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Fig 1.

Study flowchart describing the examined volunteers and analysis performed.

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Fig 1 Expand

Fig 2.

Electrical representation of a two-compartment model used to analyze respiratory impedance.

Resistance, inductance and capacitance are the analogs of mechanical resistance, inertance and compliance, respectively. R is analogous to central airway resistance and Rp describes peripheral resistance, I is associated with lung inertance and C with alveolar compliance. This analysis also evaluated the total resistance (Rt = R+Rp), which included the effects of central and peripheral airways.

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Table 1.

Biometric, spirometric and plethysmographic parameters of the studied subjects.

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Table 2.

Description of the clinical, spirometric and plethysmographic characteristics of the exposed sample.

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Fig 3.

Mean respiratory resistance (A) and reactance (B) curves as a function of frequency of the control group and asbestos-exposed workers.

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Fig 4.

Comparative analysis of the classical resistive parameters obtained from the control group and asbestos-exposed workers: Respiratory system resistance (R0; Figure A), mean resistance (Rm, Figure B), resistance in 4 Hz (R4; Figure C) and slope of respiratory resistance (S; Figure D).

The top and the bottom of the box plot represent the 25th- to 75th-percentile values, while the circle represents the mean value, and the bar across the box represents the 50th-percentile value. The whiskers outside the box represent the 10th-to 90th-percentile values.

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Fig 5.

Comparative analysis of the classical reactive parameters obtained from the control group and asbestos-exposed workers: mean respiratory reactance (Xm; Figure A), resonant frequency (fr, Figure B), dynamic compliance (Cdyn; Figure C) and respiratory impedance module in 4Hz (Z4; Figure D).

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Fig 6.

Influence of exposition to asbestos on parameter values estimated from the integer model described in Fig 1: central airway resistance (R; Figure A), peripheral resistance (Rp; Figure B), total resistance (Rt; Figure C), lung inertance (I; Figure D) and alveolar compliance (C; Figure E).

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Fig 7.

Comparative analysis of the parameters obtained from the fractional-order model in the control group and asbestos-exposed workers: Inertance (L; A), alpha coefficient (α; B), compliance (C; C), beta coefficient (β; D), damping (G; E), elastance (H; F) and hysteresivity (G).

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Table 3.

Errors in the integer and fractional-order models studied in control individuals and patients exposed to asbestos.

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Table 4.

Correlation analysis between the classical forced oscillation, eRIC and FrOr parameters and spirometry results.

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Table 5.

Analysis of the clinical potential of the classical forced oscillation parameters in detecting respiratory alterations in workers exposed to asbestos.

Values of area under the curve (AUC), sensitivity (Se), specificity (Sp) for the optimal cut-off points obtained using receiver operating characteristic (ROC) curves and leave-one-out cross-validation (LOOCV).

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Table 6.

Analysis of the diagnostic potential of the extended RIC parameters in detecting respiratory alterations in workers exposed to asbestos.

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Table 7.

Analysis of the clinical potential of the fractional-order parameters in detecting respiratory alterations in workers exposed to asbestos.

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Fig 8.

ROC curves, AUCs and the 95% confidence interval for the most accurate parameters observed in the classical analysis (Z4; AUC = 0.840), for the eRIC model (Rp; AUC = 0.831) and for the FrOr model (L; AUC = 0.998).

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Table 8.

Mean ± standard errors of the differences in the diagnostic performances of FOT and spirometric parameters, calculated by the difference between AUCs.

Positive values denote higher values of AUC for FOT parameters.

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