 9) overdependence on the technology. Clinical decision support features introduced many of these unintended consequences. CONCLUSION: Identifying and understanding the types and in some instances the causes of unintended adverse consequences associated with CPOE will enable system developers and implementers to better manage implementation and maintenance of future CPOE projects.
BACKGROUND: Genetic causes of early-onset obesity remain undercharacterized in East Asian children. This study evaluated a whole-exome sequencing (WES)-centered diagnostic workflow in Chinese children with obesity onset before 5 years. METHODS: Consecutive children with body mass index above the 95th percentile and obesity onset before 5 years who completed structured inpatient assessment at a single center between February 2022 and December 2023 were retrospectively analyzed. Phenotyping included clinical, biochemical, oral glucose tolerance, cortisol rhythm, and liver assessments. Genetic testing combined WES, mitochondrial DNA analysis, multiplex ligation-dependent probe amplification (MLPA) for obesity-related imprinting loci, WES-based copy-number variant and runs-of-homozygosity analyses, and Sanger validation. Variants were interpreted according to the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) criteria. RESULTS: Among 23 children, clinically relevant genetic findings were identified in 6 (26.1%): melanocortin-4 receptor (MC4R) c.831T>A (p.C277*), maternal uniparental disomy of 15q11-13, and four phenotype-correlated variants of uncertain significance in UCP3, BBS1, NCOA1, and SH2B1. The definitive/likely diagnostic yield, restricted to pathogenic or confirmed imprinting findings, was 8.7% (2/23). Findings involved leptin-MC4R signaling, BBSome function, fatty-acid oxidation, and chromosomal imprinting. Genetically positive children showed numerically higher alanine aminotransferase (ALT) and aspartate aminotransferase (AST), but differences were not statistically significant. BBS1 p.T374S was relatively enriched in East Asian reference data. CONCLUSIONS: A WES-centered integrated workflow detected heterogeneous genetic mechanisms in Chinese children with early-onset obesity, but variant of uncertain significance (VUS)-associated findings should be distinguished from confirmed diagnoses. Orthogonal methylation/MLPA and runs of homozygosity (ROH) analyses were necessary for imprinting diagnosis. Larger multicenter studies and functional validation are needed.
BACKGROUND: Despite the potential for rapid, asynchronous, documentable communication, the use of e-mail for physician-patient communication has not been widely adopted. OBJECTIVE: To survey physicians currently using e-mail with their patients daily to understand their experiences. METHODS: In-depth phone interviews of 45 physicians currently using e-mail with patients were audio taped and transcribed verbatim. Two investigators independently qualitatively coded comments. Differences were adjudicated by group consensus. RESULTS: Almost all of the 642 comments from these physicians who currently use e-mail with patients daily could be grouped into 1 of 4 broad domains: (1) e-mail access and content, (2) effects of e-mail on the doctor-patient relationship, (3) managing clinical issues by e-mail, and (4) integrating e-mail into office processes. The most consistent theme was that e-mail communication enhances chronic-disease management. Many physicians also reported improved continuity of care and increased flexibility in responding to nonurgent issues. Integration of e-mail into daily workflow, such as utilization of office personnel, appears to be a significant area of concern for many of the physicians. For other issues, such as content, efficiency of e-mail, and confidentiality, there were diverging experiences and opinions. Physicians appear to be selective in choosing which patients they will communicate with via e-mail, but the criteria for selection is unclear. CONCLUSION: These physician respondents did perceive benefits to e-mail with a select group of patients. Several areas, such as identifying clinical situations where e-mail communication is effective, incorporating e-mail into office flow, and being reimbursed for online medical care/communication, need to be addressed before this mode of communication diffuses into most practices.
Breast cancer remains a major cause of cancer-related mortality, and exploratory computational workflows can help prioritize immune-associated markers for further investigation. Here, we used the cancer genome atlas breast invasive carcinoma (TCGA-BRCA) bulk transcriptomic data and the public single-cell dataset GSE161529 to examine associations between myeloperoxidase (MPO) expression, clinical outcomes, immune infiltration, methylation, upstream-regulator annotations, single-cell expression patterns, virtual knockdown sensitivity outputs, drug-gene interaction retrieval, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) annotation. MPO expression was lower in breast cancer tissues than in adjacent non-tumor tissues. Higher MPO expression was associated with a longer progression-free interval, whereas its associations with overall survival and disease-specific survival were not statistically significant. Receiver operating characteristic (ROC) analysis suggested tumor-normal separation within the analyzed public dataset, but this should not be interpreted as clinical diagnostic validation. Immune deconvolution and enrichment analyses indicated that MPO expression mainly tracked with immune- and myeloid-related transcriptional features, rather than establishing tumor-intrinsic regulation of the immune microenvironment. At single-cell resolution, the MPO signal was sparse, with only 85 MPO-positive cells detected before k-nearest neighbor (KNN)-based neighborhood expansion. Detectable MPO signal and MPO-associated scores were interpreted cautiously because they may be influenced by sparse expression, cell-type annotation uncertainty, dropout, doublets, or ambient RNA. In silico virtual knockdown suggested candidate immune- and inflammatory-related transcriptional changes, but these results were considered exploratory and require validation. Drug-gene interaction database (DGIdb)-based drug-gene retrieval and ADMET annotation were used only as preliminary chemical annotations and were not interpreted as therapeutic evidence. Overall, this study provides a reproducible in silico workflow for generating hypotheses about MPO-associated immune/myeloid features in breast cancer, which require external cohort validation and experimental confirmation.
We implemented a total laboratory automation (TLA) system, currently used in Chungnam National University Hospital (CNUH), designed around the A&T Corporation to perform the general and specific laboratory testing throughout the system in a timely and cost-effective manner. The system consists of two major lines: chemistry and hematology. The analyzers attached to the hematology line include one SE 9000 hematology analyzer (Sysmex Corporation, Kobe, Japan), one SP-100 slide maker (Sysmex), and one R9000 reticulocyte counter (Sysmex). The chemistry line consists of preanalytic system and linked analyzers. The analyzers attached to chemistry line are one Hitachi 747 chemistry analyzer (Hitachi, Ltd., Tokyo, Japan), one A&T 502X analyzer (A&T Corporation, Tokyo, Japan) and one Architect i2000 immunochemistry analyzer (Abbott Diagnostics Division, Santa Clara, USA). The preanaytic system including start stocker, centrifuge, de-cap unit and aliquoting unit were connected with analyzers. The turn around time (TAT) of all tests was shortened in comparison to manual systems. Consequently it makes feasible one-day care clinic and makes reduced inherent errors in sample identification, dispensing, and reporting. In addition, real-time re-run can make test quality more reliable. As many as 12 departments can be reduced to 7 departments. The subsidiary advantages of smaller size were incorporated into reduced working steps facilitating workflow. Overall, better qualified and quicker results can be provided to the clinicians, and proper cost-effectiveness and better quality services can be anticipated as a result of much easier system management and higher reliability. In conclusion, the TLA has been successful within our laboratory.
An integrated method was constructed for the study of in situ clinical reasoning. A meta-analysis of existing theories and an exploratory case study were performed. Twelve physicians at the department of otorhinolaryngology, and three physicians and three biomedical technologists at the clinical microbiological laboratory of an 800-bed university hospital were involved in the evaluation of the method. The meta-analysis identified situations where practitioners face assignments for which they follow no routine strategy as suitable starting points for the development of the method, in which organizational processes are presented as workflow graphs. Using the critical incident technique, problem situations in the processes are identified, and stimulated recall interviews are employed to construct a model of the situation-dependent logic used in decision-making. The case study showed that the first levels of the method could easily be used by physicians without training in organizational development or cognitive psychology. It is concluded that the method can be a means for case construction in problem-oriented learning programs that have an empirical background. It can also be used in the development of clinical organization, where training is combined with the establishment of critical paths and computer support.
AIM AND OBJECTIVE: Like other health-care workers, Hong Kong nurses had their professional knowledge and skills seriously challenged during the SARS outbreak. Could current nursing practices support the care of SARS or SARS-like patients in the future? If not, alternative practices would be needed. Providing a preliminary understanding, this paper compares the conventional with different nursing delivery models in a simulated SARS ward and focuses on nurses' efficiency, infection control practices and views of the two models. DESIGN AND METHODS: This study was conducted in three phases. First, a baseline understanding of nursing practices was achieved through four workflow observations. In an eight-hour day, four research assistants observed nursing activities in the medical and fever wards. These data were used in the second phase to construct two sets of clinical vignettes, pertaining to SARS patient care in both conventional and alternative practice models. These scripts were discussed with nine nurses of various ranks from the hospital under study for their expert validation and input. In the third phase, nurse participants and patient actors enacted the vignettes in a simulated setting. Video-taped observations and four nurse participant interviews were employed. Observational data were analysed through descriptive statistics and independent t-tests. Textual data were coded and categorized for common meanings. RESULTS: Conventional practice from the findings consisted of cubicle and named nurse nursing. While the former reflected modified team and functional nursing, it did not confine patient care within a cubicle as suggested by its name. The latter depicted a modified primary nursing approach in a team, with delegation of care. Preliminary findings concerning infection control and nurse satisfaction revealed that the alternative model had an advantage over the conventional. RELEVANCE TO CLINICAL PRACTICE: This study findings lay the foundation for clinical trials, which would evaluate the significance of patient-care quality, cost-effectiveness and better human resource management by restructuring current nursing practices.
Although cardiovascular disease is the leading cause of death globally, therapeutic development in this field is slow. Given the high cost of developing new drugs and running clinical trials for cardiovascular disease, repurposing of drugs with approved safety profiles is an attractive strategy for therapeutic development that can significantly reduce the time and cost investment before phase II clinical trials. In the era of "Omics," various new methods and several large databases have been developed to enable the use of transcriptomics data for drug repurposing. This review summarizes the principles and workflow of signature mapping, which forms the foundation of statistical models used for transcriptome-based drug repurposing. We highlight the features of different analysis pipelines and databases that have been developed for signature mapping. These analysis pipelines prioritize genes that are statistically important, an approach that fundamentally differs from the pharmacological approach of identifying disease-driving and therapeutically targetable pathways. Outcomes of signature mapping pipelines are sensitive to the quality of input data, and results are not always reproducible. Moreover, all widely used RNA-seq databases are derived from cancer research and lack high-quality molecular data for cardiovascular disease. These unmet needs call for interdisciplinary collaboration and large networks of cardiovascular research-oriented biobanks to create the databases needed for transcriptomic-based signature mapping for drug repurposing efforts.
Pagers, personal data assistants (PDAs) and other devices that have wireless connectivity are becoming a popular method for delivering patient related information to medical decision makers. Although medical informatics research has emphasized the design, and implementation of pagers as event notification mechanisms, researchers have not paid as much attention to how this technology impacts medical work. We present a case study of physicians in a Surgical Intensive Care Unit (SICU) using wireless alert pagers. The pagers provide a variety of alphanumeric clinical alert messages and are widely used by SICU physicians. However, the use of the pagers has created unanticipated challenges to the physicians' traditional work practices. These challenges include: (1) flattening of hierarchical workflows, (2) coping with information overload and missing context, and (3) lack of feedback. These challenges are tied to both the specific technical design of the system and the traditional structure of medical work.
OBJECTIVES: Our objective was to design and develop a mobile clinical decision support system for emergency triage of different acute pain presentations. The system should interact with existing hospital information systems, run on mobile computing devices (handheld computers) and be suitable for operation in weak-connectivity conditions (with unstable connections between mobile clients and a server). METHODS: The MET (Mobile Emergency Triage) system was designed following an extended client-server architecture. The client component, responsible for triage decision support, is built as a knowledge-based system, with domain ontology separated from generic problem solving methods and used for the automatic creation of a user interface. RESULTS: The MET system is well suited for operation in the Emergency Department of a hospital. The system's external interactions are managed by the server, while the MET clients, running on handheld computers are used by clinicians for collecting clinical data and supporting triage at the bedside. The functionality of the MET client is distributed into specialized modules, responsible for triaging specific types of acute pain presentations. The modules are stored on the server, and on request they can be transferred and executed on the mobile clients. The modular design provides for easy extension of the system's functionality. A clinical trial of the MET system validated the appropriateness of the system's design, and proved the usefulness and acceptance of the system in clinical practice. CONCLUSIONS: The MET system captures the necessary hospital data, allows for entry of patient information, and provides triage support. By operating on handheld computers, it fits into the regular emergency department workflow without introducing any hindrances or disruptions. It supports triage anytime and anywhere, directly at the point of care, and also can be used as an electronic patient chart, facilitating structured data collection.
BACKGROUND: Nasopharyngeal carcinoma (NPC) represents a highly prevalent and aggressive malignancy endemic to Southeast Asia. Early and accurate diagnosis is critical to improving survival outcomes; however, the absence of robust, stage-specific biomarkers remains a key obstacle to clinical implementation of early screening strategies. METHODS: We performed untargeted serum proteomic profiling using mass spectrometry in 15 treatment-naïve early-stage NPC patients and 15 VCA-IgA-positive healthy controls. Bioinformatics analyses were conducted to identify differentially expressed proteins (DEPs). Machine learning (random forest combined with recursive feature elimination) was employed to prioritize candidate biomarkers, which were subsequently verified using enzyme-linked immunosorbent assay (ELISA) in independent sample cohorts. RESULTS: In total, 1,428 serum proteins were identified, among which 1,410 were reliably quantified. We observed 31 upregulated and 189 downregulated proteins in NPC patients relative to controls. Spearman correlation analysis revealed significant associations: LTA4H (leukotriene A4 hydrolase) levels correlated with serum cell infiltration (r = 0.383, p = 0.032) and CD8 + T-cell abundance (r = 0.408, p = 0.021); both SULT1A3 (sulfotransferase family 1 A member 3) and FGL1 (fibrinogen-like protein 1) levels were positively associated with M1 macrophage infiltration (r = 0.510, p = 0.003 and r = 0.430, p = 0.015, respectively). In a preliminary validation cohort (n = 80), ELISA yielded AUC values of 0.631 (95% CI: 0.515-0.736, p = 0.04) for LTA4H, 0.787 (95% CI: 0.681-0.871, p < 0.001) for SULT1A3, and 0.688 (95% CI: 0.575-0.787, p = 0.002) for FGL1. In large-scale independent validation, SULT1A3 achieved an AUC of 0.826 (95% CI: 0.766-0.876; sensitivity = 78.89%, specificity = 75.47%) in cohort 1 (n = 196) and 0.796 (95% CI: 0.723-0.857; sensitivity = 76.67%, specificity = 76.67%) in cohort 2 (n = 150). CONCLUSIONS: Through an integrated workflow combining proteomic screening, machine learning prioritization, and multi-stage ELISA validation, we identified SULT1A3 as a candidate serum-based biomarker for early detection of NPC. Preliminary findings suggest that SULT1A3 may have potential utility in clinical screening, though further validation in independent, multi‑center cohorts is required.
Computer-based clinical decision support systems (CDSSs) have been championed for their potential to improve health-care quality. However, there has been no systematic study of the types of CDSSs that have been developed. In previous work, we developed the CDSS Taxonomy for comprehensively describing the technical, workflow, and contextual characteristics of CDSSs. We now use the CDSS Taxonomy to describe outpatient CDSSs evaluated in randomized controlled trials published between 1998 and 2002. 31 studies comprising 42 CDSS systems were included in our analysis. The majority of systems used rule-based reasoning engines to "push" explicit, individualized recommendations concerning non-urgent decisions to clinicians or patients, but not both. 71% of the systems required someone to manually enter data into the system or to process the system output for use by the target decision maker. The average kappa for coding agreement was > 0.6. Our findings demonstrate that outpatient CDSSs vary greatly in design and function. Many impose a data entry or output-processing burden on clinic staff. More complete reporting of CDSS characteristics is needed in the literature.
Clinician efficiency can be enhanced by worklists that compile useful data for rapid access at the time of need. The authors report development of a web-based, user-edited "Patient List Manager" for the Clinical Image Management System (CIMS). The CIMS List Manager interfaces with the CIMS Archive to provide the user with available studies. It has tools that let the user build personal lists from the available studies. Listed studies are moved from the archive to the cache for rapid access at the time of need. Users can build/edit the list through a browser (without viewing pictures) or from within the image viewer. In this way, the List Manager distributes list building into knowledgeable hands. This is particularly valuable at the current time when health system patient registries are not mature enough to reliably support building build anticipatory patient lists.
In this study, we processed reconstructed images with a new image filter (Siemens Medical Systems, Adaptive Image Filter: AIF). As one of its characteristics, the filter uses low-pass filtering. When an image that emphasizes a high-frequency element is changed to one with a reduced high-frequency element, an image suitable for clinical use can be obtained. For the resolving characteristic and the noise characteristic, we evaluated the degree of transition, using the modulation transfer factor (MTF) and Wiener spectrum (WS). Moreover, we used the signal-to-noise ratio (SNR) to examine the total loss of signal detection capability after use of the AIF. The results showed that, when we changed to images using the AIF and made it the same level as B30 and U40, we had to hold down the kernel level to at least B60 and U80. The use of an image filter did not recognize less of an SNR in comparison with the reconstruction image. In this study, changes in detailed characteristics of the image and SNR could be evaluated objectively using the AIF. As for the effective method by AIF that raw data isn't used for is available for the control of an image (times) using reconstruction and the change of an image on database. Therefore, we consider the AIF useful to improve workflow in CT examinations.
OBJECTIVE: Problems involving drug knowledge are one of the most common causes of serious medication errors. Although the information that clinicians need is often available somewhere, retrieving it expeditiously has been problematic. At the same time, clinicians are faced with an ever-expanding pharmacology knowledge base. Recently, point-of-care technology has become more widely available and more practical with the advent of handheld, or palmtop, computing. Therefore, the authors evaluated the clinical contribution of a drug database developed for the handheld computer. ePocrates Rx (formerly known as qRx; ePocrates, San Carlos, California) is a comprehensive drug information guide that is downloadable free from the Internet and designed for the Palm OS platform align="right". DESIGN: A seven-day online survey of 3,000 randomly selected ePocrates Rx users was conducted during March 2000. MEASUREMENTS: User technology experience, product evaluation and usage patterns, and the effects of the drug reference database on information-seeking behavior, practice efficiency, decision making, and patient care. RESULTS: The survey response rate was 32 percent (n=946). Physicians reported that ePocrates Rx saves time during information retrieval, is easily incorporated into their usual workflow, and improves drug-related decision making. They also felt that it reduced the rate of preventable adverse drug events. CONCLUSIONS: Self-reported perceptions by responding clinicians endorse improved access to drug information and improved practice efficiency associated with the use of handheld devices. The clinical and practical value of using these devices in clinical settings will clearly grow further as wireless communication becomes more ubiquitous and as more applications become available.