WO2012150243A2

WO2012150243A2 - Respiration monitoring

Info

Publication number: WO2012150243A2
Application number: PCT/EP2012/057993
Authority: WO
Inventors: Rolf Kahrs Hansen; Magne Tvinnereim
Original assignee: Spiro Medical As
Priority date: 2011-05-02
Filing date: 2012-05-02
Publication date: 2012-11-08
Also published as: WO2012150243A3; NO20110653A1

Abstract

The invention, relates to a system for monitoring respiratory effort in a patient, comprising at least one pressure sensor, the pressure sensor being positioned in a catheter and being adapted for positioning in a chosen position in the esophagus, the pressure sensor being adapted to monitor the pressure in the esophagus at a chosen resolution providing a time series of pressure having a chosen length. The system comprising calculation, means for splitting the time series into a number of time windows, each window comprising at least one respiration cycle - a time series containing two crossings of a predefined zero value in the same direction -calculating the respiratory effort index indicating the pressure amplitudes within each time window thus providing a set of characteristic values for each, time window comprising said respiratory effort index and the length of each time window.

Description

RESPIRATION MONITORING

The invention relates to a system and method for monitoring respiratory effort in a patient, comprising at least one pressure sensor, the pressure sensor being positioned in a catheter and being adapted for positioning in a chosen position in the esophagus or airways of the patient.

It is internationally stated that "The measurement of esophageal pressure with continuous overnight monitoring is the reference standard for measuring respiratory effort", American Academy of Sleep Medicine (AASM) 2007, reference [6]. SRBD (Sleep Related Breathing Disorder) is a relatively newly discovered disease entity, characterized by snoring, daytime hypersomnolence and different degrees of impaired air passage (apneas and hypopneas) through a narrowed, relaxed upper airway during sleep [7].

Investigations have shown that increased airway pressure during sleep along with snoring and arousals can result in health problems like those initiated by apneas and hypopneas[8]. By additionally causing arousals and lighter sleep stages through the night, the important brain and body rest are compromised together with other functions like the arterial oxygenation and heart rate [9]. The result may be multiple changes throughout the body, such as hypertonia, heart arrhytmias, heart infarctation, hormone changes, brain haemorrhage as well as social disorders, traffic accidents etc. [10]. These problems are seen in addition to the utmost socially unaccepted snoring, which is in fact the most important reason for people to seek medical treatment. Reference [1] relates to measurements of pressure differences, i.e. difference between maximum and minimum values, being used to find the position of a narrow passage in the airways. This is an instantaneous measurement and does not relate to any developments over time or provide means to consider any long term effect of the disturbances.

Today, sleep disorders are diagnosed by whole night polysomnography as stated in American Academy of Sleep Medicine Task Force (1999) "Sleep-related breathing disorders in adults: Recommendations for syndrome definition and

measurement techniques in clinical research." Sleep 22: 667-689, but this method does not routinely employ pressure sensors capable of providing a direct and reliable estimate of the lung pressure during breathing.

Other methods aim at the detection of obstructive sleep apnea (OSAS) as described in Townsend D, Shama A, Braun E, Scatarelli I, Mc Eiver J, Eiken T,Freiberg M. "Assessing Efficacy, Outcomes and Cost Savings for Patients with Obstructive Sleep Apnea Using Two Diagnostic and Treatment Strategies." Sleep Diagnosis and Therapy 2007; 1(7): 1-8. Some devices discussed in Abdelghani A, Roisman G,

Escourrou P. " Evaluation of a home respiratory polygraphy system in the diagnosis of the obstructive sleep apnea syndrome". Rev mal Respir 2007 Mar;24(3 Pt 1): 331-8. use measurement of pressure and/or temperature in the esophagus, but the data are not used to estimate the degree of respiratory effort.

Therefore, the aim of the present invention is to provide a system and a method for monitoring respiration and being capable of detecting and analyzing respiratory effort. This is obtained using a system as described above and as

characterized in the independent claims.

The invention thus relates to a method and an assembly for the detection and analysis of respiratory effort, which comprises: measuring of lung pressure represented by the pressure in the esophagus, generating a signal corresponding to the measured time series of values. The pressure recordings, reflecting the Respiratory Effort, are used to estimate a parameter - the Respiratory Effort Index (REI) - which describes the degree of respiratory effort.

The invention will be discussed below with reference to the corresponding drawings, illustrating the invention by way of examples.

Figure 1 illustrates the positioning of the sensor in a patient.

Figure 2 illustrates the measuring sequence according to the invention.

As illustrated in figure 1 the present invention employs a catheter 1 with a pressure sensor 2 near the end, inserted through the nose of the patient 3. The catheter contains a marker positioned so that, when placed relative to the rim of the soft palate, ensures that the pressure sensor is located in the esophagus 5. The catheter 1 is connected to a small data acquisition device 4 - preferably battery operated and carried by the patient. The acquired data are stored for post-processing and analysis.

Alternatively, data can be transmitted either by wire or wirelessly to a computing device for online analysis. The measurements are carried out while the patient is lying asleep in order to estimate the sleep REI (SREI). Alternatively it can be carried out while the patient is awake at rest (AREI) or during exercise (EREI).

The REI parameters will diagnose the respiratory effort under various conditions. REI during sleep is important because it describes the fluctuations in lung pressure, also reflecting the various degrees of Upper Airway narrowing which occurs during Sleep Related Breathing Disorders (SRBD). REI while awake can be used to evaluate the various conditions affecting lung function as well as the impact of different medical treatment modalities. Moreover, breathing effort as a function of physical exercise can be evaluated.

Description

A medical catheter is a tubular device - filled or hollow, for example as described in [4]. The catheter contains at least one sensor measuring at least pressure. The sensor bandwidth (measured in Hz) must be wide enough to characterize the dynamic pressure fluctuations due to breathing, i.e. at least 0.5 Hz, preferably wider. The pressure sensitivity should be at least 2 cmH₂0, preferably better.

Other parameters in addition to the esophagus pressure may be measured:

1. One or more pressure sensors, for instance located at the rim of the soft palate (base of the tongue) [1], in combination with temperature sensors that are used to estimate air-flow (breathing). These will provide data on various types of apneas (obstructive, central, hypopneas and mixed apneas),

2. oximeter provides data on oxygen saturation (Sp0₂) in the blood as well as pulse rate,

3. Sp0₂ provides data on arousals [5],

4. leg and arm sensors provide data on activity,

5. a microphone provides data on snoring,

6. a body position sensor provides data on sleeping position,

7. Electroencephalography (EEG) and Electrooculography (EOG) (sensors)

provide data on sleep stages, arousals and sleep/awake,

8. Electrocardiography (ECG) provides information of heart function,

9. Electromyography (EMG) provides information on muscle activity The REI index can be one of several variants:

REIi. Split the pressure time series p(t) [p is pressure, t is time] into breathing cycles limited by two neighboring (in time) zero crossings in the same direction (i.e. from positive to negative or from negative to positive). For each cycle, measure the peak-to-peak pressure (the maximum pressure minus the minimum pressure). Sum up the peak to peak values and typically generate a histogram or summation curve or diagram showing counts per time interval per peak-to-peak pressure interval. Percentage of counts above a threshold value of pu_m will then denote the respiratory effort index REIi_,ii_m.

REI₂. Split the pressure time series p(t) [p is pressure, t is time] into breathing cycles limited by two neighboring (in time) zero crossings in the same direction (i.e. from positive to negative or from negative to positive). For each cycle, measure the negative peak pressure (the minimum pressure). Sum up the negative peak values and generate a histogram or summation curve or diagram showing counts per time interval per peak pressure interval. Percentage of counts below a threshold value of Pii_m will then denote the respiratory effort index REI₂, u_m.

REI3. Split the pressure time series p(t) [p is pressure, t is time] into breathing cycles limited by two neighboring (in time) zero crossings in the same direction (i.e. from positive to negative or from negative to positive). For each cycle, measure the positive peak pressure (the maximum pressure). Sum up the positive peak values and generate a histogram showing counts per time interval per peak pressure interval. Percentage of counts above threshold value of pu_m will then denote the respiratory effort index REI_3i i_im.

Perform a frequency analysis of the pressure signal p(t). For example using a bank of parallel filters or using Fourier analysis, for example using the Fast Fourier Transform (FFT). This provides data on the breathing pressure as a function of breathing frequency, both over the total observation period or as it changes over the observation period.

Based on estimates of lung volume (for example from spirometry),

(exhalation or inhalation) inspiratory and/or expiratory work in Nm (i.e. Joule) can be estimated. This provides average inspiratory and/or expiratory (inspiration work and/or expiration work) work in Watts as well as peak values, variability as well as correlation with other parameters such as sleeping position (left, right, supine, prone), arousals, oxygen saturation, leg and arm movement, snoring, obstructive apneas, hypopneas, central and mixed apneas.

REI also describes the intrathoracic pressure variations by measuring fluctuations from baseline breathing in all different groups or individual persons chosen, per time unit, per time unit asleep or awake or in total, in other chosen time sequences awake or asleep or in total, per time unit as percentage of maximum effort or total sleep time.

The preferred pressure sensor is a miniature MEMS (micro-electromechanical system) sensor that can fit into a medical catheter with diameter 2 mm or less. The sensor should have negligible temperature drift and high sensitivity.

A catheter suitable for medical use, for example as described in [4].

To summarize, the invention relates to a system for monitoring respiratory effort in a patient, comprising at least one pressure sensor, the pressure sensor being positioned in a catheter and being adapted for positioning in a chosen position in the esophagus of the patient, the pressure sensor being adapted to monitor the pressure with a chosen resolution over a chosen period of time.

The monitoring may be performed by sampling the pressure in the esophagus at a chosen frequency, preferably more than 0.5Hz or double the respiration frequency, providing a time series of sampled pressure. This way the breathing effort may be calculated over time.

The system comprises calculation means for splitting the sampled time series into a number of time windows, each window comprising a time series containing two crossings of a predefined zero value in the same direction thus in essence defining one breathing cycle, being defined as including one local maximum value in connection with an expiration and a local minimum value in connection with an inspiration. In the preferred calculation according to the invention the breathing cycle is then defined as starting when the breathing cycle crosses a threshold value, e.g. zero, in one direction and stops when crossing the samethreshold value in the same direction. Thus the breathing cycle will include a crossing of the threshold value in the opposite direction. In practice this may for example mean that the patient has started exhaling, then inhaled, and then started exhaling again. The abovementioned sampling frequency has to be sufficient to obtain sufficient accuracy in the determining the crossings of the threshold values but is otherwise not important.

The respiratory effort index indicating the fluctuation within each time window is then calculated providing a set of characteristic values for each time window comprising said respiratory effort index and the length of each time window.

A registration period may last a whole night and should at least be sufficiently long to obtain a relevant analysis, thus comprising a large number breathing cycles.

References

1. Tvinnereim , M., Hansen, R.K. Detection of breathing disturbances. Patent application WO 2001/087156.

2. Tvinnereim , M., Hansen, R.K. Breathing monitor apparatus. Patent application EP2034891.

3. Gjersoe, B. Internal registration of gas/air-and other fluid flows in a human body and use of pressure sensors for such registration. Patent application

W096118388.

4. Kallback, B., Hult, A. Tubular catheter for invasive use and manufacturing therefor. Patent application EP 2032201.

5. Levy, P., Pepin, J-L. Clinical usefulness of Sa02 variability assessment and arousal detections in patients with sleep-disordered breathing.

6. American Academy of Sleep Medicine. AASM Manual for the Scoring of Sleep and Associated Events. Rules, Terminology and Technical Specifications.

Westchester, Illinois, 2007.

7. Guilleminault C. Obstructive sleep apnea syndrome. A review. Psych Clin North Am. Dec 1987;607-12.

8. Nieto FJ, Young TB, Lind BK et al. Association of sleep-disordered breathing, sleep apnea and hypertension in a large community-based study. Sleep Heart Health Study. JAMA 2000;283: 1880-81.

9. Guilleminault C, Stoohs R., Clerk A., Cetel M. and Maistros P. A cause of excessive daytime sleepiness. The upper airway resistance syndrome. Chest 1993;104:781-7. He J, Kryger MH, Zorick FJ, et al. Mortality and apnea index in obstructive sleep apnea. Experience in 385 male patients. Chest. 1988; 94 :9-14.

Claims

C 1 a i m. s

1. System for monitoring respiratory effort in a patient, comprising at least one pressure sensor, the pressure sensor being positioned in a catheter and being adapted for positioning in a chosen position in the esophagus, the pressure sensor being adapted to monitor the pressure in the esophagus at a chosen resolution providing a time series of pressure having a chosen length,

the system comprising calculation means for splitting the time series into a number of time windows, each window comprising at least one respiration cycle - a time series containing two crossings of a predefined zero value in the same direction - calculating the respiratory effort index indicating the pressure amplitudes within each time window thus providing a set of characteristic values for each time window comprising said respiratory effort index and the length of each time window.

2. System according to claim 1 , comprising analyzing means for analyzing the frequency content of the pressure signal, e.g. using Fast Fourier Transform (FFT) analysis.

3. System according to claim. 2, wherein the analyzing means is adapted to provide a measure of the pressure as a function of frequency.

4. System according to claim 1, comprising analyzing means for measuring the length in time of a breathing cycle.

5. System according to claim 4, wherein the analyzing means is adapted to provide a measure of the pressure as a function, of breathing cycle length.

6 System according to claim I , wherein the respiratory effort index is calculated from the pressure difference between the positive and negative peak values.

7. System according to claim 1 , wherein, the respiratory effort inde is calculated from the pressure difference between one of said peak values and zero value.

8» System according to claim 1, comprising communication means for communicating signals from, said pressure sensor to an. analysis means outside the patient.

9. System, according to claim 1 , including storage means for storing an estimated lung volume.

10. System according to claim 7, wherein said analyzing means is adapted to, based on said estimated lung volume and said characteristics, estimate the exhalation, and/or the inhalation, work performed by the patient.