Extracellular Water Ratio and Phase Angle as Predictors of Exacerbation in Chronic Obstructive Pulmonary Disease
Abstract
:Highlights
- Significant differences in body composition parameters, including the extracellular water/total body water ratio (ECW/TBW) and phase angle (PhA), were observed between frequent and infrequent exacerbators.
- Increased exacerbation frequencies in COPD patients correlate with higher extracellular water ratios and lower phase angles.
- Body composition parameters such as ECW/TBW and PhA might serve as predictive markers for exacerbation risks in COPD patients, aiding targeted clinical interventions. However, larger studies are needed to confirm these findings and enhance their clinical relevance.
- Understanding these associations may enhance the management strategies for COPD, with the aim of reducing exacerbation frequencies and improving patient outcomes through tailored nutritional and therapeutic approaches.
Abstract
1. Introduction
2. Materials and Methods
2.1. Subjects and Study Protocol
2.2. Anthropometric Measurements
2.3. Statistical Analysis
3. Results
3.1. Characteristics of Participants
3.2. Body Composition and HGS in AECOPD Patients with Different COPD-Exacerbating Frequencies
3.3. Factors Associated with COPD-Exacerbating Frequency in AECOPD Patients
3.4. ROC Curve Analyses and Optimum Critical Values in AECOPD Patients
3.5. Body Composition and HGS in COPD Patients with Different COPD-Exacerbating Frequencies
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Larsson, K.; Janson, C.; Lisspers, K.; Ställberg, B.; Johansson, G.; Gutzwiller, F.S.; Mezzi, K.; Bjerregaard, B.K.; Jorgensen, L. The Impact of Exacerbation Frequency on Clinical and Economic Outcomes in Swedish COPD Patients: The ARCTIC Study. Int. J. Chron. Obstruct. Pulmon. Dis. 2021, 16, 701–713. [Google Scholar] [CrossRef]
- Adeloye, D.; Song, P.; Zhu, Y.; Campbell, H.; Sheikh, A.; Rudan, I.; NIHR RESPIRE Global Respiratory Health Unit. Global, regional, and national prevalence of, and risk factors for, chronic obstructive pulmonary disease (COPD) in 2019: A systematic review and modelling analysis. Lancet Respir. Med. 2022, 10, 447–458. [Google Scholar] [CrossRef]
- Burt, L.; Corbridge, S. COPD exacerbations. Am. J. Nurs. 2013, 113, 34–43; quiz 44. [Google Scholar] [CrossRef]
- Vogelmeier, C.F.; Diesing, J.; Kossack, N.; Pignot, M.; Friedrich, F.W. COPD Exacerbation History and Impact on Future Exacerbations—8-Year Retrospective Observational Database Cohort Study from Germany. Int. J. Chron. Obstruct. Pulmon. Dis. 2021, 16, 2407–2417. [Google Scholar] [CrossRef]
- Oussedik, F.; Khelafi, R.; Skander, F. Impact des exacerbations aiguës de BPCO sur la mortalité [The impact of acute exacerbations of COPD on mortality]. Rev. Mal. Respir. 2019, 36, 7–14. [Google Scholar] [CrossRef]
- Anzueto, A. Impact of exacerbations on COPD. Eur. Respir. Rev. 2010, 19, 113–118. [Google Scholar] [CrossRef]
- Huang, W.J.; Fan, X.X.; Yang, Y.H.; Zeng, Y.M.; Ko, C.Y. A review on the Role of Oral Nutritional Supplements in Chronic Obstructive Pulmonary Disease. J. Nutr. Health Aging 2022, 26, 723–731. [Google Scholar] [CrossRef]
- Ferreira, I.M.; Brooks, D.; White, J.; Goldstein, R. Nutritional supplementation for stable chronic obstructive pulmonary disease. Cochrane Database Syst. Rev. 2012, 12, CD000998. [Google Scholar] [CrossRef]
- de Blasio, F.; de Blasio, F.; Miracco Berlingieri, G.; Bianco, A.; La Greca, M.; Franssen, F.M.; Scalfi, L. Evaluation of body composition in COPD patients using multifrequency bioelectrical impedance analysis. Int. J. Chron. Obstruct. Pulmon. Dis. 2016, 11, 2419–2426. [Google Scholar] [CrossRef]
- Machado, F.V.C.; Spruit, M.A.; Coenjaerds, M.; Pitta, F.; Reynaert, N.L.; Franssen, F.M.E. Longitudinal changes in total and regional body composition in patients with chronic obstructive pulmonary disease. Respirology 2021, 26, 851–860. [Google Scholar] [CrossRef]
- Baccioglu, A.; Gulbay, B.E.; Acıcan, T. Body composition in patients with stable chronic obstructive pulmonary disease: Comparison with malnutrition in healthy smokers. Eurasian J. Med. 2014, 46, 169–175. [Google Scholar] [CrossRef]
- Schols, A.M.; Ferreira, I.M.; Franssen, F.M.; Gosker, H.R.; Janssens, W.; Muscaritoli, M.; Pison, C.; Rutten-van Mölken, M.; Slinde, F.; Steiner, M.C.; et al. Nutritional assessment and therapy in COPD: A European Respiratory Society statement. Eur. Respir. J. 2014, 44, 1504–1520. [Google Scholar] [CrossRef]
- Langen, R.C.; Gosker, H.R.; Remels, A.H.; Schols, A.M. Triggers and mechanisms of skeletal muscle wasting in chronic obstructive pulmonary disease. Int. J. Biochem. Cell Biol. 2013, 45, 2245–2256. [Google Scholar] [CrossRef]
- Karanikas, I.; Karayiannis, D.; Karachaliou, A.; Papanikolaou, A.; Chourdakis, M.; Kakavas, S. Body composition parameters and functional status test in predicting future acute exacerbation risk among hospitalized patients with chronic obstructive pulmonary disease. Clin. Nutr. 2021, 40, 5605–5614. [Google Scholar] [CrossRef]
- McNicholl, T.; Dubin, J.A.; Curtis, L.; Mourtzakis, M.; Nasser, R.; Laporte, M.; Keller, H. Handgrip Strength, but Not 5-Meter Walk, Adds Value to a Clinical Nutrition Assessment. Nutr. Clin. Pract. 2019, 34, 428–435. [Google Scholar] [CrossRef]
- Lee, C.T.; Wang, P.H. Handgrip strength during admission for COPD exacerbation: Impact on further exacerbation risk. BMC Pulm. Med. 2021, 21, 245. [Google Scholar] [CrossRef]
- Yee, N.; Locke, E.R.; Pike, K.C.; Chen, Z.; Lee, J.; Huang, J.C.; Nguyen, H.Q.; Fan, V.S. Frailty in Chronic Obstructive Pulmonary Disease and Risk of Exacerbations and Hospitalizations. Int. J. Chron. Obstruct. Pulmon. Dis. 2020, 15, 1967–1976. [Google Scholar] [CrossRef]
- Mete, B.; Pehlivan, E.; Gülbaş, G.; Günen, H. Prevalence of malnutrition in COPD and its relationship with the parameters related to disease severity. Int. J. Chron. Obstruct. Pulmon. Dis. 2018, 13, 3307–3312. [Google Scholar] [CrossRef]
- Hayata, A.; Minakata, Y.; Matsunaga, K.; Nakanishi, M.; Yamamoto, N. Differences in physical activity according to mMRC grade in patients with COPD. Int. J. Chron. Obstruct. Pulmon. Dis. 2016, 11, 2203–2208. [Google Scholar] [CrossRef]
- Cheng, S.L.; Lin, C.H.; Wang, C.C.; Chan, M.C.; Hsu, J.Y.; Hang, L.W.; Perng, D.W.; Yu, C.J.; Wang, H.C.; Taiwan Clinical Trial Consortium for Respiratory Disease (TCORE). Comparison between COPD Assessment Test (CAT) and modified Medical Research Council (mMRC) dyspnea scores for evaluation of clinical symptoms, comorbidities and medical resources utilization in COPD patients. J. Formos. Med. Assoc. 2019, 118, 429–435. [Google Scholar] [CrossRef]
- Kondrup, J.; Allison, S.P.; Elia, M.; Vellas, B.; Plauth, M.; Educational and Clinical Practice Committee, European Society of Parenteral and Enteral Nutrition (ESPEN). ESPEN guidelines for nutrition screening 2002. Clin. Nutr. 2003, 22, 415–421. [Google Scholar] [CrossRef]
- Kroc, Ł.; Fife, E.; Piechocka-Wochniak, E.; Sołtysik, B.; Kostka, T. Comparison of Nutrition Risk Screening 2002 and Subjective Global Assessment Form as Short Nutrition Assessment Tools in Older Hospitalized Adults. Nutrients 2021, 13, 225. [Google Scholar] [CrossRef]
- Lu, Y.; Shu, H.; Zheng, Y.; Li, C.; Liu, M.; Chen, Z.; He, X. Comparison of fat-free mass index and fat mass index in Chinese adults. Eur. J. Clin. Nutr. 2012, 66, 1004–1007. [Google Scholar] [CrossRef]
- Huang, W.J.; Ko, C.Y. Trend effect of high-fat and low-carbohydrate oral nutritional supplements on body composition and handgrip strength in individuals with chronic obstructive pulmonary disease. Curr. Top. Nutraceutical Res. 2024, 22, 39–44. [Google Scholar] [CrossRef]
- Hopkinson, N.S.; Tennant, R.C.; Dayer, M.J.; Swallow, E.B.; Hansel, T.T.; Moxham, J.; Polkey, M.I. A prospective study of decline in fat free mass and skeletal muscle strength in chronic obstructive pulmonary disease. Respir. Res. 2007, 8, 25. [Google Scholar] [CrossRef]
- Yang, L.; Zhu, Y.; Huang, J.A.; Jin, J.; Zhang, X. A Low Lean-to-Fat Ratio Reduces the Risk of Acute Exacerbation of Chronic Obstructive Pulmonary Disease in Patients with a Normal or Low Body Mass Index. Med. Sci. Monit. 2019, 25, 5229–5236. [Google Scholar] [CrossRef]
- Player, E.L.; Morris, P.; Thomas, T.; Chan, W.Y.; Vyas, R.; Dutton, J.; Tang, J.; Alexandre, L.; Forbes, A. Determinants of Smoking Cessation in Patients with COPD Treated in the Outpatient Setting. Chest 2016, 150, 554–562. [Google Scholar] [CrossRef]
- Player, E.L.; Morris, P.; Thomas, T.; Chan, W.Y.; Vyas, R.; Dutton, J.; Tang, J.; Alexandre, L.; Forbes, A. Bioelectrical impedance analysis (BIA)-derived phase angle (PA) is a practical aid to nutritional assessment in hospital in-patients. Clin. Nutr. 2019, 38, 1700–1706. [Google Scholar] [CrossRef]
- Gredic, M.; Blanco, I.; Kovacs, G.; Helyes, Z.; Ferdinandy, P.; Olschewski, H.; Barberà, J.A.; Weissmann, N. Pulmonary hypertension in chronic obstructive pulmonary disease. Br. J. Pharmacol. 2021, 178, 132–151. [Google Scholar] [CrossRef]
- Macnee, W. Right heart function in COPD. Semin. Respir. Crit. Care Med. 2010, 31, 295–312. [Google Scholar] [CrossRef]
- Chang, C.L.; Robinson, S.C.; Mills, G.D.; Sullivan, G.D.; Karalus, N.C.; McLachlan, J.D.; Hancox, R.J. Biochemical markers of cardiac dysfunction predict mortality in acute exacerbations of COPD. Thorax 2011, 66, 764–768. [Google Scholar] [CrossRef]
- de Leeuw, P.W.; Dees, A. Fluid homeostasis in chronic obstructive lung disease. Eur. Respir. J. Suppl. 2003, 46, 33s–40s. [Google Scholar] [CrossRef]
- Pérez-Morales, R.; Donate-Correa, J.; Martín-Núñez, E.; Pérez-Delgado, N.; Ferri, C.; López-Montes, A.; Jiménez-Sosa, A.; Navarro-González, J.F. Extracellular water/total body water ratio as predictor of mortality in hemodialysis patients. Ren. Fail. 2021, 43, 821–829. [Google Scholar] [CrossRef]
- Kyle, U.G.; Bosaeus, I.; De Lorenzo, A.D.; Deurenberg, P.; Elia, M.; Gómez, J.M.; Heitmann, B.L.; Kent-Smith, L.; Melchior, J.C.; Pirlich, M.; et al. Bioelectrical impedance analysis—Part I: Review of principles and methods. Clin. Nutr. 2004, 23, 1226–1243. [Google Scholar] [CrossRef]
- Horino, T.; Tokunaga, R.; Miyamoto, Y.; Akiyama, T.; Daitoku, N.; Sakamoto, Y.; Ohuchi, M.; Ogawa, K.; Yoshida, N.; Baba, H. Extracellular water to total body water ratio, a novel predictor of recurrence in patients with colorectal cancer. Ann. Gastroenterol. Surg. 2023, 8, 98–106. [Google Scholar] [CrossRef]
- Wang, X.; Liang, Q.; Li, Z.; Li, F. Body Composition and COPD: A New Perspective. Int. J. Chron. Obstruct. Pulmon. Dis. 2023, 18, 79–97. [Google Scholar] [CrossRef]
- Mamoto, T.; Fujiwara, H.; Toyama, Y.; Hirata, K.; Yoshikawa, J.; Fujimoto, S. Relationship between exercise performance and water distribution measured by new bioelectrical impedance analysis in patients with chronic obstructive pulmonary disease. Clin. Physiol. Funct. Imaging 2003, 23, 230–235. [Google Scholar] [CrossRef]
- Uemura, K.; Doi, T.; Tsutsumimoto, K.; Nakakubo, S.; Kim, M.J.; Kurita, S.; Ishii, H.; Shimada, H. Predictivity of bioimpedance phase angle for incident disability in older adults. J. Cachexia Sarcopenia Muscle 2020, 11, 46–54. [Google Scholar] [CrossRef]
- Di Vincenzo, O.; Marra, M.; Di Gregorio, A.; Pasanisi, F.; Scalfi, L. Bioelectrical impedance analysis (BIA) -derived phase angle in sarcopenia: A systematic review. Clin. Nutr. 2021, 40, 3052–3061. [Google Scholar] [CrossRef]
- Huang, W.J.; Ko, C.Y. Systematic review and meta-analysis of nutrient supplements for treating sarcopenia in people with chronic obstructive pulmonary disease. Aging Clin. Exp. Res. 2024, 36, 69. [Google Scholar] [CrossRef]
Variables | AECOPD Participants (n = 77) | COPD Participants (n = 82) | p Value |
---|---|---|---|
Age (years) | 67.0 ± 8.8 | 62.9 ± 8.3 | 0.002 |
Weight (kg) | 51.6 ± 10.7 | 58.8 ± 12.4 | <0.001 |
BMI (kg/m2) | 18.6 ± 3.4 | 21.4 ± 4.1 | <0.001 |
Education | 0.613 | ||
Pre-school or primary | 44 (57.1%) | 41 (50.0%) | |
Secondary | 32 (41.6%) | 39 (47.6%) | |
Higher | 1 (1.3%) | 2 (2.4%) | |
Occupational exposure | 49 (63.6%) | 47 (57.3%) | 0.416 |
Smoke exposure | |||
Current smoker | 12 (15.6%) | 27 (32.9%) | 0.011 |
Tobacco consumption (package/year) | 57.5 [43.4, 88.5] | 48.8 [36.8, 74.3] | 0.096 |
Alcohol exposure | 30 (39.0%) | 35 (42.7%) | 0.633 |
Disease duration (years) | 5.5 [3.0, 10.0] | 4.0 [1.4, 6.0] | <0.001 |
NRS-2002 | |||
<3 points | 21 (27.3%) | 59 (72.0%) | <0.001 |
≥3 points | 56 (72.7%) | 23 (28.0%) | |
mMRC | <0.001 | ||
Grade 0 | 2 (2.6%) | 19 (23.2%) | |
Grade 1 | 7 (9.1%) | 14 (17.1%) | |
Grade 2 | 8 (10.4%) | 27 (32.9%) | |
Grade 3 | 35 (45.5%) | 17 (20.7%) | |
Grade 4 | 25 (32.5%) | 5 (6.1%) | |
CAT | 21.0 [16.0, 26.0] | 13.5 [9.0, 18.0] | <0.001 |
Variables | Infrequent Exacerbators (n = 22) | Frequent Exacerbators (n = 55) | p Value |
---|---|---|---|
Height (cm) | 166.59 ± 5.60 | 166.24 ± 6.01 | 0.815 |
Weight (kg) | 53.61 ± 10.42 | 50.82 ± 10.91 | 0.309 |
BMI (kg/m2) | 19.25 ± 3.22 | 18.34 ± 3.52 | 0.304 |
ICW (kg) | 19.46 ± 3.25 | 17.73 ± 2.71 | 0.020 |
ECW (kg) | 12.56 ± 1.92 | 11.84 ± 1.74 | 0.114 |
TBW (kg) | 32.02 ± 5.14 | 29.57 ± 4.41 | 0.039 |
Protein (kg) | 8.40 ± 1.40 | 7.67 ± 1.18 | 0.024 |
Mineral (kg) | 2.90 ± 0.45 | 2.75 ± 0.39 | 0.128 |
BMC (kg) | 2.39 ± 0.36 | 2.27 ± 0.31 | 0.137 |
BCM (kg) | 27.86 ± 4.65 | 25.39 ± 3.89 | 0.021 |
AC (cm) | 26.10 [24.40, 28.35] | 25.55 [22.65, 27.38] | 0.313 |
AMC (cm) | 24.10 [22.68, 26.38] | 23.10 [21.45, 24.50] | 0.160 |
SLM (kg) | 40.93 ± 6.62 | 37.71 ± 5.67 | 0.036 |
SMM (kg) | 23.38 ± 4.23 | 21.12 ± 3.54 | 0.020 |
SMI (kg/m2) | 6.43 ± 1.02 | 5.83 ± 0.86 | 0.011 |
FFM (kg) | 43.33 ± 6.95 | 39.97 ± 5.94 | 0.037 |
FFMI (kg/m2) | 15.56 ± 2.02 | 14.44 ± 1.78 | 0.019 |
FM (kg) | 10.28 ± 5.26 | 10.85 ± 6.64 | 0.723 |
FMI (kg/m2) | 3.69 ± 1.82 | 3.90 ± 2.33 | 0.699 |
PBF (%) | 17.75 [13.90, 23.52] | 18.40 [14.15, 25.15] | 0.606 |
VFA (cm2) | 46.75 [38.05, 69.58] | 50.85 [37.40, 75.85] | 0.354 |
Waist circumference (cm) | 74.45 [68.78, 78.90] | 72.55 [69.98, 82.48] | 0.918 |
ECW/TBW | 0.390 [0.387, 0.400] | 0.402 [0.396, 0.405] | 0.001 |
PhA | 4.90 [4.45, 5.20] | 4.00 [3.48, 4.55] | 0.001 |
HGS (kg) | 24.64 ± 8.72 | 19.39 ± 7.03 | 0.008 |
Variables | Infrequent Exacerbators (n = 69) | Frequent Exacerbators (n = 13) | p Value |
---|---|---|---|
Height (cm) | 165.58 ± 4.92 | 165.08 ± 5.50 | 0.744 |
Weight (kg) | 58.04 ± 9.71 | 60.51 ± 21.93 | 0.513 |
BMI (kg/m2) | 21.12 ± 3.18 | 22.12 ± 7.60 | 0.433 |
ICW (kg) | 20.97 ± 3.13 | 19.47 ± 3.33 | 0.122 |
ECW (kg) | 12.85 ± 1.72 | 12.29 ± 2.10 | 0.307 |
TBW (kg) | 33.82 ± 4.82 | 31.76 ± 5.41 | 0.172 |
Protein (kg) | 9.07 ± 1.35 | 8.41 ± 1.45 | 0.115 |
Mineral (kg) | 2.99 ± 0.45 | 2.86 ± 0.43 | 0.319 |
BMC (kg) | 2.45 ± 0.40 | 2.35 ± 0.36 | 0.389 |
BCM (kg) | 30.03 ± 4.49 | 27.89 ± 4.79 | 0.123 |
AC (cm) | 28.10 [26.40, 30.40] | 28.20 [25.10, 29.50] | 0.566 |
AMC (cm) | 25.40 [24.30, 26.70] | 25.20 [22.75, 26.15] | 0.419 |
SLM (kg) | 43.42 ± 6.24 | 40.68 ± 6.92 | 0.158 |
SMM (kg) | 25.35 ± 4.08 | 23.39 ± 4.34 | 0.120 |
SMI (kg/m2) | 7.13 ± 1.84 | 6.54 ± 0.99 | 0.262 |
FFM (kg) | 45.88 ± 6.51 | 43.04 ± 7.26 | 0.162 |
FFMI (kg/m2) | 16.69 ± 1.92 | 15.74 ± 2.20 | 0.116 |
FM (kg) | 12.16 ± 5.71 | 17.47 ± 17.82 | 0.308 |
FMI (kg/m2) | 4.44 ± 2.10 | 6.38 ± 6.39 | 0.300 |
PBF (%) | 20.00 [15.00, 24.70] | 23.20 [15.20, 29.95] | 0.303 |
VFA (cm2) | 47.10 [31.90, 67.80] | 67.20 [30.00, 83.10] | 0.334 |
Waist circumference (cm) | 76.40 [71.20, 83.80] | 78.00 [68.20, 83.60] | 0.979 |
ECW/TBW | 0.380 [0.377, 0.385] | 0.385 [0.382, 0.392] | 0.003 |
PhA | 5.90 [5.30, 6.30] | 5.30 [4.65, 5.55] | 0.002 |
HGS (kg) | 32.38 ± 7.18 | 26.53 ± 6.07 | 0.008 |
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Xie, A.-N.; Huang, W.-J.; Ko, C.-Y. Extracellular Water Ratio and Phase Angle as Predictors of Exacerbation in Chronic Obstructive Pulmonary Disease. Adv. Respir. Med. 2024, 92, 230-240. https://doi.org/10.3390/arm92030023
Xie A-N, Huang W-J, Ko C-Y. Extracellular Water Ratio and Phase Angle as Predictors of Exacerbation in Chronic Obstructive Pulmonary Disease. Advances in Respiratory Medicine. 2024; 92(3):230-240. https://doi.org/10.3390/arm92030023
Chicago/Turabian StyleXie, An-Ni, Wen-Jian Huang, and Chih-Yuan Ko. 2024. "Extracellular Water Ratio and Phase Angle as Predictors of Exacerbation in Chronic Obstructive Pulmonary Disease" Advances in Respiratory Medicine 92, no. 3: 230-240. https://doi.org/10.3390/arm92030023