Chronic Obstructive Pulmonary Diseases-Journal of the Copd Foundation最新文献

This study aimed to evaluate the performance of machine learning models for predicting readmission of patients with Chronic Obstructive Pulmonary Disease (COPD) based on administrative data and chart review data. The study analyzed 4,327 patient encounters from the University of Chicago Medicine to assess the risk of readmission within 90 days after an acute exacerbation of COPD. Two random forest prediction models were compared. One was derived from chart review data, while the other was derived using administrative data. The data were randomly partitioned into training and internal validation sets using a 70%/30% split. The two models had comparable accuracy (administrative data AUC = 0.67, chart review AUC = 0.64). These results suggest that despite its limitations in precisely identifying COPD admissions, administrative data may be useful for developing effective predictive tools and offer a less labor-intensive alternative to chart reviews.

Introduction: Lung physiology and chronic obstructive pulmonary disease (COPD) pathophysiology differ between sexes. This post hoc analysis investigated the InforMing the Pathway of COPD Treatment (IMPACT) trial outcomes by patient sex.

Methods: IMPACT was a double-blind, 52-week trial. Patients ≥40 years with symptomatic COPD and a history of exacerbations were randomized 2:2:1 to fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) 100/62.5/25μg, FF/VI 100/25μg, or UMEC/VI 62.5/25μg. Annual rate and risk of moderate/severe exacerbations, change from baseline in trough forced expiratory volume in 1 second (FEV₁) and St George's Respiratory Questionnaire (SGRQ) score, and safety were assessed.

Results: Of 10,355 patients, 66.3% were male. More females reported ≥2 moderate/severe prior exacerbations (58% versus 53%) at screening versus males. Additionally, females had worse mean (standard deviation) SGRQ scores (52.4[15.97] versus 49.8[17.24]) at baseline. FF/UMEC/VI improved annual exacerbation rate, lung function, and health status for both sexes versus dual therapy. The difference in trough FEV₁ across time points with FF/UMEC/VI versus FF/VI was 103mL-110mL in males and 70mL-84mL in females. On-treatment moderate/severe exacerbation rates remained higher for females (FF/UMEC/VI: 0.99; FF/VI: 1.19; UMEC/VI: 1.35) than males (0.87; 1.01; 1.14). Fewer exacerbations were experienced by females with eosinophil counts <150 cells/µL (0.81[0.68, 0.97], p=0.024) or <2 exacerbations in the past year (0.73[0.57, 0.94], p=0.013) with FF/UMEC/VI versus UMEC/VI.

Conclusion: More females with COPD reported exacerbations in the prior year at screening, as well as during the study, versus males, across all treatments. FF/UMEC/VI improved exacerbation rates versus UMEC/VI in females with eosinophil counts <150 cells/µL or <2 exacerbations in the prior year, suggesting inhaled corticosteroids may play an important role in exacerbation reduction for females in this patient population. Clinical Trial Registration: GSK (CTT116855/NCT021645B).

Introduction: A recent study found that the prevalence of chronic obstructive pulmonary disease (COPD) is significantly higher among adults who began smoking cigarettes before (versus after) 15 years of age, independent of current smoking, cigarette pack years, and smoking duration. The current analysis went a step further to also account for secondhand smoke exposure, using data from U.S. adults aged 40+ years during Wave 5 (2018-2019) of the Population Assessment of Tobacco and Health Study.

Methods: Adults who had ever smoked cigarettes were asked at what age they began smoking fairly regularly. Multivariable Poisson regression assessed the risk of self-reported COPD diagnosis due to childhood smoking (<15 years), adjusting for current smoking, cigarette pack years or smoking duration, secondhand smoke exposure, and sociodemographic covariates.

Results: Overall, 13.4% reported that they had COPD. COPD prevalence was 7.5% for adults who never smoked compared to 29.0% and 21.1% for smoking onset at age <15 and 15+ years, respectively. Adults who initiated smoking at <15 (versus 15+) years had a higher prevalence of current smoking (45.9% versus 33.3%), longer smoking duration (mean 34.2 versus 27.3 years), greater cigarette pack years (mean 48.8 versus 30.8), and greater secondhand smoke exposure (p's<0.05). In multivariable analysis, the relative risk for COPD for smoking onset <15 (versus 15+) years of age was 1.27 (95% confidence interval=1.06, 1.51).

Conclusion: The increased risk of COPD due to childhood smoking was independent of cigarette pack years, smoking duration, secondhand smoke exposure, and current smoking. The findings give further evidence of increased COPD risk related to childhood smoking.

Rationale: Acute exacerbations of chronic obstructive pulmonary disease (AECOPDs) are heterogeneous. Machine learning (ML) has previously been used to dissect some of the heterogeneity in COPD. The widespread adoption of electronic health records (EHRs) has led to the rapid accumulation of large amounts of patient data as part of routine clinical care. However, it is unclear whether the implementation of ML in EHR-derived data has the potential to identify subgroups of AECOPD.

Objectives: To determine whether ML implementation using EHR data from severe AECOPDs requiring hospitalization identifies relevant subgroups.

Methods: This study used 2 retrospective cohorts of patients with AECOPDs (non-COVID-19 and COVID-19) treated at Yale-New Haven Hospital. K-means clustering was used to identify patient subgroups.

Measurements and main results: We identified 3 subgroups in the non-COVID cohort (n=1736). Each subgroup had distinct clinical characteristics. The reference subgroup was the largest (n=904), followed by cardio-renal (n=548) and eosinophilic (n=284). The eosinophilic subgroup had milder severity of AECOPD, including a shorter hospital stay (p<0.01). The cardio-renal subgroup had the highest mortality during (5%) and in the year after hospitalization (30%). Validation of the severe AECOPD classifier in the COVID-19 cohort recapitulated the characteristics seen in the non-COVID cohort. AECOPD subgroups in the COVID-19 cohort had different interleukin (IL)-1 beta, IL-2R, and IL-8 levels (false discovery rate ≤ 0.05). These specific leukocyte and cytokine profiles resulted in inflammatory differences between the AECOPD subgroups based on C-reactive protein levels.

Conclusions: Incorporating ML with EHR data allows the identification of specific clinical and biological subgroups for severe AECOPD.

Background: Continuous respiratory monitoring can support integrated care for chronic obstructive pulmonary disease (COPD) patients, by coupling them with remote clinical personnel who triage patients in coordination with their health care providers. When deploying such services, there remains uncertainty surrounding outcomes when at-risk patients are proactively identified and escalated for provider evaluation. This study presents findings from a service deployed in a real-world COPD cohort by analyzing the clinical interventions made during in-person and telehealth pulmonary outpatient visits following remote escalations.

Methods: A single-center, retrospective, observational study of real-world COPD patients at a multisite pulmonary practice was conducted. Patients who were enrolled in a continuous respiratory monitoring service for at least one year and were seen by a provider within 7 days of an escalation by the service (N=168) were included. To evaluate the potential impact of these escalations on provider and patient burden, medical charts from outpatient visits were manually reviewed and grouped into 6 categories based on the clinical action(s) taken by the provider.

Results: A total of 245 outpatient visits occurred from 168 patients within 7 days of escalation. Of the 245 visits, 206 (84.1%) resulted in clinical intervention and 163 (66.5%) resulted in treatment consistent with acute exacerbations of COPD. A total of 1.6% of the outpatient visits resulted in referral to the emergency department.

Conclusion: Provider encounters occurring following the escalation of a patient from a continuous respiratory monitoring service consistently resulted in that provider administering a treatment to the escalated patient.

Rationale: Evidence-based guidelines recommend screening all individuals with chronic obstructive pulmonary disease (COPD) for the genetic disorder alpha-1 antitrypsin deficiency (AATD). However, it is estimated that only 5% of people with COPD have been tested for AATD, and a large fraction of the estimated 70,000 to 100,000 Americans with AATD have not yet been diagnosed. Low familiarity with AATD and limited knowledge about diagnostic tests and available treatments contribute to suboptimal screening rates.

Objectives: Our objective was to address barriers to and improve rates of guideline-based AATD diagnostic testing among racially and ethnically diverse patients with COPD at a large community health center.

Methods: A quality improvement initiative consisting of educational sessions and electronic health record (EHR) system interventions was implemented to improve the adoption of guideline-based screening for AATD in patients with COPD.

Results: An analysis of EHR data demonstrated that among patients with a COPD diagnosis (n=1030), 22.2% (n=229) were screened for AATD in the 12 months following the start of the quality improvement initiative compared with 1.3% (n=13) of patients with a COPD diagnosis (n=972) seen in the 12 months prior to the start of the quality improvement initiative (P<0.001).

Conclusions: A quality improvement initiative consisting of educational sessions and EHR system modifications was successful in increasing clinicians' knowledge and diagnostic screening rates for AATD in patients with COPD at a large community health center.

Alpha-1 antitrypsin (AAT) deficiency is an autosomal codominant disorder caused by SERPINA1 gene mutations. PI*Z and PI*S mutations commonly underlie this deficiency, but rarer homozygous PI*Null (Q0) mutations may result in a complete loss of AAT. Such rare mutations lead to severe AAT deficiency and early onset of lung disease. We present a case of a 35-year-old female never-smoker born to consanguineous parents who developed severe panlobular emphysema and end-stage respiratory insufficiency requiring lung transplantation. Subsequent genetic testing identified her as homozygous for a novel c.82del mutation-here named Q0_Bani-Yas based on the region of the primary carrier's origin-which resulted in undetectable levels of the AAT protein.

Background: Falls are frequent among people with chronic obstructive pulmonary disease (COPD) and are associated with increased morbidity, mortality, and health care costs. Understanding modifiable medication factors that contribute to fall risk is an important step to developing fall prevention strategies for this highly susceptible group.

Methods: This is a retrospective cohort study using electronic health record data from a single health system linked to Washington State death certificates of adults ages 40 or older who died between 2014-2018 with COPD. We identified demographics, comorbidities, fall-risk increasing drug (FRID) burden, and the occurrence of injurious falls within the 2 years prior to the date of death. We defined injurious falls using published algorithms of the International Classification of Diseases codes.

Results: Of 8204 decedents with COPD, 2454 (30%) had an injurious fall in the 2 years before death, and FRID use was common among 65%. A higher percentage of patients with falls received prescriptions for anticonvulsants (35% versus 26%), antipsychotics (24% versus 13%), atypical antidepressants (28% versus 19%), and tricyclic antidepressants (10% versus 5%) versus those without a fall. In multivariable logistic regression, after adjusting for confounders, FRID burden was associated with greater odds of an injurious fall (odds ratio 1.07 [95% confidence interval 1.04-1.09]).

Conclusion: Our findings highlight an opportunity for collaboration between pharmacists, pulmonologists, and patients to develop new processes to potentially deprescribe and optimize the use of FRIDs among patients with COPD to increase safety.

Background: Chronic obstructive pulmonary disease (COPD) is a progressive respiratory disease associated with respiratory muscle weakness and activity-limiting symptoms such as dyspnea. Respiratory muscle strength training (RMST) is an empirically validated therapy to increase respiratory muscle strength. The theoretically-informed, technology-enhanced RESPiratory FITness (RESP-FIT) intervention for COPD is a 6-week combined inspiratory and expiratory muscle strength training program with symptom measurement in real time via ecological momentary assessment (EMA).

Objectives: In addition to hypothesis-generating purposes, the purpose of this randomized control pilot study was to explore whether observed effects (on symptoms, patient-reported outcomes, and respiratory muscle strength) support carrying out a future large-scale trial of RESP-FIT.

Methods: A total of 30 adults with COPD were randomized to intervention (n=15) or control groups, with the intervention group undergoing 6 weeks of mHealth-enhanced RMST. Daily symptom data were collected in real time over the 6-week intervention period using EMA.

Results: Compared to the control group, participants in the intervention group reported decreased dyspnea and anxiety, increased happiness, and improved respiratory muscle strength. However, reports of fatigue and sleep disturbance increased in the intervention group compared to the control group.

Conclusion: Results support the hypothesis that the 6-week RESP-FIT program will improve respiratory muscle strength, emotional state (anxiety and happiness), and breathlessness in COPD but may contribute to fatigue, at least in the short term. Future work is needed to determine the efficacy of RESP-FIT, determine mechanisms of action on dyspnea and fatigue, and conduct within-participant comparisons of EMA data to explore individual or environmental fluctuations in COPD symptoms.