NO20110653A1 - Respirasjonsovervakning - Google Patents

Abstract

The invention relates to a system for monitoring respiratory distress for a patient, comprising at least one pressure sensor which will be positioned in a catheter and which will be adapted for positioning at a selected position in the esophagus, where the pressure sensor will be adapted to be able to monitor the pressure. the esophagus at a selected resolution which provides a time series of pressures of a selected length. The system will comprise calculating means that can split the time series into a number of time windows, each time window being comprised of at least the respiratory cycle - a time series containing two intersections of a predefined zero value in the same direction - which calculates the respiratory trouble index indicating the pressure amplitudes within each time window, thus providing a set of characteristic values for each time window comprising said respiratory trouble index and the length of each time window.

Description

RESPIRATORY MONITORING

The invention relates to a system and a method for being able to monitor respiratory distress for a patient, comprising at least one pressure sensor, where the pressure sensor will be located in a catheter and will be adapted to be placed at a selected location in the esophagus or in the airways in the patient.

Internationally, it is claimed that "The measurement of esophageal pressure with continuous nocturnal monitoring will be the reference standard for the measurement of monitored respiratory distress"

(English: "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]. Sleep-related breathing disorder, SRBD (from English: "Sleep Related Breathing Disorder"), is a term for disorders that have been discovered relatively recently, and which are characterized by snoring, hypersomnolence and varying degrees of reduced air passage (apneas and hypopneas) through narrowed, relaxed upper respiratory tract during sleep [7].

Studies have shown that increased pressure in the airways during sleep, together with snoring and awakenings, can lead to health problems, such as those initiated by apneas and hypopneas [8]. As there are also awakenings and sleep stages with lighter sleep throughout the night, the important head and body rest could be compromised along with other functions, such as arterial oxygen supply and heart rhythm [9]. The result could be a multitude of changes throughout the body, such as hypertension (high blood pressure), cardiac arrhythmias, heart attacks, hormone changes, cerebral hemorrhage, as well as social disturbances, traffic accidents and so on [10]. These problems can be found in addition to the socially unacceptable snoring, which is actually the most important reason why people seek medical treatment. Reference [1] concerns measurements of different pressure differences, that is, the difference between maximum and minimum values, which are used to be able to find the place where there is a narrow passage for the airways. This could be an immediate measurement, and could not be linked to any development over time, or provide any means to be able to assess any long-term effects of the disturbances.

Today, sleep disorders will be diagnosed through a full night of polysomnography, as has been described in the 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 will not be able to routinely use pressure sensors, which will be able to provide a direct and reliable estimate of lung pressure during breathing.

Other methods aim at the detection of obstructive sleep apnea (English: "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, which have been discussed in Abdelfihani 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, uses measurement of pressure and/or temperature in the esophagus, but the data is not used to estimate the degree of respiratory distress.

For this reason, the aim of the present invention will be to provide a system and a method to be able to monitor respiration, and to be able to detect and analyze the respiratory difficulty. This can be achieved by using a system that has been described above, and which has been characterized in the independent requirements.

The invention thus relates to a method and an assembly for the detection and analysis of respiratory distress, and may be comprised of: measurement of lung pressure, represented by the pressure in the oesophagus, which generates a signal which will correspond to the measured time series of values. The pressure recordings, which reflect the respiratory effort, are used to estimate a parameter - the respiratory effort index (English: "the Respiratory Effort Index" (REI)), which describes the degree of respiratory effort.

The invention will be described below with reference to the corresponding drawings which will illustrate the invention by means of examples.

Figure 1 illustrates placement of a sensor on a patient.

Figure 2 illustrates the sequence for the measurement according to the invention.

As illustrated in fig. 1, the present invention will be able to use a catheter 1 with a pressure sensor 2 near the end, which is inserted through the patient's nose. The catheter contains a marker which has been positioned so that, when placed in relation to the edge of the soft palate, it will ensure that the pressure sensor will be located in the esophagus 5. The catheter 1 will be connected to a small device 4 for data acquisition - which preferably will be battery operated and be carried by the patient. The acquired data will be stored for post-processing and analysis. Alternatively, data could be sent to be made, either by wire or wirelessly, to a computer device, to be able to perform online analysis. The measurements can be carried out while the patient is lying down and sleeping, in order to be able to estimate sleep REI (SREI). Alternatively, they can be performed while the patient is awake at rest (AREI) or during exercise (EREI).

The REI parameters will be able to diagnose the respiratory distress under different conditions. REI during sleep will be important, because it describes the fluctuations in lung pressure, which also reflect the different degrees of narrowing of the upper airways, which can occur in sleep-related breathing disorders (English: "Sleep Related Breathing Disorders" (SRBD)). An REI while awake can be used to evaluate the different conditions that affect lung function as well as the effect of different medical treatments. Furthermore, breathing difficulties as a function of physical exercises can be evaluated.

Description

A medical catheter will be a tube device - which is filled or is hollow, for example as described in [4]. The catheter will be able to contain at least one sensor, which measures at least one pressure. The bandwidth of the sensor (measured in Hz) must be wide enough to be able to characterize the dynamic pressure fluctuations that occur due to breathing, i.e. at least 0.5 Hz, preferably better. Other parameters, in addition to the esophageal pressure that can be measured, will be: 1. One or more pressure sensors, which can for example be placed on the edge of the soft palate (root of the tongue) [1], in combination with temperature sensors that will be used to to be able to measure air flow (breathing). These will provide data on different types of apneas (obstructive, central, hypopneas and mixed apneas), 2. oximeter, which provides data on oxygen saturation (Sp02) in the blood, as well as pulse rate,

3. Sp02 provides as data on awakenings [5],

4. leg and arm sensors that provide data on activity,

5. a microphone that provides snoring data,

6. a body position sensor that provides data on sleep position,

7. electroencephalography ("Electroencephalography" - EEG) and electrooculography ("Electrooculography" - EOG) (sensors) which provide data on sleep stages, awakenings and sleep / wakefulness, 8. Electrocardiography (ECG) which provides information on heart function, 9. Electromyography ( EMG) which provides information about muscle activity.

The REI index could be one of several variants:

REII. Split the pressure time series p(t) [p is pressure, t is time] into breathing cycles bounded by two adjacent (in time) zero crossings in the same direction (that is, from positive to negative or from negative to positive). For each cycle, measure peak-to-peak pressure (maximum pressure minus minimum pressure). Sum up peak-to-peak values and typically generate a histogram or summation curve, or a chart showing counts per time interval per peak-to-peak pressure interval. The percentage of counts above a threshold value for piim will then name that index of respiratory distress, REIi;iim.

REI2. Split the pressure time series p(t) [p is pressure, t is time] into breathing cycles bounded by two adjacent (in time) zero crossings in the same direction (that is, from positive to negative or from negative to positive). For each cycle, measure the peak negative pressure

(minimum pressure). Sum the negative peak values and generate a histogram or a summation curve or chart showing counts per time interval per peak pressure interval. Percentage of counts that are below a threshold value of pumvil then name an index for respiratory distress REl2,iim.

REI3. Split the pressure time series p(t) [p is pressure, t is time] into breathing cycles bounded by two adjacent (in time) zero crossings in the same direction (that is, from positive to negative or from negative to positive). For each cycle, measure the positive peak pressure (maximum pressure). Sum the positive peak values and generate a histogram or summation curve or chart showing counts per time interval per peak pressure interval. The percentage of counts that are below a threshold value of piimwill then be called the respiratory distress index REI^um.

Perform a frequency analysis of the pressure signal p(t). For example by using a battery of parallel filters or by applying Fourier analysis, for example by using Fast Fourier transform (FFT). This will provide data on breathing pressure as a function of breathing rate, both over the overall observation period or as it changes over the observation period.

Based on estimates of lung volume (for example from spirometry), the (exhalation or inhalation) inspiratory and/or expiratory work in Nm (that is, Joule) can be estimated. This provides inspiratory and/or expiratory (work of inspiration and/or work of expiration) work in Watts, as well as peak values, variation as well as correlation with other parameters, such as sleeping position (left, right, supine, prone), awakenings, oxygen saturation, legs - and arm movements, snoring, obstructive apneas, hypopneas, centric and mixed apneas.

REI also describes intrathoracic pressure variations by measuring fluctuations from baseline breathing in all different groups or individual subjects selected, per time unit, per time unit in sleeping or awake state, or aggregated, in other selected time sequences in awake or asleep state, or aggregated , per time unit as a percentage of maximum effort or total sleep time.

The preferred pressure sensor would be a miniature MEMS (micro electromechanical system) sensor that would be able to fit into a medical catheter of 2 mm diameter or less. The sensor should be able to have negligible temperature drift and high sensitivity. A catheter which would be suitable for medical use, for example as has been described in [4].

To summarize, the invention relates to a system for being able to monitor respiratory distress in a patient, comprising at least one pressure sensor, where the pressure sensor will be located in a catheter and which will be adapted for placement in a selected position in the esophagus of a patient, where the pressure sensor will be adapted to be able to monitor the pressure with a selected resolution over a selected period of time.

The monitoring could be performed by sampling the pressure in the esophagus at a selected frequency, which is preferably higher than 0.5 Hz or twice the respiratory frequency, which provides a time series of sampled pressure. In this way, the breathing difficulty can be calculated over time.

The system includes calculation means to be able to split the time series with sampling into a number of time windows, where each window will be able to be comprised of a time series that will be able to contain two crossings of a predefined zero value in the same direction, which thus essentially defines a breathing cycle, which will be defined to be able to include a local minimum value in connection with an exhalation and a local minimum value in connection with an inhalation. In the preferred calculation according to the invention, the breathing cycle will thus be defined to be able to start when the breathing cycle crosses a threshold value, for example zero, in one direction and stops when it crosses the same threshold value in the opposite direction. In practice, this could mean, for example, that the patient has started to breathe out, then breathed in, and then started to breathe out again. The above-mentioned sampling frequency must be sufficient to be able to achieve sufficient accuracy when determining the crossings of the threshold values, but otherwise will not be important.

The respiratory distress index, which indicates the fluctuation within each time window, will then be calculated, which in turn will provide a set of characteristic values for each time window which will be covered by said respiratory distress index and length of each time window.

A registration period could last a whole night, and should be sufficiently long to be able to achieve a relevant analysis, which will thus be comprised of a large number of breathing cycles.

References

1. Tvinnereim, M., Hansen, RK. Detection of breathing disturbances. Patent application WO 2001/087156. 2. Tvinnereim, M., Hansen, RK. Breathing monitor apparatus. Patent application

EP2034891. 3. Gjersøe, 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. Kållbåck, B., Hult, A. Tubular catheter for invasive use and manufacturing therefor. Patent application EP 2032201. 5. Lévy, P., Pépin, 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. 10. 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 (10)

1. System for being able to monitor respiratory distress in a patient, which is comprised of at least one pressure sensor, where the pressure sensor will be positioned in a catheter and will be adapted for positioning in a selected position in the esophagus, where the pressure sensor will be adapted to be able to monitor pressure in the esophagus at a selected resolution providing a time series of pressure having a selected length, where the system will be comprised of calculation means to be able to split the time series into a number of time windows, where each time window will be comprised of at least a respiratory cycle - a time series containing two crossings of a predefined zero value in the same direction - which calculates the index of respiratory distress, which indicates the pressure amplitudes within each time window, thus providing a set of characteristic values for each time window comprising the aforementioned index of respiratory distress and the length of each time window. 2. System according to claim 1, which will be comprised of analysis means to be able to analyze the frequency content of the pressure signal, for example using Fast Fourier Transform (FFT) analysis. 3. System according to claim 2, in which the analysis means will be adapted to be able to provide a measure of the pressure as a function of frequency. 4. System according to claim 1, comprising analysis means to be able to measure the length of time in a breathing cycle. 5. System according to claim 1, in which the analysis means can be adapted to be able to provide a measure of the pressure as a function of the length of the breathing cycle. 6. System according to claim 1, in which the respiratory distress index is calculated from the pressure difference between the positive and the negative peak values. 7. System according to claim 1, in which the index for respiratory distress is calculated from the pressure difference between one of said peak values and zero value. 8. System according to claim 1, comprising communication means to be able to communicate signals from said pressure sensor to an analysis means outside the patient. 9. System according to claim 1, which includes storage means to be able to store an estimated lung volume. 10. System according to claim 7, in which said analysis means will be adapted to be able, based on said estimated lung volume and said characteristics, to estimate the exhalation and/or inhalation work performed by the patient.