Josep Morera

Chronic Obstructive Pulmonary Disease Stage and Health-Related Quality of Life

The 1995 American Thoracic Society statement on the diagnosis and care of patients with chronic obstructive pulmonary disease [1] proposed that a staging system would have many potential applications, including clinical recommendations, prognostication, and health resource planning. Because FEV1 is highly correlated with morbidity and mortality and because knowledge about other potential dimensions of staging was lacking, the American Thoracic Society adopted FEV1 as the basis for staging patients with chronic obstructive pulmonary disease. Health-related quality of life in chronic obstructive pulmonary disease is thought to vary with severity: Stage I chronic obstructive pulmonary disease (FEV1 > 49% of the predicted value) minimally affects health-related quality of life, whereas stage II (FEV1, 35% to 49% of the predicted value) and stage III (FEV1 < 35% of the predicted value) disease are associated with profound deterioration in health-related quality of life [1]. However, little empirical evidence documents the suspected relation between disease stage and health-related quality of life. The European Respiratory Society [2] proposed a staging system that is based on FEV1 but uses different cut-off points. We examined the relation between the American Thoracic Societys system for staging chronic obstructive pulmonary disease and health-related quality of life. Particular attention was given to the influence of self-reported chronic comorbid conditions on the relation between health-related quality of life and severity of chronic obstructive pulmonary disease. Methods Study Sample Between April 1993 and July 1994, we recruited all consecutive male patients with clinical symptoms of chronic obstructive pulmonary disease who were attending outpatient respiratory clinics of participating centers. Two university public referral hospitals and one primary health care center for the population of Barcelona, Spain (an urban area); a public referral hospital for the population of Osona County, Spain (a semirural area in Barcelona Province); and a public referral hospital for the inhabitants of Castellon (an urban area) participated in the study. Inclusion criteria were 1) chronic airflow impairment [defined as FEV1 < 80% of the predicted value, a ratio of FEV1 to FVC 70%, and clinical stability of respiratory disease for at least 1 month before study entry with neither acute clinical decline nor a hospital admission] and 2) an increase in FEV1 less than both 200 mL and 15% after bronchodilator therapy. The study protocol was approved by the institutional review boards of the participating centers. Seventeen of 352 patients recruited were ineligible: Nine had airflow obstruction reversibility, 5 had an FEV1 greater than 80%, 2 had a ratio of FEV1 to FVC greater than 70%, and 1 was mentally incapacitated. Of the 335 patients who met the inclusion criteria, 14 (4.2%) refused to participate. Thus, 321 patients participated in the study. Patient Evaluation We measured FEV1 and FVC by using standard techniques [3] in the 2 months before or after the patient interview. For 90% of patients, questionnaires were administered and spirometry was performed no more than 23 days apart. Results of blood gas analysis done for diagnostic or therapeutic purposes up to 6 months before study enrollment were obtained from patient medical records; these values were available for 98% of patients with an FEV1 of 49% of the predicted value or less and 29% of patients with an FEV1 greater than 49% of the predicted value. Dyspnea was assessed by using an adapted version of the American Thoracic Society dyspnea questionnaire [4, 5] and a 10-point visual analogue scale [6]. The presence of comorbid conditions was determined by asking patients if they had any of 11 chronic conditions. Social class was assigned according to occupation by using an adapted version of the British Registrar Generals Social Classes [7]: class I (professional), class II (intermediate occupations [such as nurse, manager, or schoolteacher]), class III (skilled nonmanual occupations), and classes IV and V (manual occupations). Most patients completed the Spanish versions of the St. Georges Respiratory Questionnaire [8], the Nottingham Health Profile [9], and the 5-item Mental Health Inventory of the Medical Outcome Study 36-item short form health survey [10] on their own. Trained interviewers administered questionnaires to those patients (27%) who had vision problems or were functionally illiterate. Questionnaires were randomly ordered: Half of the study sample responded to the Nottingham Health Profile first, and the other half responded to the St. Georges Respiratory Questionnaire first. The St. Georges Respiratory Questionnaire is a standardized questionnaire that is designed to be completed without assistance. It measures health status and perceived well-being in persons with obstructive airway diseases. The Spanish version of the St. Georges Respiratory Questionnaire has been shown to be conceptually equivalent to the original instrument and similarly valid and reliable [8]. It contains 50 items (76 levels) divided into three sections: Symptoms deals with the frequency and severity of respiratory manifestations, activity relates to activities that cause or are limited by breathlessness, and impacts covers aspects of social function and psychosocial disturbances that result from respiratory diseases. Scores on the St. Georges Respiratory Questionnaire range from 0 (no disturbance of health-related quality of life) to 100 [11]. Mean scores obtained from a sample of persons (n = 74) between 17 and 80 years of age (mean age, 46 years) who had no history of respiratory disease (mean FEV1, 95%) served as reference values (Jones PW. Scoring Manual of the St. Georges Respiratory Questionnaire). The Nottingham Health Profile is a multidimensional health status questionnaire that has been found to be appropriate for Spanish patients with chronic obstructive pulmonary disease [12]. It contains 38 items divided into six aspects of health (energy, pain, emotional reactions, sleep, social isolation, and physical mobility). A total score on the Nottingham Health Profile is calculated as the proportion of affirmative answers and ranges from 0 (no perceived distress) to 100 (maximum perceived distress). Scores from a representative sample of 610 men older than 40 years of age from the general population of Barcelona served as reference values [13]. Mental Health Inventory scores range from 0 (worst psychological well-being) to 100 (best psychological well-being) [14]. The severity of chronic obstructive pulmonary disease was staged according to the American Thoracic Society guidelines [15] as follows: stage I, FEV1 greater than 49% of the predicted value; stage II, FEV (1) 35% to 49% of the predicted value; and stage III, FEV1 less than 35% of the predicted value. Predicted FEV1 values were taken from a sample of Mediterranean persons [16]. Categories of Pao 2 included no hypoxemia (Pao 2 >87 mm Hg), mild hypoxemia (Pao 2, 75 to 87 mm Hg), and moderate to severe hypoxemia (Pao 2 <75 mm Hg). Statistical Analysis The Kruskal-Wallis test (with correction for ties when necessary) was used to compare health-related quality-of-life scores with clinical and functional categories of chronic obstructive pulmonary disease. The Spearman correlation coefficient (r) was calculated to assess the association between health-related quality-of-life scores and clinical or functional variables. Differences in health-related quality-of-life scores and other continuous variables according to the presence of comorbid conditions were tested by using the t-test. The Statistical Package for the Social Sciences [17] was used for calculations. Multivariate linear regression was used to identify variables that were associated with total scores on the Nottingham Health Profile and the St. Georges Respiratory Questionnaire. Residual values from parametric regression were distributed normally. We used SAS software [18] to assess the adjusted least-squares means. Results Demographic and clinical characteristics of the study sample are shown in Table 1. The mean age of the patients was 64.9 9.6 years; more than two thirds of the patients were retired. One hundred thirty-one patients (41%) had stage I disease (mean percentage of predicted FEV1 SD, 62.9% 8.4%), 76 patients (24%) had stage II disease (mean percentage of predicted FEV1, 41.8% 4.2%), and 114 patients (35%) had stage III disease (mean percentage of predicted FEV1, 25.3% 6.0%). Eighty-four percent of patients reported at least one coexisting chronic condition; osteoarthritis was the most prevalent (37.7% of patients). Table 1. Characteristics of 321 Men with Chronic Obstructive Pulmonary Disease Both specific and generic health-related quality-of-life instruments showed decreased health-related quality of life with increased stage of chronic obstructive pulmonary disease (Table 2). This pattern was shown most clearly and consistently by the St. Georges Respiratory Questionnaire scores (Figure 1). In all sections of the St. Georges Respiratory Questionnaire, scores were moderately to strongly associated with FEV1 categories (r = 0.27 to 0.51). Of note, values for patients with stage I disease showed substantial and statistically significant impairment compared with reference values in all sections of the St. Georges Respiratory Questionnaire (total score, 34 compared with 6; P < 0.001) and the Nottingham Health Profile (total score, 11 compared with 21; P < 0.001). Dyspnea also decreased in a statistically significant manner as FEV1 worsened (Table 2). The association between level of hypoxemia and staging categories for chronic obstructive pulmonary disease was statistically significant only for the activity section of the St. Georges Respiratory Questionnaire. Table 2. Mean Health-Related Quality-of-Life Scores by Clinical and Functional Char

Acoustic analysis of snoring sound in patients with simple snoring and obstructive sleep apnoea

Snoring, a symptom which may indicate the presence of the obstructive sleep apnoea syndrome (OSA), is also common in the general population. Recent studies have suggested that the acoustic characteristics of snoring sound may differ between simple snorers and OSA patients. We have studied a small number of patients with simple snoring and OSA, analysing the acoustic characteristics of the snoring sound. Seventeen male patients, 10 with OSA (apnoea/hypopnoea index (AHI) 26.2 events x h(-1)) and seven simple snorers (AHI 3.8 events x h(-1)), were studied. Full night polysomnography was performed and the snoring sound power spectrum was analysed. Spectral analysis of snoring sound showed the existence of two different patterns. The first pattern was characterized by the presence of a fundamental frequency and several harmonics. The second pattern was characterized by a low frequency peak with the sound energy scattered on a narrower band of frequencies, but without clearly identified harmonics. The seven simple snorers and two of the 10 patients with OSA (AIH 13 and 14 events x h(-1), respectively) showed the first pattern. The rest of the OSA patients showed the second pattern. The peak frequency of snoring was significantly lower in OSA patients, with all but one OSA patient and only one simple snorer showing a peak frequency below 150 Hz. A significant negative correlation was found between AHI and peak and mean frequencies of the snoring power spectrum (p<0.0016 and p<0.0089, respectively). In conclusion, this study demonstrates significant differences in the sound power spectrum of snoring sound between subjects with simple snoring and obstructive sleep apnoea patients.

MEASUREMENT OF GENERAL HEALTH STATUS OF NON-OXYGEN-DEPENDENT CHRONIC OBSTRUCTIVE PULMONARY DISEASE PATIENTS

Chronic obstructive pulmonary disease is a prevalent condition causing a high level of disability, and it is one of the leading causes of death. To assess the general health status of moderate to severe Chronic obstructive pulmonary disease patients, we studied 76 male patients attending an outpatient hospital clinic who were not dependent on oxygen and who did not present bronchial obstruction reversibility. We assessed clinical status (dyspnea, six-minute walking distance) and functional respiratory impairment (spirometry, and blood gas analysis) of the patients and also asked them to respond to the Spanish version of the Nottingham Health Profile, a multi-dimensional generic health status measure. Patients scored especially higher than the general population (denoting more level of distress) in energy, physical mobility and sleep Nottingham Health Profile dimensions. The former two dimensions scores had a high correlation with dyspnea (respectively Spearman Rs = 0.60, and Rs = 0.64; P less than 0.01). High levels of sleep disturbances were found for patients reporting low or very low dyspnea level. Health status measurement (Nottingham Health Profile dimension scores) and functional respiratory impairment were not correlated. Results underscore the importance of measuring symptoms carefully when assessing these patients, whose health status is substantially affected by the Chronic obstructive pulmonary disease. They also suggest that it is relevant to assess sleep disturbances in these patients.

Quality of life in severe chronic obstructive pulmonary disease: correlation with lung and muscle function

UNLABELLED Chronic obstructive pulmonary disease (COPD) patients suffer from significant impairment in quality of life (QL), but the variables related to this impairment are not well known. The aim of this study has been to identify physiological parameters related to QL in severe COPD patients undergoing long-term oxygen therapy. MATERIALS AND METHODS We studied 47 COPD patients using long-term oxygen therapy (43 men/four women, 65.17 SD 8.21 years, 3.17 SD 2.61 years on oxygen). The Nottingham Health Profile (NHP) and activities of daily living (ADL) questionnaire were used to measure QL. Subjective assessment of dyspnoea was performed using a visual analogue scale. The physiological parameters determined were lung function (spirometry, arterial blood gases, lung volumes and carbon monoxide diffusing capacity), muscle function (maximum inspiratory and expiratory pressures, deltoid muscle and handgrip strength), and nutrition status (tricipital skin fold and mid-arm muscle circumference). RESULTS High ADL (8.32 SD 6.97) and NHP scores (energy 63.3 SD 40.43, pain 35.11 SD 31.56, emotional reactions 43.03 SD 25.13, sleep 51.91 SD 32.75, social isolation 30.64 SD 26.98, physical mobility 49.73 SD 24.93) demonstrated clinically significant QL impairment in the severe COPD patients studied. Stepwise multiple regression analysis found a correlation between lung function and QL. Low FEV1% was associated with impairment in energy, physical mobility and social isolation NHP scores and ADL score (r = -0.3, P < 0.05). RV/TLC also correlated with ADL and social isolation scores (r = 0.3, P < 0.05). Lung function explained 39-45% of the variation in these QL dimensions. QL did not correlate with other lung function parameters, muscle function or nutrition status. CONCLUSION COPD patients using long-term oxygen suffer from severe QL impairment affecting not only energy and mobility but also emotional reactions, social isolation and sleep. Lung function is related to energy, mobility and social isolation dimensions, but muscle function is unrelated to QL in these patients.

Variability and effects of bronchial colonisation in patients with moderate COPD

Sputum and lung function were periodically assessed in stable moderate chronic obstructive pulmonary disease (COPD) outpatients to determine relationships between bronchial colonisation and inflammation. Relationships between potentially pathogenic microorganism (PPM) typology, bronchial inflammation (neutrophilia, tumour necrosis factor-α, interleukin (IL)-1β, IL-6, IL-8, IL-10 and IL-12) and post-bronchodilator decline in forced expiratory volume in 1 s (FEV1) were analysed. PPMs periodically showing the same molecular profile using pulse field gel electrophoresis were considered long-term persistent. Bronchial colonisation was observed in 56 out of 79 follow-up examinations (70.9%) and was mainly due to Haemophilus influenzae, Pseudomonas aeruginosa and enterobacteria (n = 47). These PPMs were all related to sputum neutrophilia (p≤0.05, Chi-squared test), and H. influenzae was related to higher levels of IL-1β (p = 0.005) and IL-12 (p = 0.01), with a dose–response relationship (Spearman’s correlation coefficient of 0.38 for IL-1β (p = 0.001), and of 0.32 for IL-12 (p = 0.006)). Haemophilus parainfluenzae was not associated with an identifiable inflammatory response. Long-term persistence of the same strain was observed in 12 examinations (21.4%), mainly due to P. aeruginosa or enterobacteria. A neutrophilic bronchial inflammatory response was associated with a statistically significant decline in FEV1 during follow-up (OR 2.67, 95% CI 1.07–6.62). A load-related relationship to bronchial inflammation in moderate COPD was observed for colonisation by H. influenzae, but not for colonisation by H. parainfluenzae.

Colour of sputum is a marker for bacterial colonisation in chronic obstructive pulmonary disease

BackgroundBacterial colonisation in chronic obstructive pulmonary disease (COPD) contributes to airway inflammation and modulates exacerbations. We assessed risk factors for bacterial colonisation in COPD.MethodsPatients with stable COPD consecutively recruited over 1 year gave consent to provide a sputum sample for microbiologic analysis. Bronchial colonisation by potentially pathogenic microorganisms (PPMs) was defined as the isolation of PPMs at concentrations of ≥102 colony-forming units (CFU)/mL on quantitative bacterial culture. Colonised patients were divided into high (>105 CFU/mL) or low (<105 CFU/mL) bacterial load.ResultsA total of 119 patients (92.5% men, mean age 68 years, mean forced expiratory volume in one second [FEV1] [% predicted] 46.4%) were evaluated. Bacterial colonisation was demonstrated in 58 (48.7%) patients. Patients with and without bacterial colonisation showed significant differences in smoking history, cough, dyspnoea, COPD exacerbations and hospitalisations in the previous year, and sputum colour. Thirty-six patients (62% of those colonised) had a high bacterial load. More than 80% of the sputum samples with a dark yellow or greenish colour yielded PPMs in culture. In contrast, only 5.9% of white and 44.7% of light yellow sputum samples were positive (P < 0.001). Multivariate analysis showed an increased degree of dyspnoea (odds ratio [OR] = 2.63, 95% confidence interval [CI] 1.53-5.09, P = 0.004) and a darker sputum colour (OR = 4.11, 95% CI 2.30-7.29, P < 0.001) as factors associated with the presence of PPMs in sputum.ConclusionsAlmost half of our population of ambulatory moderate to very severe COPD patients were colonised with PPMs. Patients colonised present more severe dyspnoea, and a darker colour of sputum allows identification of individuals more likely to be colonised.

Automatic detection of snoring signals: validation with simple snorers and OSAS patients

Relationship between snoring and Obstructive Sleep Apnea Syndrome (OSAS) has been reported in the literature. Recently, studies of snoring sound intensity, but also estimation of spectral features for each snoring episode, have been published. Usually, patients that are suspected of OSAS pathology are studied by polysomnography during all the night. To analyze the snoring signal, it is very useful to automatically detect each episode, in order to calculate several features that describe the signal. In this work an automatic detection algorithm of acoustic snoring signals has been designed, to work with long duration respiratory sound recordings. Two blocs compose the detector. The former is a segmentation subsystem that detects changes of variance on the signal. The latter is a 2-layer Feedforward Multilayer Neural Network with backpropagation learning algorithm. The network was trained with 625-selected events, including snores with different shapes and characteristics, from normal snorers and OSAS patients, and other sounds. In this way, the detector was designed to select snoring episodes from simple snorers and OSAS patients, and to reject cough, voice and other artifacts. The detector has been applied to real snoring signals recorded during polysomnographic studies. In order to validate the detector, more than 500 snores were analyzed from 10 excerpts, taken at random from a database of 30 snorer subjects with different apnea/hipoanea index (AHI). Results were compared with manual annotations done by a medical doctor. The detector showed a good performance and achieved a Sensitivity of 82% and a Positive Predictive Value of 90%.

Spectral envelope analysis in snoring signals from simple snorers and patients with Obstructive Sleep Apnea

Several studies have shown a relationship between snoring and obstructive sleep apnea syndrome (OSAS). Beyond conventional sound intensity analysis, some spectral differences have been found between snores from simple snores and post-apneic snores from OSAS patients. Snoring spectrum has two components, a fundamental frequency and a spectral envelope. Spectral density studies analyze them altogether. In this work we approach the estimation of the spectral envelope alone, which is closely related to the mechanism of snoring production. Linear prediction autoregressive (AR) modeling with a low order is used for spectral envelope estimation. Two methods are proposed for automatic order estimation. Formant frequencies of the spectral envelope are calculated. A total of 447 snores from 8 simple snorers, and 236 normal and 429 post-apneic snores from 8 OSAS patients are analyzed. Significant differences are found (p<0.005) in formant frequencies variability between simple snorers and OSAS patients, even when non postapneic snores are considered.

Efficacy of moxifloxacin in the treatment of bronchial colonisation in COPD

This study was designed to investigate the efficacy of moxifloxacin for the eradication of bacterial colonisation of the airways in patients with moderate-to-severe chronic obstructive pulmonary disease (COPD). Out of 119 stable patients with COPD screened, 40 (mean age 69 yrs, mean forced expiratory volume in 1 s 50% predicted) were colonised with potentially pathogenic microorganisms (PPMs) and were included in a randomised, double-blind, placebo-controlled trial with moxifloxacin 400 mg daily for 5 days. Eradication rates were 75% with moxifloxacin and 30% with placebo at 2 weeks (p = 0.01). Bacterial persistence at 8 weeks was still higher (not significantly) in the placebo arm (five (25%) out of 20 versus one (5%) out of 20; p = 0.18). The frequencies of acquisition of a new PPM were high and similar in both treatment groups; consequently, the prevalence of colonisation at 8 weeks was also similar between treatment arms. No difference was found in the number of patients with exacerbations during the 5-month follow-up. Only the acquisition of a new PPM during follow-up showed a statistically significant relationship with occurrence of an exacerbation. Moxifloxacin was effective in eradicating PPMs in patients with positive sputum cultures. However, most patients were recolonised after 8 weeks of follow-up. Acquisition of a new strain of bacteria was associated with an increased risk of developing an exacerbation.

Pitch analysis in snoring signals from simple snorers and patients with obstructive sleep apnea

The relationship between snoring and obstructive sleep apnea syndrome (OSAS) has been reported in the literature. Classically, sound intensity and spectral features were the parameters measured for each snoring episode. Recently, studies of pitch analysis in snoring signals have also been published. Availability of automatic detectors of snores, and variability of snoring signal during polysomnography, are the main limitations to analyze the pitch. In this work, we applied an automatic snore detector previously developed by our group. The main goal of this paper is the pitch analysis of snoring signals. For each snoring episode, we calculated different parameters to quantify the pitch: mean value, standard deviation and density of pitch. A total number of 447 inspiratory snores from 8 normal subjects and 236 post-apneic snores from 8 OSAS patients were analyzed, taken at random from a database of 30 snorer subjects with different apnea/hipoapnea index (AHI). Results show a relationship between pitch and snoring patterns. Differences in pitch parameters were found between simple snorers and OSAS patients. A relationship between pitch parameters and AHI is also shown. Pitch analysis of snoring signals provides a promising tool for monitoring snoring activity and their relation with OSAS pathology.