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Background Alpha-1 antitrypsin deficiency (AATD) is an autosomal co-dominant condition that predisposes to emphysema, cirrhosis, panniculitis, and vasculitis. Under-recognition has prompted efforts to enhance early detection and testing of at-risk individuals. Direct-to-consumer (DTC) genetic testing represents an additional method of detection. Research Question The study addressed three questions: 1) Does a DTC testing service identify previously undetected individuals with AATD? 2) What was the time interval between initial AATD-related symptoms and initial diagnosis of AATD in such individuals? and 3) What was the behavioral impact of learning about a new diagnosis of AATD through a DTC test? Study Design and Methods In this cross-sectional study, 195,014 individuals responded to a survey within the 23andMe, Inc. research platform. Results Among 195,014 study participants, the allele frequency for either the PI*S and PI*Z AATD variants was 21.6% (6.5% for PI*Z and 15.1% for PI*S); 0.63% were PI*ZZ, half of whom reported having a physician confirm the diagnosis. Approximately 27% of those with physician-diagnosed AATD reported first becoming aware of AATD through the DTC test. Among those newly-aware participants, the diagnostic delay interval was 22.3 years. Participants frequently shared their DTC test results with healthcare providers (HCPs) and the reported impact of learning a diagnosis of AATD was high. For example, 51.1% of PI*ZZ individuals shared their DTC result with an HCP. The odds ratio for PI*ZZ smokers to report smoking reduction as a result of receiving the DTC result was 1.7 [CI 1.4, 2.2] compared to those without a Z allele and for reduced alcohol consumption was 4.0 [CI 2.6, 5.9]. Interpretation In this largest available report on DTC testing for AATD, this test, in combination with clinical follow-up, can help to identify previously undiagnosed AATD patients. Moreover, receipt of the DTC AATD report was associated with positive behavior change, especially among those with risk variants.

A 21-year-old male college student presented for a second opinion with low alpha-1 antitrypsin (AAT) levels and complaints of episodic dyspnea with wheezing and cough. He was a never smoker with a medical history of frequent respiratory tract infections in early childhood and allergy to dander, dust mites, peanuts, and eggs. There was no travel history outside of the continental United States. His mother had asthma. His symptoms were not controlled on inhaled corticosteroids and bronchodilators. His AAT genotype was found to be PI∗SZ, and augmentation therapy (with pooled human-plasma derived AAT) was recommended locally.

Having a strategic plan is important to reach organizational goals. Equally important is knowing how to develop and execute that plan. Also, such plans evolve and are executed in the context of the organization's culture, which is another critical success element. Using a garden metaphor, the arrangement of the plants in the garden is like the strategy. With a good strategy, the arrangement of the plants will be appealing. But the soil in the garden is the organizational culture. If the soil is fouled, no plants will grow, regardless of how appealing the garden plan. This "How We Do It" paper addresses the issue of developing and executing a strategy and then, in a companion piece, the related process of envisioning and cultivating an organizational culture. The strategic planning discussion invokes a "real-win-worth" paradigm to address the real-world case of assuring uniform, best-in-class ICU outcomes across multiple ICUs in a large academic medical center system.

Deficiencies in risk assessment for patients with pulmonary nodules (PNs) contribute to unnecessary invasive testing and delays in diagnosis.What is the accuracy of a novel PN risk model that includes plasma proteins and clinical factors? How does the accuracy compare with that of an established risk model?Based on technology using magnetic nanosensors, assays were developed with seven plasma proteins. In a training cohort (n = 429), machine learning approaches were used to identify an optimal algorithm that subsequently was evaluated in a validation cohort (n = 489), and its performance was compared with the Mayo Clinic model.In the training set, we identified an support vector machine algorithm that included the seven plasma proteins and six clinical factors that demonstrated an area under the receiver operating characteristic curve of 0.87 and met other selection criteria. The resulting risk reclassification model (RRM) was used to recategorize patients with a pretest risk of between 10% and 84%, and its performance was assessed across five risk strata (low, ≤ 10%; moderate, 10%-34%; intermediate, 35%-70%; high, 71%-84%; very high,85%). Stratification by the RRM decreased the proportion of intermediate-risk patients from 26.7% to 10.8% (P .001) and increased the low-risk and high-risk strata from 16.8% to 21.9% (P .001) and from 3.7% to 12.1% (P .001), respectively. Among patients classified as low risk by the RRM and Mayo Clinic model, the corresponding true-negative to false-negative ratios were 16.8 and 19.5, respectively. Among patients classified as very high risk by the RRM and Mayo Clinic model, the corresponding true-positive to false-positive ratios were 28.5 and 17.0, respectively. Compared with the Mayo Clinic model, the RRM provided higher specificity at the low-risk threshold and higher sensitivity at the very high-risk threshold.The RRM accurately reclassified some patients into low-risk and very high-risk categories, suggesting the potential to improve PN risk assessment.

Organizational culture matters Culture is a key driver of organizational performance and underpins strategy. As previously discussed, if the strategy is the plants and the garden plan for a garden, the culture is the soil. Without a healthy culture, nothing will grow, irrespective of how well planned the garden or how beautiful the individual flowers. Using the case of establishing the culture in an institute at the Cleveland Clinic, the article examines an approach to establishing and maintaining an organizational culture. Anchors for this process are a situational assessment of the current culture as a new leader steps in and mindfulness by the leader of how members of the institute should experience the organization. Critical success factors include open communication and establishing psychological safety as well as modeling integrity. Fundamentally, when cultures are grounded in the seven classical virtues—trust, compassion, courage, justice, wisdom, temperance, and hope—they are best positioned to unleash the discretionary effort of its members. When people expend discretionary effort, they do the right thing when nobody is watching and the performance drivers are internal motivation and alignment with mission rather than external drivers to seek reward (carrots) or to avoid punishment (sticks).

Emotional intelligence (EI) has become widely appreciated as an important leadership attribute, in business, education and, increasingly, in health care. Defined as "the capacity to understand your own and others' emotions and to motivate and develop yourself and others in service of improved work performance and enhanced organizational effectiveness," EI is correlated with a number of success attributes in several sectors; for example, in business, with enhanced business performance and enhanced personal career success, and in health care, with enhanced patient satisfaction, lower burnout, lower litigation risk, and enhanced leadership success. While multiple models of EI have evolved, perhaps the most popular model is framed around four general rubrics with component competencies. The general rubrics are: self-awareness, self-management, social awareness, and relationship management. EI can be measured by using available instruments, and it can be learned and taught. Indeed, teaching EI has become increasingly common in health-care organizations in service of improving health care and health-care leadership. Although more research is needed, ample evidence supports the notion that EI is a critical success element for success as a health-care leader, especially because EI competencies differ markedly from the clinical and scientific skills that are core to being a clinician and/or investigator. This review of EI presents evidence in support of the relevance of EI to health care and health-care leadership, discusses how and when EI can be developed among health-care providers, and considers remaining questions.

In the context that leadership matters and that leadership competencies differ from those needed to practice medicine or conduct research, developing leadership competencies for physicians is important. Indeed, effective leadership is needed ubiquitously in health care, both at the executive level and at the bedside (eg, leading clinical teams and problem-solving on the ward). Various leadership models have been proposed, most converging on common attributes, like envisioning a new and better future state, inspiring others around this shared vision, empowering others to effect the vision, modeling the expected behaviors, and engaging others by appealing to shared values. Attention to creating an organizational culture that is informed by the seven classic virtues (trust, compassion, courage, justice, wisdom, temperance, and hope) can also unleash discretionary effort in the organization to achieve high performance. Health care-specific leadership competencies include: technical expertise, not only in one's clinical/scientific arena to garner colleagues' respect but also regarding operations; strategic thinking; finance; human resources; and information technology. Also, knowledge of the regulatory and legislative environments of health care is critical, as is being a problem-solver and lifelong learner. Perhaps most important to leadership in health care, as in all sectors, is having emotional intelligence. A spectrum of leadership styles has been described, and effective leaders are facile in deploying each style in a situationally appropriate way. Overall, leadership competencies can be developed, and leadership development programs are signature features of leading health-care organizations.

Background Hypogammaglobulinemia (serum IgG levels Research Question To determine the relationship between hypogammaglobulinemia and the risk of hospitalization in patients with COPD. Study Design and Methods Serum IgG levels were measured on baseline samples from four COPD cohorts (n = 2,259): Azithromycin for Prevention of AECOPD (MACRO, n = 976); Simvastatin in the Prevention of AECOPD (STATCOPE, n = 653), Long-Term Oxygen Treatment Trial (LOTT, n = 354), and COPD Activity: Serotonin Transporter, Cytokines and Depression (CASCADE, n = 276). IgG levels were determined by immunonephelometry (MACRO; STATCOPE) or mass spectrometry (LOTT; CASCADE). The effect of hypogammaglobulinemia on COPD hospitalization risk was evaluated using cumulative incidence functions for this outcome and deaths (competing risk). Fine-Gray models were performed to obtain adjusted subdistribution hazard ratios (SHR) related to IgG levels for each study and then combined using a meta-analysis. Rates of COPD hospitalizations per person-year were compared according to IgG status. Results The overall frequency of hypogammaglobulinemia was 28.4%. Higher incidence estimates of COPD hospitalizations were observed among participants with low IgG levels compared with those with normal levels (Gray's test, P Interpretation Hypogammaglobulinemia is associated with a higher risk of COPD hospital admissions.

Background Although inhaled therapy reduces exacerbations among patients with COPD, the effectiveness of providing inhaled treatment per risk stratification models remains unclear. Research Question Are inhaled regimens that align with the 2017 Global Initiative for Chronic Obstructive Lung Disease (GOLD) strategy associated with clinically important outcomes? Study Design and Methods We conducted secondary analyses of Long-term Oxygen Treatment Trial (LOTT) data. The trial enrolled patients with COPD with moderate resting or exertional hypoxemia between 2009 and 2015. Our exposure was the patient-reported inhaled regimen at enrollment, categorized as either aligning with, undertreating, or potentially overtreating per the 2017 GOLD strategy. Our primary composite outcome was time to death or first hospitalization for COPD. Additional outcomes included individual components of the composite outcome and time to first exacerbation. We generated multivariable Cox proportional hazard models across strata of GOLD-predicted exacerbation risk (high vs low) to estimate between-group hazard ratios for time to event outcomes. We adjusted models a priori for potential confounders, clustered by site. Results The trial enrolled 738 patients (73.4% men; mean age, 68.8 years). Of the patients, 571 (77.4%) were low risk for future exacerbations. Of the patients, 233 (31.6%) reported regimens aligning with GOLD recommendations; most regimens (54.1%) potentially overtreated. During a 2.3-year median follow-up, 332 patients (44.9%) experienced the composite outcome. We found no difference in time to composite outcome or death among patients reporting regimens aligning with recommendations compared with undertreated patients. Among patients at low risk, potential overtreatment was associated with higher exacerbation risk (hazard ratio, 1.42; 95% CI, 1.09-1.87), whereas inhaled corticosteroid treatment was associated with 64% higher risk of pneumonia (incidence rate ratio, 1.64; 95% CI, 1.01-2.66). Interpretation Among patients with COPD with moderate hypoxemia, we found no difference in clinical outcomes between inhaled regimens aligning with the 2017 GOLD strategy compared with those that were undertreated. These findings suggest the need to reevaluate the effectiveness of risk stratification model-based inhaled treatment strategies.

Comprehensive US epidemiologic data for adult pleural disease are not available.What are the epidemiologic measures related to adult pleural disease in the United States?Retrospective cohort study using Healthcare Utilization Project databases (2007-2016). Adults (≥ 18 years of age) with malignant pleural mesothelioma, malignant pleural effusion, nonmalignant pleural effusion, empyema, primary and secondary spontaneous pneumothorax, iatrogenic pneumothorax, and pleural TB were studied.In 2016, ED treat-and-discharge (TD) visits totaled 42,215, accounting for charges of $286.7 million. In 2016, a total of 361,270 hospitalizations occurred, resulting in national costs of $10.1 billion. A total of 64,174 readmissions contributed $1.16 billion in additional national costs. Nonmalignant pleural effusion constituted 85.5% of ED TD visits, 63.5% of hospitalizations, and 66.3% of 30-day readmissions. Contemporary sex distribution (male to female ratio) in primary spontaneous pneumothorax (2.1:1) differs from older estimates (6.2:1). Decadal analyses of annual hospitalization rates/100,000 adult population (2007 vs 2016) showed a significant (P .001) decrease for malignant pleural mesothelioma (1.3 vs 1.09, respectively), malignant pleural effusion (33.4 vs 31.9, respectively), iatrogenic pneumothorax (17.9 vs 13.9, respectively), and pleural TB (0.20 vs 0.09, respectively) and an increase for empyema (8.1 vs 11.1, respectively) and nonmalignant pleural effusion (78.1 vs 100.1, respectively). Empyema hospitalizations have high costs per case ($38,591) and length of stay (13.8 days). The mean proportion of readmissions attributed to a pleural cause varied widely: malignant pleural mesothelioma, 49%; malignant pleural effusion, 45%; nonmalignant pleural effusion, 31%; empyema, 27%; primary spontaneous pneumothorax, 27%; secondary spontaneous pneumothorax, 27%; and iatrogenic pneumothorax, 20%. Secondary spontaneous pneumothorax had the shortest time to readmission in 2016 (10.3 days, 95% CI, 8.8-11.8 days).Significant epidemiologic trends and changes in various pleural diseases were observed. The analysis identifies multiple opportunities for improvement in management of pleural diseases.

Because teams can accomplish goals that individuals cannot, teams matter. Indeed, teams especially matter in settings such as health care, where favorable outcomes depend critically on the contributions of many different people with diverse skills. As important as effective teambuilding is for health care, how to build teams is often not included in medical curricula, and physicians learn to build teams through "hidden curricula." In the context that we can do better, this "How I Do It" presents an approach to building a team in a common scenario for the chest physician: picking up the inpatient Pulmonary Consult Service. The approach is informed by considering the attributes of an effective team, knowledge of common team dysfunctions, and best practices for building a team. The importance of teambuilding is underscored by substantial evidence that effective teamwork produces superior clinical outcomes.

In the context that leadership matters and that leadership competencies differ from those needed to practice medicine or conduct research, developing leadership competencies for physicians is important. Indeed, effective leadership is needed ubiquitously in healthcare, both at the executive level and at the bedside, e.g., leading clinical teams and problem-solving on the ward. Various leadership models have been proposed, most converging on common attributes – as described by Kouzes and Posner – of envisioning a new and better future state, inspiring others around this shared vision, empowering others to effect the vision, modeling the expected behaviors, and engaging others by appealing to shared values. Attention to creating an organizational culture that is informed by the 7 classic virtues – trust, compassion, courage, justice, wisdom, temperance, and hope – can also unleash discretionary effort in the organization to achieve high performance. Healthcare-specific leadership competencies include technical expertise, not only in one’s clinical/scientific arena in order to garner colleagues’ respect, but also regarding operations, strategic thinking, finance, human resources, and information technology. Also, knowledge of the regulatory and legislative environments of healthcare is critical, as is being a problem-solver and life-long learner. Perhaps most important to leadership in healthcare, as in all sectors, is having emotional intelligence. A spectrum of leadership styles has been described, and effective leaders are facile in deploying each style in a situationally appropriate way. Overall, leadership competencies can be developed and leadership development programs are signature features of leading healthcare organizations.

Emotional intelligence (EI) has become widely appreciated as an important leadership attribute, in business, education and, increasingly, in health care. Defined as "the capacity to understand your own and others' emotions and to motivate and develop yourself and others in service of improved work performance and enhanced organizational effectiveness," EI is correlated with a number of success attributes in several sectors; for example, in business, with enhanced business performance and enhanced personal career success, and in health care, with enhanced patient satisfaction, lower burnout, lower litigation risk, and enhanced leadership success. While multiple models of EI have evolved, perhaps the most popular model is framed around four general rubrics with component competencies. The general rubrics are: self-awareness, self-management, social awareness, and relationship management. EI can be measured by using available instruments, and it can be learned and taught. Indeed, teaching EI has become increasingly common in health-care organizations in service of improving health care and health-care leadership. Although more research is needed, ample evidence supports the notion that EI is a critical success element for success as a health-care leader, especially because EI competencies differ markedly from the clinical and scientific skills that are core to being a clinician and/or investigator. This review of EI presents evidence in support of the relevance of EI to health care and health-care leadership, discusses how and when EI can be developed among health-care providers, and considers remaining questions.

Change is a fact of life; the absence of change creates stagnation. This is perhaps especially true in health care, where progress in treating disease depends on innovation and progress. At the same time, change is often uncomfortable. Thus, it is helpful to model the change process to optimize the chances of successfully effecting change. Furthermore, how to lead change is a critical leadership competency. Three models for leading change are reviewed: the first-the eight stages of change-which was not designed for health care; the second called "switch"; and the third called Amicus, which was uniquely designed for health care. The models share many common features, with the explicit reminder in the third model that physicians should be involved in the change effort early. Although sparse, the evidence does suggest the applicability of these models to health care. Beyond having a roadmap for leading change, it is helpful to assess the worthiness of undertaking a change effort and of predicting the phasic response to change efforts, given that humans are often change-averse. In this regard, both the "payoff matrix" and the change curve, derived from the work of Kübler-Ross on grieving, are offered as tools. Finally, physicians' avidity for change is framed by two opposing vectors. On the one hand, physicians share in the general human aversion to change. On the other hand, physicians are data-reverent and also wish to do their best for patients, which encourages their embrace of ever-increasing evidence and change.

Hypogammaglobulinemia (serum IgG levels 7.0 g/L) has been associated with increased risk of COPD exacerbations but has not yet been shown to predict hospitalizations.To determine the relationship between hypogammaglobulinemia and the risk of hospitalization in patients with COPD.Serum IgG levels were measured on baseline samples from four COPD cohorts (n = 2,259): Azithromycin for Prevention of AECOPD (MACRO, n = 976); Simvastatin in the Prevention of AECOPD (STATCOPE, n = 653), Long-Term Oxygen Treatment Trial (LOTT, n = 354), and COPD Activity: Serotonin Transporter, Cytokines and Depression (CASCADE, n = 276). IgG levels were determined by immunonephelometry (MACRO; STATCOPE) or mass spectrometry (LOTT; CASCADE). The effect of hypogammaglobulinemia on COPD hospitalization risk was evaluated using cumulative incidence functions for this outcome and deaths (competing risk). Fine-Gray models were performed to obtain adjusted subdistribution hazard ratios (SHR) related to IgG levels for each study and then combined using a meta-analysis. Rates of COPD hospitalizations per person-year were compared according to IgG status.The overall frequency of hypogammaglobulinemia was 28.4%. Higher incidence estimates of COPD hospitalizations were observed among participants with low IgG levels compared with those with normal levels (Gray's test, P .001); pooled SHR (meta-analysis) was 1.29 (95% CI, 1.06-1.56, P = .01). Among patients with prior COPD admissions (n = 757), the pooled SHR increased to 1.58 (95% CI, 1.20-2.07, P .01). The risk of COPD admissions, however, was similar between IgG groups in patients with no prior hospitalizations: pooled SHR = 1.15 (95% CI, 0.86-1.52, P =.34). The hypogammaglobulinemia group also showed significantly higher rates of COPD hospitalizations per person-year: 0.48 ± 2.01 vs 0.29 ± 0.83, P .001.Hypogammaglobulinemia is associated with a higher risk of COPD hospital admissions.

We appreciate Drs Nathanson and Oulette’s 1 response and concur that American College of Chest Physicians (now branded as CHEST) evidence-based guidelines (EBGs) are rigorously prepared and are of high quality. Notwithstanding their considerable value, CHEST EBGs still fail to achieve global coverage. To off er global coverage and relevance, EBGs must satisfy the condition of addressing clinical issues and circumstances of global patient populations (ie, patients throughout the range of socioeconomic circumstances and access to health-care technology and expertise). Our colleagues off er four lines of reasoning to defend their “pro” position; we believe that this rebuttal debunks each.