CClinicalTrials.gg
Status unknownNCT01552031Updated Mar 6, 2017

Monitoring Chronic Obstructive Pulmonary Disease Patients at Home by a Forced Oscillation Technique Device

An observational study in COPD, sponsored by Raffaele Dellaca. Status unknown at 5 sites in 2 countries. Open to participants aged 40 Years to 80 Years. Per ClinicalTrials.gov, last updated 2017-03-06.

Sponsored by Raffaele Dellaca · Observational

The sponsor has not verified this record recently (last verified Mar 2017), so the status shown — last known as Recruiting — may be out of date.
Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
80
Ages
40 Years to 80 Years
Sex
All
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Study summary

Chronic obstructive pulmonary disease (COPD) is a pathological condition whose progression is characterized by stable periods broken up by intermittent acute exacerbations of the symptoms, during which a severe inflammatory process occurs often requiring hospitalization. During exacerbations the risk of death is very high making the social and economical impact of such events important.

The need of rationalize the utilization of health care resources together with the optimization of patient's care has prompted the development of models of assistance based on home monitoring. At the present time most of the suggested models were based on the utilization of diaries for symptoms perceived by the patients. Even if positive results are reported in terms of reduction of in hospitalization many COPD patients tend to underestimate the severity of their condition and their compliance in recording their symptoms rapidly decreases with time.

Attempts of using more objective measurements such as home spirometers have been done but poor results were reported mainly due to the difficulties in performing a spirometric test without medical supervision.

A more suitable approach to get objective information on the function of the respiratory system is the Forced Oscillation Technique (FOT). Such methodology is based on the analysis of the response of the system to small pressure stimuli over-imposed to the normal breathing of the patients. The measurements require minimal cooperation and can be performed without medical supervision.

The purpose of this study is to measure daily variability of FOT data measured at home of a group of COPD patients in order to identify possible correlations between symptoms change, breathing pattern, lung mechanical impedance and occurrence of exacerbation.

Read the detailed description

The continuous progresses of medical science and technology and the improvement of life conditions have increased the life expectancy in industrialized countries: the result is the progressive population aging [UN, 2002]. One of the consequences of this trend is the increasing number of people suffering from chronic diseases.

Among these pathologies chronic obstructive pulmonary disease (COPD) is the more important for number of patients and deaths affecting 80 million people in the world [WHO, 2006]. The time course of the disease is characterized by stable periods broken up by intermittent acute exacerbations of the symptoms, during which a severe inflammatory process occurs, leading to increased airways obstruction. During exacerbations the risk of death is very high [Connors et al, 1996;Soler-Cataluna et al, 2005]. Moreover the frequency and severity of exacerbations correlate with the worsening of the health condition of the patient [Anzueto et al, 2009; Donaldson et al, 2002].

The burden of care of patients with COPD on the national health care systems and society is high. The utilization of health care resources by patients with COPD is primarily due to acute exacerbations requiring care in the emergency rooms and hospital [Dal Negro, 2008] .

In the last few years the need to rationalize the health care costs has prompted to the development of new technologies for the home monitoring of these patients mainly aimed at the early detection of the onset of exacerbations. This could help the development of new therapeutic and organizational models aimed at reducing the impact of such events on the quality of life of the patient and on the national health care systems.

Published data offer several different follow-up models of home monitoring of COPD. Written and electronic diaries, questionnaires, telephonic assistance by respiratory nurses or specialized clinical personnel and use of web-based call centers have all been suggested for the follow up of patients after discharge from hospitals. Even if positive results are reported in terms of reduction of in hospitalization [Vitacca et al, 2009] many COPD patients tend to underestimate the severity of their condition [Cote et al, 1998] and patient's compliance in recording their symptoms rapidly decreases with time [Cote et al, 1998]. Moreover, other authors address the difficulty to evaluate correctly the impact of such models on patient's quality of life and on the reduction of hospitalization and mortality rate [Ram et al, 2004; Bolton et al, 2010].

An effective home monitoring system for COPD patients should have the following characteristics:

  1. easy to be used in unsupervised environment,
  2. able to provide sensible and objective information about patient status,
  3. low cost.

Clinically, diagnosis and monitoring of COPD patients is based on spirometric parameters, such as FEV1 (forced expiratory volume in 1 second), FVC (forced vital capacity) and FEV1/FVC obtained from forced expiratory maneuvers [Gold, 2009]. However, for most patients affected by COPD, it is very difficult to execute spirometry correctly because of their poor ability to perform forced maneuvers. For this reason it is necessary that the test is supervised by a physician [Miller et al, 2005]. Moreover, there is general belief in the medical community that FEV1 is insensitive to changes over short periods of time in patients with COPD so controversy surrounds the reliance of this parameter as an accurate metric for acute respiratory events.

These may be some of the reasons why most of the studies where patients have been monitored by home spirometry or peak-flow meters have reported poor results[Brouwer et al, 2010].

A promising technology for the home monitoring of respiratory diseases is represented by the Forced Oscillations Technique (FOT). FOT is based on the analysis of the response of the respiratory system to external pressure stimuli superimposed to the spontaneous breathing of the patient. It does not require the cooperation of the patient and it can provide accurate measurements even without the supervision of specialized personnel.

In the last few years new technologies based on FOT and special algorithms were developed by the respiratory research group of the Bioengineering Department of the Politecnico di Milano University, Italy. These methodologies have been already tested proving to be effective for the automatic and quantitative evaluation of several phenomena including:

  • the presence or not of Expiratory Flow Limitation (EFL) breath by breath [Dellaca' et al, 2004];
  • airways resistance corrected from the artifacts introduced by EFL [Dellaca' et al, 2009];
  • the degree of airways heterogeneities measured by the analysis of the frequency dependency of the resistance;
  • the response of the respiratory system to the administration of bronchodilators and bronchoconstrictors [Dellaca' et al, 2009].

Recently a spin-off company of respiratory group of the Bioengineering Department of the Politecnico di Milano has made available a special device (RESMONPRO-diary) suitable to collect data at patient's home without medical supervision. Data from a prototype device recorded on asthmatic patients have shown its suitability for remote unsupervised monitoring of chronic conditions.

AIM OF THE STUDY

The aim of the present study is to evaluate the possibility of monitoring oscillatory parameters of lung mechanics, measured by the Forced Oscillation Technique (FOT), for the early detection of exacerbations in COPD patients.

Therefore primary outcome will be the identification of the relationship between changes in patient's symptoms, breathing pattern, lung mechanical impedance indices and occurrence of and exacerbation.

A further outcome of the study will be the identification and classification of the occurred exacerbations.

STUDY PROTOCOL

Pre-study measurements:

After the enrollment in the study, every subject will be visited by physician and will undergo a standard pulmonary function test.

Moreover the following data will be collected:

  • exacerbation history
  • smoking history
  • disease history
  • presence of co-morbidities

Daily home monitoring program:

All patients will be monitored at home using a device for oscillometric measurement of lung functionality (RESMON pro).

The duration of the measurement will be 2-3 minutes once a day for a period comprised between 6 and 8 months. At the beginning of the measurement the device will ask the patient to fill a simple questionnaire for self-evaluation of their symptoms (dyspnoea, amount and purulence of sputum, wheeze, cough). For the duration of the study, the participant will be asked to wear an Actiwatch Spectrum 24 hours a day. The Actiwatch Spectrum, a small watch-like device, measures activity by recording and analyzing the readings from the on-board accelerometer. Each 1-minute activity epoch is analyzed and the statistical results stored in the on-board memory which can hold up to six-months of data. The Actigraphy data provides an objective record of activity and has been validated to determine normal and abnormal sleep / wake patterns.

A nurse will perform a weekly phone interview in order to collect information about presence and timing of the following events:

  • Change in current drug therapy
  • Systemic steroids use/prescription
  • Antibiotic use/prescription
  • Hospitalization due to respiratory causes
  • Emergency Room admission
  • Unscheduled GP call
  • Unscheduled GP visit
  • Specialist visit
  • Worsening in sleep
  • Worsening in dyspnea during daily life activity
  • Fever

DATA ANALYSIS

The time-series data and their variability will be analyzed using the method of the time irreversibility, sample and multiscale entropy, and Gumbel's extreme values statistic. The predictor of an exacerbation will then be derived by calculating the conditional probability of having a future acute event given the trend or the variability of indices derived from the above methods. Additionally data will be analyzed also using a deterministic approach: linear and non-linear modelling analysis

02

Conditions studied

  • COPD

Keywords

  • COPD exacerbations
  • FOT variability
03

In context

Lead sponsor

This is the only study on the registry with Raffaele Dellaca as lead sponsor.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
40 Years to 80 Years
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Probability sample

Study population

80 COPD patients, with the characteristics of frequent exacerbators (> 2 exacerbations in the past year), will be enrolled in the study.

Inclusion criteria

  • COPD at stage 3 and 4 of GOLD classification(spirometric values after bronchodilator: FEV1/VC \< 95th percentile of predicted and FEV1 \< 50% of predicted)
  • patients who reported more than two exacerbations in the past year OR
  • patients who required more than two hospital admission in the last year OR
  • patients with ER admission in the last year due to acute respiratory failure

better if:

  • depressive phenotype
  • worsening of dyspnea during walk (measured by MRC-Medical Research Council score)
  • malnutrition or obesity (BMI \< 19 or > 25)
  • patient lives alone

Exclusion criteria

Exclusion Criteria:

  • Other respiratory diseases
  • Alpha-1antitrypsin deficiency
  • Significant inflammatory diseases other than COPD
  • Organ or systemic diseases that may impair the ventilatory function (any restrictive pulmonary disease, cystic fibrosis and so on)
  • Prior lung surgery
  • Concomitant enrollment in other trials
  • Any major non-COPD disease or condition, such as uncontrolled malignancy, end-stage heart disease, liver or renal insufficiency (that requires current evaluation for liver or renal transplantation or dialysis), amyotrophic lateral sclerosis, or severe stroke, or other as deemed appropriate by investigator as determined by review of medical history and / or patient reported medical history
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Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
80 participants (estimated)

Groups and cohorts

  • Observational group
06

What researchers measure

Primary outcomes

  1. Day-by-day changes of lung mechanical impedance

    Changes in within-breath total respiratory input impedance (Zrs), resistance (Rrs) and Reactance (Xrs) measured day-by-day by the RESMONPRO device

    Time frame: Every day for 8 months

  2. Day-by-day changes of patient's symptom

    Changes of perceived symptoms as reported by the patients no the RESMONPRO device

    Time frame: Every day for 8 months

  3. Day-by-day changes of patient activity

    level of activity of the patient as recorded by the Actiwatch.

    Time frame: Every day for 8 months

  4. Number of exacerbation

    On the basis of the presence of the following events an exacerbation will be detected and classified as: Mild exacerbation: changes in current treatment or prescription of a short acting bronchodilator Intermediate exacerbation: prescription of a steroids per os Severe exacerbation: prescription of systemic antibiotic Very severe exacerbation: hospital admission

    Time frame: 8 months

  5. Day-by-day changes of breathing pattern

    Changes in breathing pattern measured while performing FOT by RESMONPRO device

    Time frame: Every day for 8 months

07

Study locations

1 of 5 sites recruiting
  • Woolcock Institute of Medical Research
    Glebe, New South Wales 2037, Australia
    Recruiting
  • Divisione di Pneumologia, Fondazione S. Maugeri, IRCCS
    Lumezzane, BS, Italy
    Completed
  • Pneumologia-Fisiopatologia Respiratoria, Azienda Ospedaliera S. Luigi Gonzaga
    Orbassano, Torino, Italy
    Completed
  • Unità Operativa di Riabilitazione Pneumologica, Fondazione S. Maugeri, IRCCS
    Pavia, 27100, Italy
    Completed
  • U.O. Pneumologia - A.O. Ospedale di Circolo e Fondazione Macchi
    Varese, 21100, Italy
    Completed
08

References and documents

Publications

  • United Nations Population Division, World Population Ageing: 1950-2050 2002.
  • Connors AF Jr, Dawson NV, Thomas C, Harrell FE Jr, Desbiens N, Fulkerson WJ, Kussin P, Bellamy P, Goldman L, Knaus WA. Outcomes following acute exacerbation of severe chronic obstructive lung disease. The SUPPORT investigators (Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments). Am J Respir Crit Care Med. 1996 Oct;154(4 Pt 1):959-67. doi: 10.1164/ajrccm.154.4.8887592. Erratum In: Am J Respir Crit Care Med 1997 Jan;155(1):386. PubMed 8887592 ↗
  • Soler-Cataluna JJ, Martinez-Garcia MA, Roman Sanchez P, Salcedo E, Navarro M, Ochando R. Severe acute exacerbations and mortality in patients with chronic obstructive pulmonary disease. Thorax. 2005 Nov;60(11):925-31. doi: 10.1136/thx.2005.040527. Epub 2005 Jul 29. PubMed 16055622 ↗
  • Anzueto A, Leimer I, Kesten S. Impact of frequency of COPD exacerbations on pulmonary function, health status and clinical outcomes. Int J Chron Obstruct Pulmon Dis. 2009;4:245-51. doi: 10.2147/copd.s4862. Epub 2009 Jul 20. PubMed 19657398 ↗
  • Donaldson GC, Seemungal TA, Bhowmik A, Wedzicha JA. Relationship between exacerbation frequency and lung function decline in chronic obstructive pulmonary disease. Thorax. 2002 Oct;57(10):847-52. doi: 10.1136/thorax.57.10.847. Erratum In: Thorax. 2008 Aug;63(8):753. PubMed 12324669 ↗
  • Dal Negro R. Optimizing economic outcomes in the management of COPD. Int J Chron Obstruct Pulmon Dis. 2008;3(1):1-10. doi: 10.2147/copd.s671. PubMed 18488425 ↗
  • Vitacca M, Bianchi L, Guerra A, Fracchia C, Spanevello A, Balbi B, Scalvini S. Tele-assistance in chronic respiratory failure patients: a randomised clinical trial. Eur Respir J. 2009 Feb;33(2):411-8. doi: 10.1183/09031936.00005608. Epub 2008 Sep 17. PubMed 18799512 ↗
  • Rennard S, Decramer M, Calverley PM, Pride NB, Soriano JB, Vermeire PA, Vestbo J. Impact of COPD in North America and Europe in 2000: subjects' perspective of Confronting COPD International Survey. Eur Respir J. 2002 Oct;20(4):799-805. doi: 10.1183/09031936.02.03242002. PubMed 12412667 ↗
  • Cote J, Cartier A, Malo JL, Rouleau M, Boulet LP. Compliance with peak expiratory flow monitoring in home management of asthma. Chest. 1998 Apr;113(4):968-72. doi: 10.1378/chest.113.4.968. PubMed 9554633 ↗
  • Ram FS, Wedzicha JA, Wright J, Greenstone M. Hospital at home for patients with acute exacerbations of chronic obstructive pulmonary disease: systematic review of evidence. BMJ. 2004 Aug 7;329(7461):315. doi: 10.1136/bmj.38159.650347.55. Epub 2004 Jul 8. Erratum In: BMJ. 2004 Oct 2;329(7469):773. PubMed 15242868 ↗
  • Bolton CE, Waters CS, Peirce S, Elwyn G; EPSRC and MRC Grand Challenge Team. Insufficient evidence of benefit: a systematic review of home telemonitoring for COPD. J Eval Clin Pract. 2011 Dec;17(6):1216-22. doi: 10.1111/j.1365-2753.2010.01536.x. Epub 2010 Sep 16. PubMed 20846317 ↗
  • Gold PM. The 2007 GOLD Guidelines: a comprehensive care framework. Respir Care. 2009 Aug;54(8):1040-9. Erratum In: Respir Care. 2009 Nov;54(11):1501. PubMed 19650945 ↗
  • Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, Crapo R, Enright P, van der Grinten CP, Gustafsson P, Jensen R, Johnson DC, MacIntyre N, McKay R, Navajas D, Pedersen OF, Pellegrino R, Viegi G, Wanger J; ATS/ERS Task Force. Standardisation of spirometry. Eur Respir J. 2005 Aug;26(2):319-38. doi: 10.1183/09031936.05.00034805. No abstract available. PubMed 16055882 ↗
  • Brouwer AF, Visser CA, Duiverman EJ, Roorda RJ, Brand PL. Is home spirometry useful in diagnosing asthma in children with nonspecific respiratory symptoms? Pediatr Pulmonol. 2010 Apr;45(4):326-32. doi: 10.1002/ppul.21183. PubMed 20196110 ↗
  • Dellaca RL, Santus P, Aliverti A, Stevenson N, Centanni S, Macklem PT, Pedotti A, Calverley PM. Detection of expiratory flow limitation in COPD using the forced oscillation technique. Eur Respir J. 2004 Feb;23(2):232-40. doi: 10.1183/09031936.04.00046804. PubMed 14979497 ↗
  • Dellaca RL, Pompilio PP, Walker PP, Duffy N, Pedotti A, Calverley PM. Effect of bronchodilation on expiratory flow limitation and resting lung mechanics in COPD. Eur Respir J. 2009 Jun;33(6):1329-37. doi: 10.1183/09031936.00139608. Epub 2009 Jan 22. PubMed 19164347 ↗
  • Zimmermann SC, Huvanandana J, Nguyen CD, Bertolin A, Watts JC, Gobbi A, Farah CS, Peters MJ, Dellaca RL, King GG, Thamrin C. Day-to-day variability of forced oscillatory mechanics for early detection of acute exacerbations in COPD. Eur Respir J. 2020 Sep 10;56(3):1901739. doi: 10.1183/13993003.01739-2019. Print 2020 Sep. PubMed 32430416 ↗
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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Mar 6, 2017, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT01552031
Lead sponsor
Raffaele Dellaca
Collaborators
Restech Srl, Politecnico di Milano, Fondazione Salvatore Maugeri, Azienda Ospedaliera S. Luigi, Orbassano (TO), Baylor College of Medicine, Ospedale di Circolo e Fondazione Macchi, Varese, Woolcock Institute of Medical Research
Responsible party
Raffaele Dellaca (Professor, Politecnico di Milano) — Sponsor-investigator
First posted
Mar 13, 2012
Start date
Nov 2011
Primary completion
Dec 2017 (estimated)
Completion
Jul 2018 (estimated)
Last update
Mar 6, 2017

Study contacts

Raffaele L Dellaca', PhD
Contact
raffaele.dellaca@polimi.it
+393804799108
Raffaele L Dellaca', PhD
principal investigator · Politecnico di Milano, Italy
Michele Vitacca, MD
principal investigator · Pneumology Division Fondazione Salvatore Maugeri, IRCCS, Lumezzane, Italy
Alessandro Gobbi, PhD
principal investigator · Politecnico di Milano, Italy
Pasquale P Pompilio, PhD
principal investigator · Politecnico di Milano, Italy
Emanuela Zannin, PhD
principal investigator · Politecnico di Milano, Italy
Carlo Gulotta, MD
principal investigator · Pneumologia-Fisiopatologia Respiratoria, Azienda Ospedaliera S. Luigi Gonzaga Orbassano, Torino, Italy
Amir Sharafkhaneh, MD, PhD
principal investigator · Sleep Disorders & Research Center Michael E. DeBakey VA Medical Center
Piero Ceriana, MD
principal investigator · Unità Operativa di Riabilitazione Pneumologica, Fondazione Salvatore Maugeri, IRCCS, Pavia, Italy
Fausto Colombo, MD
principal investigator · Direttore U.O. Pneumologia - A.O. Ospedale di Circo lo e Fondazione Macchi, Varese

Oversight

Data monitoring committee
No
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