Research ArticleOriginal Research

Waveforms Analysis in Patients With Amyotrophic Lateral Sclerosis for Enhanced Efficacy of Mechanically Assisted Coughing

Jesus Sancho, Santos Ferrer, Enric Bures, Lucía Fernandez-Presa, Pilar Bañuls, M Cruz Gonzalez and Jaime Signes-Costa
Respiratory Care October 2022, 67 (10) 1226-1235; DOI: https://doi.org/10.4187/respcare.09978

Abstract

BACKGROUND: Effectiveness of mechanical assisted coughing with insufflation-exsufflation (MI-E) in amyotrophic lateral sclerosis (ALS) depends largely on severity of bulbar dysfunction, which can generate different upper-airway responses. The aim of the study was to evaluate the use of graphs generated by MI-E in ALS to detect airway obstruction and set parameters to achieve an effective mechanically assisted coughing.

METHODS: This was a prospective study enrolling patients with ALS. Several sessions with MI-E were applied, administering different insufflation-exsufflation (± 20, ± 30, ± 40, ± 50 cm H2O) levels in each session. The graphs produced were recorded and analyzed, and the results were used to select the parameters resulting in more effective MI-E.

RESULTS: Sixty-nine subjects with ALS were included, yielding a total of 351 analyzed records. A pattern of obstruction during insufflation was detected in 34 subjects (50.7%) and of upper-airway collapse during exsufflation in 18 subjects (26%). The variable associated with obstruction during insufflation was bulbar upper motor neuron dysfunction (odds ratio 7.19 [95% CI 2.32–22.29], P = .001), whereas bulbar lower motor neuron dysfunction was related to upper-airway collapse during exsufflation (odds ratio 0.32 [95% CI 0.11–0.98], P = .046). After parameters were adjusted, in 68 subjects (98.55%) an effective MI-E was achieved. The only variable that predicted absence of alterations in the graphs was Norris bulbar score (odds ratio 0.87 [95% CI 0.78–0.96], P = .007).

CONCLUSIONS: Analysis of graphics generated by applying MI-E in ALS was an effective method to detect upper-airway responses and select optimal set parameters. Obstruction during insufflation is related to bulbar upper motor neuron dysfunction and collapse during exsufflation to bulbar lower motor neuron dysfunction.

Introduction

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative motor neuron disease that produces respiratory muscle weakness, resulting in respiratory failure and an ineffective cough effort.1 Mechanical assisted coughing with insufflation-exsufflation (MI-E) has proven effective in noninvasive respiratory secretion removal in most patients with ALS with an ineffective cough and is thus recommended as a first-line treatment for mucus removal in ALS.2

The effectiveness of MI-E is limited by decreased thoracic pulmonary compliance and increased airway resistance during respiratory infections (episodes urgently requiring secretion clearance), which can be reversed by increasing pressure.3 The main limiting factor of this technique in patients with ALS, however, is severity of bulbar involvement, which appears inexorably in almost all patients with ALS over the course of the disease.4 In patients with ALS, bulbar dysfunction is associated with obstruction of the upper airway in both insufflation and exsufflation cycles; and the greater the pressure applied during MI-E the greater the obstruction, which reduces technique effectiveness and can even render it ineffective.5,6 This is of vital importance given that failure to manage respiratory secretions in ALS is one of the main factors prompting invasive techniques to remove respiratory secretions (fibrobronchoscopy) during respiratory infections and endotracheal intubation for subsequent tracheostomy.7 In this way, nowadays it’s recommended an individual titration of MI-E parameters in patients with ALS with bulbar dysfunction.2,6

Performance of transnasal fiberoptic laryngoscopy during MI-E has recently been proposed, with the aim of adjusting pressure settings to minimize the effects of bulbar involvement on technique effectiveness.6 As an invasive technique, nonetheless, it could interfere with the flows generated; furthermore, use of local anesthesia could affect upper-airway reflexes; and in patients with bulbar dysfunction, observations at glottic level might not be possible.6 Lacombe et al8 recently showed the utility of analyzing flow-volume curve during MI-E in subjects with ALS to determine upper-airway obstruction based on previous findings that negative expiratory pressure technique was useful to assess upper-airway collapsibility during spontaneous breathing.9 MI-E graph analysis is a good alternative in this regard to optimize MI-E parameters and achieve effective flows while circumventing the disadvantages of nasofibroscopy. Our hypothesis was that by analyzing (mainly flow time and pressure time) waveforms obtained from MI-E in subjects with ALS set parameters can be individualized to achieve effective mechanically assisted coughing.

QUICK LOOK

Current Knowledge

Effectiveness of mechanical assisted coughing with insufflation-exsufflation (MI-E) in amyotrophic lateral sclerosis (ALS) is largely dependent of severity of bulbar dysfunction. In these patients, upper-airway responses to MI-E can decrease the effectiveness of mechanically assisted cough to the point of being ineffective. Bulbar dysfunction is associated with obstruction of upper airway in both insufflation and exsufflation cycles.

What This Paper Contributes to Our Knowledge

Analysis of graphics generated by applying MI-E in ALS is a noninvasive and effective method to select optimal set parameters. Two phenotypes have been found, obstruction during insufflation that is related to bulbar upper motor neuron dysfunction and collapse during exsufflation to bulbar lower motor neuron dysfunction.

Methods

This prospective cohort study included consecutive subjects with ALS diagnosis according to the revised El Escorial criteria10 who were admitted to the respiratory care unit of a tertiary hospital from June 2018–June 2020. Exclusion criteria were refusal to participate in the study; home tracheostomy ventilation; presence of bronchial pathology, pulmonary bullae, or bronchial hyper-responsiveness; history of barotrauma; presence of disease associated with poor prognosis; and presence of ALS-associated severe frontotemporal dementia that could interfere with procedures.

Informed consent was obtained, and the protocol was approved by the hospital’s research ethics committee; the study protocol was registered at INCLIVA Health Research Institute, Spain (2017/MI-E Waveforms ALS Study).

After inclusion in the study, subjects underwent clinical assessment and a functional respiratory evaluation. Demographic and clinical variables included time from ALS onset and time from ALS diagnosis, type of ALS onset (spinal/bulbar/respiratory), and predominance of upper or lower bulbar motor neuron dysfunction. Neurological functional assessment was performed with the Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R),11 Norris bulbar subscore (NBS),12 and the bulbar subscale of ALSFRS-R (ALSFRS-R-B).11 Pulmonary function assessment was performed with a spirometry (MS 2000, Schatzman, Madrid, Spain) recording FVC in accordance with European Respiratory Society guidelines and suggested reference values13; maximum inspiratory pressure and maximum expiratory pressure were measured at mouth with the check valve held closed, in accordance with the Black and Hyatt technique14; and sniff nasal inspiratory pressure was measured in an occluded nostril during a maximal sniff through the contralateral nostril (MicroRPM, Micro Medical, Rochester, Kent, United Kingdom).15 Cough capacity was assessed by measuring cough peak flow (CPF), maximum insufflation capacity, and manual CPF according to the previously described technique.16

Protocol

The mechanically assisted cough technique (CoughAssist E70, Philips Respironics, Murrysville, Pennsylvania) was applied through an oronasal mask (Martín Vecino, Madrid, Spain), and 6–8 cycles were administered in each of 4 sessions carried out 5 min apart. Different in-exsufflation pressures (± 20 cm H2O, ± 30 cm H2O, ± 40 cm H2O, and ± 50 cm H2O) were applied in each session. Automatic mode was used in all sessions, with an insufflation time 2 s, an exsufflation time 3 s, and a pause 1 s, without using added high-frequency oscillations. Subjects were asked to try to keep their airways open but to otherwise remain passive and let the MI-E device act unimpeded, without any cough effort. In each session, pressure-time, flow-time, and volume-time waveforms were recorded and mechanically assisted CPF (CPFMI-E), volume of insufflation (Vin), and volume of exsufflation (Vex) were measured, taking as baseline the pause between each cycles.

Pressure, flow, and volume generated by the MI-E were measured using a linear pneumotachograph with a wide flow range (±800 L/min) (TSD107B, Biopac Systems, Goleta, California) and a differential pressure transd-ucer for low-range pressure monitoring (±75 cm H2O) (TSD160D, Biopac Systems) placed in line between the mask and the MI-E device circuit and connected to an amplifier (DA100C, Biopac Systems). The signals collected were digitized at 128 Hz and modified for analysis using an analog/visual acquisition system (MP100, Biopac Systems) controlled by a computer using AcqKnowledge software (version 3.7, Biopac Systems) (Fig. 1).

Fig. 1.
Fig. 1.

Optimal flow-time and pressure-time graphs generated by mechanically assisted coughing with insufflation-exsufflation. Ex = exsufflation; ER = elastic recoil; in = insufflation; P = pause; CPFMI-E = MI-E cough peak flow.

After recording the graphs and measurement of the described variables, we analyzed the curves produced, evaluating possible alterations from previously established reference waveforms.8,17,18 Graphs were considered pathological when alterations were present in at least 3 cycles of the session. On the basis of this analysis, optimal pressures for both insufflation and exsufflation were set, and duration of the insufflation and exsufflation times was modified to be capable of generating effective CPFMI-E and a graph without alterations. Taking these selected parameters, the graphs and measurements of the described variables were recorded in a new session. The selection criteria for optimal parameters can be found in the online material (see related supplementary materials at http://www.rcjournal.com).

End Points

The primary end point of the study was to determine whether analysis of the graphs generated during MI-E in subjects with ALS could be used to select the appropriate parameters to achieve an effective mechanically assisted cough. Effective mechanically assisted cough was considered when CPFMI-E was > 2.7 L/s,5 and no alterations were detected in any of the graphs.8,17,18 The secondary end points were to analyze the different patterns found in the ventilator graphics and relate these patterns to different clinical variables.

Statistical Analysis

Binary and categorical variables were summarized using frequency counts and percentages. Continuous normally distributed variables were expressed as mean + SD. Data comparisons were performed using Student t test. Dichotomic variables were compared with the chi-square test. We evaluated the effect of different set pressures in upper-airway obstruction and the changes in recorded variables according to different set pressures with linear mixed-effects model analysis. Logistic regression analysis was performed to evaluate which variables could predict obstruction at upper airway during insufflation and exsufflation and also to determine which variables would predict absence of alterations in graphs. The multivariate analysis model included those variables exhibiting a significant association in the univariate model (P < .2). Receiver operating characteristic (ROC) curves were used to identify a cut-off point in variables best predicting absence of alterations in all analyzed graphs. Statistical significance was set at P < .05. Statistical analysis was performed using IBM SPSS Statistics software (version 26.0, IBM, Armonk, New York).

Results

During the study period, 87 patients with ALS followed up by our unit were eligible to participate. Fifteen with mechanical ventilation through tracheostomy and 3 with severe dementia were excluded; thus, 69 consecutive subjects with ALS in medically stable condition were enrolled in the study, with a total of 351 records analyzed. Each complete session with each subject lasted around 20 min. Demographic and clinical characteristics are shown in Table 1. In 44 (63.8%) subjects, ALS onset was spinal; in 24 (34.8%), it was bulbar, and one subject (1.4%) presented respiratory onset. All subjects had some level of bulbar dysfunction; 39 (56.6%) subjects presented predominantly upper motor neuron involvement at the bulbar level and 30 (43.5%) bulbar lower motor neuron predominant dysfunction. In all, 39 subjects (56.5%) were using NIV at home (mean daily h of use 10.05 ± 4.71); 36 (52.2%) used MI-E, and 21 (30.4%) had a gastrostomy for enteral nutrition.

View this table:
Table 1.

Demographic Data and Pulmonary Function at Study Inclusion

Insufflation Analysis

A pattern of obstruction during insufflation was detected in 34 subjects (50.7%), consisting of a spike at the beginning of insufflation in the flow-time graph, with a subsequent flattening of the rest of the curve until the end of insufflation, in contrast with the smooth and concave stroke of the patterns described as normal (Fig. 2). This spike also coincided with a spike on the pressure-time curve during insufflation. The obstructive pattern was more frequent in subjects with predominantly upper motor neuron dysfunction at bulbar level (27 vs 8 subjects, P = .001); moreover, subjects with obstruction during insufflation had more severe bulbar dysfunction as assessed with NBS (18.82 ± 11.95 vs 24.82 ± 12.01, P = .042). Obstruction was present in 3 subjects (4.3%) with a set pressure of 20 cm H2O, in 12 (17.4%) with 30 cm H2O, in 26 (37.7%) with 40 cm H2O, and in 28 (40.6%) with 50 cm H2O; in this way, the model showed a relationship between set pressures and the presence of obstructive events (β 0.01 [95% CI 0.01–0.02], P = .001) With set pressures > 30 cm H2O, the CPFMI-E (β −0.60 [95% CI −0.82 to −0.39], P = .001), Vin (β −0.31 [95% CI −0.48 to −0.22], P = .001), and Vex (β −0.47 [95% CI −0.63 to −0.31], P = .001) were lower in subjects with obstructive events during insufflation (Table 2). Results of the univariate logistic regression analysis are shown in Table 3; in multivariate logistic regression analysis, the only variable predicting obstruction during insufflation was upper motor neuron dysfunction at bulbar level (odds ratio 7.19 [95% CI 2.32–22.29], P = .001).

Fig. 2.
Fig. 2.

Flow-time (top) and pressure-time (bottom) graphs generated by mechanically assisted coughing with insufflation-exsufflation showing upper-airway obstruction during insufflation (insufflation pressure +40 cm H2O, exsufflation pressure −40 cm H2O, insufflation time 2 s, exsufflation time 3 s, insufflation flow high, pause 1 s).

View this table:
Table 2.

Mechanical Variables Generated According to Set Pressures and Presence of Upper Airway Obstructive Events

View this table:
Table 3.

Univariate Analysis of Upper-Airway Obstructive Events

Another pattern detected was oscillations in flow-time curve, observed in 11 subjects (15.9%): 4 with upper bulbar motor neuron and 7 with lower bulbar motor neuron predominance (P = .15). A pattern of overlong insufflation was present in 30 subjects and short insufflation time in 2 (Fig. 3, E5, see related supplementary materials at http://www.rcjournal.com).

Exsufflation Analysis

A pattern of upper-airway collapse during exsufflation was detected in 18 subjects (26%), comprising flow decrease occurring abruptly after reaching CPFMI-E at the beginning of exsufflation (Fig. E4). Upper-airway collapse during exsufflation was present mainly in those subjects with predominantly upper motor neuron bulbar involvement (12 vs 6, P = .02). No statistical differences were found in severity of bulbar dysfunction assessed with NBS between those with or without upper-airway collapse during exsufflation (21.44 ± 11.90 vs 21.90 ± 12.51, P = .89). Collapse was present with a pressure set at −20 cm H2O in 2 subjects (2.9%), with −30 cm H2O in another 2 (2.9%), with −40 cm H2O in 8 (11.6%), and with −50 cm H2O in 16 (23.2%); in this way, the model showed a relationship between set pressures and presence of obstructive events (β 0.01 [95% CI 0–0.01], P = .001). With set pressures more negative than −30 cm H2O, Vex was lower in subjects with obstructive events during exsufflation (Table 2) (β −0.35 [95% CI −0.48 to −0.22], P = .001). Results of univariate logistic regression analysis are shown in Table 3; in multivariate logistic regression analysis, the only variable predicting upper-airway collapse during exsufflation was lower motor neuron dysfunction at the bulbar level (odds ratio 3.20 [95% CI 0.11–0.98], P = .041). Five subjects presented obstruction both in insufflation and exsufflation: 2 with upper motor neuron dysfunction and 3 with lower motor neuron dysfunction at the bulbar level (ALSFRS-R 27.2 ± 10.7, ALSFRS-R-B 8.7 ± 2.7, NBS 27.2 ± 12.8).

Fig. 3.
Fig. 3.

Flow-time (top) and pressure-time (bottom) graphs generated by mechanically assisted coughing with insufflation-exsufflation showing upper-airway collapse during exsufflation (insufflation pressure +50 cm H2O, exsufflation pressure −50 cm H2O, insufflation time 2 s, exsufflation time 3 s, insufflation flow high, pause 1 s).

Three subjects presented a pattern of excessively long exsufflation (2 of them with lower motor neuron dysfunction, ALSFRS-R 16.0 ± 11.7, ALSFRS-R-B 5.0 ± 6.2, and NBS 13.0 ± 20.8). (Fig. E6, see related supplementary materials at http://www.rcjournal.com). Although MI-E was applied passively without patient effort, 2 subjects presented repeated cough efforts, as demonstrated by several spikes during exsufflation (Fig. E8, see related supplementary materials at http://www.rcjournal.com). Oscillations during exsufflation in flow-time curve were detected in 5 subjects (7.3%) (ALSFRS-R 26.6 ± 6.7, ALSFRS-R-B 8.2 ± 2.5, NBS 24.0 ± 8.6). (Fig. E9, see related supplementary materials at http://www.rcjournal.com): 4 with lower and one with upper bulbar motor neuron predominance (P = .09).

Optimal Parameters

In 13 subjects (18.8%), no alterations were detected in any of the graphs using different parameters. Table 4 shows the differences between subjects with no alteration and subjects with alteration in any graph, whereas Table 5 displays the results of univariate logistic regression analysis to assess variables that predict absence of alteration in graphs. In multivariate logistic regression analysis, the only variable that predicted no alterations in the generated graphs was NBS (odds ratio 0.87 [95% CI 0.78–0.96], P = .007). In ROC analysis, the variable with highest area under the curve was NBS (area under the curve 0.790 [95% CI 0.680–0.890], P = .001), with a cut-off point of 27 (sensitivity 0.84, specificity 0.71, positive predictive value 0.41, and negative predictive value 0.95) (Fig E13, see related supplementary materials at http://www.rcjournal.com).

View this table:
Table 4.

Demographic and Clinical Data According to Presence/Absence of Alterations in Mechanical Assisted Coughing With Insufflation-Exsufflation Generated Graphs

View this table:
Table 5.

Univariate Analysis for Absence of Alterations in Mechanical Assisted Coughing With Insufflation-Exsufflation Generated Graphs

Five subjects did not tolerate pressures set at ± 50 cm H2O, and in 3 subjects, pressure settings of ± 40 and ± 50 cm H2O were not tolerated.

After analyzing the graphics during MI-E with different parameters, we selected the parameters that totally or largely resolved the detected alterations (Figures E10, E11, E12, see related supplementary materials at http://www.rcjournal.com). The obstructive events detected both in insufflation or exsufflation were corrected by decreasing the pressure setting (Fig. 4). The mean optimal set parameters were insufflation pressure 34.25 ± 7.55 cm H2O, exsufflation pressure 39.62 ± 4.87 cm H2O, insufflation time 1.65 ± 0.44 s, exsufflation time 2.94 ± 0.20 s, and high insufflation flow in 52 (75.4%) subjects. With these set parameters, the mean recorded measurements were CPFMI-E 4.06 ± 0.73 L/s, Vin 0.67 ± 0.49 L, and Vex 0.62 ± 0.41 L. A total of 38 subjects (55.07%) presented asymmetrical optimal set pressures (34 with lower absolute values in insufflation pressure than in exsufflation). Only one subject failed to achieve an effective MI-E after parameters were adjusted (ALSFRS-R 15, NBS 8, ALSFRS-R-B 5, predominantly lower motor neuron dysfunction at bulbar level, FVC 0.73 L, %FVC 18.0%).

Fig. 4.
Fig. 4.

Proposed algorithm to adjust parameters in mechanical assisted coughing with insufflation-exsufflation in patients with ALS according to the results of the present study. NBS = Norris bulbar subscore, MI-E = mechanically insufflation-exsufflation, CPF = cough peak flow.

Discussion

The findings of the present study show that visual analysis of graphics generated from MI-E in subjects with ALS can be used to select the optimal parameters for an effective mechanically assisted cough. We also observed that obstruction during insufflation is related to bulbar upper motor neuron dysfunction, and collapse during exsufflation is associated with lower motor neuron dysfunction. Moreover, presence of alterations in the generated graphs depends on severity of bulbar dysfunction.

MI-E effectiveness in patients with ALS is largely dependent on severity of bulbar dysfunction.5,6 In these patients, upper-airway responses to MI-E can decrease the effectiveness of mechanically assisted cough even to the point of being ineffective.6,8 In subjects with ALS, Andersen et al6 found upper-airway obstruction during insufflation secondary to true vocal folds adduction, a retroflex movement of the epiglottis and a backward movement of the tongue base. This obstruction during insufflation is more prominent when greater insufflation pressures are used.6 Our results revealed a pattern of obstruction during insufflation, mainly when greater pressure levels are used, in some patients; this obstruction of upper airway during insufflation prevents lung inflation prior to exsufflation, compromising MI-E effectiveness and decreasing generated Vex and CPFMI-E. During exsufflation, Andersen et al6 found an obstruction of upper airway due to a constriction of the hypopharynx; similar findings were previously described on the basis of computed tomography images.5 In a recent study including 27 neuromuscular subjects analyzing flow-volume curves generated during exsufflation when applying MI-E, Lacombe et al8 found that when a collapse of upper airway was produced due to upper-airway dysfunction an increase in CPFMI-E was detected despite a decrease in MI-E effectiveness assessed by a decrease in Vex. These findings are in line with the results of a previous bench study in which an MI-E device was attached to a lung simulator through a collapsible tube simulating upper-airway structures.19 Our findings were similar; in subjects with upper-airway collapse during exsufflation, as assessed in flow-time curve by an abrupt decrease in flow after reaching CPFMI-E at the beginning of exsufflation, we found no changes in CPFMI-E and a decrease in Vex. This behavior is attributed to rapid expulsion of the air contained in the upper airway, generating a flow spike due to dynamic airway compression of the compliant upper-airway structures.8 This is followed by a rapid decrease in flow due to an increased oropharynx resistance caused by the collapse. These findings should be taken into account when adjusting MI-E pressures; in the presence of collapse during exsufflation, CPFMI-E measurement alone can give a false reading of an effective technique, whereas analysis of flow-time graphs provides important data to help adjust the parameters. This collapse is more pronounced when the exsufflation pressure is more negative: in this regard, when we detected collapse of the upper airway during exsufflation we adjusted the exsufflation pressure accordingly, making it less negative to avoid obstruction.

Our results confirm the importance of bulbar dysfunction in MI-E effectiveness, showing that severity of bulbar dysfunction measured with NBS is the factor related to absence of alterations in graphs, which theoretically signifies no or minimal upper-airway obstruction during MI-E.

Another important finding of our study is that we have identified difference of patient phenotypes according to presence of obstruction during MI-E application. We found that predominantly upper motor neuron dysfunction at bulbar level is directly related to obstruction during insufflation and predominantly lower motor neuron dysfunction to collapse during exsufflation. Using transnasal fiberoptic laryngoscopy during MI-E in subjects with ALS, Andersen et al6 found that all the participants (both with upper motor neuron and lower motor neuron) had constriction at the hypopharyngeal level during exsufflation, very narrow in 4/7 in lower motor neuron and in 1/7 in upper motor neuron. Insufflation was the biggest problem in subjects with bulbar symptoms. When the scope had a visual view, all lower motor neuron subjects had clearly adduction during insufflation at the supraglottic level but adequate control at the glottic level. Upper motor neuron subjects had more problems at the glottic level but also supraglottic level at the higher treatment pressures. Upper motor neuron dysfunction results in spasticity and hyperreflexia, in which case laryngeal closure reflex may be increased, allowing mechanical stimuli produced by flow generated during insufflation to trigger this reflex and cause glottis closure and laryngeal adduction.20 Otherwise, lower motor neuron dysfunction is characterized by hypotonia and hyporeflexia. Applying negative pressure during expiration in healthy subjects triggers genioglossus muscle contraction to maintain upper-airway patency; in some healthy subjects, application of negative pressure induces partial or total narrowing of the upper airway, due to overlong patency of the pharyngeal dilator reflex, and decreased trigger sensitivity or intensity of the response.21 In patients with ALS with predominant lower motor neuron dysfunction, however, due to oropharyngeal muscle weakness, hypotonia, and hyporeflexia, application of negative pressure during exsufflation can induce collapse of supraglottic structures.

This study has some limitations to be considered. Ventilator graphics were analyzed without an image of upper airway during MI-E application, although we took previously described graphs as a reference8,17,18; and transnasal fiberoptic laryngoscopy could interfere with the flows generated during MI-E sessions, whereas use of local anesthesia could interfere with upper-airway reflexes; moreover, it has been reported that observations at the glottic level might not be possible with transnasal fiberoptic laryngoscopy in patients with bulbar dysfunction6; in this way, studies are needed to confirm the correlation of our results with anatomical changes in the upper airway to the MI-E application. Another limitation is that protocol was carried out without subject cough effort during exsufflation or applying thoracoabdominal thrust due to our aim of assessing upper-airway responses to MI-E without interference. Moreover, this study has been developed in clinical-stable situation; in this sense, more studies are needed to value the clinical response after making the changes in parameters according to analysis of waveforms (amount of expelled secretions, weight of secretions, need for invasive techniques to remove secretions). Although this was a single-center study, the enrolled subjects with ALS represent the heterogeneity of this disease, with upper and lower motor neuron disfunction, different onset, or different degrees of bulbar dysfunction.

Conclusions

Analysis of graphics generated during MI-E in subjects with ALS was a noninvasive and effective method to detect upper-airway responses and select optimal set parameters. We also identified 2 main phenotypes: obstruction during insufflation, which is related to upper motor neuron dysfunction at bulbar level, and collapse during exsufflation, which is related to lower motor neuron dysfunction.

Footnotes

  • Correspondence: Jesus Sancho MD PhD, Respiratory Care Unit, Respiratory Medicine Department, Hospital Clínico Universitario, Avd Blasco Ibañez 17, 46010 Valencia, Spain. E-mail: jesus.sancho{at}uv.es

  • See the Related Editorial on Page 1363

  • The authors have disclosed no conflicts of interest.

  • This research was supported by a grant from Fundación Neumología Comunidad Valenciana.

  • Supplementary material related to this paper is available at http://www.rcjournal.com.

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