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1.
Braz. j. med. biol. res ; 44(5): 453-459, May 2011. ilus, tab
Article in English | LILACS | ID: lil-586509

ABSTRACT

Our objective was to determine whether anthropometric measurements of the midarm (MA) could identify subjects with whole body fat-free mass (FFM) depletion. Fifty-five patients (31 percent females; age: 64.6 ± 9.3 years) with mild/very severe chronic obstructive pulmonary disease (COPD), 18 smokers without COPD (39 percent females; age: 49.0 ± 7.3 years) and 23 never smoked controls (57 percent females; age: 48.2 ± 9.6 years) were evaluated. Spirometry, muscle strength and MA circumference were measured. MA muscle area was estimated by anthropometry and MA cross-sectional area by computerized tomography (CT) scan. Bioelectrical impedance was used as the reference method for FFM. MA circumference and MA muscle area correlated with FFM and biceps and triceps strength. Receiver operating characteristic curve analysis showed that MA circumference and MA muscle area cut-off points presented sensitivity and specificity >82 percent to discriminate FFM-depleted subjects. CT scan measurements did not provide improved sensitivity or specificity. For all groups, there was no significant statistical difference between MA muscle area [35.2 (29.3-45.0) cm²] and MA cross-sectional area values [36.4 (28.5-43.3) cm²] and the linear correlation coefficient between tests was r = 0.77 (P < 0.001). However, Bland-Altman plots revealed wide 95 percent limits of agreement (-14.7 to 15.0 cm²) between anthropometric and CT scan measurements. Anthropometric MA measurements may provide useful information for identifying subjects with whole body FFM depletion. This is a low-cost technique and can be used in a wider patient population to identify those likely to benefit from a complete body composition evaluation.


Subject(s)
Adult , Female , Humans , Male , Middle Aged , Arm , Malnutrition/diagnosis , Pulmonary Disease, Chronic Obstructive/complications , Body Composition , Case-Control Studies , Malnutrition/etiology , Malnutrition , Muscle Strength/physiology , Muscle, Skeletal/anatomy & histology , Sensitivity and Specificity , Severity of Illness Index , Tomography, X-Ray Computed
2.
Braz. j. med. biol. res ; 44(1): 46-52, Jan. 2011. ilus, tab
Article in English | LILACS | ID: lil-571365

ABSTRACT

Few studies show patient outcomes over time in chronic obstructive pulmonary disease (COPD). In the present study, we monitored forced expiratory volume in the first second (FEV1) and other manifestations of the disease over 3 years in 133 COPD patients (69 percent males, age = 65 ± 9 years, FEV1 = 59 ± 25 percent) evaluated at baseline. During follow-up, 15 patients (11 percent) died and 23 (17 percent) dropped out. Measurements for 95 (72 percent) COPD patients alive after 3 years were analyzed. FEV1, body mass index (BMI), 6-min walking distance (6MWD), Medical Research Council scale (MRC), Saint George’s Respiratory Questionnaire (SGRQ), Charlson Comorbidity index, and BODE index were obtained at baseline and after 3 years. At baseline, 17 patients (18 percent) presented mild, 39 percent moderate, 19 percent severe, and 24 percent very severe COPD. Predicted FEV1 percent and BMI did not change over the period (P > 0.05). FEV1 in liters [1.25 (0.96-1.72) vs 1.26 (0.88-1.60) L; P < 0.001], 6MWD (438 ± 86 vs 412 ± 100 m; P < 0.001), MRC [1 (1-2) vs 2 (1-3); P = 0.002], Charlson index [3 (3-4) vs4 (3-5); P = 0.009], BODE index (2.2 ± 1.8 vs 2.6 ± 2.3; P = 0.008), and total SGRQ (42 ± 19 vs 44 ± 19 percent; P = 0.041) worsened after 3 years compared to baseline measurements. These data show that COPD patients deteriorated during the 3-year follow-up despite the fact that they had only minor modifications in airway obstruction and body composition. They support the need for comprehensive patient assessment to better identify disease progression.


Subject(s)
Aged , Female , Humans , Male , Middle Aged , Disease Progression , Forced Expiratory Volume/physiology , Pulmonary Disease, Chronic Obstructive/physiopathology , Body Mass Index , Exercise Tolerance/physiology , Follow-Up Studies , Severity of Illness Index , Spirometry
3.
Braz. j. med. biol. res ; 41(10): 860-865, Oct. 2008. graf, tab
Article in English | LILACS | ID: lil-496803

ABSTRACT

Few studies have evaluated the relationship between Airways Questionnaire 20 (AQ20), a measure of the quality of life, scores and physiological outcomes or with systemic markers of disease in patients with chronic obstructive pulmonary disease (COPD). The aim of the present study was to investigate the relationship of forced expiratory volume in 1 s (FEV1), body mass index, fat-free mass index, 6-min walk test (6MWT) results, dyspnea sensation and peripheral oxygen saturation (SpO2) with the quality of life of COPD patients. Ninety-nine patients with COPD (mean age: 64.2 ± 9.2 years; mean FEV1: 60.4 ± 25.2 percent of predicted) were evaluated using spirometry, body composition measurement and the 6MWT. The baseline dyspnea index (BDI) and the Modified Medical Research Council (MMRC) scale were used to quantify dyspnea. Quality of life was assessed using the AQ20 and the St. George's Respiratory Questionnaire (SGRQ). The Charlson index was used to determine comorbidity. The body mass index/airflow obstruction/dyspnea/exercise capacity (BODE) index was also calculated. AQ20 and SGRQ scores correlated significantly with FEV1, SpO2, 6MWT, MMRC and BDI values as did with BODE index. In the multivariate analyses, MMRC or BDI were identified as predictors of AQ20 and SGRQ scores (P < 0.001 in all cases). Thus, the relationship between AQ20 and disease severity is similar to that described for SGRQ. Therefore, the AQ20, a simple and brief instrument, can be very useful to evaluate the general impact of disease when the time allotted for measurement of the quality of life is limited.


Subject(s)
Aged , Female , Humans , Male , Middle Aged , Pulmonary Disease, Chronic Obstructive/physiopathology , Quality of Life , Severity of Illness Index , Body Mass Index , Cohort Studies , Exercise Test , Forced Expiratory Volume , Regression Analysis , Sickness Impact Profile , Spirometry , Surveys and Questionnaires
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