Specialist respiratory outreach: a case-finding initiative for identifying undiagnosed COPD in primary care.
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ABSTRACT:
SUBMITTER: Ray E
PROVIDER: S-EPMC7878732 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveChronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality, yet research suggests this disease is greatly underdiagnosed. This literature review sought to summarize the most common and significant variables associated with case-finding or missed cases of COPD to inform more effective and efficient detection of high-risk COPD patients in primary care.MethodsPubMed and EMBASE were searched for articles describing case-finding and epidemiologic research to detect or characterize new cases of COPD. International studies in primary and non-primary care settings, published in English from 2002-2014, were eligible for inclusion. Studies related to risk factors for development of COPD were excluded.ResultsOf the 33 studies identified and reviewed, 21 were case-finding or screening and 12 were epidemiological, including cross-sectional, longitudinal, and retrospective designs. A range of variables were identified within and across studies. Variables common to both screening and epidemiological studies included age, smoking status, and respiratory symptoms. Seven significant predictors from epidemiologic studies did not appear in screening tools. No studies targeted discovery of higher risk patients such as those with reduced lung function or risks for exacerbations.ConclusionVariables used to identify new cases of COPD or differentiate COPD cases and non-cases are wide- ranging, (from sociodemographic to self-reported health or health history variables), providing insight into important factors for case identification. Further research is underway to develop and test the best, smallest variable set that can be used as a screening tool to identify people with undiagnosed, high-risk COPD in primary care.
| S-EPMC4521771 | biostudies-literature
Project description:Underuse or unavailability of spirometry is one of the most important factors causing underdiagnosis of COPD. We reported the development of a COPD prediction model to identify at-risk, undiagnosed COPD patients when spirometry was unavailable. This cross-sectional study enrolled subjects aged ?40 years with respiratory symptoms and a smoking history (?20 pack-years) in a medical center in two separate periods (development and validation cohorts). All subjects completed COPD assessment test (CAT), peak expiratory flow rate (PEFR) measurement, and confirmatory spirometry. A binary logistic model with calibration (Hosmer-Lemeshow test) and discrimination (area under receiver operating characteristic curve [AUROC]) was implemented. Three hundred and one subjects (development cohort) completed the study, including non-COPD (154, 51.2%) and COPD cases (147; stage I, 27.2%; II, 55.8%; III-IV, 17%). Compared with non-COPD and GOLD I cases, GOLD II-IV patients exhibited significantly higher CAT scores and lower lung function, and were considered clinically significant for COPD. Four independent variables (age, smoking pack-years, CAT score, and percent predicted PEFR) were incorporated developing the prediction model, which estimated the COPD probability (PCOPD). This model demonstrated favorable discrimination (AUROC: 0.866/0.828; 95% CI 0.825-0.906/0.751-0.904) and calibration (Hosmer-Lemeshow P?=?0.332/0.668) for the development and validation cohorts, respectively. Bootstrap validation with 1000 replicates yielded an AUROC of 0.866 (95% CI 0.821-0.905). A PCOPD of ?0.65 identified COPD patients with high specificity (90%) and a large proportion (91.4%) of patients with clinically significant COPD (development cohort). Our prediction model can help physicians effectively identify at-risk, undiagnosed COPD patients for further diagnostic evaluation and timely treatment when spirometry is unavailable.
| S-EPMC6538645 | biostudies-literature
Project description:Many cases of chronic obstructive pulmonary disease (COPD) are diagnosed only after significant loss of lung function or during exacerbations.This study is part of a multi-method approach to develop a new screening instrument for identifying undiagnosed, clinically significant COPD in primary care.Subjects with varied histories of COPD diagnosis, risk factors and history of exacerbations were recruited through five US clinics (four pulmonary, one primary care). Phase I: Eight focus groups and six telephone interviews were conducted to elicit descriptions of risk factors for COPD, recent or historical acute respiratory events, and symptoms to inform the development of candidate items for the new questionnaire. Phase II: A new cohort of subjects participated in cognitive interviews to assess and modify candidate items. Two peak expiratory flow (PEF) devices (electronic, manual) were assessed for use in screening.Of 77 subjects, 50 participated in Phase I and 27 in Phase II. Six themes informed item development: exposure (smoking, second-hand smoke); health history (family history of lung problems, recurrent chest infections); recent history of respiratory events (clinic visits, hospitalisations); symptoms (respiratory, non-respiratory); impact (activity limitations); and attribution (age, obesity). PEF devices were rated easy to use; electronic values were significantly higher than manual (P<0.0001). Revisions were made to the draft items on the basis of cognitive interviews.Forty-eight candidate items are ready for quantitative testing to select the best, smallest set of questions that, together with PEF, can efficiently identify patients in need of diagnostic evaluation for clinically significant COPD.
| S-EPMC4532157 | biostudies-literature
Project description:Chronic obstructive pulmonary disease (COPD) often remains undiagnosed and untreated. To date, COPD screening/case finding has not been designed to identify clinically significant COPD, disease ready for therapies beyond smoking cessation. Herein, we describe the ongoing prospective, pragmatic cluster-randomized controlled trial to assess specificity and sensitivity of the COPD Assessment in Primary Care To Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE) tool consisting of 5 questions and peak expiratory flow. The tool is designed to identify clinically significant COPD (forced expiratory volume in 1 second [FEV1] to forced vital capacity [FVC] ratio <.70 plus FEV1% predicted <60% or increased risk for exacerbation) and the trial will explore the impact of CAPTURE-based screening on COPD diagnosis and treatment rates in primary care patients. Of a total planned enrollment of 5000 English- or Spanish-speaking patients 45 to 80 years of age without a prior COPD diagnosis from 100 primary care practices, a total of 68 practices and 3064 patients have been enrolled in the study. Practices are centrally randomized to either usual care or clinician receipt of patient-level CAPTURE results. All clinicians receive basic COPD education with those in intervention practices also receiving CAPTURE interpretation education. In a single visit, patient participants complete a CAPTURE screening, pre- and post-bronchodilator spirometry and baseline demographic and health questionnaires to validate CAPTURE sensitivity, specificity, and predictive value of identifying undiagnosed, clinically significant COPD. One-year follow-up chart reviews and participant surveys assess the impact of sharing versus not sharing CAPTURE results with clinicians on clinical outcomes including level of respiratory symptoms and events and clinicians' initiation of recommendation-concordant COPD care. This is one of the first U.S. studies to validate and assess impact of a simple COPD screening tool in primary care.
| S-EPMC8047605 | biostudies-literature
Project description:BackgroundChronic obstructive pulmonary disease (COPD) is widely underdiagnosed, but the most effective approach for identifying these patients is unknown.AimsThe aim of this study was to summarise and compare the effectiveness of different case finding approaches for undiagnosed COPD in primary care.MethodsA systematic review of primary studies of any design evaluating case finding strategies for COPD in primary care among individuals aged ⩾35 years with no prior diagnosis was conducted. Medline, Embase and other bibliographic databases were searched from 1997 to 2013, and methodological quality was assessed using standard tools. Results were described and meta-analysis of the uptake and yield from different approaches was performed where there was sufficient homogeneity.ResultsThree randomised controlled trials (RCTs), 1 controlled trial and 35 uncontrolled studies were identified that assessed the identification of new cases of COPD through systematic case finding. A range of approaches were used including pre-screening with questionnaires (n=13) or handheld flow meters (n=5) or direct invitation to diagnostic spirometry (n=30). Overall, any approach identified more undiagnosed COPD compared with usual care. Targeting those at higher risk (e.g., smokers) and pre-screening (e.g., using questionnaires) is likely to increase the yield. However, studies were heterogeneous and were limited by a lack of comparison groups, inadequate reporting and diversity in the definition of COPD, which limited our ability to draw firm conclusions.ConclusionsThere is extensive heterogeneity among studies evaluating case finding strategies for COPD, with few RCTs. Well-conducted RCTs comparing case finding approaches are needed to identify the most effective target population, recruitment strategy and screening tests, using a clinical definition of COPD, and addressing the limitations highlighted in this review. There is also a need to evaluate the impact of case finding on clinical care and patient outcomes.
| S-EPMC4551096 | biostudies-literature
Project description:Clinical case reports are the 'eyewitness reports' of medicine and provide a valuable, unique, albeit noisy and underutilized type of evidence. Generally, a case report has a single main finding that represents the reason for writing up the report in the first place. However, no one has previously created an automatic way of identifying main finding sentences in case reports. We previously created a manual corpus of main finding sentences extracted from the abstracts and full text of clinical case reports. Here, we have utilized the corpus to create a machine learning-based model that automatically predicts which sentence(s) from abstracts state the main finding. The model has been evaluated on a separate manual corpus of clinical case reports and found to have good performance. This is a step toward setting up a retrieval system in which, given one case report, one can find other case reports that report the same or very similar main findings. The code and necessary files to run the main finding model can be downloaded from https://github.com/qi29/main_ finding_recognition, released under the Apache License, Version 2.0.
| S-EPMC7287507 | biostudies-literature
Project description:Previous research in Victoria, Australia, found differences in prostate cancer outcomes in regional and metropolitan areas. This investigation of undiagnosed men in regional areas and a metropolitan area of South Australia sought their perspectives on prostate cancer. Our aim was to learn whether men who had not been diagnosed could shed light on why men outside metropolitan areas tended to have poorer outcomes than metropolitan men. Our goal was to build on evidence contributing to improving outcomes in prostate cancer care. Semi-structured interviews were designed to elicit explanation and meaning. 15 men (10 metropolitan, 5 regional) not diagnosed with prostate cancer were recruited through widely-distributed flyers in medical and community settings. Interviews were recorded and transcribed; transcripts were analysed thematically. Five main themes were identified, four of which were prompted by the questions: Addressing prostate health, Experiences with and expectations of GPs, Differences in care between regional and metropolitan areas, and Achieving early diagnosis. The fifth theme arose spontaneously: Australian masculinity. Men identified as problematic the limited availability of GPs in regional areas, the lack of consistency in approaches to prostate cancer detection, and men's reluctance to seek medical care. Community-level strategies appear to be valued to encourage men to address prostate health. Maintaining and extending a systemic approach to prostate care may improve outcomes for men in Australia.
| S-EPMC6405086 | biostudies-literature
Project description:BackgroundMany people with clinically significant chronic obstructive pulmonary disease (COPD) remain undiagnosed worldwide. There are a number of small studies which have examined possible methods of case finding through primary care, but no large RCTs that have adequately assessed the most cost-effective approach.Methods/designIn this study, using a cluster randomised controlled trial (RCT) in 56 general practices in the West Midlands, we plan to investigate the effectiveness and cost-effectiveness of a Targeted approach to case finding for COPD compared with routine practice. Using an individual patient RCT nested in the Targeted arm, we plan also to compare the effectiveness and cost-effectiveness of Active case finding using a postal questionnaire (with supplementary opportunistic questionnaires), and Opportunistic-only case finding during routine surgery consultations.All ever-smoking patients aged 40-79 years, without a current diagnosis of COPD and registered with participating practices will be eligible. Patients in the Targeted arm who report positive respiratory symptoms (chronic cough or phlegm, wheeze or dyspnoea) using a brief questionnaire will be invited for further spirometric assessment to ascertain whether they have COPD or not. Post-bronchodilator spirometry will be conducted to ATS standards using an Easy One spirometer by trained research assistants.The primary outcomes will be new cases of COPD and cost per new case identified, comparing targeted case finding with routine care, and two types of targeted case finding (active versus opportunistic). A multilevel logistic regression model will be used to model the probability of detecting a new case of COPD for each treatment arm, with clustering of patients (by practice and household) accounted for using a multi-level structure.A trial-based analysis will be undertaken using costs and outcomes collected during the trial. Secondary outcomes include the feasibility, efficiency, long-term cost-effectiveness, patient and primary care staff views of each approach.DiscussionThis will be the largest RCT of its kind, and should inform how best to identify undiagnosed patients with COPD in the UK and other similar healthcare systems. Sensitivity analyses will help local policy-makers decide which sub-groups of the population to target first.Trial registrationCurrent controlled trials ISRCTN14930255.
| S-EPMC4271517 | biostudies-literature
Project description:BackgroundEbstein anomaly (EA) is a rare congenital abnormality of the tricuspid valve which can lead to progressive right heart dilatation and arrhythmias. While often seen in conjunction with other congenital cardiac lesions, such as atrial septal defects, it is not normally associated with atrial myxomas.Case summaryWe present a case report of an incidental finding of a right atrial myxoma in the context of undiagnosed EA, in a 16-year-old male who presented with appendicitis. Subtle cardiomegaly on routine chest X-ray prompted further investigation, which demonstrated characteristic findings of both conditions and culminated in surgical repair using the Cone procedure. At 4-month follow-up, the patient was asymptomatic, and transthoracic echocardiography demonstrated a mean gradient of 4.5 mmHg across the tricuspid valve with mild regurgitation.DiscussionThe combination of EA with right-sided myxoma is exceedingly rare, and, in this case, it may be that the apical displacement of the tricuspid valve was protective against right atrioventricular obstruction. We are reminded that although subtle abnormalities on routine investigations can be of limited significance, they can also indicate more serious underlying pathology and so consideration should be given to an appropriate cascade of further investigations to yield a timely diagnosis and enable prompt treatment.
| S-EPMC10660375 | biostudies-literature
Project description:The global tuberculosis (TB) control plan has historically emphasized passive case finding (PCF) as the most practical approach for identifying TB suspects in high burden settings. The success of this approach in controlling TB depends on infectious individuals recognizing their symptoms and voluntarily seeking diagnosis rapidly enough to reduce onward transmission. It now appears, at least in some settings, that more intensified case-finding (ICF) approaches may be needed to control TB transmission; these more aggressive approaches for detecting as-yet undiagnosed cases obviously require additional resources to implement. Given that TB control programs are resource constrained and that the incremental yield of ICF is expected to wane over time as the pool of undiagnosed cases is depleted, a tool that can help policymakers to identify when to implement or suspend an ICF intervention would be valuable. In this article, we propose dynamic case-finding policies that allow policymakers to use existing observations about the epidemic and resource availability to determine when to switch between PCF and ICF to efficiently use resources to optimize population health. Using mathematical models of TB/HIV coepidemics, we show that dynamic policies strictly dominate static policies that prespecify a frequency and duration of rounds of ICF. We also find that the use of a diagnostic tool with better sensitivity for detecting smear-negative cases (e.g., Xpert MTB/RIF) further improves the incremental benefit of these dynamic case-finding policies.
| S-EPMC3677479 | biostudies-literature