The respiratory physiome: Clustering based on a comprehensive lung function assessment in patients with COPD

Demystification of artificial intelligence for respiratory clinicians managing patients with obstructive lung diseases

INTRODUCTION

Asthma and chronic obstructive pulmonary disease (COPD) are leading causes of morbidity and mortality worldwide. Despite all available diagnostics and treatments, these conditions pose a significant individual, economic and social burden. Artificial intelligence (AI) promises to support clinical decision-making processes by optimizing diagnosis and treatment strategies of these heterogeneous and complex chronic respiratory diseases. Its capabilities extend to predicting exacerbation risk, disease progression and mortality, providing healthcare professionals with valuable insights for more effective care. Nevertheless, the knowledge gap between respiratory clinicians and data scientists remains a major constraint for wide application of AI and may hinder future progress. This narrative review aims to bridge this gap and encourage AI deployment by explaining its methodology and added value in asthma and COPD diagnosis and treatment.

AREAS COVERED

This review offers an overview of the fundamental concepts of AI and machine learning, outlines the key steps in building a model, provides examples of their applicability in asthma and COPD care, and discusses barriers to their implementation.

EXPERT OPINION

Machine learning can advance our understanding of asthma and COPD, enabling personalized therapy and better outcomes. Further research and validation are needed to ensure the development of clinically meaningful and generalizable models.

Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans

BACKGROUND

Treatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subtypes with distinct characteristics, prognoses and genetic associations.

METHODS

New CT emphysema subtypes were identified by unsupervised machine learning on only the texture and location of emphysematous regions on CT scans from 2853 participants in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), a COPD case-control study, followed by data reduction. Subtypes were compared with symptoms and physiology among 2949 participants in the population-based Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study and with prognosis among 6658 MESA participants. Associations with genome-wide single-nucleotide-polymorphisms were examined.

RESULTS

The algorithm discovered six reproducible (interlearner intraclass correlation coefficient, 0.91-1.00) CT emphysema subtypes. The most common subtype in SPIROMICS, the combined bronchitis-apical subtype, was associated with chronic bronchitis, accelerated lung function decline, hospitalisations, deaths, incident airflow limitation and a gene variant near DRD1, which is implicated in mucin hypersecretion (p=1.1 ×10-8). The second, the diffuse subtype was associated with lower weight, respiratory hospitalisations and deaths, and incident airflow limitation. The third was associated with age only. The fourth and fifth visually resembled combined pulmonary fibrosis emphysema and had distinct symptoms, physiology, prognosis and genetic associations. The sixth visually resembled vanishing lung syndrome.

CONCLUSION

Large-scale unsupervised machine learning on CT scans defined six reproducible, familiar CT emphysema subtypes that suggest paths to specific diagnosis and personalised therapies in COPD and pre-COPD.

Study protocol: pneumonia and inhaled corticosteroid treatment patterns in chronic obstructive pulmonary disease - a cohort study using sequence analysis (PICCS)

INTRODUCTION

Treatment with inhaled corticosteroids (ICS) is a widely used treatment in chronic obstructive pulmonary disease. The main effects include a reduction in the number of exacerbations and, for some patients, an increase in expected mortality. Unfortunately, the treatment is also linked to an increased risk of pneumonia, and very little is known about which patients experience this increased risk. There is a need for identification of patient characteristics associated with increased risk of pneumonia and treatment with ICS.

METHODS AND ANALYSIS

This is a register-based cohort study that uses the nationwide Danish registers. Data from several registers in the years 2008-2018 will be merged on an individual level using the personal identification numbers that are unique to every citizen in Denmark. Clusters based on pneumonia incidence and ICS treatment patterns will be explored with a sequence analysis in a 3-year follow-up period.

ETHICS AND DISSEMINATION

This is a register-based study and research ethics approval is not required according to Danish Law and National Ethics Committee Guidelines. The results will be submitted to peer-reviewed journals and reported at appropriate national and international meetings.

Differential Outcomes Following 4 Weeks of Aclidinium/Formoterol in Patients with COPD: A Reanalysis of the ACTIVATE Study

Rationale

It is difficult to predict the effects of long-acting bronchodilators (LABD) on lung function, exercise capacity and physical activity in patients with chronic obstructive pulmonary disease (COPD). Therefore, the multidimensional response to LABD was profiled in COPD patients participating in the ACTIVATE study and randomized to LABD.

Methods

In the ACTIVATE study, patients were randomized to aclidinium bromide/formoterol fumarate (AB/FF) or placebo for four weeks. The primary outcomes included (1) lung function as measured by functional residual capacity (FRC), residual volume (RV), and spirometric outcomes; (2) exercise performance as measured by a constant work rate cycle ergometry test (CWRT); and (3) physical activity (PA) using an activity monitor. Self-organizing maps (SOMs) were used to create an ordered representation of the patients who were randomly assigned to four weeks of AB/FF and cluster them into different outcome groups.

Results

A total of 250 patients were randomized to AB/FF (n = 126) or placebo (n = 124). Patients in the AB/FF group (39.6% women) had moderate-to-severe COPD, static hyperinflation (FRC: 151.4 (27.7)% predicted) and preserved exercise capacity. Six clusters with differential outcomes were identified. Patients in clusters 1 and 2 had significant improvements in lung function compared to the remaining AB/FF-treated patients. Patients in clusters 1 and 3 had significant improvements in CWRT time, and patients in clusters 2, 3 and 6 had significant improvements in PA compared to the remaining AB/FF-treated patients.

Conclusion

Individual responses to 4 weeks of AB/FF-treatment in COPD are differential and the degree of change differs across domains of lung function, exercise capacity and PA. These results indicate that clinical response to LABD therapy is difficult to predict and is non-linear, and show doctors that it is important to look at multiple outcomes simultaneously when evaluating the clinical response to LABD therapy.

Clinical Trial Registration

The original ACTIVATE study was registered on ClinicalTrials.gov, registration number NCT02424344.

Multidimensional outcome assessment of pulmonary rehabilitation in traits-based clusters of COPD patients

Background

Clusters of COPD patients have been reported in order to individualize the treatment program. Neither co-morbidity clusters, nor integrated respiratory physiomics clusters contributed to a better prediction of outcomes. Based on a thoroughly assessed set of pulmonary and extra-pulmonary traits at the start of a pulmonary rehabilitation (PR) program, we recently described seven clusters of COPD patients. The aims of this study are to confirm multidimensional differential response and to assess the potential of pulmonary and extra-pulmonary traits-based clusters to predict this multidimensional response to PR pulmonary in COPD patients.

Methods

Outcomes of a 40-session PR program for COPD patients, referred by a chest physician, were evaluated based on the minimal clinically important difference (MCID) for 6-minute walk distance (6MWD), cycle endurance time, Canadian Occupational Performance Measure performance and satisfaction scores, Hospital Anxiety and Depression Scale anxiety and depression scores, MRC dyspnea grade and St George’s Respiratory Questionnaire. The aforementioned response indicators were used to calculate the overall multidimensional response and patients were grouped in very good, good, moderate and poor responders. In the same way, responses to pulmonary rehabilitation were compared based on seven previously identified pulmonary and extra-pulmonary traits-based clusters.

Results

Of the whole sample, drop out was 19% and 419 patients (55.4% males, age: 64.3 ± 8.8, FEV₁% of predicted: 48.9 ± 20) completed the pulmonary rehabilitation program. Very good responders had significantly worse baseline characteristics with a higher burden of disease, a higher proportion of rollator-users, higher body mass index (BMI), more limitations of activities in daily life, emotional dysfunction, higher symptoms of dyspnea and worse quality of life. Of the seven pre-identified clusters, ‘the overall best functioning cluster’ and ‘the low disease burden cluster’ both including the best 6MWD, the lowest dyspnea score and the overall best health status, demonstrated attenuated outcomes, while in ‘the cluster of disabled patients’, 76% of the patients improved health status with at least 2 times MCID. This ‘cluster of disabled patients’ as well as ‘the multimorbid cluster’, ‘the emotionally dysfunctioning cluster’, ‘the overall worst-functioning cluster’ and ‘the physically dysfunctioning cluster’ all demonstrated improvements in performance and satisfaction for occupational activities (more than 65% of patients improved with > 1MCID), emotional functioning (more than 50% of patients improved with > 1 MCID) and overall health status (more than 58%).

Conclusion

The current study confirms the differential response to pulmonary rehabilitation based on multidimensional response profiling. Cluster analysis of baseline traits illustrates that non-linear, clinically important differences can be achieved in the most functionally and emotionally impaired clusters and that ‘the overall best functional cluster’ as well as ‘the low disease burden cluster’ had an attenuated outcome.

COPD profiles and treatable traits using minimal resources: identification, decision tree and stability over time

Background and objective

Profiles of people with chronic obstructive pulmonary disease (COPD) often do not describe treatable traits, lack validation and/or their stability over time is unknown. We aimed to identify COPD profiles and their treatable traits based on simple and meaningful measures; to develop and validate a decision tree and to explore profile stability over time.

Methods

An observational, prospective study was conducted. Clinical characteristics, lung function, symptoms, impact of the disease (COPD Assessment Test—CAT), health-related quality of life, physical activity, lower-limb muscle strength and functional status were collected cross-sectionally and a subsample was followed-up monthly over six months. A principal component analysis and a clustering procedure with k-medoids were applied to identify profiles. A decision tree was developed and validated cross-sectionally. Stability was explored over time with the ratio between the number of timepoints that a participant was classified in the same profile and the total number of timepoints (i.e., 6).

Results

352 people with COPD (67.4 ± 9.9 years; 78.1% male; FEV1 = 56.2 ± 20.6% predicted) participated and 90 (67.6 ± 8.9 years; 85.6% male; FEV1 = 52.1 ± 19.9% predicted) were followed-up. Four profiles were identified with distinct treatable traits. The decision tree included CAT (< 18 or ≥ 18 points); age (< 65 or ≥ 65 years) and FEV1 (< 48 or ≥ 48% predicted) and had an agreement of 71.7% (Cohen’s Kappa = 0.62, p < 0.001) with the actual profiles. 48.9% of participants remained in the same profile whilst 51.1% moved between two (47.8%) or three (3.3%) profiles over time. Overall stability was 86.8 ± 15%.

Conclusion

Four profiles and treatable traits were identified with simple and meaningful measures possibly available in low-resource settings. A decision tree with three commonly used variables in the routine assessment of people with COPD is now available for quick allocation to the identified profiles in clinical practice. Profiles and treatable traits may change over time in people with COPD hence, regular assessments to deliver goal-targeted personalised treatments are needed.

Stratification of COPD patients towards personalized medicine: reproduction and formation of clusters

BACKGROUND

The global initiative for chronic obstructive lung disease (GOLD) 2020 emphasizes that there is only a weak correlation between FEV₁, symptoms and impairment of the health status of patients with chronic obstructive pulmonary disease (COPD). Various studies aimed to identify COPD phenotypes by cluster analyses, but behavioral aspects besides smoking were rarely included.

METHODS

The aims of the study were to investigate whether (i) clustering analyses are in line with the classification into GOLD ABCD groups; (ii) clustering according to Burgel et al. (Eur Respir J. 36(3):531-9, 2010) can be reproduced in a real-world COPD cohort; and (iii) addition of new behavioral variables alters the clustering outcome. Principal component and hierarchical cluster analyses were applied to real-world clinical data of COPD patients newly referred to secondary care (n = 155). We investigated if the obtained clusters paralleled GOLD ABCD subgroups and determined the impact of adding several variables, including quality of life (QOL), fatigue, satisfaction relationship, air trapping, steps per day and activities of daily living, on clustering.

RESULTS

Using the appropriate corresponding variables, we identified clusters that largely reflected the GOLD ABCD groups, but we could not reproduce Burgel's clinical phenotypes. Adding six new variables resulted in the formation of four new clusters that mainly differed from each other in the following parameters: number of steps per day, activities of daily living and QOL.

CONCLUSIONS

We could not reproduce previously identified clinical COPD phenotypes in an independent population of COPD patients. Our findings therefore indicate that COPD phenotypes based on cluster analysis may not be a suitable basis for treatment strategies for individual patients.

COPD Diagnosis: Time for Disruption

Articulating a satisfactory definition of a disease is surprisingly difficult. Despite the alarming individual, societal and economic burden of chronic obstructive pulmonary disease (COPD), diagnosis is still largely based on a physiologically dominated disease conception, with spirometrically determined airflow limitation as a cardinal feature of the disease. The diagnostic inaccuracy and insensitivity of this physiological disease definition is reviewed considering scientific developments of imaging of the respiratory system in particular. Disease must be approached as a fluid concept in response to new scientific and medical discoveries, but labelling as well as mislabelling someone as diseased, will have enormous individual, social and financial implications. Nosology of COPD urgently needs to dynamically integrate more sensitive diagnostic procedures to detect the breadth of abnormalities early in the disease process. Integration of broader information for the identification of abnormalities in the respiratory system is a cornerstone for research models of underlying pathomechanisms to create a breakthrough in research.

Longitudinal changes in total and regional body composition in patients with chronic obstructive pulmonary disease

Background and objective

Low fat‐free mass (FFM) is common in patients with chronic obstructive pulmonary disease (COPD) and contributes to morbidity and mortality. Few studies have evaluated longitudinal changes in body composition in patients with COPD compared with non‐COPD controls. This study aimed to compare longitudinal changes in total and regional body composition between patients with COPD and non‐COPD controls and investigate predictors of changes in body composition in COPD.

Methods

Patients with COPD and non‐COPD controls participating in the Individualized COPD Evaluation in relation to Ageing (ICE‐Age) study, a single‐centre, longitudinal, observational study, were included. Subjects were assessed at baseline and after 2 years of follow‐up. Among other procedures, body composition was measured by dual‐energy X‐ray absorptiometry scan. The number of exacerbations/hospitalizations 1 year before inclusion and during follow‐up were assessed in patients with COPD.

Results

A total of 405 subjects were included (205 COPD, 87 smoking and 113 non‐smoking controls). Patients with COPD and smoking controls presented a significant decline in total FFM (mean [95% CI]: −1173 [−1527/−820] g and −486 [−816/−156] g, respectively) while body composition remained stable in non‐smoking controls. In patients with COPD, the decline in FFM was more pronounced in legs (−174 [−361/14] g) and trunk (−675 [−944/406] g) rather than in arms (54 [−19/126] g). The predictors of changes in total and regional FFM in patients with COPD were gender, number of previous hospitalizations, baseline values of FFM and BMI.

Conclusion

Patients with COPD present a significant decline in FFM after 2 years of follow‐up, this decline is more pronounced in their legs and trunk.

Patients with chronic obstructive pulmonary disease (COPD) present a significant decline in total, leg and trunk low fat‐free mass (FFM), while arms FFM remains stable after 2 years of follow‐up. We identified a subgroup of patients with preserved FFM at baseline and history of previous hospitalizations that present greater decline in total and leg FFM compared to other patients with COPD.

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Lung function and peak oxygen uptake in chronic obstructive pulmonary disease phenotypes with and without emphysema

Previous studies of associations of forced expiratory lung volume in one second (FEV₁) with peak oxygen uptake (VO_2peak) in chronic obstructive pulmonary disease (COPD) have not taken sex, age and height related variance of dynamic lung volumes into account. Nor have such demographic spread of spirometric measures been considered in studies comparing VO_2peak between COPD phenotypes characterized by degree of emphysema. We aimed to assess the association of FEV_1Z-score with VO_2peak in COPD (n = 186) and investigate whether this association differs between emphysema (E-COPD) and non-emphysema (NE-COPD) phenotypes. Corresponding assessments using standardized percent predicted FEV₁ (ppFEV₁) were performed for comparison. Additionally, phenotype related differences in VO_2peak were compared using FEV_1Z-score and ppFEV₁ as alternative expressions of FEV₁. E-COPD and NE-COPD were defined by transfer factor of the lung for carbon monoxide below and above lower limits of normal (LLN), respectively. The associations were assessed in linear regression models. One unit reduction in FEV_1Z-score was associated with 1.9 (95% CI 1.4, 2.5) ml/kg/min lower VO_2peak. In stratified analyses, corresponding estimates were 2.2 (95% CI 1.4, 2.9) and 1.2 (95% CI 0.2, 2.2) ml/kg/min lower VO_2peak in E-COPD and NE-COPD, respectively. The association did not differ statistically by COPD phenotype (p-value for interaction = 0.153). Similar estimates were obtained in analyses using standardized ppFEV₁. Compared to NE-COPD, VO_2peak was 2.2 (95% CI 0.8, 3.6) and 2.1 (95% CI 0.8, 3.5) ml/kg/min lower in E-COPD when adjusted for FEV_1Z-score and ppFEV₁, respectively. In COPD, FEV_1Z-score is positively associated with VO_2peak. This association was stronger in E-COPD but did not differ statistically by phenotype. Both the association of FEV₁ with VO_2peak and the difference in VO_2peak comparing COPD phenotypes seems independent of sex, age and height related variance in FEV₁. Mechanisms leading to reduction in FEV₁ may contribute to lower VO_2peak in E-COPD.

One-Year Evolution of Symptoms and Health Status of the COPD Multi-Dimensional Phenotypes: Results from the Follow-Up of the STORICO Observational Study

Aim

Describing the 1-year evolution of symptoms and health status in COPD patients enrolled in the STORICO study (observational study on characterization of 24-h symptoms in patients with COPD) classified in multidimensional phenotypes (m-phenotypes).

Methods

In our previous study, we performed an exploratory factor analysis to identify clinical and pathophysiological variables having the greatest classificatory properties, followed by a cluster analysis to group patients into m-phenotypes (mild COPD (MC), mild emphysematous (ME), severe bronchitic (SB), severe emphysematous (SE), and severe mixed COPD (SMC)). COPD symptoms were recorded at baseline, 6-, and 12-month follow-up and their evolution was described as frequency of patients with always present, always absent, arising’, ‘no more present symptoms. QoL and quality of sleep were evaluated using the SGRQ and CASIS questionnaires, respectively.

Results

We analyzed 379 subjects (144 MC, 71 ME, 96 SB, 14 SE, 54 SMC). M-phenotypes were stable over time in terms of presence of symptoms and health status with selected differences in evolution of symptoms in mild vs severe m-phenotypes. Indeed, 28.1% SB, 50.0% SE and 24.1% SMC vs 0.7% MC and 5.6% ME with night-time symptoms at baseline had no more symptoms at 6-month (p-value night-time symptom evolution MC vs SB, SE, SMC and ME vs SB, SE, SMC <0.0001). All m-phenotypes improved in quality of sleep, more markedly the severe than the mild ones (p-values CASIS score change between baseline and 6- or 12-month in MC, ME vs SB, SE, SMC <0.0001). QoL did not change during observation, irrespectively of m-phenotype.

Conclusion

Over 1 year, severe m-phenotypes showed an improvement in night-time symptoms and quality of sleep, but not QoL. Being stable over time, m-phenotypes seem worthy of testing for classificatory and prognostic purposes.

Profiling of Patients with COPD for Adequate Referral to Exercise-Based Care: The Dutch Model

A loss of physical functioning (i.e., a low physical capacity and/or a low physical activity) is a common feature in patients with chronic obstructive pulmonary disease (COPD). To date, the primary care physiotherapy and specialized pulmonary rehabilitation are clearly underused, and limited to patients with a moderate to very severe degree of airflow limitation (GOLD stage 2 or higher). However, improved referral rates are a necessity to lower the burden for patients with COPD and for society. Therefore, a multidisciplinary group of healthcare professionals and scientists proposes a new model for referral of patients with COPD to the right type of exercise-based care, irrespective of the degree of airflow limitation. Indeed, disease instability (recent hospitalization, yes/no), the burden of disease (no/low, mild/moderate or high), physical capacity (low or preserved) and physical activity (low or preserved) need to be used to allocate patients to one of the six distinct patient profiles. Patients with profile 1 or 2 will not be referred for physiotherapy; patients with profiles 3-5 will be referred for primary care physiotherapy; and patients with profile 6 will be referred for screening for specialized pulmonary rehabilitation. The proposed Dutch model has the intention to get the right patient with COPD allocated to the right type of exercise-based care and at the right moment.

Treatable traits qualifying for nonpharmacological interventions in COPD patients upon first referral to a pulmonologist: the COPD sTRAITosphere

Introduction

The present study assessed the prevalence of nine treatable traits (TTs) pinpointing nonpharmacological interventions in patients with COPD upon first referral to a pulmonologist, how these TTs co-occurred and whether and to what extent the TTs increased the odds having a severely impaired health status.

Methods

Data were collected from a sample of 402 COPD patients. A second sample of 381 patients with COPD was used for validation. Nine TTs were assessed: current smoking status, activity-related dyspnoea, frequent exacerbations <12 months, severe fatigue, depressed mood, poor physical capacity, low physical activity, poor nutritional status and a low level of self-management activation. For each TT the odds ratio (OR) of having a severe health status impairment was calculated. Furthermore, a graphic representation was created, the COPD sTRAITosphere, to visualise TTs prevalence and OR.

Results

On average 3.9±2.0 TTs per patient were observed. These TTs occurred relatively independently of each other and coexisted in 151 unique combinations. A significant positive correlation was found between the number of TTs and Clinical COPD Questionnaire total score (r=0.58; p<0.001). Patients with severe fatigue (OR: 8.8), severe activity-related dyspnoea (OR: 5.8) or depressed mood (OR: 4.2) had the highest likelihood of having a severely impaired health status. The validation sample corroborated these findings.

Conclusions

Upon first referral to a pulmonologist, COPD patients show multiple TTs indicating them to several nonpharmacological interventions. These TTs coexist in many different combinations, are relatively independent and increase the likelihood of having a severely impaired health status.

Association between patient-reported outcomes and exercise test outcomes in patients with COPD before and after pulmonary rehabilitation

Background

Over the years, the scope of outcomes assessment in chronic obstructive pulmonary disease (COPD) has broadened, allowing for the evaluation of various patient-reported outcomes (PROs). As it still remains unclear whether and to what extent PROs mirror the exercise performance of patients with COPD, the current study aimed to assess the association between different exercise test outcomes and PROs, before and after pulmonary rehabilitation (PR).

Methods

Correlations between PROs used to describe health-related quality of life (HRQoL), mood status, level of care dependency and dyspnea in patients with COPD and commonly used laboratory- and field-based exercise test outcomes were evaluated in 518 individuals with COPD attending PR.

Results

Overall, correlations between PROs and exercise test outcomes at baseline were statistically significant. The correlation between modified Medical Research Council (mMRC) dyspnea score and 6-min walking distance (6MWD) was strongest (ρ:-0.65; p<0.001). HRQoL related PROs showed weak correlations with exercise outcomes at baseline. Moderate correlations were found between St George’s Respiratory Questionnaire total score and 6MWD (r:-0.53; p<0.001) and maximal workload achieved during cardiopulmonary exercise testing (ρ:-0.48; p<0.001); and between Clinical COPD Questionnaire (CCQ) total score and 6MWD (r:-0.48; p<0.001) and maximal workload (ρ:-0.43; p<0.001). When significant, correlations between changes in exercise test outcomes and changes in PROs after PR were generally very weak or weak. The highest correlation was found between changes in CCQ total score and changes in 6MWD (ρ: − 0.36; p<0.001).

Conclusions

PROs and exercise test outcomes, although significantly correlated with each other, assess different disease features in patients with COPD. Individual PROs need to be supported by additional functional measurements whenever possible, in order to get a more detailed insight in the effectiveness of a PR program.

Trial registration

Netherlands Trial Register (NL3263/NTR3416). Registered 2 May 2012.

Incorporating Comprehensive Assessment Parameters to Better Characterize and Plan Rehabilitation for Persons with Chronic Obstructive Pulmonary Disease

OBJECTIVES

The current management of chronic obstructive pulmonary disease (COPD) largely ignores its heterogeneous pulmonary and extrapulmonary manifestations in the individual patient. This study aimed to identify clusters of patients with COPD based on a thorough traits assessment.

DESIGN

An observational, prospective, single-center study.

SETTING AND PARTICIPANTS

Patients with COPD referred by chest physicians for a comprehensive pulmonary rehabilitation program to CIRO (Horn, the Netherlands) were eligible to participate. CIRO is a specialized pulmonary rehabilitation center in the southern part of the Netherlands for patients with complex underlying respiratory diseases.

METHODS

Clinically stable patients with COPD underwent a comprehensive assessment, including pulmonary traits (airflow limitation, static hyperinflation, gas transfer, respiratory pressures, and arterial blood gases), extrapulmonary functional traits, and health status (quadriceps muscle strength, physical functioning, body composition, comorbidities, symptoms perception, and social and emotional functioning). Clusters were generated using the SOM-Ward Cluster algorithm, a hybrid algorithm that applies the classical hierarchical method of Ward on top of the self-organizing map topology.

RESULTS

Based on the abovementioned attributes of 518 patients with mild to very severe COPD (44% women, age 64.1 ± 9.1 years, forced expiratory volume in the first second 48.6% ± 20.0% of predicted), 7 clusters were identified. Clusters had unique patterns differing in demographics, pulmonary, extrapulmonary functional, and behavioral traits and/or health status.

CONCLUSION AND IMPLICATIONS

The tremendous heterogeneity in pulmonary, extrapulmonary functional and behavioral traits, and health status in patients with COPD supports the need for an individual comprehensive assessment and a goal-directed personalized management strategy.

Early Detection of In-Patient Deterioration: One Prediction Model Does Not Fit All

Supplemental Digital Content is available in the text.

Objectives:

Early detection of subacute potentially catastrophic illnesses using available data is a clinical imperative, and scores that report risk of imminent events in real time abound. Patients deteriorate for a variety of reasons, and it is unlikely that a single predictor such as an abnormal National Early Warning Score will detect all of them equally well. The objective of this study was to test the idea that the diversity of reasons for clinical deterioration leading to ICU transfer mandates multiple targeted predictive models.

Design:

Individual chart review to determine the clinical reason for ICU transfer; determination of relative risks of individual vital signs, laboratory tests and cardiorespiratory monitoring measures for prediction of each clinical reason for ICU transfer; and logistic regression modeling for the outcome of ICU transfer for a specific clinical reason.

Setting:

Cardiac medical-surgical ward; tertiary care academic hospital.

Patients:

Eight-thousand one-hundred eleven adult patients, 457 of whom were transferred to an ICU for clinical deterioration.

Interventions:

None.

Measurements and Main Results:

We calculated the contributing relative risks of individual vital signs, laboratory tests and cardiorespiratory monitoring measures for prediction of each clinical reason for ICU transfer, and used logistic regression modeling to calculate receiver operating characteristic areas and relative risks for the outcome of ICU transfer for a specific clinical reason. The reasons for clinical deterioration leading to ICU transfer were varied, as were their predictors. For example, the three most common reasons—respiratory instability, infection and suspected sepsis, and heart failure requiring escalated therapy—had distinct signatures of illness. Statistical models trained to target-specific reasons for ICU transfer performed better than one model targeting combined events.

Conclusions:

A single predictive model for clinical deterioration does not perform as well as having multiple models trained for the individual specific clinical events leading to ICU transfer.

Effects of Non-Invasive Ventilation Combined with Oxygen Supplementation on Exercise Performance in COPD Patients with Static Lung Hyperinflation and Exercise-Induced Oxygen Desaturation: A Single Blind, Randomized Cross-Over Trial

The effects of non-invasive ventilation (NIV) in addition to supplemental oxygen on exercise performance in patients with chronic obstructive pulmonary disease (COPD) with hyperinflation and exercise-induced desaturation (EID) remain unclear. We hypothesized that these patients would benefit from NIV and that this effect would be an add-on to oxygen therapy. Thirteen COPD patients with a residual volume >150% of predicted, normal resting arterial oxygen pressure (P_aO₂) and carbon-dioxide pressure (P_aCO₂) and EID during a six-minute walk test were included. Patients performed four constant work-rate treadmill tests, each consisting of two exercise bouts with a recovery period in between, wearing an oronasal mask connected to a ventilator and oxygen supply. The ventilator was set to the following settings in fixed order with clockwise rotation: Sham (continuous positive airway pressure (CPAP) 2 cm H₂O, FiO₂ 21%), oxygen (CPAP 2 cm H₂O, FiO₂ 35%), NIV and oxygen (inspiratory positive airway pressure (IPAP) 14 cm H₂O/expiratory positive airway pressure (EPAP) 6 cm H₂O, inspired oxygen fraction (FiO₂) 35%), intermittent (walking: Sham setting, recovery: NIV and oxygen setting). During the first exercise, bout patients walked further with the oxygen setting compared to the sham setting (225 ± 107 vs 120 ± 50 meters, p < 0.05), but even further with the oxygen/NIV setting (283 ± 128 meters; p < 0.05). Recovery time between two exercise bouts was shortest with NIV and oxygen. COPD patients with severe static hyperinflation and EID benefit significantly from NIV in addition to oxygen during exercise and recovery.

The COPD multi-dimensional phenotype: A new classification from the STORICO Italian observational study

Background

This paper is aimed to (i) develop an innovative classification of COPD, multi-dimensional phenotype, based on a multidimensional assessment; (ii) describe the identified multi-dimensional phenotypes.

Methods

An exploratory factor analysis to identify the main classificatory variables and, then, a cluster analysis based on these variables were run to classify the COPD-diagnosed 514 patients enrolled in the STORICO (trial registration number: NCT03105999) study into multi-dimensional phenotypes.

Results

The circadian rhythm of symptoms and health-related quality of life, but neither comorbidity nor respiratory function, qualified as primary classificatory variables. Five multidimensional phenotypes were identified: the MILD COPD characterized by no night-time symptoms and the best health status in terms of quality of life, quality of sleep, level of depression and anxiety, the MILD EMPHYSEMATOUS with prevalent dyspnea in the early-morning and day-time, the SEVERE BRONCHITIC with nocturnal and diurnal cough and phlegm, the SEVERE EMPHYSEMATOUS with nocturnal and diurnal dyspnea and the SEVERE MIXED COPD distinguished by higher frequency of symptoms during 24h and worst quality of life, of sleep and highest levels of depression and anxiety.

Conclusions

Our results showed that properly collected respiratory symptoms play a primary classificatory role of COPD patients. The longitudinal observation will disclose the discriminative and prognostic potential of the proposed multidimensional phenotype.

Trial registration

Trial registration number: NCT03105999, date of registration: 10th April 2017.

Organizational aspects of pulmonary rehabilitation in chronic respiratory diseases

Adult patients with chronic respiratory diseases may suffer from multiple physical (pulmonary and extra-pulmonary), emotional and social features which necessitate a comprehensive, interdisciplinary rehabilitation programme. To date, pulmonary rehabilitation programmes show a lot of variation in setting, content, frequency and duration. Future projects should strive for a standard set of assessment measures to identify patients eligible for pulmonary rehabilitation, taking disease complexity into consideration, which should result in referral to an appropriate rehabilitation setting. Local circumstances may complicate this crucial endeavour.

Personalized medicine for patients with COPD: where are we?

Chronic airflow limitation is the common denominator of patients with chronic obstructive pulmonary disease (COPD). However, it is not possible to predict morbidity and mortality of individual patients based on the degree of lung function impairment, nor does the degree of airflow limitation allow guidance regarding therapies. Over the last decades, understanding of the factors contributing to the heterogeneity of disease trajectories, clinical presentation, and response to existing therapies has greatly advanced. Indeed, diagnostic assessment and treatment algorithms for COPD have become more personalized. In addition to the pulmonary abnormalities and inhaler therapies, extra-pulmonary features and comorbidities have been studied and are considered essential components of comprehensive disease management, including lifestyle interventions. Despite these advances, predicting and/or modifying the course of the disease remains currently impossible, and selection of patients with a beneficial response to specific interventions is unsatisfactory. Consequently, non-response to pharmacologic and non-pharmacologic treatments is common, and many patients have refractory symptoms. Thus, there is an ongoing urgency for a more targeted and holistic management of the disease, incorporating the basic principles of P4 medicine (predictive, preventive, personalized, and participatory). This review describes the current status and unmet needs regarding personalized medicine for patients with COPD. Also, it proposes a systems medicine approach, integrating genetic, environmental, (micro)biological, and clinical factors in experimental and computational models in order to decipher the multilevel complexity of COPD. Ultimately, the acquired insights will enable the development of clinical decision support systems and advance personalized medicine for patients with COPD.

Add-on interventions during pulmonary rehabilitation

Both pulmonary rehabilitation (PR) and chronic obstructive pulmonary disease (COPD) are generic terms and it increasingly becomes clear that rehabilitation programmes need to be tailored to the complexity and circumstances of the individual patient. Indeed, PR is described as a comprehensive, individualized intervention based on thorough assessment of identifiable treatable traits. The current review summarizes ongoing developments regarding additional interventions and tools to facilitate PR and improve outcomes in patients with a chronic respiratory disease.

Comprehensive Lung Function Assessment Does not Allow to Infer Response to Pulmonary Rehabilitation in Patients with COPD

The degree of lung function is frequently used as referral criterion for pulmonary rehabilitation. The efficacy of pulmonary rehabilitation was assessed in 518 chronic obstructive pulmonary disease (COPD) patients, after clustering based on a comprehensive pre-rehabilitation lung function assessment. Mean improvements in dyspnea, exercise performance, health status, mood status and problematic activities of daily life after pulmonary rehabilitation were mostly comparable between the seven clusters, despite significant differences in the degree of lung function. The current study demonstrates no significant relationship between the seven lung-function-based clusters and response to pulmonary rehabilitation. Therefore, baseline lung function cannot be used to identify those who will respond well to pulmonary rehabilitation, and moreover, cannot be used as a criterion for referral to pulmonary rehabilitation in patients with COPD.