The Laboratory-based Intermountain Validated Exacerbation (LIVE) Score is associated with mortality and chronic obstructive pulmonary disease (COPD) exacerbation risk across multiple health systems. However, whether the LIVE Score and its associated risk is a stable patient characteristic is unknown. We validated the LIVE Score in a fourth health system. Then we determined the LIVE Score stability in a retrospective cohort of 98 766 patients with COPD in four health systems where it was previously validated. We assessed whether LIVE Scores changed or remained the same over time. Stability was defined as a majority of surviving patients having the same LIVE Score 4 years later. The LIVE Score separated patients into three LIVE Score risk groups of low, medium, and high mortality and LIVE Score stability. Mortality ranged from 6.2% for low-risk LIVE to 45.8% for high-risk LIVE (p<0.001). We found that low-risk LIVE groups were stable and high-risk LIVE groups were unstable. Low-risk LIVE group patients remained low risk, but few high-risk LIVE group patients remained high risk (79.0% high vs 48.1% medium vs 8.8% low, p<0.001 for all pairwise comparisons). The LIVE Score identifies three major clinically actionable cohorts: a stable low-risk LIVE group, an unstable high-risk LIVE group with high mortality rates, and a medium-risk LIVE group. These observations further our understanding of how existing data used to calculate the LIVE Score may target interventions across risk cohorts of patients with COPD in a health system.

Background: Identifying COPD patients at high risk for mortality or healthcare utilization remains a challenge. A robust system for identifying high-risk COPD patients using Electronic Health Record (EHR) data would empower targeting interventions aimed at ensuring guideline compliance and multimorbidity management. The purpose of this study was to empirically derive, validate, and characterize subgroups of COPD patients based on routinely collected clinical data widely available within the EHR. Methods: Cluster analysis was used in 5,006 patients with COPD at Intermountain to identify clusters based on a large collection of clinical variables. Recursive Partitioning (RP) was then used to determine a preferred tree that assigned patients to clusters based on a parsimonious variable subset. The mortality, COPD exacerbations, and comorbidity profile of the identified groups were examined. The findings were validated in an independent Intermountain cohort and in external cohorts from the United States Veterans Affairs (VA) and University of Chicago Medicine systems. Measurements and Main Results: The RP algorithm identified five LIVE Scores based on laboratory values: albumin, creatinine, chloride, potassium, and hemoglobin. The groups were characterized by increasing risk of mortality. The lowest risk, LIVE Score 5 had 8% 4-year mortality vs. 56% in the highest risk LIVE Score 1 (p < 0.001). These findings were validated in the VA cohort (n = 83,134), an expanded Intermountain cohort (n = 48,871) and in the University of Chicago system (n = 3,236). Higher mortality groups also had higher COPD exacerbation rates and comorbidity rates. Conclusions: In large clinical datasets across different organizations, the LIVE Score utilizes existing laboratory data for COPD patients, and may be used to stratify risk for mortality and COPD exacerbations.

Rationale: Although chronic obstructive pulmonary disease (COPD) exacerbation frequency is stable in research cohorts, whether severe COPD exacerbation frequency can be used to identify patients at high risk for future severe COPD exacerbations and/or mortality is unknown. Methods: Severe COPD exacerbation frequency stability was determined in 3 distinct clinical cohorts. A total of 17,450 patients with COPD in Intermountain Healthcare were categorized based on the number of severe COPD exacerbations per year. We determined whether exacerbation frequency was stable and whether it predicted mortality. These findings were validated in 83,134 patients from the U.S. Veterans Affairs (VA) nationwide health care system and 3326 patients from the University of Chicago Medicine health system. Results: In the Intermountain Healthcare cohort, the majority (84%, 14,706 patients) had no exacerbations in 2009 and were likely to remain non-exacerbators with a significantly lower 6-year mortality compared with frequent exacerbators (2 or more exacerbations per year) (25% versus 57%, p<0.001). Similar findings were noted in the VA health system and the University of Chicago Medicine health system. Non-exacerbators were likely to remain non-exacerbators with the lowest overall mortality. In all cohorts, frequent exacerbator was not a stable phenotype until patients had at least 2 consecutive years of frequent exacerbations. COPD exacerbation frequency predicted any cause mortality. Conclusions: In clinical datasets across different organizations, severe COPD exacerbation frequency was stable after at least 2 consecutive years of frequent exacerbations. Thus, severe COPD exacerbation frequency identifies patients across a health care system at high risk for future COPD-related health care utilization and overall mortality.

Small pulmonary nodules are most often managed by surveillance imaging with computed tomography (CT) of the chest, but the optimal frequency and duration of surveillance are unknown. The Watch the Spot Trial is a multicenter, pragmatic, comparative-effectiveness trial with cluster randomization by hospital or health system that compares more- versus less-intensive strategies for active surveillance of small pulmonary nodules. The study plans to enroll approximately 35,200 patients with a small pulmonary nodule that is newly detected on chest CT imaging, either incidentally or by screening. Study protocols for more- and less-intensive surveillance were adapted from published guidelines. The primary outcome is the percentage of cancerous nodules that progress beyond American Joint Committee on Cancer seventh edition stage T1a. Secondary outcomes include patient-reported anxiety and emotional distress, nodule-related health care use, radiation exposure, and adherence with the assigned surveillance protocol. Distinctive aspects of the trial include: 1) the pragmatic integration of study procedures into existing clinical workflow; 2) the use of cluster randomization by hospital or health system; 3) the implementation and evaluation of a system-level intervention for protocol-based care; 4) the use of highly efficient, technology-enabled methods to identify and (passively) enroll participants; 5) reliance on data collected as part of routine clinical care, including data from electronic health records and state cancer registries; 6) linkage with state cancer registries for complete ascertainment of the primary study outcome; and 7) intensive engagement with a diverse group of patient and nonpatient stakeholders in the design and execution of the study.

We sought to validate prognostic scores in coronavirus disease 2019 including National Early Warning Score, Modified Early Warning Score, and age-based modifications, and define their performance characteristics.

Design

We analyzed prospectively collected data from the Adaptive COVID-19 Treatment Trial. National Early Warning Score was collected daily during the trial, Modified Early Warning Score was calculated, and age applied to both scores. We assessed prognostic value for the end points of recovery, mechanical ventilation, and death for score at enrollment, average, and slope of score over the first 48 hours.

Setting

A multisite international inpatient trial.

Patients

A total of 1,062 adult nonpregnant inpatients with severe coronavirus disease 2019 pneumonia.

Interventions

Adaptive COVID-19 Treatment Trial 1 randomized participants to receive remdesivir or placebo. The prognostic value of predictive scores was evaluated in both groups separately to assess for differential performance in the setting of remdesivir treatment.

Measurements and main results

For mortality, baseline National Early Warning Score and Modified Early Warning Score were weakly to moderately prognostic (c-index, 0.60-0.68), and improved with addition of age (c-index, 0.66-0.74). For recovery, baseline National Early Warning Score and Modified Early Warning Score demonstrated somewhat better prognostic ability (c-index, 0.65-0.69); however, National Early Warning Score+age and Modified Early Warning Score+age further improved performance (c-index, 0.68-0.71). For deterioration, baseline National Early Warning Score and Modified Early Warning Score were weakly to moderately prognostic (c-index, 0.59-0.69) and improved with addition of age (c-index, 0.63-0.70). All prognostic performance improvements due to addition of age were significant (p < 0.05).

Conclusions

In the Adaptive COVID-19 Treatment Trial 1 cohort, National Early Warning Score and Modified Early Warning Score demonstrated moderate prognostic performance in patients with severe coronavirus disease 2019, with improvement in predictive ability for National Early Warning Score+age and Modified Early Warning Score+age. Area under receiver operating curve for National Early Warning Score and Modified Early Warning Score improved in patients receiving remdesivir versus placebo early in the pandemic for recovery and mortality. Although these scores are simple and readily obtainable in myriad settings, in our data set, they were insufficiently predictive to completely replace clinical judgment in coronavirus disease 2019 and may serve best as an adjunct to triage, disposition, and resourcing decisions.

Background: Since publication of the 2012 Berlin definition of acute respiratory distress syndrome (ARDS), several developments have supported the need for an expansion of the definition, including the use of high-flow nasal oxygen, the expansion of the use of pulse oximetry in place of arterial blood gases, the use of ultrasound for chest imaging, and the need for applicability in resource-limited settings. Methods: A consensus conference of 32 critical care ARDS experts was convened, had six virtual meetings (June 2021 to March 2022), and subsequently obtained input from members of several critical care societies. The goal was to develop a definition that would 1) identify patients with the currently accepted conceptual framework for ARDS, 2) facilitate rapid ARDS diagnosis for clinical care and research, 3) be applicable in resource-limited settings, 4) be useful for testing specific therapies, and 5) be practical for communication to patients and caregivers. Results: The committee made four main recommendations: 1) include high-flow nasal oxygen with a minimum flow rate of ⩾30 L/min; 2) use PaO2:FiO2 ⩽ 300 mm Hg or oxygen saturation as measured by pulse oximetry SpO2:FiO2 ⩽ 315 (if oxygen saturation as measured by pulse oximetry is ⩽97%) to identify hypoxemia; 3) retain bilateral opacities for imaging criteria but add ultrasound as an imaging modality, especially in resource-limited areas; and 4) in resource-limited settings, do not require positive end-expiratory pressure, oxygen flow rate, or specific respiratory support devices. Conclusions: We propose a new global definition of ARDS that builds on the Berlin definition. The recommendations also identify areas for future research, including the need for prospective assessments of the feasibility, reliability, and prognostic validity of the proposed global definition.

Rationale: Diagnosis of chronic obstructive pulmonary disease (COPD) relies on abnormal spirometry. However, spirometry may underestimate the effects of smoking, missing smokers with respiratory disease who have minimal or no airflow obstruction. Objectives: To develop a multidimensional definition of a lung-related "resilient smoker" that is useful in research studies and then identify a resilient smoker subgroup in the SPIROMICS (SubPopulations and InteRmediate Outcome Measures In COPD Study) cohort using this definition. Methods: We performed a three-round modified Delphi survey among a panel of COPD experts to identify and reach a consensus on clinical and radiographic domains to be included in a lung-related resilient smoker definition. Consensus on domains of resilience was defined as ⩾80% of experts voting "agree" or "strongly agree" on a 5-point Likert scale. The Delphi-derived definition of resilience was applied to SPIROMICS to identify resilient smokers, whom we then characterized using known biomarkers of COPD. Results: Consensus was achieved on 6 of 12 diagnostic items, which include cough and sputum production, dyspnea, radiographic measures of emphysema and small airways disease, exacerbations, and decline in forced expiratory volume in 1 second. Although 892 SPIROMICS participants were classified as smokers with preserved lung function by spirometry, only 149 participants (16.7%) qualified as resilient smokers by our definition. Blood biomarker expression of CRP (C-reactive protein) and sTNFRSF1A (soluble tumor necrosis receptor factor1A) was lower in resilient than nonresilient smokers (P = 0.02 and P = 0.03). Conclusions: A Delphi-derived consensus definition of resilient smoker identified 83.3% of smokers with preserved spirometry as "nonresilient" based on the presence of adverse effects of smoking on the lung. Resilient smokers were biologically distinct from nonresilient smokers based on CRP measurements. Clinical trial registered with ClinicalTrials.gov (NCT01969344).

A workshop Electronic Health Records and Pulmonary Function Data: Developing an Interoperability Roadmap was held at the American Thoracic Society 2019 International Conference. Interoperability is defined as is the ability of different information-technology systems and software applications to directly communicate, exchange data, and use the information that has been exchanged. At present, pulmonary function test (PFT) equipment is not required to be interoperable with other clinical data systems, including electronic health records (EHRs). For this workshop, we assembled a diverse group of experts and stakeholders, including representatives from patient-advocacy groups, adult and pediatric general and pulmonary medicine, informatics, government and healthcare organizations, pulmonary function laboratories, and EHR and PFT equipment and software companies. The participants were tasked with two overarching Aobjectives: 1) identifying the key obstacles to achieving interoperability of PFT systems and the EHR and 2) recommending solutions to the identified obstacles. Successful interoperability of PFT data with the EHR impacts the full scope of individual patient health and clinical care, population health, and research. The existing EHR-PFT device platforms lack sufficient data standardization to promote interoperability. Cost is a major obstacle to PFT-EHR interoperability, and incentives are insufficient to justify the needed investment. The current vendor-EHR system lacks sufficient flexibility, thereby impeding interoperability. To advance the goal of achieving interoperability, next steps include identifying and standardizing priority PFT data elements. To increase the motivation of stakeholders to invest in this effort, it is necessary to demonstrate the benefits of PFT interoperability across patient care and population health.

Background

Many advances in health care fail to reach patients. Implementation science is the study of novel approaches to mitigate this evidence-to-practice gap.

Methods

The American Thoracic Society (ATS) created a multidisciplinary ad hoc committee to develop a research statement on implementation science in pulmonary, critical care, and sleep medicine. The committee used an iterative consensus process to define implementation science and review the use of conceptual frameworks to guide implementation science for the pulmonary, critical care, and sleep community and to explore how professional medical societies such as the ATS can promote implementation science.

Results

The committee defined implementation science as the study of the mechanisms by which effective health care interventions are either adopted or not adopted in clinical and community settings. The committee also distinguished implementation science from the act of implementation. Ideally, implementation science should include early and continuous stakeholder involvement and the use of conceptual frameworks (i.e., models to systematize the conduct of studies and standardize the communication of findings). Multiple conceptual frameworks are available, and we suggest the selection of one or more frameworks on the basis of the specific research question and setting. Professional medical societies such as the ATS can have an important role in promoting implementation science. Recommendations for professional societies to consider include: unifying implementation science activities through a single organizational structure, linking front-line clinicians with implementation scientists, seeking collaborations to prioritize and conduct implementation science studies, supporting implementation science projects through funding opportunities, working with research funding bodies to set the research agenda in the field, collaborating with external bodies responsible for health care delivery, disseminating results of implementation science through scientific journals and conferences, and teaching the next generation about implementation science through courses and other media.

Conclusions

Implementation science plays an increasingly important role in health care. Through support of implementation science, the ATS and other professional medical societies can work with other stakeholders to lead this effort.

Background

Clinical trials initiated during emerging infectious disease outbreaks must quickly enroll participants to identify treatments to reduce morbidity and mortality. This may be at odds with enrolling a representative study population, especially when the population affected is undefined.

Methods

We evaluated the utility of the Centers for Disease Control and Prevention's COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), the COVID-19 Case Surveillance System (CCSS), and 2020 United States (US) Census data to determine demographic representation in the 4 stages of the Adaptive COVID-19 Treatment Trial (ACTT). We compared the cumulative proportion of participants by sex, race, ethnicity, and age enrolled at US ACTT sites, with respective 95% confidence intervals, to the reference data in forest plots.

Results

US ACTT sites enrolled 3509 adults hospitalized with COVID-19. When compared with COVID-NET, ACTT enrolled a similar or higher proportion of Hispanic/Latino and White participants depending on the stage, and a similar proportion of African American participants in all stages. In contrast, ACTT enrolled a higher proportion of these groups when compared with US Census and CCSS. The proportion of participants aged ≥65 years was either similar or lower than COVID-NET and higher than CCSS and the US Census. The proportion of females enrolled in ACTT was lower than the proportion of females in the reference datasets.

Conclusions

Although surveillance data of hospitalized cases may not be available early in an outbreak, they are a better comparator than US Census data and surveillance of all cases, which may not reflect the population affected and at higher risk of severe disease.