Entropy change of biological dynamics in COPD

Figures & data

Figure 1 PRISMA flow diagram.

Table 1 GRADE analysis: applied entropy to physiologic parameters of COPD

Primary/secondary outcome	N (arms)	Risk of bias	Inconsistency	Indirectness	Imprecision	Publication bias	Large effect	Overall quality of evidence
HRV	46 (3)	No	No	No	No	No	No	+/+/+/+/; high
Airflow	104 (1)	No	No	No	No	No	No	+/+/+/+/; high
Hormone secretion	17 (1)	No	No	No	No	Serious	No	+/+/+/−/; moderate
Gait variability	48 (1)	No	No	No	No	No	No	+/+/+/+/; high
Airway pressure	12 (1)	No	No	No	No	Serious	No	+/+/+/−/; moderate
Respiratory sound	37 (3)	No	No	No	No	No	No	+/+/+/+/; high
MMG	16 (2)	No	No	No	No	No	No	+/+/+/+/; high

Notes: GRADE working group grades of evidence: high quality, further research is very unlike to change our confidence in the estimate of effect. Moderate quality, further research is likely to have an important effect on our confidence in the estimate of effect and may change the estimate. Low quality, further research is very likely to have an important effect on our confidence in the estimate of effect and is likely to change the estimate. Very low quality, the estimate of effect is uncertain.

Abbreviations: GRADE, grading of recommendations assessment, development, and evaluation; HRV, heart rate variability; MMG, mechanomyogram signal.

Table 2 Entropy studies for comparison between healthy people and patients with COPD

Physiologic signals	Study (year)	Entropy method	Location	Number of subjects	Age in years as mean ± SD or range	Gender Ratio (M/F)	Pulmonary function	Entropy result	Jadad score
Heart rate variability	Goulart Cda et al^Citation1 (2016)	ApEn and SampEn	Brazil	COPD I: 2 COPD II: 3 COPD III: 5 Controls: 0	61.2±6.7	8/2	FEV1/FVC =46.5±11.6 FEV1% predicted =58.7±15.4	Decreases during respiratory sinus arrhythmias	5
	Mazzuco et al^Citation2 (2015)	ApEn	Brazil	Stage II to IV: 16	66.3±8.4	16/0	FEV1/FVC =44.0±10.8 FEV1 % predicted =53.9±19.7	Decreases during respiratory sinus arrhythmias	5
	Borghi-Silva et al^Citation3 (2015)	SampEn	Brazil	COPD II: 2 COPD III: 13 COPD IV: 5	COPD: 67±7 Controls: 66±10	COPD: 7/3 Controls: 5/5	FEV1 % predicted COPD: 32±11 Controls: 35±12	Increases after 6 weeks of physical training program	5
Airflow	Dames et al^Citation4 (2014)	SampEn	Brazil	COPD I: 11 COPD II: 18 COPD III: 16 COPD IV: 14 ^NE: 13 Controls: 16	COPD: 66.3±10.2 ^NE: 54.9±6.7 Controls: 61.4±13.6	N/A	FEV1/FVC: COPD: 53.3±8.5 ^NE: 77.9±3.3 Controls: 78.5±6	Decreases with increasing airway obstruction during resting breathing	5
Gait variability	Yentes et al^Citation32 (2017)	SampEn	America	COPD: 20 Controls: 28	COPD: 63.6±9.7 Controls: 62.5±8.2	COPD: 16/4 Controls: 9/11	FEV1/FVC: COPD: 52.0±12 Controls: 79±6	The entropy of gait variability in COPD patients is lower than that of healthy controls while walking	5
Hormone secretion	Iranmanesh et al^Citation5 (2011)	ApEn and Cross-ApEn	America	COPD: 9 Controls: 8	Case: 65±4.3 Controls: 53±2.5	COPD: 9/0 Controls: 8/0	FEV1 % predicted: COPD: 43±6.4 Controls: 93±4.4	The entropy of hormone secretion in COPD patients is higher than that in healthy persons during maximal exercise	5
Airway pressure	Letellier et al^Citation35 (2008)	Shannon	France	COPD: 4 OHS: 4 Controls: 4	N/A	N/A	N/A	Less than 1 means the quality of patient-ventilator interactions during NIV is high	4
Respiratory sound	Mendes et al^Citation7 (2014)	Shannon	Portugal	Online breath sounds datasets of COPD	N/A	N/A	N/A	Higher in presence of cracks	/
	Mondal et al^Citation37 (2012)	SampEn	India	COPD/ILD/asthma: 20 Controls: 10	N/A	N/A	N/A	Higher in abnormal subjects	5
	Aydore et al^Citation9 (2009)	Renyi	America	COPD/asthma: 7	50±17	4/3	N/A	Higher in presence of wheezes	4
Mechanomyogram signal	Torres et al^Citation10 (2010)	Renyi	Spain	COPD III: 6 Controls: 0	68.2±9.6	N/A	FEV1/FVC =41.0±8.1	Increases with increased inspiratory pressure	4
	Sarlabous et al^Citation38 (2015)	SampEn	Spain	COPD III: 5 COPD IV: 5 Controls: 0	COPD III: 72.8±9.6 COPD IV: 63.7±8.2	COPD III 5/0 COPD IV 5/0	FEV1 % predicted: COPD III: 40.0±6.5 COPD IV: 20.5±3.0	Higher in very severe COPD patients than in severe COPD patients	5

Note:

^ Smoking subjects that presented a normal respiratory response to the spirometric exam.

Abbreviations: ApEn, approximate entropy; cross-ApEn, cross-approximate entropy; FEV₁, forced expiratory volume in 1 second; fSampEn, fixed sample entropy; GOLD, Global Initiative for Chronic Obstructive Lung Disease; ILD, interstitial lung disease; NIV, noninvasive ventilation; OHS, obesity hypoventilation syndrome; SampEn, sample entropy; N/A, not available.

Figure 2 Entropy change in COPD.

Notes: The error bar represents standard error. First part uses approximate entropy and sample entropy as mentioned in Goulart Cda et al.¹ Second part uses sample entropy as mentioned in Borghi-Silva et al.³ Third part uses sample entropy as mentioned in Dames et al.⁴ ^Smoking subjects that presented a normal respiratory response to the spirometric exam. Fourth part uses fixed sample entropy as mentioned in Sarlabous et al.¹¹
Abbreviations: HRV, heart rate variability; MMG, mechanomyogram signal; RSA-M, respiratory sinus arrhythmia maneuver.

Goulart CdaLSimonJCSchneiders PdeBRespiratory muscle strength effect on linear and nonlinear heart rate variability parameters in COPD patientsInt J Chron Obstruct Pulmon Dis2016111671167727555757

 PubMed Web of Science ®Google Scholar

MazzucoAMedeirosWMSperlingMPRelationship between linear and nonlinear dynamics of heart rate and impairment of lung function in COPD patientsInt J Chron Obstruct Pulmon Dis2015101651166126316739

 PubMed Web of Science ®Google Scholar

Borghi-SilvaAMendesRGTrimerRPotential effect of 6 versus 12-weeks of physical training on cardiac autonomic function and exercise capacity in chronic obstructive pulmonary diseaseEur J Phys Rehabil Med201551221122124594853

 PubMed Web of Science ®Google Scholar

DamesKKLopesAJde MeloPLAirflow pattern complexity during resting breathing in patients with COPD: effect of airway obstructionRespir Physiol Neurobiol2014192394724334010

 PubMed Web of Science ®Google Scholar

YentesJMRennardSISchmidKKBlankeDStergiouNPatients with chronic obstructive pulmonary disease walk with altered step time and step width variability as compared with healthy control subjectsAnn Am Thorac Soc201714685886628267374

 PubMed Web of Science ®Google Scholar

IranmaneshARochesterDFLiuJVeldhuisJDImpaired adrenergic-and corticotropic-axis outflow during exercise in chronic obstructive pulmonary diseaseMetabolism201160111521152921632072

 PubMed Web of Science ®Google Scholar

LetellierCRabarimanantsoaHAchourLCuvelierAMuirJFRecurrence plots for dynamical analysis of non-invasive mechanical ventilationPhilos Trans A Math Phys Eng Sci2008366186562163417698467

 PubMed Web of Science ®Google Scholar

MendesLCarvalhoPTeixeiraCAPaivaRPHenriquesJRobust features for detection of crackles: an exploratory studyConf Proc IEEE Eng Med Biol Soc201420141473147625570247

 PubMedGoogle Scholar

MondalABhattacharyatPSahaGDiagnosing of the lungs status using morphological anomalies of the signals in transformed domainPaper presented at: Intelligent Human Computer Interaction (IHCI), 4th International Conference27–29 December; 2012Kharagpur, India

 Google Scholar

AydoreSSenIKahyaYPMihcakMClassification of respiratory signals by linear analysisConf Proc IEEE Eng Med Biol Soc200920092617262019965225

 PubMedGoogle Scholar

TorresASarlabousLFizJANoninvasive measurement of inspiratory muscle performance by means of diaphragm muscle mechanomyographic signals in COPD patients during an incremental load respiratory testConf Proc IEEE Eng Med Biol Soc201020102493249621096168

 PubMedGoogle Scholar

SarlabousLTorresAFizJAGeaJMartinez-LlorensJMJaneREfficiency of mechanical activation of inspiratory muscles in COPD using sample entropyEur Respir J20154661808181126493808

 PubMed Web of Science ®Google Scholar

SarlabousLTorresAFizJAJaneREvidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance valuesPLoS One201492e8890224586436

 PubMed Web of Science ®Google Scholar