| Background and Objective Successful assisted ventilation is critically depended on adapting ventilation to patient's need, it is particularly true for noninvasive positive pressure ventilation (NPPV) because the patient is conscious and if pressure support is too high or low the ventilation would be ineffective or uncomfortable and the patient may reject it. Individualized pressure support can as appropriately as possible decrease respiratory muscle effort and improve gas exchange between lung and the atmosphere. In absence of a simple or noninvasive method for assessing respiratory mechanics during NPPV, setting pressure support is based on patient's comfort or clinical symptoms such as improvement of dyspnea as well as laboratory indicators as artery blood oxygen partial pressure, etc. but this does not provide information about the respiratory mechanical status and the clinician, therefore, does not sure whether or not the pressure support has totally overcome the elevated airway resistance. The forced oscillation (FOT) is a useful technique available at present for assessing mechanical properties of the respiratory system in nonparalysed patients subjected to NPPV, it is more easily applicable and less invasive than those conventional methods as oesophageal manometry to evaluate the mechanical status of the patients, and requires no patient's cooperation. Total respiratory system resistance (Rrs) and reactance (Xrs) can be computed online from the oscillatory components of the pressure and flow signals recorded at the airway opening of the patient, and the respiratory resistance and elatance can be estimated from these two oscillatory indices respectively. In present of expiratory flow limitation (EFL), Xrs can also be used to detect the development of EFL. Therefore, Rrs and Xrs data could be helpful for setting the optimal inspiratory positive airway pressure (IPAP), which totally overcome the patient's elevated airway resistance, and the optimal expiratory positive airway pressure (EPAP), which eliminates EFL. At present, most of the commercially available FOT devices are aimed at lung function laboratory application and not suitable for delineating changes of Rrs and Xrs within breathing cycle at different NPPV mode and pressure support level due to unstability of the oscillation generator and the influence of noise and nonlinearity caused by the ventilator. Consequently, the aim of this study is to design an oscillation generator in order to withstand the pressure fluctuation of the respiratory circuit due to the NPPV ventilator, and optimize the signal processing procedure to eliminate the influence of nonlinearity and, therefore, improve measuring accuracy of oscillatory impedance of respiratory system. Then, the reliability and accuracy of the designed FOT measuring system were tested on a respiratory one order linear mechanical model and in 8 healthy subjects respectively.Instrumentation and Method The study was firstly carried out on a resistance-inertance-compliance (R-I-E model) analog simulating the respiratory system, the R-I-E model consists in series of a 6-layer mesh-wire screen mounted on a ?2 cmH2O resistance tube (R), a ?2 cmH2O cylindrical tube (I) and a rubber bellows (C), the precise value of impedance of the R-I-E analog was unknown but it did not matter because the aim of the study was to assess whether the oscillation generator is able to withstand pressure fluctuation beyond physiological range. To this end, the inlet of the analog was connected to a conventional BiPAP generator (BiPAP synchrony, Resiparonic, USA) and the ventilator parameters were set as control mode, repiratory rate 20 bpm, inspiratory time 1 sec, respectively, IPAP was increased from 8 cmH2O to 24 cmH2O by steps of 8 cmH2O and EPAP was fixed to 4 cmH2O. A loudspeaker (subwoofer, 10'', 250W, designed by the Ye Feng professional audio equipment factory, Guangzhou, CHINA) was connected in parallel to the BiPAP ventilator, the rear part of the loudspeaker was enclosed in a 4.3L air chamber to allow the loudspeaker cone to withstand the pressure fluctuation due to the BiPAP ventilator, and driven by sinusoidal signals generated by a functional signal generator (CA1640, CALTEK Electrical Instrument Co. TAIWAN ) at frequencies of 4, 8, 16Hz respectively, the amplitude of the forced oscillatory pressure was adjusted approximately to 2, 4 and 6 cmH2O peak to peak, respectively. In order to meet the requirement of practical application, the frequency response of the designed loudspeaker and amplifier was decreased so that it closes to or covers the oscillatory frequencies, and the maximum power output of the amplifier is at least 1.5 times or above the loudspeaker, by this way, the work efficiency of the loudspeaker and the amplifier are enhanced and the stability of the FOT measuring system improved. For measurement, airway pressure (Pao) and flow (V') were recorded for a period of 2min at inlet of the analog with a piezoresistive transducer (P-300B, Jinsanjiang Transducer Technology Co. LTD, Shenzhen, CHINA) and with a Fleisch No. 2 pneumotacho- graph connected to a differential pressure transducer (MLT141, ADInstruments Co. Australia), respectively. The common mode rejection ratio of the flow measuring system is 96dB at 50Hz. Pressure and flow signals were sampled at a rate of 100Hz with a data acquisition system (Powerlab/16sp and Chart V5.2, ADInstruments Co. Australia) and digitalized by a 16bit analog to digital convertor (ADC). A self-designed signal analysis programme for computer (Bocom system project Co. Beijing, CHINA) was adopted to compute Rrs and Xrs based on a conventional algorithm. Briefly, the sampled pressure and flow signals were first digitally lowpass filtered at a cut-off frequency of 30Hz (FIR filter, Kaiser window) and then moving average filtered (0.2s) to separate the breathing noise. The oscillatory components of pressure and flow were obtained by subtracting the outputs of the moving average filter from the raw signals. By means of linear approximation and cross correlation, Rrs and Xrs were computed on a oscillatory cylce by oscillatory cycle basis from the Fourrier coefficients of oscillatory pressure and flow signals, and then digitally smoothed by moving average filtering (0.4s). In addition to compute respiratory impedance, the coherence function r2 is also computed from the auto-spectra of pressure (Gpp) and flow (Gvv) and the cross-spectrum of pressure and flow (Gpv) from the pressure and flow signals recorded over a period of 16 sec to evaluate the reliability of the FOT measuring system. The stability of oscillatory generator was also assessed by investigating the frequencies and amplitudes of the oscillatory waveform at different NPPV pressure support levels. Additionally, the FOT measuring system was also applied to 8 healthy subjects to evaluate the accuracy of the FOT measuring system, the protocol was similar to the previous one on R-I-E model. To this end, the R-I-E analog was replaced by the subjects and 5Hz oscillatory pressure (2 cmH2O peak to peak) was applied to nasal mask connected the subject to the NPPV ventilator. Oesophageal pressure (Pes) was measured with a conventional balloon-catheter system connected to a piezoresistive transducer similar to that used to measure Pao in R-I-E model study, the balloon was located at the lower esophagus and its position was verified by the occlusion test. For each subject and measurement conditon, the NPPV modes and parameters were firstly set as BiPAP mode, IPAP 8 and 12 cmH2O, EPAP fxed to 4 cmH2O, and then CPAP 4, 8 and 12 cmH2O respectively. Before measurement, each NPPV mode and pressure support level was maintained for a period of 10 min to allow subject's adaptation, and possible mask leak was minimized (<50mL/s) and upper airway shunt was reduced by firmly support the cheeks of the subject. Then nasal pressure ( Pn ), flow and Pes were recorded for a period of 2min and stored for subsequent analysis. To evaluate the measuring accuracy of the FOT system, the least square multiple linear regression, which is a well established reference method, was adopted to compute lung resistance (RL), and then the agreement between RL and Rrs was compared. To this end, Rrs was computed on a breathing cycle by breathing cycle basis for each subject according to the method mentioned above and averaged for each NPPV mode and pressure support level. To compute RL corresponding to Rrs, transpulmonary pressure (Ptp) was obtained from the difference between Pn and Pes and volume (V) by digital integration of flow, then Ptp, flow and V data were fitted by least square multiple linear regression to the one order linear model: Ptp = P0 + RL·V'+ EL·△V , where RL and EL are total respiratory resistance and elatance, and P0 is the static recoil pressure at end expiratory. To discard artefactual breathing cycles, e.g. those respiratory muscular activity or oesophageal spasm were apparent, only those breathing cycles whose root mean square difference (RMSD) met the following criteria with the one order linear modle: 1) RMSD<1.5 RMSDmin or RMSD-RMSDmin<0.5hpa, 2) the resulting RL and EL were positive, were accepted, where RMSDmin was the lowest RMSD observed in the 2min piece of record. Results were shown as mean±SD, comparisons between resistance or reactance values were analyzed by paired t tests, and the relationship between Rrs and RL was assessed by linear correlation analysis. Statistical significance was considered at the P=0.05 level.Results 1) The coherence function r2computed from the power spectra of pressure and flow signals over a period of 16 sec are both above 0.95 in R-I-E model and healthy subjects study. 2) The oscillatory generator designed for practical application is able to withstand external loading pressure up to a maximum pressure difference of 20 cmH2O due to BiPAP ventilator, and this allowed the forced oscillation of sufficient amplitude (~6 cmH2O) and frequency extent (4~16Hz) for exact measurement of respiratory resistance and reactance. The FOT measuring system maintained steady status for a long period of time during measurement. 3) Rrs measured by 5Hz forecd oscillation (one subject exhibited very high value of Rrs and was far beyond the mean±2SD, so the data was excluded) at BiPAP mode and different pressure support levels (IPAP/EPAP 12/4, 8/4 cmH2O, respectively) were 6.37±1.63 and 5.84±1.12 cmH2O·s·L-1,respectively, the coefficient of correlation ( r ) was 0.97,P<0.01. The coefficients of variance were 7.00±2.94 and 9.86±4.59%, respectively, and no significant difference was found between them. For Xrs, the mean values were -3.16±1.36 and -3.01±1.12 cmH2O·s·L-1,respectively, r=0.96,P<0.01, and the coefficients of variance were 12.4±7.9 and 14.1±7.5%, respectively, there was also no significant difference between them. 4) Rrs at CPAP 4, 8 and 12 cmH2O were 4.55±1.17,4.61±1.12 and 4.54±2.07 cmH2O·s·L-1,respectively, r ranged from 0.77 to 0.98,P<0.05. The coefficients of variance were similar to those measured at BiPAP and showed no significant differences among them. As to Xrs, the mean values were -2.02±0.86, -2.06±0.67 and -1.96±0.54 cmH2O·s·L-1,respectively, r ranged from 0.54 to 0.89, P<0.05 to each other. The coefficients of variance were similar to those measured at BiPAP and also showed no significant differences. 5) Rrs measured at BiPAP mode were slightly higher than that at CPAP: 6.10±1.42 and 4.62±1.52 cmH2O·s·L-1,respectively, r was 0.63, P<0.01. The coefficients of variation were 8.43±4.18 and 8.21±6.23 cmH2O·s·L-1, respectively, and no significant differences were found between them. Xrs (absolute value) showed the same tendency as Rrs: -3.15±1.33 and -2.00±0.62 cmH2O·s·L-1, respectively, r was 0.87, P<0.01. The coefficients of variation were 13.29±7.45 and 10.43±7.01 cmH2O·s·L-1, respectively, and no significant differences were found between them. 6) The mean value of Rrs measured by FOT at different NPPV mode and pressure support level is almost the same as RL computed by the least square multiple linear regression: 5.25±1.69 and 5.50±1.98 cmH2O·s·L-1, respectively, the coefficient of linear correlation ( r ) between this two indices was 0.66, P<0.01. The coefficient of variance of Rrs and RL were 10.83±7.16 and 10.17±7.48 cmH2O·s·L-1,respectively, and showed no significant difference. The line of best fit to RL from Rrs is R L = 1 .40+0.77Rrs, P<0.01. 7) The mean value of Xrs measured by FOT at different NPPV mode and pressure support level is -2.48±1.12 cmH2O·s·L-1, EFOT ((EFOT = -2πfXrs)) is significantly higher than EL (7.13±2.48 cmH2O/L), r = 0.40,P<0.01.Conclusion 1) The generator designed for practical application is able to withstand extrinsic loading pressure due to NPPV and allows sufficient oscillatory amplitude and frequency range for precise measurement of respiratory resistance and reactance at different NPPV modes and pressure supprot levels. 2) The self-designed signal analysis programme for computation of respiratory impedance is capble of decreasing the influence of nonlinearity due to NPPV and combines computation accuracy and reliability of recommended oscillatory measuring system. 3) NPPV mode and pressure support level play a negligible role in FOT measurement, oscillatory resistance is able to estimate RL precisely, and therefore, helpful for setting of NPPV pressure support. Background and objective One of the most common clinical application of noninvasive positive pressure ventilation (NPPV) is in acute exacerbation of chronic obstructive pulmonary disease (COPD). In order to match the ventilator to patient's requirement appropriately, two important aspects must be taken into account during setting pressure support parameters of NPPV, one is IPAP, which should high enough to totally overcome the elevated airway resistance and low enough to avoid discomfort, the other is EPAP, which eliminate expiratory limitation (EFL) and maintain patency of the peripheral airway and, meanwhile, aviod pulmonary hyperinflation at end-expiratory. At present, the forecd oscillation technique (FOT) is the only tool available to noninvasively evaluate respiratory mechanics in nonparalysed patient during NPPV, the oscillatory respiratory resistance (Rrs) can be used to assess noninvasively lung resistance (RL), and reactance (Xrs) to detect the development of EFL, consequently, these two oscillatory indices might be used as references to optimal IPAP or EPAP titration. In our previous study, we had designed a FOT measuring system that was proved to be reliable and accurate in oscillatory assessment of respiratory mechanics at different NPPV modes and pressure levels. Therefore, the purpose of this study is to apply the FOT measureing system to severe COPD patients with chronic respiratory failure and investigate the feasibility of using Rrs and Xrs to optimize the NPPV pressure parameters.Subjects The study was carried out in 8 COPD patients with type 2 chronic respiratory failure from Guangzhou Institute of Respiratory Disease and the 3rd affiliated hospital of Guangzhou Medical College. The patients met the standard diagnostic criteria of the Chinese Medical Association for COPD and type 2 respiratory faillure. The patients are all male and and were current or exsmokers, with a mean age of 77.38±3.25 years old, and forced expiratory volume in 1st second (FEV1) of 25.38±7.09% of the predicted value, and FEV1/forced vital capacity (FVC) ratio of 38.88±10.18%. The mean±SD value of artery blood oxygen partial pressure (PaO2) was 75.88±13.4mmHg and artery blood carbon dioxide partial pressure (PaCO2) 62.9±12.09 mmHg. The patients were in stable condition at the time of study and had no any contraindications for NPPV. The study was approved by the institutional research ethics committee of Guangzhou Medical College, and written informed consent was obtained from each subject.Method The measurement and protocol of current study is similar to the previous one in healthy subject, briefly, the patients were in sitting posture as his preference and 5Hz oscillatory pressure (2 cmH2 O peak to peak) was applied to nasal mask connected the subject to the NPPV ventilator. Oesophageal pressure (Pes) was measured with a conventional baloon-catheter system connected to a piezoresistive transducer, the balloon was located at the lower esophagus, its position was verified by the occlusion test. Nasal pressure (Pn) was measured with a piezoresistive transducer similar to that in Pes measurement and and flow (V') with a Fleisch No. 2 pneumotachograph connected to a differential pressure transducer, respectively. For each subject and measurement conditon, the NPPV parameters were set as BiPAP mode, IPAP 8 and 12 cmH2O, EPAP fxed to 4cmH2O, and CPAP 4, 8 and 12cmH2O respectively. Before measurement, each NPPV condition was maintained for a period of 10min to allow subject's adaptation, and possible mask leak was minimized (<50mL/s) and upper airway shunt was reduced by firmly support the patient's cheeks. Then Pn, V'and Pes signals were recorded for a period of 2min and stored for subsequent analysis. Rrs and its mean value during inspiratory (Rrs,in), and Xrs and its mean values duing inspiratory ( X rs, in) as well as expiratory ( X rs, ex) were computed on a breathing cycle by breathing cycle basis for each subject and averaged for each NPPV mode and pressure support level. RL and inspiratory RL (RL,in) corresponding to Rrs and Rrs,in were also computed by least square multiple linear regression. To discard artefactual breathing cycles, e.g. those respiratory muscular activity or oesophageal spasms were apparent, only those breathing cycles whose root mean square difference (RMSD) met the following criteria with the one order linear modle: 1) RMSD<1.5 RMSDmin or RMSD-RMSDmin<0.5hpa, 2) the resulting RL and EL were positive, were accepted, where RMSDmin was the lowest RMSD among the breathing cycles of the recorded signal over a peroid of 2min. To assess the utility of Rrs for setting optimal IPAP, the agreement between Rrs,in and RL,in was compared and prediction equation to RL,in from Rrs obtained by the linear regression. To detect EFL, each breathing cycle of a concecutive period of 32 sec signal of the recorded signals at different NPPV modes and pressure support levels was analyzed by means of the Mead-Whittenberger method. Then, the relationship between EFL and the mean value of the difference between X rs, exand X rs, in (ΔX rs) was analyzed, and their relations to CPAP levels were also assessed. After that, the sensitivity and specificity ofΔX rs for detection of EFL were computed and the optimalΔX rs (sensitivity and specificity were maximum) determined by means of Dellacà 's method. Finally, The utility ofΔX rs for optimal EPAP was analyzed. Results were shown as means±SD, comparisons between resistance values were analyzed by paired t tests, and the relationship between Rrs,in and RL,in was assessed by linear correlation analysis. Statistical significance was considered at the P = 0.05 level.Results 1) The mean value of coherence function r2 computed from the power spectra of pressure and flow signals over a period of 16 sec is about 0.91. 2) Rrs measured by 5Hz forced oscillation at different NPPV mode and pressure support level is similar to each other, ranged from 3.84~9.85 cmH2O·s·L-1 and with a mean value of 6.13±1.40 cmH2O·s·L-1, the coefficients of correlation (r) among them are all above 0.90, and the coeficients of variance showed no significant difference. Xrs exhibited the same tendency and with a mean value of 5.33±2.84 cmH2O·s·L-1. Rrs is slightly lower than RL ( 9.46±4.37 cmH2O·s·L-1), the coefficient of correlation ( r ) between these two resistances was 0.52,P<0.01. The coefficients of variance were 7.06±4.63 and 9.03±5.43%, respectively, and showed no significant difference between them. 3) Rrs,in measured by FOT at different NPPV mode and pressure support levels ranged 3.95~11.90 cmH2O·s·L-1, and exhibiting a mean value of 6.52±1.61 cmH2O·s·L-1, and RL,in ranged 1.05±21.97 cmH2O·s·L-1 with a mean value of 9.37±4.61 cmH2O·s·L-1, respectively, the coefficient of linear correlation ( r ) between this two indices was 0.64, P<0.01. The line of best fit to RL,in from Rrs,in isRL,in = -1.62 + 1.69Rrs,in, P<0.01. 4) CPAP level is related negatively toΔXrs and EFL, Increase in CPAP level resulted in a progressive decrease inΔXrs and in EFL breathing cycles. The ratios of the EFL/nonEFL breathing cycles are 15.2%, 12.4% and 6.7% at CPAP levels of 4, 8 and 12 cmH2O, repectively. The optimalΔXrs is 1.83 cmH2O·s·L-1, its sensitivity and specificity to detect EFL are 94% and 97%, respectively.Conclusion 1) NPPV mode and pressure support level play a negligible role to FOT measurement in COPD patient. 2) Although Rrs,in measured by 5Hz forecd oscillation in COPD patients during NPPV is slightly lower than RL,in, they are significantly correlated with a coefficient of linear correlation of 0.58. Rrs,in can be used to estimate RL,in and helpful for setting optimal IPAP. 3) The optimalΔXrs (1.83 cmH2O·s·L-1) is a critical threshold to detect EFL, the corresponding CPAP level is capable of a reference to optimal EPAP which will eliminate the majority of EFL breathing cycles.
|
PDF Full Text Request