RESUMEN

Innovative approaches are needed for managing risk and system change in healthcare. This paper presents a case study of a project that took place over two years, taking a systems approach to managing the risk of healthcare acquired infection in an acute hospital setting, supported by an Access Risk Knowledge Platform which brings together Human Factors Ergonomics, Data Science, Data Governance and AI expertise. Evidence for change including meeting notes and use of the platform were studied. The work on the project focused on first systematically building a rich picture of the current situation from a transdisciplinary perspective. This allowed for understanding risk in context and developing a better capability to support enterprise risk management and accountability. From there a linking of operational and risk data took place which led to mapping of the risk pattern in the hospital.

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Innovative ways of supporting the processes for managing risk, developing accountability and building resilience and system change in healthcare are needed.This paper presents a study that took place over two years, taking a systems approach to managing the risk of healthcare acquired infection in an acute hospital setting, supported by Human Factors Ergonomics, Data Science, Data Governance and AI.The work focused on systematically building a proactive capability to understand all data sources and harness their ability to support the proactive management of the risk of healthcare acquired infection.

RESUMEN

The high dropout rates in programming courses emphasise the need for monitoring and understanding student engagement, enabling early interventions. This activity can be supported by insights into students' learning behaviours and their relationship with academic performance, derived from student learning log data in learning management systems. However, the high dimensionality of such data, along with their numerous features, pose challenges to their analysis and interpretability. In this study, we introduce entropy-based metrics as a novel manner to represent students' learning behaviours. Employing these metrics, in conjunction with a proven community detection method, we undertake an analysis of learning behaviours across higher- and lower-performing student communities. Furthermore, we examine the impact of the COVID-19 pandemic on these behaviours. The study is grounded in the analysis of empirical data from 391 Software Engineering students over three academic years. Our findings reveal that students in higher-performing communities typically tend to have lower volatility in entropy values and reach stable learning states earlier than their lower-performing counterparts. Importantly, this study provides evidence of the use of entropy as a simple yet insightful metric for educators to monitor study progress, enhance understanding of student engagement, and enable timely interventions.

RESUMEN

We analyze the correlation between different assets in the cryptocurrency market throughout different phases, specifically bearish and bullish periods. Taking advantage of a fine-grained dataset comprising 34 historical cryptocurrency price time series collected tick-by-tick on the HitBTC exchange, we observe the changes in interactions among these cryptocurrencies from two aspects: time and level of granularity. Moreover, the investment decisions of investors during turbulent times caused by the COVID-19 pandemic are assessed by looking at the cryptocurrency community structure using various community detection algorithms. We found that finer-grain time series describes clearer the correlations between cryptocurrencies. Notably, a noise and trend removal scheme is applied to the original correlations thanks to the theory of random matrices and the concept of Market Component, which has never been considered in existing studies in quantitative finance. To this end, we recognized that investment decisions of cryptocurrency traders vary between bearish and bullish markets. The results of our work can help scholars, especially investors, better understand the operation of the cryptocurrency market, thereby building up an appropriate investment strategy suitable to the prevailing certain economic situation.

RESUMEN

We analyze tick-by-tick data representing major cryptocurrencies traded on some different cryptocurrency trading platforms. We focus on such quantities like the inter-transaction times, the number of transactions in time unit, the traded volume, and volatility. We show that the inter-transaction times show long-range power-law autocorrelations. These lead to multifractality expressed by the right-side asymmetry of the singularity spectra f ( α ) indicating that the periods of increased market activity are characterized by richer multifractality compared to the periods of quiet market. We also show that neither the stretched exponential distribution nor the power-law-tail distribution is able to model universally the cumulative distribution functions of the quantities considered in this work. For each quantity, some data sets can be modeled by the former and some data sets by the latter, while both fail in other cases. An interesting, yet difficult to account for, observation is that parallel data sets from different trading platforms can show disparate statistical properties.

RESUMEN

Chronic HIV infection causes a progressive decrease in the ability to maintain homeostasis resulting, after some time, in eventual break down of immune functions. Recent clinical research has shed light on a significant contribution of the lymphatic tissues, where HIV causes accumulation of collagen, (fibrosis). Specifically, where tissue is populated by certain types of functional stromal cells designated Fibroblastic Reticular Cells (FRCs), these have been found to play a crucial role in balancing out apoptosis and regeneration of naïve T-cells through 2-way cellular signaling. Tissue fibrosis not only impedes this signaling, effectively reducing T-cell levels through increased apoptosis of cells of both T- and FRC type but has been found to be irreversible by current HIV standard treatment (cART). While the therapy aims to block the viral lifecycle, cART-associated increase of T-cell levels in blood appears to conceal existing FRC impairment through fibrosis. This hidden impairment can lead to adverse consequences if treatment is interrupted, e.g. due to poor adherence (missing doses) or through periods recovering from drug toxicities. Formal clinical studies on treatment interruption have indicated possible adverse effects, but quantification of those effects in relation to interruption protocol and patient predisposition remains unclear. Accordingly, the impact of treatment interruption on lymphatic tissue structure and T-cell levels is explored here by means of computer simulation. A novel Stochastic Cellular Automata model is proposed, which utilizes all sources of clinical detail available to us (though sparse in part) for model parametrization. Sources are explicitly referenced and conflicting evidence from previous studies explored. The main focus is on (i) spatial aspects of collagen build up, together with (ii) collagen increase after repeated treatment interruptions to explore the dynamics of HIV-induced fibrosis and T-cell loss.

Asunto(s)

Infecciones por VIH , Simulación por Computador , Genotipo , Infecciones por VIH/tratamiento farmacológico , Humanos , Tejido Linfoide , Linfocitos T

RESUMEN

OBJECTIVE: To investigate the epidemiology and treatment of rheumatoid arthritis (RA) in a population broadly representative of employed adults in the US, using a retrospective cohort design. METHODS: Incident and prevalent RA cohorts were defined from a sample of 4.66 million adults with complete followup data from the period of January 2005 through September 2008 in the Pharmetrics medical claims database. Demographics, comorbidity, and medical therapies were summarized using descriptive statistics. RESULTS: Median duration in the database was 5.7 years. Age- and sex-adjusted incidence in 2006 was 0.71 per 1,000 persons at risk (n = 3,992) and prevalence in 2005 was 0.63% (n = 30,530). Within 12 months after diagnosis, 65%, 64%, and 20% of the incident cohort had been prescribed corticosteroids, nonbiologic disease-modifying antirheumatic drugs (DMARDs), and tumor necrosis factor (TNF) inhibitors, respectively. Median time to first anti-TNF prescription was 6 months; 31% switched to a second drug and 15% to a third. An aggressive subcohort (11% of incident patients) received more DMARDs (83%) and TNF inhibitors (43%), and was more likely to switch. Twenty-eight percent of incident patients received only symptomatic therapy over a minimum of 1.75 years of followup; these patients were older with more comorbidities and contraindications to methotrexate. CONCLUSION: In this insured population-based cohort, only two-thirds of newly diagnosed RA patients were prescribed a DMARD in year 1 and 28% received no antirheumatic therapy. Although limited by lack of clinical information and by left-censoring, administrative databases capture clinical practice and suggest that gaps exist in treatment options available to a significant number of patients.

Asunto(s)

Antirreumáticos/uso terapéutico , Artritis Reumatoide/tratamiento farmacológico , Artritis Reumatoide/epidemiología , Seguro de Salud , Pautas de la Práctica en Medicina/tendencias , Distribución por Edad , Anciano , Antirreumáticos/efectos adversos , Artritis Reumatoide/diagnóstico , Artritis Reumatoide/inmunología , Comorbilidad , Bases de Datos Factuales , Sustitución de Medicamentos , Quimioterapia Combinada , Femenino , Disparidades en Atención de Salud/tendencias , Humanos , Incidencia , Masculino , Persona de Mediana Edad , Terapia Molecular Dirigida , Prevalencia , Estudios Retrospectivos , Distribución por Sexo , Factores de Tiempo , Resultado del Tratamiento , Factor de Necrosis Tumoral alfa/antagonistas & inhibidores , Factor de Necrosis Tumoral alfa/inmunología , Estados Unidos/epidemiología

RESUMEN

Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions). Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

RESUMEN

With the fast development of high-throughput sequencing technologies, a new generation of genome-wide gene expression measurements is under way. This is based on mRNA sequencing (RNA-seq), which complements the already mature technology of microarrays, and is expected to overcome some of the latter's disadvantages. These RNA-seq data pose new challenges, however, as strengths and weaknesses have yet to be fully identified. Ideally, Next (or Second) Generation Sequencing measures can be integrated for more comprehensive gene expression investigation to facilitate analysis of whole regulatory networks. At present, however, the nature of these data is not very well understood. In this paper we study three alternative gene expression time series datasets for the Drosophila melanogaster embryo development, in order to compare three measurement techniques: RNA-seq, single-channel and dual-channel microarrays. The aim is to study the state of the art for the three technologies, with a view of assessing overlapping features, data compatibility and integration potential, in the context of time series measurements. This involves using established tools for each of the three different technologies, and technical and biological replicates (for RNA-seq and microarrays, respectively), due to the limited availability of biological RNA-seq replicates for time series data. The approach consists of a sensitivity analysis for differential expression and clustering. In general, the RNA-seq dataset displayed highest sensitivity to differential expression. The single-channel data performed similarly for the differentially expressed genes common to gene sets considered. Cluster analysis was used to identify different features of the gene space for the three datasets, with higher similarities found for the RNA-seq and single-channel microarray dataset.

Asunto(s)

Expresión Génica , Análisis de Secuencia por Matrices de Oligonucleótidos/métodos , ARN/genética , Análisis de Secuencia de ARN/métodos , Animales , Análisis por Conglomerados , Bases de Datos Genéticas , Drosophila melanogaster , Perfilación de la Expresión Génica/métodos , ARN/metabolismo

RESUMEN

Gene regulatory networks (GRNs) are complex biological systems that have a large impact on protein levels, so that discovering network interactions is a major objective of systems biology. Quantitative GRN models have been inferred, to date, from time series measurements of gene expression, but at small scale, and with limited application to real data. Time series experiments are typically short (number of time points of the order of ten), whereas regulatory networks can be very large (containing hundreds of genes). This creates an under-determination problem, which negatively influences the results of any inferential algorithm. Presented here is an integrative approach to model inference, which has not been previously discussed to the authors' knowledge. Multiple heterogeneous expression time series are used to infer the same model, and results are shown to be more robust to noise and parameter perturbation. Additionally, a wavelet analysis shows that these models display limited noise over-fitting within the individual datasets.

Asunto(s)

Redes Reguladoras de Genes , Modelos Genéticos , Procesos Estocásticos , Algoritmos , Redes Reguladoras de Genes/genética

RESUMEN

OBJECTIVE: • To compare prostate cancer, prostate-related surgery and acute urinary retention rates, as well as associated healthcare resource use over 11 years in African American and Caucasian men with benign prostatic hyperplasia (BPH). PATIENTS AND METHODS: • The BPH-related medical and surgical charges and events were determined for 398 African American men and 1656 Caucasian men followed for a mean of 10.2 years within a health maintenance organization. • Racial differences in clinical outcomes were evaluated using time-to-event analysis, stratifying results by baseline prostate-specific antigen (PSA) values. RESULTS: • Risk of a prostate cancer diagnosis was 2.2 times greater in African American than Caucasian men (95% CI 1.48-3.35, P < 0.001) in analyses adjusting for serum PSA level. • Although African Americans were more likely to receive medical therapy for symptoms of BPH than Caucasians (43.5% vs 37.2%, respectively; P= 0.029), there were no clinically meaningful differences with respect to subsequent acute urinary retention or BPH-related surgery between them, or BPH-related medical charges (US $407 vs US $405 per month). CONCLUSION: • As evidenced by this analysis of 'real-world' clinical practice, African Americans with BPH have a much greater risk of developing prostate cancer than similar Caucasian men highlighting the need for education and early detection in this population.

Asunto(s)

Negro o Afroamericano/estadística & datos numéricos , Hiperplasia Prostática/etnología , Hiperplasia Prostática/epidemiología , Neoplasias de la Próstata/etnología , Retención Urinaria/etnología , Población Blanca/estadística & datos numéricos , Inhibidores de 5-alfa-Reductasa/uso terapéutico , Antagonistas Adrenérgicos alfa/uso terapéutico , Anciano , Estudios de Seguimiento , Humanos , Masculino , Michigan/epidemiología , Persona de Mediana Edad , Prevalencia , Estudios Prospectivos , Antígeno Prostático Específico/sangre , Hiperplasia Prostática/terapia , Factores de Riesgo

RESUMEN

BACKGROUND: Inferring Gene Regulatory Networks (GRNs) from time course microarray data suffers from the dimensionality problem created by the short length of available time series compared to the large number of genes in the network. To overcome this, data integration from diverse sources is mandatory. Microarray data from different sources and platforms are publicly available, but integration is not straightforward, due to platform and experimental differences. METHODS: We analyse here different normalisation approaches for microarray data integration, in the context of reverse engineering of GRN quantitative models. We introduce two preprocessing approaches based on existing normalisation techniques and provide a comprehensive comparison of normalised datasets. CONCLUSIONS: Results identify a method based on a combination of Loess normalisation and iterative K-means as best for time series normalisation for this problem.

Asunto(s)

Algoritmos , Perfilación de la Expresión Génica/métodos , Redes Reguladoras de Genes , Análisis de Secuencia por Matrices de Oligonucleótidos/métodos , Ciclo Celular/genética , Biología Computacional/métodos , Reproducibilidad de los Resultados , Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/genética

RESUMEN

BACKGROUND: Recent advances in Immunology highlighted the importance of local properties on the overall progression of HIV infection. In particular, the gastrointestinal tract is seen as a key area during early infection, and the massive cell depletion associated with it may influence subsequent disease progression. This motivated the development of a large-scale agent-based model. RESULTS: Lymph nodes are explicitly implemented, and considerations on parallel computing permit large simulations and the inclusion of local features. The results obtained show that GI tract inclusion in the model leads to an accelerated disease progression, during both the early stages and the long-term evolution, compared to a theoretical, uniform model. CONCLUSIONS: These results confirm the potential of treatment policies currently under investigation, which focus on this region. They also highlight the potential of this modelling framework, incorporating both agent-based and network-based components, in the context of complex systems where scaling-up alone does not result in models providing additional insights.

Asunto(s)

Síndrome Hipereosinofílico/epidemiología , Trastornos Mieloproliferativos/epidemiología , Anciano , Femenino , Humanos , Incidencia , Masculino , Receptor alfa de Factor de Crecimiento Derivado de Plaquetas/análisis , Programa de VERF , Estados Unidos/epidemiología , Factores de Escisión y Poliadenilación de ARNm/análisis

RESUMEN

BACKGROUND: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very difficult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insufficient. RESULTS: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and offer a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. CONCLUSIONS: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identified and a platform for development of appropriate model formalisms is established.

Asunto(s)

Algoritmos , Evolución Molecular , Redes Reguladoras de Genes , Biología Computacional/métodos , Expresión Génica , Perfilación de la Expresión Génica , Análisis de Secuencia por Matrices de Oligonucleótidos

RESUMEN

Risk factors for pulmonary embolism (PE) have been identified among populations in Western countries but have not been well characterized in Japan. A hospital-based case-control design employed cases with PE, which diagnosed by standard imaging techniques; controls were individuals drawn by systematic random sampling from the hospital admission register. A total of 100 (38 males and 62 females) and 199 controls were identified. Patients with PE were younger (56.5 vs 60.9 years) and more likely to be female. The odds ratio ([OR] adjusted for other factors) and 95% confidence interval (CI) for risk of PE was elevated for the following: female gender, prolonged immobilization, history of prior venous thromboembolism (VTE), lower extremity varicose veins, body mass index (BMI) > or = 25 kg/m( 2), extremity paralysis, and gout/hyperuricemia. Inherited thrombophilia was found in 14 patients with PE (14%). Risk factors for PE in Japan are comparable in magnitude to those in Western countries; only one third of PE cases had received VTE prophylaxis.

Asunto(s)

Embolia Pulmonar/etiología , Consumo de Bebidas Alcohólicas , Índice de Masa Corporal , Estudios de Casos y Controles , Femenino , Hospitalización , Humanos , Japón , Masculino , Persona de Mediana Edad , Factores de Riesgo , Fumar

RESUMEN

OBJECTIVES: To evaluate changes in prostate volume (PV) and its association with selected urological measures and risk of surgical intervention in Japanese men with benign prostatic hyperplasia (BPH). METHODS: The medical records of all consecutive urologist-diagnosed BPH patients of >or=40 years old who attended any of four urology clinics in Japan during January 2004-June 2006 were reviewed. Both cross-sectional and longitudinal data were captured to analyze baseline correlations among urological measures, to evaluate the longitudinal changes in PV and selected urological measures, and to examine the predictors of surgical intervention. RESULTS: The follow-up period was 2.8 years. Mean PV and mean prostate-specific antigen (PSA) of 1331 eligible patients were 34.0 mL and 4.0 ng/mL, respectively. Both measures increased directly with age. Baseline PV correlated with residual urine volume (r = 0.18, P < 0.05) and PSA (r = 0.41, P < 0.001). Among 319 patients who had more than one PV measurement, PV increased in 51% of patients, remained the same in 28% and decreased in 21%. Use of alpha-blockers at baseline and during follow up was not associated with PV change. Patients who had a PV >or=30 mL, a severe International Prostate Symptom Score and a PSA level >or=1.5 ng/mL at baseline, were more likely to have surgical intervention during the follow-up period. CONCLUSIONS: Predictors generated in this study may help to identify a subset of BPH patients at high risk of surgical intervention.

Asunto(s)

Pueblo Asiatico/estadística & datos numéricos , Próstata/patología , Prostatectomía/estadística & datos numéricos , Hiperplasia Prostática , Adulto , Anciano , Estudios Transversales , Estudios de Seguimiento , Humanos , Japón/epidemiología , Estudios Longitudinales , Masculino , Persona de Mediana Edad , Valor Predictivo de las Pruebas , Hiperplasia Prostática/etnología , Hiperplasia Prostática/patología , Hiperplasia Prostática/cirugía , Estudios Retrospectivos , Factores de Riesgo

RESUMEN

Using poly(lactide-co-glycolide) (PLGA) particles for drug encapsulation and delivery has recently gained considerable popularity for a number of reasons. An advantage in one sense, but a drawback of PLGA use in another, is that drug delivery systems made of this material can provide a wide range of dissolution profiles, due to their internal structure and properties related to particles' manufacture. The advantages of enriching particulate drug design experimentation with computer models, are evident with simulations used to predict and optimize design, as well as indicate choice of best manufacturing parameters. In the present work, we seek to understand the phenomena observed for PLGA micro- and nanospheres, through Cellular Automata (CA) agent-based Monte Carlo (MC) models. Systems are studied both over large temporal scales (capturing slow erosion of PLGA) and for various spatial configurations (capturing initial as well as dynamic morphology). The major strength of this multi-agent approach is to observe dissolution directly, by monitoring the emergent behaviour: the dissolution profile manifested, as a sphere erodes. Different problematic aspects of the modelling process are discussed in details in this paper. The models were tested on experimental data from literature, demonstrating very good performance. Quantitative discussion is provided throughout the text in order to make a demonstration of the use in practice of the proposed model.

Asunto(s)

Ácido Láctico/química , Microesferas , Nanopartículas , Ácido Poliglicólico/química , Proteínas/química , Modelos Teóricos , Copolímero de Ácido Poliláctico-Ácido Poliglicólico , Porosidad , Solubilidad

RESUMEN

In order to better understand and predict the release of proteins from bioerodible microspheres or nanospheres, it is important to know the influences of different initial factors on the release mechanisms, though often it is difficult to assess what exactly is at the origin of a certain dissolution profile. We propose here a new class of fine-grained multi-agent models built to incorporate increasing complexity, permitting the exploration of the role of different parameters, especially that of the internal morphology of the spheres, in the exhibited release profile. This approach, based on Monte Carlo (MC) and cellular automata (CA) techniques, has permitted the testing of various assumptions and hypotheses about several experimental systems of nanospheres encapsulating proteins. Results have confirmed that this modelling approach has increased the resolution over the complexity involved, opening promising perspectives for future developments, especially complementing in vitro experimentation.

Asunto(s)

Portadores de Fármacos/química , Imagenología Tridimensional/métodos , Ácido Láctico/química , Modelos Químicos , Nanoestructuras/química , Nanoestructuras/ultraestructura , Ácido Poliglicólico/química , Proteínas/química , Simulación por Computador , Difusión , Microesferas , Conformación Molecular , Tamaño de la Partícula , Copolímero de Ácido Poliláctico-Ácido Poliglicólico

RESUMEN

OBJECTIVE: The natural history of benign prostatic hyperplasia (BPH) in Japan resembles Western studies in that symptoms worsen, improve or stabilize in equal proportions of patients. We sought to determine if this pattern persisted in men seeking care at a urology referral center and if worsening of symptoms was due to increase in prostate volume (PV). METHODS: We reviewed the records of all BPH patients who attended the Urology Clinic of Sapporo Medical University Hospital, during December 2003 and June 2004 with the inclusion criterion that they have at least two PV and lower urinary tract symptoms measurements using the International Prostate Symptom Score (IPSS). Patients who had prostate cancer or who underwent hormone therapy or prostate surgery between the two visits were excluded. Correlation (Spearman's rank) was used to assess interrelationships among variables at baseline and follow up; the strength of association between change in IPSS and change in PV were modeled by multiple linear regression. RESULTS: Sixty-seven patients were eligible. Baseline PV correlated with residual urine volume (r = 0.37, P < 0.05) and prostate-specific antigen (PSA; r = 0.65, P < 0.001) but not IPSS (r =-0.16). PV increased in 46 (70%) men, remained the same in 10 and decreased in 11; in the former group, the mean prostate enlargement generally increased as baseline PV increased. In multiple linear regression models that included baseline IPSS, correlation between change in IPSS and change in PV was 0.47 (P = 0.05) based on 25 patients with measures at concurrent visits. Change in PV was also correlated with change in quality of life score (0.46, P = 0.02) but not with change in PSA (r = 0.38, P = 0.07, maximum flow rate (-0.24) or residual urine volume (-0.06). CONCLUSIONS: IPSS were not correlated with any laboratory measure of urinary function at baseline; however, change in IPSS was associated with change in PV. PV was also moderately correlated to PSA levels and residual urine volume at baseline.

Asunto(s)

Antígeno Prostático Específico/sangre , Próstata/patología , Hiperplasia Prostática/complicaciones , Trastornos Urinarios/sangre , Trastornos Urinarios/patología , Anciano , Anciano de 80 o más Años , Indicadores de Salud , Humanos , Estudios Longitudinales , Masculino , Persona de Mediana Edad , Tamaño de los Órganos , Hiperplasia Prostática/sangre , Hiperplasia Prostática/patología , Estudios Retrospectivos , Trastornos Urinarios/etiología

RESUMEN

To grasp the burden and management status of COPD in Japan, a large telephone survey was conducted. In initial screening 400 individuals > or =45 years were identified as either having been given a diagnosis of COPD or fulfilling criteria for their respiratory-related symptoms and smoking history (baseline population) and they were recruited for a detailed investigation (interview sample). They were asked about demographic information, exacerbation, impact of COPD on daily life, and management and treatment. Of the 400 interview samples, 209 subjects (52%) had a diagnosis of COPD, and the remaining 191 ones (48%) were not, retrospectively. It was confirmed that proportions of a current smoker in the COPD (35.4%) and non-COPD (35.6%) groups were almost at the same level. The use of inhaled bronchodilators, recommended by guidelines in 157 treated subjects, was 16% or less, whereas respiratory conditions affected daily activities in 70% of all the subjects. In conclusion, COPD in Japanese subjects significantly affects daily life yet is undiagnosed; there is a need to improve COPD diagnosis and management by general practitioners through disseminating guidelines for diagnosis, management, and prevention of COPD in Japan.

Asunto(s)

Costo de Enfermedad , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico , Anciano , Femenino , Humanos , Entrevistas como Asunto , Japón , Masculino , Persona de Mediana Edad