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David Gillespie,1,2 Nick Francis,3 Haroon Ahmed,4 Kerenza Hood,2 Carl Llor,5 Patrick White,6 Emma Thomas-Jones,2 Helen Stanton,2 Bernadette Sewell,7 Rhiannon Phillips,8 Gurudutt Naik,4 Hasse Melbye,9 Rachel Lowe,2 Nigel Kirby,2 Ann Cochrane,10 Janine Bates,2 Mohammed Fasihul Alam,11 Christopher Butler1 1Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, England, UK; 2Centre for Trials Research, School of Medicine, College of Biomedical & Life Sciences, Cardiff University, Cardiff, Wales, UK; 3Primary Care, Population Sciences and Medical Education, University of Southampton, Southampton, England, UK; 4Division of Population Medicine, School of Medicine, Cardiff University, Cardiff, Wales, UK; 5University Institute in Primary Care Research Jordi Gol, Via Roma Health Centre, Barcelona, Spain; 6School of Population Health and Environmental Sciences, Kings College London, London, England, UK; 7Swansea Centre for Health Economics, Swansea University, Swansea, Wales, UK; 8Cardiff School of Sport & Health Science, Cardiff Metropolitan University, Cardiff, Wales, UK; 9General Practice Research Unit, Department of Community Medicine, UIT the Arctic University of Norway, Tromsø, Norway; 10York Trials Unit, Department of Health Sciences, University of York, York, England, UK; 11Department of Public Health, College of Health Sciences, QU-Health, Qatar University, Doha, QatarCorrespondence: David Gillespie, Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, England, OX2 6GG, UK, Email david.gillespie@phc.ox.ac.ukBackground: It has been demonstrated that antibiotic prescribing for Acute Exacerbations of Chronic Obstructive Pulmonary Disease (AECOPD) can be safely reduced in primary care when general practitioners have access to C-reactive protein (CRP) rapid testing.Aim: To investigate the factors associated with post-consultation COPD health status in patients presenting with AECOPD in this setting.Design and Setting: A cohort study of patients enrolled in a randomised controlled trial. Patients aged 40+ years with a clinical diagnosis of COPD who presented in primary care across England and Wales with an AECOPD were included.Methods: Participants were contacted for follow-up at one- and two-weeks by phone and attended the practice four weeks after the index consultation. The outcome of interest was the Clinical COPD Questionnaire (CCQ) score. Multivariable multilevel linear regression models fitted to examine the factors associated with COPD health status in the four-weeks following consultation for an AECOPD.Results: A total of 649 patients were included, with 1947 CCQ total scores analysed. Post-consultation CCQ total scores were significantly higher (worse) in participants with diabetes (adjusted mean difference [AMD]=0.26; 95% confidence interval (CI) 0.08– 0.45), obese patients compared to those with normal body mass index (AMD = 0.25, 95% CI 0.07– 0.43), and those who were prescribed oral antibiotics in the prior 12 months (AMD = 0.26; 95% CI 0.11– 0.41), but only the two latter associations remained after adjusting for other sociodemographic variables.Conclusion: COPD health status was worse in the four weeks following primary care consultation for AECOPD in patients with obesity and those prescribed oral antibiotics in the preceding year.Keywords: chronic obstructive, health status, Primary Health Care, pulmonary disease, symptom exacerbation

Nick A Francis,1 David Gillespie,2 Mandy Wootton,3 Patrick White,4 Janine Bates,2 Jennifer Richards,3 Hasse Melbye,5 Kerenza Hood,2 Christopher C Butler6 1Primary Care, Population Sciences and Medical Education, University of Southampton, Southampton, England, UK; 2Centre for Trials Research, Cardiff University, Cardiff, Wales, UK; 3Specialist Antimicrobial Chemotherapy Unit, Microbiology Cardiff, Public Health Wales, Cardiff, Wales, UK; 4School of Population Health and Environmental Sciences, King’s College London, London, England, UK; 5Department of Community Medicine, UIT the Arctic University of Norway, Tromsø, Norway; 6Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, England, UKCorrespondence: Nick A FrancisPrimary Care, Population Sciences and Medical Education, University of Southampton, Aldermoor Health Centre, Southampton SO16 5ST, UKEmail nick.francis@soton.ac.ukIntroduction: Identifying predictors of bacterial and viral pathogens in sputum from patients with acute exacerbations of chronic obstructive pulmonary disease (COPD) may help direct management.Methods: We used data from a trial evaluating a C-reactive protein (CRP) point of care guided approach to managing COPD exacerbations in primary care. We used regression analyses to identify baseline clinical features, including CRP value in those randomized to testing, associated with bacterial, viral or mixed infections, defined by the presence of bacterial and viral pathogens in sputum, detected by culture or polymerase chain reaction (PCR), respectively.Results: Of 386 participants with baseline sputum samples, 79 (20.5%), 123 (31.9%), and 91 (23.6%) had bacterial, viral/atypical, and mixed bacterial/viral/atypical pathogens identified, respectively. Increasing sputum purulence assessed by color chart was associated with increased odds of finding bacterial and mixed (bacterial and viral/atypical) pathogens in sputum (area under the ROC curve (AUROC) for bacterial pathogens =0.739 (95% CI: 0.670, 0.808)). Elevated CRP was associated with increased odds of finding bacterial pathogens and mixed pathogens but did not significantly increase the AUROC for predicting bacterial pathogens over sputum color alone (AUROC for combination of sputum color and CRP = 0.776 (95% CI: 0.708, 0.843), p for comparison of models = 0.053). We found no association between the presence of sputum pathogens and other clinical or demographic features.Conclusion: Sputum purulence was the best predictor of sputum bacterial pathogens and mixed bacterial viral/atypical pathogens in patients with COPD exacerbations in our study. Elevated CRP was associated with bacterial pathogens but did not add to the predictive value of sputum purulence.Keywords: COPD, exacerbation, infection, bacteria, sputum, primary care

Laura Nimmon,1,2 Joanna Bates,1,3 Gil Kimel,4,5 Lorelei Lingard6 On behalf of the Heart Failure/Palliative Care Teamwork Research Group 1Centre for Health Education Scholarship, 2Department of Occupational Science and Occupational Therapy, 3Department of Family Practice, Faculty of Medicine, University of British Columbia, 4Palliative Care Program, St Paul’s Hospital, 5Department of Medicine, Division of Internal Medicine, University of British Columbia, Vancouver, BC, 6Centre for Education Research and Innovation, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada Background: Informal caregivers play a vital role in supporting patients with heart failure (HF). However, when both the HF patient and their long-term partner suffer from chronic illness, they may equally suffer from diminished quality of life and poor health outcomes. With the focus on this specific couple group as a dimension of the HF health care team, we explored this neglected component of supportive care. Materials and methods: From a large-scale Canadian multisite study, we analyzed the interview data of 13 HF patient–partner couples (26 participants). The sample consisted of patients with advanced HF and their long-term, live-in partners who also suffer from chronic illness. Results: The analysis highlighted the profound enmeshment of the couples. The couples’ interdependence was exemplified in the ways they synchronized their experience in shared dimensions of time and adapted their day-to-day routines to accommodate each other’s changing health status. Particularly significant was when both individuals were too ill to perform caregiving tasks, which resulted in the couples being in a highly fragile state. Conclusion: We conclude that the salience of this couple group’s oscillating health needs and their severe vulnerabilities need to be appreciated when designing and delivering HF team-based care. Keywords: teamwork, complex adaptive system, palliative care, caregivers, chronic disease, interdependence, dimensions of time

Joseph S Ross,1–4 Jonathan Bates,4 Craig S Parzynski,4 Joseph G Akar,4,5 Jeptha P Curtis,4,5 Nihar R Desai,4,5 James V Freeman,4,5 Ginger M Gamble,4 Richard Kuntz,6 Shu-Xia Li,4 Danica Marinac-Dabic,7 Frederick A Masoudi,8 Sharon-Lise T Normand,9,10 Isuru Ranasinghe,11 Richard E Shaw,12 Harlan M Krumholz2–5 1Section of General Medicine, Department of Medicine, 2Robert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, 3Department of Health Policy and Management, Yale School of Public Health, 4Center for Outcomes Research and Evaluation, Yale–New Haven Hospital, 5Section of Cardiovascular Medicine, Department of Medicine, Yale School of Medicine, New Haven, CT, 6Medtronic Inc, Minneapolis, MN, 7Division of Epidemiology, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, 8Division of Cardiology, Department of Medicine, University of Colorado, Aurora, CO, 9Department of Health Care Policy, Harvard Medical School, 10Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA; 11Discipline of Medicine, University of Adelaide, Adelaide, SA, Australia; 12Department of Clinical Informatics, California Pacific Medical Center, San Francisco, CA, USA Background: Machine learning methods may complement traditional analytic methods for medical device surveillance.Methods and results: Using data from the National Cardiovascular Data Registry for implantable cardioverter–defibrillators (ICDs) linked to Medicare administrative claims for longitudinal follow-up, we applied three statistical approaches to safety-signal detection for commonly used dual-chamber ICDs that used two propensity score (PS) models: one specified by subject-matter experts (PS-SME), and the other one by machine learning-based selection (PS-ML). The first approach used PS-SME and cumulative incidence (time-to-event), the second approach used PS-SME and cumulative risk (Data Extraction and Longitudinal Trend Analysis [DELTA]), and the third approach used PS-ML and cumulative risk (embedded feature selection). Safety-signal surveillance was conducted for eleven dual-chamber ICD models implanted at least 2,000 times over 3 years. Between 2006 and 2010, there were 71,948 Medicare fee-for-service beneficiaries who received dual-chamber ICDs. Cumulative device-specific unadjusted 3-year event rates varied for three surveyed safety signals: death from any cause, 12.8%–20.9%; nonfatal ICD-related adverse events, 19.3%–26.3%; and death from any cause or nonfatal ICD-related adverse event, 27.1%–37.6%. Agreement among safety signals detected/not detected between the time-to-event and DELTA approaches was 90.9% (360 of 396, k=0.068), between the time-to-event and embedded feature-selection approaches was 91.7% (363 of 396, k=–0.028), and between the DELTA and embedded feature selection approaches was 88.1% (349 of 396, k=–0.042).Conclusion: Three statistical approaches, including one machine learning method, identified important safety signals, but without exact agreement. Ensemble methods may be needed to detect all safety signals for further evaluation during medical device surveillance. Keywords: implanted cardioverter–defibrillator, methodology, surveillance

Glendon R Tait,1 Joanna Bates,2 Kori A LaDonna,3 Valerie N Schulz,4 Patricia H Strachan,5 Allan McDougall,3 Lorelei Lingard3 1Department of Psychiatry and Division of Medical Education, Dalhousie University, Halifax, NS, 2Centre for Health Education Scholarship, Vancouver General Hospital, Vancouver, BC, 3Centre for Education Research and Innovation, Schulich School of Medicine and Dentistry, Western University, 4Palliative Care, London Health Sciences Centre, University Hospital, London; 5School of Nursing, McMaster University, Hamilton, ON, Canada Background: Heart failure (HF), one of the three leading causes of death, is a chronic, progressive, incurable disease. There is growing support for integration of palliative care’s holistic approach to suffering, but insufficient understanding of how this would happen in the complex team context of HF care. This study examined how HF care teams, as defined by patients, work together to provide care to patients with advanced disease. Methods: Team members were identified by each participating patient, generating team sampling units (TSUs) for each patient. Drawn from five study sites in three Canadian provinces, our dataset consists of 209 interviews from 50 TSUs. Drawing on a theoretical framing of HF teams as complex adaptive systems (CAS), interviews were analyzed using the constant comparative method associated with constructivist grounded theory. Results: This paper centers on the dominant theme of system practices, how HF care delivery is reported to work organizationally, socially, and practically, and describes two subthemes: “the way things work around here”, which were commonplace, routine ways of doing things, and “the way we make things work around here”, which were more conscious, effortful adaptations to usual practice in response to emergent needs. An adaptive practice, often a small alteration to routine, could have amplified effects beyond those intended by the innovating team member and could extend to other settings. Conclusion: Adaptive practices emerged unpredictably and were variably experienced by team members. Our study offers an empirically grounded explanation of how HF care teams self-organize and how adaptive practices emerge from nonlinear interdependencies among diverse agents. We use these insights to reframe the question of palliative care integration, to ask how best to foster palliative care-aligned adaptive practices in HF care. This work has implications for health care’s growing challenge of providing care to those with chronic medical illness in complex, team-based settings. Keywords: palliative care, qualitative, complex adaptive system, multimorbidity, health care teams

An overview from the past and an outlook for the future of fundamentallaser-plasma interactions research enabled by emerging laser systems.