Monitoring of Physiological Parameters to Predict Exacerbations of Chronic Obstructive Pulmonary Disease (COPD): A Systematic Review

Developing effective strategies to optimize physical activity and cardiorespiratory fitness in the long Covid population- The need for caution and objective assessment

The Post Covid-19 Condition (commonly known as Long Covid) has been defined by the World Health Organisation as occurring in individuals with a history of probable or confirmed SARS CoV 2 infection, usually within 3 months from the onset of acute Covid-19 infection with symptoms that last for at least two months which cannot be explained by an alternative diagnosis. Long Covid is associated with over two hundred recognised symptoms and affects tens of millions of people worldwide. Widely reported reductions in quality of life(QoL) and functional status are caused by extremely sensitive and cyclical symptom profiles that are augmented following exposure to physical, emotional, orthostatic, and cognitive stimuli. This manifestation prevents millions of people from engaging in routine activities of daily living (ADLs) and has important health and well-being, social and economic impacts. Post-exertional symptom exacerbation (PESE) (also known as post-exertional malaise) is an exacerbation in the severity of fatigue and other symptoms following physical, emotional, orthostatic and cognitive tasks. Typically, this will occur 24-72 h after "over-exertion" and can persist for several days and even weeks. It is a hallmark symptom of Long Covid with a reported prevalence of 86%. The debilitating nature of PESE prevents patients from engaging in physical activity which impacts functional status and QoL. In this review, the authors present an update to the literature relating to PESE in Long Covid and make the case for evidence-based guidelines that support the design and implementation of safe rehabilitation approaches for people with Long Covid. This review also considers the role of objective monitoring to quantify a patient's response to external stimuli which can be used to support the safe management of Long Covid and inform decisions relating to engagement with any stimuli that could prompt an exacerbation of symptoms.

A randomized clinical trial of home telemonitoring in patients with advanced heart and lung diseases

BRIEF SUMMARY

The addition of home monitoring to an integrated care model in patients with advanced chronic heart/lung diseases decreases mortality, hospital and emergency admissions, improves functional status, HRQoL, and is cost-effective.

BACKGROUND

Telemonitoring is a promising implement for medicine, but its efficacy is unknown in patients with advanced heart and lung failure (AHLF).

OBJECTIVE

To determine the efficacy of a telemonitoring system added to coordinated clinical care in patients with AHLF.

DESIGN

Randomized phase 3 multicenter clinical trial with parallel groups in adult patients.

PARTICIPANTS

Five spanish centers including patients with AHLF at discharge or in out-patient clinics.

INTERVENTION

Patients were randomly assigned to receive a remote bio-parameters telemonitoring system (TELECARE) or best usual care (UCARE). TELECARE patients were provided with devices that collected symptoms and bio-parameters, and transferred them synchronously to a call-center, with a real-time health-care response.

MAIN MEASURES

Primary end point was the need of admissions/emergency room visits at 45, 90, 180 days. Secondary end points included health care requirements, mortality, functional assessment, health related quality of life (HRQoL), perceived satisfaction, and cost-efficacy.

RESULTS

510 patients were included (54.5% women, median age 76.5 years; 63.1% suffered heart failure, 13.9% lung failure, and 22.9% both conditions). Clinical and functional features were comparable in both arms. TELECARE globally needed less admissions with respect UCARE after 45 days of inclusion (35.4% vs. 46.9%, p < 0.05). This tendency was maintained in the subgroups of patients with multimorbidity (34.2% vs. 46.9%, p < 0.05), intermediate risk of mortality (36.5% vs. 51.1%, p < 0.05), and those included after hospital discharge (34.9% vs. 50.5%, p < 0.01). HRQoL significantly improved (TELECARE/UCARE EuroQol baseline of 56.2 ± 18.2/55.1 ± 19.7, p = 0.054, and 64 ± 19.9/56.3 ± 21.6; p < 0.01 at the end), and perceived satisfaction was also higher (6.77 ± 0.52 vs. 6.62 ± 0.81, p < 0.001; highest possible score = 7). A trend to mortality decrease was also observed (12.9% vs. 19.3%, p = 0.13). TELECARE was cost-efficacious (TELECARE/UCARE QALY 3.94 Euros/0.81Euros).

CONCLUSIONS

The addition of a telemonitoring system to an integrated care model in patients with AHLF decreases hospital and emergency admissions, improves functional status as well as HRQoL, and is cost-efficacious.

Wearable technology interventions in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death and is associated with multiple medical and psychological comorbidities. Therefore, future strategies to improve COPD management and outcomes are needed for the betterment of patient care. Wearable technology interventions offer considerable promise in improving outcomes, but prior reviews fall short of assessing their role in the COPD population. In this systematic review and meta-analysis we searched ovid-MEDLINE, ovid-EMBASE, CINAHL, CENTRAL, and IEEE databases from inception to April 2023 to identify studies investigating wearable technology interventions in an adult COPD population with prespecified outcomes of interest including physical activity promotion, increasing exercise capacity, exacerbation detection, and quality-of-life. We identified 7396 studies, of which 37 were included in our review. Meta-analysis showed wearable technology interventions significantly increased: the mean daily step count (mean difference (MD) 850 (494-1205) steps/day) and the six-minute walk distance (MD 5.81 m (1.02-10.61 m). However, the impact was short-lived. Furthermore, wearable technology coupled with another facet (such as health coaching or pulmonary rehabilitation) had a greater impact that wearable technology alone. Wearable technology had little impact on quality-of-life measures and had mixed results for exacerbation avoidance and prediction. It is clear that wearable technology interventions may have the potential to form a core part of future COPD management plans, but further work is required to translate this into meaningful clinical benefit.

A Fast Calibration Method for Pneumotachograph with a 3L Syringe

The pneumotachograph (PNT), a commonly used flowmeter in pulmonary function diagnostic equipment, is the required frequency calibration to maintain high accuracy. Aiming to simplify calibration steps, we developed a fast calibration system with a commercially available 3L syringe to provide a real output flow waveform. The acquisition of the real output flow waveform is based on the reliable measurement of in-cylinder pressure and the real-time detection of plunger speed. To improve the calibration accuracy, the tapping position for measuring in-cylinder pressure was optimized by CFD dynamic-mesh updating technique. The plunger speed was obtained by tracking the handle of the plunger with a smart terminal. Then, the real output flow was corrected using a compensation model equation. The calibration system was verified by the pulmonary waveform generator that the accuracy satisfied the requirements for respiratory flow measurement according to ATS standardization. The experimental results suggest that the developed method promises the fast calibration of PNT.

Intelligent Clinical Decision Support System for Managing COPD Patients

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. Health remote monitoring systems (HRMSs) play a crucial role in managing COPD patients by identifying anomalies in their biometric signs and alerting healthcare professionals. By analyzing the relationships between biometric signs and environmental factors, it is possible to develop artificial intelligence models that are capable of inferring patients' future health deterioration risks. In this research work, we review recent works in this area and develop an intelligent clinical decision support system (CIDSS) that is capable of providing early information concerning patient health evolution and risk analysis in order to support the treatment of COPD patients. The present work's CIDSS is composed of two main modules: the vital signs prediction module and the early warning score calculation module, which generate the patient health information and deterioration risks, respectively. Additionally, the CIDSS generates alerts whenever a biometric sign measurement falls outside the allowed range for a patient or in case a basal value changes significantly. Finally, the system was implemented and assessed in a real case and validated in clinical terms through an evaluation survey answered by healthcare professionals involved in the project. In conclusion, the CIDSS proves to be a useful and valuable tool for medical and healthcare professionals, enabling proactive intervention and facilitating adjustments to the medical treatment of patients.

Machine learning for the development of diagnostic models of decompensated heart failure or exacerbation of chronic obstructive pulmonary disease

Heart failure (HF) and chronic obstructive pulmonary disease (COPD) are two chronic diseases with the greatest adverse impact on the general population, and early detection of their decompensation is an important objective. However, very few diagnostic models have achieved adequate diagnostic performance. The aim of this trial was to develop diagnostic models of decompensated heart failure or COPD exacerbation with machine learning techniques based on physiological parameters. A total of 135 patients hospitalized for decompensated heart failure and/or COPD exacerbation were recruited. Each patient underwent three evaluations: one in the decompensated phase (during hospital admission) and two more consecutively in the compensated phase (at home, 30 days after discharge). In each evaluation, heart rate (HR) and oxygen saturation (Ox) were recorded continuously (with a pulse oximeter) during a period of walking for 6 min, followed by a recovery period of 4 min. To develop the diagnostic models, predictive characteristics related to HR and Ox were initially selected through classification algorithms. Potential predictors included age, sex and baseline disease (heart failure or COPD). Next, diagnostic classification models (compensated vs. decompensated phase) were developed through different machine learning techniques. The diagnostic performance of the developed models was evaluated according to sensitivity (S), specificity (E) and accuracy (A). Data from 22 patients with decompensated heart failure, 25 with COPD exacerbation and 13 with both decompensated pathologies were included in the analyses. Of the 96 characteristics of HR and Ox initially evaluated, 19 were selected. Age, sex and baseline disease did not provide greater discriminative power to the models. The techniques with S and E values above 80% were the logistic regression (S: 80.83%; E: 86.25%; A: 83.61%) and support vector machine (S: 81.67%; E: 85%; A: 82.78%) techniques. The diagnostic models developed achieved good diagnostic performance for decompensated HF or COPD exacerbation. To our knowledge, this study is the first to report diagnostic models of decompensation potentially applicable to both COPD and HF patients. However, these results are preliminary and warrant further investigation to be confirmed.

Use of Remote Cardiorespiratory Monitoring is Associated with a Reduction in Hospitalizations for Subjects with COPD

Background

Chronic obstructive pulmonary disease (COPD) is prevalent and results in high healthcare resource utilization. The largest impact on health status and proportion of healthcare costs in COPD are related to hospitalizations for acute exacerbations. Accordingly, the Centers for Medicare & Medicaid Services have advocated for remote patient monitoring (RPM) to aid in chronic disease management. However, there has been a lack of evidence for the effectiveness of RPM in reducing the need for unplanned hospitalizations for patients with COPD.

Methods

This pre/post study was a retrospective analysis of unplanned hospitalizations in a cohort of COPD subjects started on RPM at a large, outpatient pulmonary practice. The study included all subjects with at least one unplanned, all-cause hospitalization or emergency room visit in the prior year, who had elected to enroll in an RPM service for assistance with clinical management. Additional inclusion criteria included being on RPM for at least 12 months and a patient of the practice for at least two years (12 months pre- and post-initiation of RPM).

Results

The study included 126 subjects. RPM was associated with a significantly lower rate of unplanned hospitalizations per patient per year (1.09 ± 0.07 versus 0.38 ± 0.06, P<0.001).

Conclusion

Unplanned, all-cause hospitalization rates were lower in subjects started on RPM for COPD when compared to their prior year. These results support the potential of RPM to improve the long-term management of COPD.

Trend of Admissions Due to Chronic Lower Respiratory Diseases: An Ecological Study

Objective: This study aimed to examine the trend of hospital admissions related to chronic lower respiratory diseases in England and Wales between 1999 and 2020. Method: This ecological analysis used data that were made accessible to the public and were taken from the Patient Episode Database for Wales (PEDW) and the Hospital Episode Statistics (HES) databases in England for the time span between April 1999 and April 2020. The patients were grouped into four age groups: under 15, 15−59, 60−74, and 75 years and above. Results: In 2020, there were 432,193 chronic lower respiratory disease hospital admissions, which increased from 239,606 in 1999. The hospital admission rate increased by 57.5% (from 459.54 (95% CI 457.71−461.38) in 1999 to 723.70 (95% CI 721.55−725.85) in 2020 per 100,000 people, p < 0.5). The majority of hospital admissions for chronic lower respiratory diseases were found to be directly linked to age (more prevalent in the 75+ age group). Moreover, female hospital admission rates for chronic lower respiratory diseases grew by 85.2% between 1999 and 2020, increasing from 445.45 (95% CI 442.92−447.97) to 824.96 (95% CI 821.73−828.19) per 100,000 people. Conclusion: The rate of hospital admissions due to chronic lower respiratory diseases has sharply increased during the past two decades. COPD was the most common cause for chronic lower respiratory disease admissions. Ageing was also found to be a factor in increased hospital admissions. Future studies are warranted to identify other risk factors of hospital admissions due to chronic lower respiratory diseases and specifically COPD.

Remote patient monitoring in the management of chronic obstructive pulmonary disease

Remote patient monitoring allows monitoring high-risk patients through implementation of an expanding number of technologies in coordination with a healthcare team to augment care, with the potential to provide early detection of exacerbation, prompt access to therapy and clinical services, and ultimately improved patient outcomes and decreased healthcare utilization.In this review, we describe the application of remote patient monitoring in chronic obstructive pulmonary disease including the potential benefits and possible barriers to implementation both for the individual and the healthcare system.

A proof of concept for continuous, non-invasive, free-living vital signs monitoring to predict readmission following an acute exacerbation of COPD: a prospective cohort study

Background

The use of vital signs monitoring in the early recognition of an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) post-hospital discharge is limited. This study investigated whether continuous vital signs monitoring could predict an AECOPD and readmission.

Methods

35 people were recruited at discharge following hospitalisation for an AECOPD. Participants were asked to wear an Equivital LifeMonitor during waking hours for 6 weeks and to complete the Exacerbations of Chronic Pulmonary Disease Tool (EXACT), a 14-item symptom diary, daily. The Equivital LifeMonitor recorded respiratory rate (RR), heart rate (HR), skin temperature (ST) and physical activity (PA) every 15-s. An AECOPD was classified as mild (by EXACT score), moderate (prescribed oral steroids/antibiotics) or severe (hospitalisation).

Results

Over the 6-week period, 31 participants provided vital signs and symptom data and 14 participants experienced an exacerbation, of which, 11 had sufficient data to predict an AECOPD. HR and PA were associated with EXACT score (p < 0.001). Three days prior to an exacerbation, RR increased by mean ± SD 2.0 ± 0.2 breaths/min for seven out of 11 exacerbations and HR increased by 8.1 ± 0.7 bpm for nine of these 11 exacerbations.

Conclusions

Increased heart rate and reduced physical activity were associated with worsening symptoms. Even with high-resolution data, the variation in vital signs data remains a challenge for predicting AECOPDs. Respiratory rate and heart rate should be further explored as potential predictors of an impending AECOPD.

Trial registration: ISRCTN registry; ISRCTN12855961. Registered 07 November 2018—Retrospectively registered, https://www.isrctn.com/ISRCTN12855961

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02018-5.

Usability of Wearable Multiparameter Technology to Continuously Monitor Free-Living Vital Signs in People Living With Chronic Obstructive Pulmonary Disease: Prospective Observational Study

Background

Vital signs monitoring (VSM) is routine for inpatients, but monitoring during free-living conditions is largely untested in chronic obstructive pulmonary disease (COPD).

Objective

This study investigated the usability and acceptability of continuous VSM for people with COPD using wearable multiparameter technology.

Methods

In total, 50 people following hospitalization for an acute exacerbation of COPD (AECOPD) and 50 people with stable COPD symptoms were asked to wear an Equivital LifeMonitor during waking hours for 6 weeks (42 days). The device recorded heart rate (HR), respiratory rate (RR), skin temperature, and physical activity. Adherence was defined by the number of days the vest was worn and daily wear time. Signal quality was examined, with thresholds of ≥85% for HR and ≥80% for RR, based on the device’s proprietary confidence algorithm. Data quality was calculated as the percentage of wear time with acceptable signal quality. Participant feedback was assessed during follow-up phone calls.

Results

In total, 84% of participants provided data, with average daily wear time of 11.8 (SD 2.2) hours for 32 (SD 11) days (average of study duration 76%, SD 26%). There was greater adherence in the stable group than in the post-AECOPD group (≥5 weeks wear: 71.4% vs 45.7%; P=.02). For all 84 participants, the median HR signal quality was 90% (IQR 80%-94%) and the median RR signal quality was 93% (IQR 92%-95%). The median HR data quality was 81% (IQR 58%-91%), and the median RR data quality was 85% (IQR 77%-91%). Stable group BMI was associated with HR signal quality (r_s=0.45, P=.008) and HR data quality (r_s=0.44, P=.008). For the AECOPD group, RR data quality was associated with waist circumference and BMI (r_s=–0.49, P=.009; r_s=–0.44, P=.02). In total, 36 (74%) participants in the Stable group and 21 (60%) participants in the AECOPD group accepted the technology, but 10 participants (12%) expressed concerns with wearing a device around their chest.

Conclusions

This wearable multiparametric technology showed good user acceptance and was able to measure vital signs in a COPD population. Data quality was generally high but was influenced by body composition. Overall, it was feasible to continuously measure vital signs during free-living conditions in people with COPD symptoms but with additional challenges in the post-AECOPD context.

Application of oxygen saturation variability analysis for the detection of exacerbation in individuals with COPD: A proof-of-concept study

BACKGROUND

Individuals with chronic obstructive pulmonary disease (COPD) commonly experience exacerbations, which may require hospital admission. Early detection of exacerbations, and therefore early treatment, could be crucial in preventing admission and improving outcomes. Our previous research has demonstrated that the pattern analysis of peripheral oxygen saturation (Sp O2 ) fluctuations provides novel insights into the engagement of the respiratory control system in response to physiological stress (hypoxia). Therefore, this pilot study tested the hypothesis that the pattern of Sp O2 variations in overnight recordings of individuals with COPD would distinguish between stable and exacerbation phases of the disease.

METHODS

Overnight pulse oximetry data from 11 individuals with COPD, who exhibited exacerbation after a period of stable disease, were examined. Stable phase recordings were conducted overnight and one night prior to exacerbation recordings were also analyzed. Pattern analysis of Sp O2 variations was carried examined using sample entropy (for assessment of irregularity), the multiscale entropy (complexity), and detrended fluctuation analysis (self-similarity).

RESULTS

Sp O2 variations displayed a complex pattern in both stable and exacerbation phases of COPD. During an exacerbation, Sp O2 entropy increased (p = 0.029) and long-term fractal-like exponent (α2) decreased (p = 0.002) while the mean and standard deviation of Sp O2 time series remained unchanged. Through ROC analyses, Sp O2 entropy and α2 were both able to classify the COPD phases into either stable or exacerbation phase. With the best positive predictor value (PPV) for sample entropy (PPV = 70%) and a cut-off value of 0.454. While the best negative predictor value (NPV) was α2 (NPV = 78%) with a cut-off value of 1.00.

CONCLUSION

Alterations in Sp O2 entropy and the fractal-like exponent have the potential to detect exacerbations in COPD. Further research is warranted to examine if Sp O2 variability analysis could be used as a novel objective method of detecting exacerbations.

Predictive performance and impact of algorithms in remote monitoring of chronic conditions: A systematic review and meta-analysis

BACKGROUND

The use of telehealth interventions, such as the remote monitoring of patient clinical data (e.g. blood pressure, blood glucose, heart rate, medication use), has been proposed as a strategy to better manage chronic conditions and to reduce the impact on patients and healthcare systems. The use of algorithms for data acquisition, analysis, transmission, communication and visualisation are now common in remote patient monitoring. However, their use and impact on chronic disease management has not been systematically investigated.

OBJECTIVES

To investigate the use, impact, and performance of remote monitoring algorithms across various types of chronic conditions.

METHODS

A literature search of MEDLINE complete, CINHAL complete, and EMBASE was performed using search terms relating to the concepts of remote monitoring, chronic conditions, and data processing algorithms. Comparable outcomes from studies describing the impact on process measures and clinical and patient-reported outcomes were pooled for a summary effect and meta-analyses. A comparison of studies reporting the predictive performance of algorithms was also conducted using the Youden Index.

RESULTS

A total of 89 articles were included in the review. There was no evidence of a positive impact on healthcare utilisation [OR 1.09 (0.90 to 1.31); P = .35] and mortality [OR 0.83 (0.63 to 1.10); P = .208], but there was a positive effect on generic health status [SDM 0.2912 (0.06 to 0.51); P = .010] and diabetes control [SDM -0.53 (-0.74 to -0.33); P < .001; I² = 15.71] (with two of the three diabetes studies being identified as having a high risk of bias). While the majority of impact studies made use of heuristic threshold-based algorithms (n = 27,87%), most performance studies (n = 36, 62%) analysed non-sequential machine learning methods. There was considerable variance in the quality, sample size and performance amongst these studies. Overall, algorithms involved in diagnosis (n = 22, 47%) had superior performance to those involved in predicting a future event (n = 25, 53%). Detection of arrythmia and ischaemia utilising ECG data showed particularly promising results.

CONCLUSION

The performance of data processing algorithms for the diagnosis of a current condition, particularly those related to the detection of arrythmia and ischaemia, is promising. However, there appears to exist minimal testing in experimental studies, with only two included impact studies citing a performance study as support for the intervention algorithm used. Because of the disconnect between performance and impact studies, there is currently limited evidence of the effect of integrating advanced inference algorithms in remote monitoring interventions. If the field of remote patient monitoring is to progress, future impact studies should address this disconnect by evaluating high performance validated algorithms in robust clinical trials.

A qualitative study of clinician perceptions regarding the potential role for digital health interventions for the management of COPD

Effective self-management of chronic obstructive pulmonary disease (COPD) can lead to increased patient control and reduced health care costs. However, both patients and healthcare professionals encounter significant challenges. Digital health interventions, such as smart oximeters and COPD self-management applications, promise to enhance the management of COPD, yet, there is little evidence to support their use and user-experience issues are still common. Understanding the needs of healthcare professionals is central for increasing adoption and engagement with digital health interventions but little is known about their perceptions of digital health interventions in COPD. This paper explored the perceptions of healthcare professionals regarding the potential role for DHI in the management of COPD. Snowball sampling was used to recruit the participants (n = 32). Each participant underwent a semi-structured interview. Using NVivo 12 software, thematic analysis was completed. Healthcare professionals perceive digital health interventions providing several potential benefits to the management of COPD including the capture of patient status indicators during the interappointment period, providing new patient data to support the consultation process and perceived digital health interventions as a potential means to improve patient engagement. The findings offer new insights regarding potential future use-cases for digital health interventions in COPD, which can help ease user-experience issues as they align with the needs of healthcare professionals.

Assessing the Tidal Volume through Wearables: A Scoping Review

The assessment of respiratory activity based on wearable devices is becoming an area of growing interest due to the wide range of available sensors. Accordingly, this scoping review aims to identify research evidence supporting the use of wearable devices to monitor the tidal volume during both daily activities and clinical settings. A screening of the literature (Pubmed, Scopus, and Web of Science) was carried out in December 2020 to collect studies: i. comparing one or more methodological approaches for the assessment of tidal volume with the outcome of a state-of-the-art measurement device (i.e., spirometry or optoelectronic plethysmography); ii. dealing with technological solutions designed to be exploited in wearable devices. From the initial 1031 documents, only 36 citations met the eligibility criteria. These studies highlighted that the tidal volume can be estimated by using different technologies ranging from IMUs to strain sensors (e.g., resistive, capacitive, inductive, electromagnetic, and optical) or acoustic sensors. Noticeably, the relative volumetric error of these solutions during quasi-static tasks (e.g., resting and sitting) is typically ≥10% but it deteriorates during dynamic motor tasks (e.g., walking). As such, additional efforts are required to improve the performance of these devices and to identify possible applications based on their accuracy and reliability.

Home parasternal electromyography tracks patient-reported and physiological measures of recovery from severe COPD exacerbation

Exacerbations of COPD remain a leading cause of emergency hospitalisations worldwide, and up to 28% of patients are readmitted within 30 days of discharge [1]. Recent analyses of more than 2.3 million COPD hospitalisations highlight the dynamic and time-dependent nature of readmission risk, which peaks within the first 72 h of discharge [2, 3]. Effective readmission prevention strategies remain elusive and recognition of re-exacerbations beyond daily symptom variability is challenging for both patients and clinicians. Promotion of transitional care services and 30-day readmission penalties implemented by policymakers worldwide have had limited impact [4]. Telemonitoring strategies incorporating symptom and vital observation monitoring (peripheral oxygen saturation (S_pO2), heart rate, respiratory frequency) have consistently failed to demonstrate beneficial effects on hospitalisation risk [5]. Objective physiological monitoring has been explored using the forced oscillation technique. However, this also failed to prolong time to first hospitalisation [6].

Physiological phenotyping using daily home-based assessments reveals early improvement in load–capacity–drive imbalance following #AECOPD and feasibility of home parasternal electromyography measurement, which tracks symptoms, health status and spirometryhttps://bit.ly/3o6I0Ty

A Home Telemedicine System for Continuous Respiratory Monitoring

This article presents a continuous home telemonitoring system for chronic respiratory patients using 5G connectivity developed in partnership with Vodafone as a part of the 5G Trial in Milan established by the Italian Ministry of Economic Development. The system features a wearable respiratory and activity monitor, an environmental sensor and a pulse oximeter sending the data through a 5G router to a Multi-Edge Computing server, incorporated in the Vodafone 5G infrastructure, where they are stored and accessible for visualization. In particular, activity, respiratory and environmental data are continuously streamed and collected. The solution has been tested on 18 healthy volunteers during non-supervised recordings lasting at least 48 hours. The combination of recognized activities and associated respiratory parameters provided statistically significant variations in breathing patterns between one activity and the other, thus giving more complete information to the clinicians than previously studied telemedicine systems based on spot-checks. In particular, statistically significant differences are found in tidal volume and minute ventilation between horizontal and vertical postures (p < 0.001) and between vertical postures and dynamic activities (p < 0.001); the respiratory rate shows statistically significant differences between horizontal and vertical postures (p < 0.001). Some environmental parameters have different mean values between day and night, such as carbon dioxide (p < 0.001). Trials on patients are needed to further study this telemedicine solution and make it commercially available in the future. The main further technical development suggested is the use of commercial 5G smartphones as routers, in order to make the system usable outside of home settings.

Protocol for an observational study to identify potential predictors of an acute exacerbation in patients with chronic obstructive pulmonary disease (the PACE Study)

INTRODUCTION

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are the most critical events for patients with COPD that have a negative impact on patients' quality of life, accelerate disease progression, and can result in hospital admissions and death. Although there is no distinct definition or detailed knowledge about AECOPD, it is commonly used as primary outcome in clinical studies. Furthermore, it may be difficult in clinical practice to differentiate the worsening of symptoms due to an AECOPD or to the development of heart failure. Therefore, it is of major clinical importance to investigate the underlying pathophysiology, and if possible, predictors of an AECOPD and thus to identify patients who are at high risk for developing an acute exacerbation.

METHODS AND ANALYSIS

In total, 355 patients with COPD will be included prospectively to this study during a 3-week inpatient pulmonary rehabilitation programme at the Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee (Germany). All patients will be closely monitored from admission to discharge. Lung function, exercise tests, clinical parameters, quality of life, physical activity and symptoms will be recorded, and blood samples and exhaled air will be collected. If a patient develops an AECOPD, there will be additional comprehensive diagnostic assessments to differentiate between cardiac, pulmonary or cardiopulmonary causes of worsening. Follow-up measures will be performed at 6, 12 and 24 months.Exploratory data analyses methods will be used for the primary research question (screening and identification of possible factors to predict an AECOPD). Regression analyses and a generalised linear model with a binomial outcome (AECOPD) will be applied to test if predictors are significant.

ETHICS AND DISSEMINATION

This study has been approved by the Ethical Committee of the Philipps University Marburg, Germany (No. 61/19). The results will be presented in conferences and published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

NCT04140097.

Clinical Evaluation of Respiratory Rate Measurements on COPD (Male) Patients Using Wearable Inkjet-Printed Sensor

Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a progressive disease that causes long-term breathing problems. The reliable monitoring of respiratory rate (RR) is very important for the treatment and management of COPD. Based on inkjet printing technology, we have developed a stretchable and wearable sensor that can accurately measure RR on normal subjects. Currently, there is a lack of comprehensive evaluation of stretchable sensors in the monitoring of RR on COPD patients. We aimed to investigate the measurement accuracy of our sensor on COPD patients. Methodology: Thirty-five patients (Mean ± SD of age: 55.25 ± 13.76 years) in different stages of COPD were recruited. The measurement accuracy of our inkjet-printed (IJPT) sensor was evaluated at different body postures (i.e., standing, sitting at 90°, and lying at 45°) on COPD patients. The RR recorded by the IJPT sensor was compared with that recorded by the reference e-Health sensor using paired T-test and Wilcoxon signed-rank test. Analysis of variation (ANOVA) was performed to investigate if there was any significant effect of individual difference or posture on the measurement error. Statistical significance was defined as p-value less than 0.05. Results: There was no significant difference between the RR measurements collected by the IJPT sensor and the e-Health reference sensor overall and in three postures (p > 0.05 in paired T-tests and Wilcoxon signed-rank tests). The sitting posture had the least measurement error of −0.0542 ± 1.451 bpm. There was no significant effect of posture or individual difference on the measurement error or relative measurement error (p > 0.05 in ANOVA). Conclusion: The IJPT sensor can accurately measure the RR of COPD patients at different body postures, which provides the possibility for reliable monitoring of RR on COPD patients.

Assessing the Usefulness of the Prevexair Smartphone Application in the Follow-Up High-Risk Patients with COPD

Introduction

This manuscript analyzes the exacerbations recorded by the Prevexair application through the daily analysis of symptoms in high-risk patients with COPD and explores its usefulness in assessing clinical stability with respect to that reported in visits.

Patients and Methods

This study is a multi-centre cohort of COPD patients with the exacerbator phenotype who were monitored over 6 months. The Prevexair application was installed on the patients' smartphones. Patients used the app to record symptom changes, use of medication and use of healthcare resources. It is not established a recommended action plan when worsening of symptoms. At their clinical visit during the follow-up period, patients were asked about exacerbations suffered during these 6 months of monitoring. The investigators who conducted the visit were blinded about the Prevexair app records.

Results

The patients experienced a total of 185 exacerbations according to daily records in the app whereas only 64 exacerbations were recalled during medical visits. Perception became more accurate for severe exacerbations (kappa 0.6577), although we found no factors that predicted poor recall. The proportion of 72.5% patients were classified as unstable if the exacerbations captured by Prevexair were used to define stability, versus 47.8% if the exacerbations recall in visit was used. Two-thirds of the exacerbations recorded in the Prevexair application were not reported to doctors during their clinical visits. Almost half were treated with oral corticosteroids and/or antibiotics and more than one-quarter of the exacerbations treated did not seek medical attention.

Conclusion

The findings of this cohort study confirm that patients do not always remember the exacerbations suffered during their medical visit. The prevexair application is useful in monitoring COPD patients at high risk, in order to a better assessment of exacerbations of COPD during medical visits. Further research must be carried out to evaluate this strategy in clinical practice.

Once Daily Versus Overnight and Symptom Versus Physiological Monitoring to Detect Exacerbations of Chronic Obstructive Pulmonary Disease: Pilot Randomized Controlled Trial

Background

Earlier detection of chronic obstructive pulmonary disease (COPD) exacerbations may facilitate more rapid treatment with reduced risk of hospitalization. Changes in pulse oximetry may permit early detection of exacerbations. We hypothesized that overnight pulse oximetry would be superior to once-daily monitoring for the early detection of exacerbations.

Objective

This study aims to evaluate whether measuring changes in heart rate and oxygen saturation overnight is superior to once-daily monitoring of both parameters and to assess symptom changes in facilitating earlier detection of COPD exacerbations.

Methods

A total of 83 patients with COPD were randomized to once-daily or overnight pulse oximetry. Both groups completed the COPD assessment test questionnaire daily. The baseline mean and SD for each pulse oximetry variable were calculated from 14 days of stable monitoring. Changes in exacerbation were expressed as Z scores from this baseline.

Results

The mean age of the patients was 70.6 (SD 8.1) years, 52% (43/83) were female, and the mean FEV1 was 53.0% (SD 18.5%) predicted. Of the 83 patients, 27 experienced an exacerbation. Symptoms were significantly elevated above baseline from 5 days before to 12 days after treatment initiation. Day-to-day variation in pulse oximetry during the stable state was significantly less in the overnight group than in the once-daily group. There were greater relative changes at exacerbation in heart rate than oxygen saturation. An overnight composite score of change in heart rate and oxygen saturation changed significantly from 7 days before initiation of treatment for exacerbation and had a positive predictive value for exacerbation of 91.2%. However, this was not statistically better than examining changes in symptoms alone.

Conclusions

Overnight pulse oximetry permits earlier detection of COPD exacerbations compared with once-daily monitoring. Monitoring physiological variables was not superior to monitoring symptoms, and the latter would be a simpler approach, except where there is a need for objective verification of exacerbations.

Trial Registration

ClinicalTrials.gov NCT03003702; https://clinicaltrials.gov/ct2/show/NCT03003702

Measuring hemoglobin spectra: searching for carbamino-hemoglobin

SIGNIFICANCE

The arterial carbon dioxide (CO2) partial pressure PaCO2 is a clinically relevant variable. However, its measurement requires arterial blood sampling or bulky and expensive transcutaneous PtcCO2 meters. While the spectrophotometric determination of hemoglobin species-such as oxy-hemoglobin (O2Hb) and deoxy-hemoglobin (HHb)-allowed for the development of pulse oximetry, the measurement of CO2 blood content with minimal discomfort has not been addressed yet.

AIM

Characterizing human carbamino-hemoglobin (CO2Hb) absorption spectrum, which is missing from the literature. Providing the theoretical background that will allow for transcutaneous, noninvasive PaCO2 measurements.

APPROACH

A tonometry-based approach was used to obtain gas-equilibrated, lysed, diluted human blood. Equilibration was performed with both CO2, dinitrogen (N2), and ambient air. Spectrophotometric measurements were carried out on the 235- to 1000-nm range. A theoretical background was also derived from that of pulse oximetry.

RESULTS

The absorption spectra of both CO2Hb and HHb were extremely close and comparable with that of state-of-the-art HHb. The above-mentioned theoretical background led to an estimated relative error above 30% on the measured amount of CO2Hb in a subject's blood. Auxiliary measurements revealed that the use of ethylene diamine tetraacetic acid did not interfere with spectrophotometric measurements, whereas sodium metabisulfite did.

CONCLUSIONS

CO2Hb absorption spectrum was measured for the first time. Such spectrum being close to that of HHb, the use of a theoretical background based on pulse oximetry theory for noninvasive PaCO2 measurement seems extremely challenging.

Telemedicine in COPD: An Overview by Topics

COPD is a major cause of morbidity and mortality worldwide and carries a huge and growing economic and social burden. Telemedicine might allow the care of patients with limited access to health services and improve their self-management. During the COVID-19 pandemic, patient's safety represents one of the main reasons why we might use these tools to manage our patients. The authors conducted a literature search in MEDLINE database. The retrieval form of the Medical Subject Headings (Mesh) was ((Telemedicine OR Tele-rehabilitation OR Telemonitoring OR mHealth OR Ehealth OR Telehealth) AND COPD). We only included systematic reviews, reviews, meta-analysis, clinical trials and randomized-control trials, in the English language, with the selected search items in title or abstract, and published from January 1st 2015 to 31st May 2020 (n = 56). There was a positive tendency toward benefits in tele-rehabilitation, health-education and self-management, early detection of COPD exacerbations, psychosocial support and smoking cessation, but the heterogeneity of clinical trials and reviews limits the extent to which this value can be understood. Telemonitoring interventions and cost-effectiveness had contradictory results. The literature on teleconsultation was scarce during this period. The non-inferiority tendency of telemedicine programmes comparing to conventional COPD management seems an opportunity to deliver quality healthcare to COPD patients, with a guarantee of patient's safety, especially during the COVID-19 outbreak.

Remote Patient Monitoring for the Detection of COPD Exacerbations

Background

COPD exacerbations occur more frequently with disease progression and are associated with worse prognosis and higher healthcare expenditure.

Purpose

To utilize a networked system, optimized with statistical process control (SPC), for remote patient monitoring (RPM) and to identify potential predictors of COPD exacerbations.

Methods

Seventeen subjects, mean (SD) age of 69.7 (7.2) years, with moderate to severe COPD received RPM. Over 2618 patient-days (7.17 patient-years) of monitoring, we obtained daily symptom scores, treatment adherence, self-reported activity levels, daily spirometry (SVC, FEV₁, FVC, PEF), inspiratory capacity (IC), and oxygenation (SpO₂). These data were used to identify predictors of exacerbations defined using Anthonisen and other criteria.

Results

After implementation of SPC, concordance analysis showed substantial agreement between FVC (decrease below the 7-day rolling average minus 1.645 SD) and self-reported healthcare utilization events (κ=0.747, P<0.001) as well as between increased use of inhaled short-acting bronchodilators and exacerbations defined by two Anthonisen criteria (κ=0.611, P<0.001) or modified Anthonisen criteria (κ=0.622, P<0.001). There was a moderate agreement between FEV₁ (decrease >1.645 SD below the 7-day rolling average) and self-reported healthcare utilization events (κ=0.475, P<0.001) and between SpO₂ less than 90% and exacerbations defined by two Anthonisen criteria (κ=0.474, P<0.001) or modified Anthonisen criteria (κ=0.564, P<0.001).

Conclusion

Exacerbations were best predicted by FVC and FEV₁ below the one-sided 95% confidence interval derived from SPC but also by increased use of inhaled short-acting bronchodilators and fall in oxygen saturation. An RPM program that captures these parameters may be used to guide appropriate interventions aimed at reducing healthcare utilization in COPD patients.

Comparison between the Airgo™ Device and a Metabolic Cart during Rest and Exercise

The aim of this study is to compare the accuracy of Airgo™, a non-invasive wearable device that records breath, with respect to a gold standard. In 21 healthy subjects (10 males, 11 females), four parameters were recorded for four min at rest and in different positions simultaneously by Airgo™ and SensorMedics 2900 metabolic cart. Then, a cardio-pulmonary exercise test was performed using the Erg 800S cycle ergometer in order to test Airgo™'s accuracy during physical effort. The results reveal that the relative error median percentage of respiratory rate was of 0% for all positions at rest and for different exercise intensities, with interquartile ranges between 3.5 (standing position) and 22.4 (low-intensity exercise) breaths per minute. During exercise, normalized amplitude and ventilation relative error medians highlighted the presence of an error proportional to the volume to be estimated. For increasing intensity levels of exercise, Airgo™'s estimate tended to underestimate the values of the gold standard instrument. In conclusion, the Airgo™ device provides good accuracy and precision in the estimate of respiratory rate (especially at rest), an acceptable estimate of tidal volume and minute ventilation at rest and an underestimation for increasing volumes.

Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison

Background

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death by disease worldwide and has a 30-day readmission rate of 22.6%. In 2015, COPD was added to the Medicare Hospital Readmission Reductions Program.

Objective

The objective of this paper was to survey the current medical technologies for remote patient monitoring (RPM) tools that forecast COPD exacerbations in order to reduce COPD readmissions.

Methods

We searched literature and digital health news to find commercially available RPM devices focused on predicting COPD exacerbations. These technologies were reviewed and compared according to four criteria: forecasting ability, cost, ease of use, and appearance. A rating system was developed to facilitate the evaluation process.

Results

As of June 2019, a list of handheld and hands-free devices was compiled. We compared features and found substantial variations. Devices that ranked higher on all criteria tended to have a high or unlisted price. Commonly mass-marketed devices like the pulse oximeter and spirometer surprisingly fulfilled the least criteria.

Conclusions

The COPD RPM technologies with most technological promise and compatibility with daily living appear to have high or unlisted prices. Consumers and providers need better access to product information to make informed decisions.

How stable is lung function in patients with stable chronic obstructive pulmonary disease when monitored using a telehealth system? A longitudinal and home-based study

Background

Many telehealth systems have been designed to identify signs of exacerbations in patients with chronic obstructive pulmonary disease (COPD), but few previous studies have reported the nature of recorded lung function data and what variations to expect in this group of individuals. The aim of the study was to evaluate the nature of individual diurnal, day-to-day and long-term variation in important prognostic markers of COPD exacerbations by employing a telehealth system developed in-house.

Methods

Eight women and five men with COPD performed measurements (spirometry, pulse oximetry and the COPD assessment test (CAT)) three times per week for 4–6 months using the telehealth system. Short-term and long-term individual variations were assessed using the relative density and weekly means respectively. Quality of the spirometry measurements (forced expiratory volume in one second (FEV₁) and inspiratory capacity (IC)) was assessed employing the criteria of American Thoracic Society (ATS)/European Respiratory Society (ERS) guidelines.

Results

Close to 1100 measurements of both FEV₁ and IC were performed during a total of 240 patient weeks. The two standard deviation ranges for intra-individual short-term variation were approximately ±210 mL and ± 350 mL for FEV₁ and IC respectively. In long-term, spirometry values increased and decreased without notable changes in symptoms as reported by CAT, although it was unusual with a decrease of more than 50 mL per measurement of FEV₁ between three consecutive measurement days. No exacerbation occurred. There was a moderate to strong positive correlation between FEV₁ and IC, but weak or absent correlation with the other prognostic markers in the majority of the participants.

Conclusions

Although FEV₁ and IC varied within a noticeable range, no corresponding change in symptoms occurred. Therefore, this study reveals important and, to our knowledge, previously not reported information about short and long-term variability in prognostic markers in stable patients with COPD. The present data are of significance when defining criteria for detecting exacerbations using telehealth strategies.

A multicenter randomized clinical trial to evaluate the efficacy of telemonitoring in patients with advanced heart and lung chronic failure. Study protocol for the ATLAN_TIC project

Background

Using technologies of information and communication (TICs) is emerging in medical assistance. TICs application for medical assistance is promising. Its applicability in advanced heart and/or respiratory failure is still controversial because studies have shown methodological weakness which could put in danger their conclusions. Our objective is to evaluate efficacy of the application of home monitoring biological parameters in a multi-level model of coordinated clinical care for patients with chronic diseases with advanced heart (HF) and/or respiratory failure (RF) in comparison with conventional clinical care.

Method

/Design: Multicentric, phase III, randomized, parallel groups, controlled clinical trial. Patients with advanced HF and/or RF were eligible to participate. Patients received medical assistance by a multi-level model of coordinated clinical care with or without home monitoring. Follow up was performed until 180 days after inclusion. Primary efficacy outcome was defined as the percentage of patients with hospitalization/emergency room visits. Secondary efficacy outcomes were hospital admissions, admissions to hospital emergencies and Primary Care Emergencies, number of days of hospital stay, total cost per patient in euros, mortality, change in functional status, quality of life, assistance and technology devices. Intention to treat, as well as per protocol, and incremental cost-effectiveness analysis will be performed. The number of recruits patients per arm is set at 255, a total of 510 patients.

Discussion

This trial could provide some knowledge about the real impact of home monitoring for patients with advanced HF and/or RF within a multi-level model of integrated care.

A Pervasive Healthcare System for COPD Patients

Chronic obstructive pulmonary disease (COPD) is one of the most severe public health problems worldwide. Pervasive computing technology creates a new opportunity to redesign the traditional pattern of medical system. While many pervasive healthcare systems are currently found in the literature, there is little published research on the effectiveness of these paradigms in the medical context. This paper designs and validates a rule-based ontology framework for COPD patients. Unlike conventional systems, this work presents a new vision of telemedicine and remote care solutions that will promote individual self-management and autonomy for COPD patients through an advanced decision-making technique. Rules accuracy estimates were 89% for monitoring vital signs, and environmental factors, and 87% for nutrition facts, and physical activities.

Global use, utility, and methods of tele-health in COPD: a health care provider survey

Introduction

Advances in technology offer various solutions that might help optimize the care provided to patients living with chronic non-communicable diseases such as chronic obstructive pulmonary disease (COPD). However, the efficacy of tele-health in COPD is still controversial. Despite this, there appears to be widespread adoption of this technology.

Aim

To explore the international use of tele-heath for COPD, to assess the perceptions of clinicians employing tele-health in COPD, and to summarize the techniques that have been used by health care providers to personalize alarm limits for patients with COPD enrolled on tele-health programs.

Methods

A cross-sectional survey consisting of 15 questions was distributed and advertised to health care professionals worldwide. Questions were designed to cover five different aspects of tele-health in COPD: purpose of use, equipment type, clinician perceptions, variables monitored, and personalization of alarm limits.

Results

A total of 138 participants completed the survey from 29 different countries. As high as 59% of the participants had ever used tele-health for COPD, and 33% still provided tele-health services to patients with COPD. Tele-health was most commonly used for baseline monitoring, with 90% believing it to be effective. The three most commonly monitored variables were oxygen saturation, heart rate, and the use of rescue medication.

Conclusion

Twenty-nine different countries use tele-health for managing COPD and therefore there is widespread international use of tele-health in COPD. The majority of providers thought tele-health was effective despite evidence to the contrary.

Internet of Things Applied in Healthcare Based on Open Hardware with Low-Energy Consumption

Objectives

The Internet of Things (IoT) and its applications are growing simultaneously. These applications need new intelligent devices along heterogeneous networking. Which makes them costly to implement indeed. Platforms and open devices designed for open-source hardware are possible solutions. This research was conducted under an IoT design, implementation, and assessment model for the remote monitoring of pulse oximetry via oxygen partial saturation (SpO₂) and heart rate (HR) with low-energy consumption.

Methods

This study focused on the development of SpO₂ and HR measurements that will allow the monitoring and estimation in real time of the user's state and health related to the established parameters. Measurements were acquired and recorded using a remote web server that recorded the acquired variables for further processing. The statistical analysis data allows comparison of the registered data measured with theoretical models.

Results

The IoT model was developed use Bluetooth low-energy devices, which comply with low-cost and open-hardware solutions operated via ‘HTTP requests’ for data transmission and reception from a cloud server to an edge device. Network performance assessment was conducted to guarantee the availability and integrity of the acquired values and signals. The system measured SpO₂ and HR variables. The most significant result was to achieve energy consumption 20% lower than that of devices in the market.

Conclusions

In summary, the acquired data validation based on the IoT model had a transmission error of 0.001% which proves its applicability in healthcare.

Use, utility and methods of telehealth for patients with COPD in England and Wales: a healthcare provider survey

Introduction

Although the effectiveness of domiciliary monitoring (telehealth) to improve outcomes in chronic obstructive pulmonary disease (COPD) is controversial, it is being used in the National Health Service (NHS).

Aim

To explore the use of teleheath for COPD across England and Wales, to assess the perceptions of clinicians employing telehealth in COPD and to summarise the techniques that have been used by healthcare providers to personalise alarm limits for patients with COPD enrolled in telehealth programmes.

Methods

A cross-sectional survey consisting of 14 questions was sent to 230 COPD community services in England and Wales. Questions were designed to cover five aspects of telehealth in COPD: purpose of use, equipment type, clinician perceptions, variables monitored and personalisation of alarm limits.

Results

65 participants completed the survey from 52 different NHS Trusts. 46% of Trusts had used telehealth for COPD, and currently, 31% still provided telehealth services to patients with COPD. Telehealth is most commonly used for baseline monitoring and to allow early detection of exacerbations, with 54% believing it to be effective. The three most commonly monitored variables were oxygen saturation, heart rate and breathlessness. A variety of methods were used to set alarm limits with the majority of respondents believing that at least 40% of alarms were false.

Conclusion

Around one-third of responded community COPD services are using telehealth, believing it to be effective without robust evidence, with a variety of variables monitored, a variety of hardware and varying techniques to set alarm limits with high false alarm frequencies.

Effort Oxygen Saturation and Effort Heart Rate to Detect Exacerbations of Chronic Obstructive Pulmonary Disease or Congestive Heart Failure

Background: current algorithms for the detection of heart failure (HF) and chronic obstructive pulmonary disease (COPD) exacerbations have poor performance. Methods: this study was designed as a prospective longitudinal trial. Physiological parameters were evaluated at rest and effort (walking) in patients who were in the exacerbation or stable phases of HF or COPD. Parameters with relevant discriminatory power (sensitivity (Sn) or specificity (Sp) ≥ 80%, and Youden index ≥ 0.2) were integrated into diagnostic algorithms. Results: the study included 127 patients (COPD: 56, HF: 54, both: 17). The best algorithm for COPD included: oxygen saturation (SaO₂) decrease ≥ 2% in minutes 1 to 3 of effort, end-of-effort heart rate (HR) increase ≥ 10 beats/min and walking distance decrease ≥ 35 m (presence of one criterion showed Sn: 0.90 (95%, CI(confidence interval): 0.75–0.97), Sp: 0.89 (95%, CI: 0.72–0.96), and area under the curve (AUC): 0.92 (95%, CI: 0.85–0.995)); and for HF: SaO₂ decrease ≥ 2% in the mean-of-effort, HR increase ≥ 10 beats/min in the mean-of-effort, and walking distance decrease ≥ 40 m (presence of one criterion showed Sn: 0.85 (95%, CI: 0.69–0.93), Sp: 0.75 (95%, CI: 0.57–0.87) and AUC 0.84 (95%, CI: 0.74–0.94)). Conclusions: effort situations improve the validity of physiological parameters for detection of HF and COPD exacerbation episodes.

Effectiveness of tele-monitoring by patient severity and intervention type in chronic obstructive pulmonary disease patients: A systematic review and meta-analysis

BACKGROUND

Chronic obstructive pulmonary disease is a major burden on healthcare systems worldwide. Tele-monitoring has recently been used for management of chronic obstructive pulmonary disease patients.

OBJECTIVES

We analyzed the effect of tele-monitoring on chronic obstructive pulmonary disease patients and performed subgroup analysis by patient severity and intervention type.

DESIGN

Systematic review.

DATA SOURCE

Electronic databases including Ovid-Medline, Ovid-Embase, and the Cochrane Library.

REVIEW METHODS

We conducted a meta-analysis of randomized controlled trials published up to April 2017. Three databases were searched, two investigators independently extracted data and assessed study quality using risk of bias.

RESULTS

Out of 1,185 studies, 27articles were identified to be relevant for this study. The included studies were divided by intervention: 15studies used tele-monitoring only, 4studies used integrated tele-monitoring (pure control), and 8studies used integrated tele-monitoring (not pure control). We also divided the studies by patient severity: 16studies included severely ill patients, 8studies included moderately ill patients, and 3studies did not discuss the severity of the patients' illness. Meta-analysis showed that tele-monitoring reduced the emergency room visits (risk ratio 0.63, 95% confidence interval 0.55-0.72) and hospitalizations (risk ratio 0.88, 95% confidence interval 0.80-0.97). The subgroup analysis of patient severity showed that tele-monitoring more effectively reduced emergency room visits in patients with severe vs. moderate disease (risk ratio 0.48, 95% confidence interval 0.31-0.74; risk ratio 1.28, 95% confidence interval 0.61-2.69, retrospectively) and hospitalizations (risk ratio 0.92, 95% confidence interval 0.82-1.02; risk ratio 1.24, 95% confidence interval 0.57-2.70, retrospectively). The mental health quality of life score (mean difference 3.06, 95% confidence interval 2.15-3.98) showed more improved quality of life than the physical health quality of life score (mean difference -0.11, 95% confidence interval -0.83-0.61).

CONCLUSIONS

Tele-monitoring reduced rates of emergency room visits and hospitalizations and improved the mental health quality of life score. Integrated tele-monitoring including the delivery of coping skills or education by online methods including pulmonary rehabilitation is recommended to produce significant improvement. This application of integrated tele-monitoring (the delivery of education, exercise etc. in addition to tele-monitoring) is more useful for patients with (very) severe chronic obstructive pulmonary disease than those with moderate disease. Tele-monitoring might be a useful application of information and communication technologies, if the intervention includes the appropriate intervention components for eligible patients. Further studies such as large size randomized controlled trials with sub-group by patient severity and intervention type is needed to confirm these finding.

Effectiveness of telemonitoring versus usual care for chronic obstructive pulmonary disease: A systematic review and meta-analysis

AIMS

The purpose of this research was to investigate the effectiveness of telemonitoring for chronic obstructive pulmonary disease.

METHODS

We searched MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials and CINAHL up to September 2018. We selected randomised controlled trials comparing telemonitoring and control groups for chronic obstructive pulmonary disease management. Two reviewers independently examined articles based on eligibility, extracted data and evaluated the risk of bias. The Cochrane tool was applied for assessing the risk of bias. The 95% confidence interval was calculated.

RESULTS

A total of 28 randomised controlled trials were included. Meta-analysis revealed that there were no variables showing a statistically significant difference between telemonitoring and control groups. Chronic obstructive pulmonary disease exacerbation rate (six studies) was not different between two groups (risk ratio 0.67, 95% confidence interval 0.31-1.42). Subgroup analysis showed that telemonitoring reduced exacerbation rates when the intervention continued for longer than six months or pulmonary function was monitored. No differences between groups were noticed for mortality (seven studies, risk ratio 0.89, 95% confidence interval 0.60-1.34). Similarly, no differences between groups were observed in the patient-reported outcomes (St George's Respiratory Questionnaire, Chronic Respiratory Disease Questionnaire-Dyspnea score) and for health service utilization (length of hospital stay, number of hospital admissions, number of emergency room visits).

CONCLUSIONS

Telemonitoring for chronic obstructive pulmonary disease was unlikely to result in statistically significant improvements in health outcomes. However, our novel finding was that at least six months of intervention duration and monitoring of pulmonary function play roles in activating the effects of telemonitoring.

Enhancing our understanding of the time course of acute exacerbations of COPD managed on an outpatient basis

Purpose

Acute exacerbations of COPD (AECOPD) are associated with pulmonary/systemic changes; however, quantification of those changes during AECOPD managed on an outpatient basis and factors influencing recovery are lacking. This study aimed to characterize patients’ changes during AECOPD and identify factors influencing their recovery.

Methods

Body mass index, the modified British Medical Research Council questionnaire, number of exacerbations in the previous year, and the Charlson comorbidity index (independent variables) were collected within 24–48 hours of hospital presentation (T0). Peripheral oxygen saturation (SpO₂), forced expiratory volume in one second, percentage predicted (FEV₁% predicted), maximum inspiratory pressure, quadriceps muscle strength, 5 times sit-to-stand, and COPD assessment test (CAT) (dependent variables) were collected at T0 and approximately at days 8 (T1), 15 (T2), and 45 (T3) after T0.

Results

A total of 44 outpatients with AECOPD (31♂; 68.2±9.1 years; 51.1±20.3 FEV₁% predicted) were enrolled. All variables improved overtime (P<0.05); however, at day 8, only SpO₂ and CAT (P≤0.001) showed significant improvements. Changes in FEV₁% predicted and SpO₂ were not influenced by any independent measure, while changes in other outcome measures were influenced by at least one of the independent measures. Independently of the time of data collection, being underweight or overweight and having increased dyspnea, previous exacerbations, and severe comorbidities negatively affected patients’ outcomes.

Conclusion

FEV₁% predicted and SpO₂ were not influenced by any independent measure and, thus, seem to be robust measures to follow-up outpatients with AECOPD. No single indicator was able to predict patients’ recovery for all measures; thus, a comprehensive assessment at the onset of the AECOPD is required to personalize interventions.

Validation of ACCESS: an automated tool to support self-management of COPD exacerbations

Background

To support patients with COPD in their self-management of symptom worsening, we developed Adaptive Computerized COPD Exacerbation Self-management Support (ACCESS), an innovative software application that provides automated treatment advice without the interference of a health care professional. Exacerbation detection is based on 12 symptom-related yes-or-no questions and the measurement of peripheral capillary oxygen saturation (SpO₂), forced expiratory volume in one second (FEV₁), and body temperature. Automated treatment advice is based on a decision model built by clinical expert panel opinion and Bayesian network modeling. The current paper describes the validity of ACCESS.

Methods

We performed secondary analyses on data from a 3-month prospective observational study in which patients with COPD registered respiratory symptoms daily on diary cards and measured SpO₂, FEV₁, and body temperature. We examined the validity of the most important treatment advice of ACCESS, ie, to contact the health care professional, against symptom- and event-based exacerbations.

Results

Fifty-four patients completed 2,928 diary cards. One or more of the different pieces of ACCESS advice were provided in 71.7% of all cases. We identified 115 symptom-based exacerbations. Cross-tabulation showed a sensitivity of 97.4% (95% CI 92.0-99.3), specificity of 65.6% (95% CI 63.5-67.6), and positive and negative predictive value of 13.4% (95% CI 11.2-15.9) and 99.8% (95% CI 99.3-99.9), respectively, for ACCESS' advice to contact a health care professional in case of an exacerbation.

Conclusion

In many cases (71.7%), ACCESS gave at least one self-management advice to lower symptom burden, showing that ACCES provides self-management support for both day-to-day symptom variations and exacerbations. High sensitivity shows that if there is an exacerbation, ACCESS will advise patients to contact a health care professional. The high negative predictive value leads us to conclude that when ACCES does not provide the advice to contact a health care professional, the risk of an exacerbation is very low. Thus, ACCESS can safely be used in patients with COPD to support self-management in case of an exacerbation.

Oxygen saturation measurements in telemonitoring of patients with COPD: a systematic review

INTRODUCTION

Telemonitoring applications are expected to become a key component in future healthcare. Despite the frequent use of SpO₂ measurements in telemonitoring of patients with chronic obstructive pulmonary disease (COPD), no profound overview is available about these measurements. Areas covered: A systematic search identified 71 articles that performed SpO₂ measurements in COPD telemonitoring. The results indicate that long-term follow-up of COPD patients using daily SpO₂ spot checks is practically feasible. Very few studies specified protocols for performing these measurements. In many studies, deviating SpO₂ values were used to raise alerts that led to immediate action from healthcare professionals. However, little information was available about the exact implementation and performance of these alerts. Therefore, no firm conclusions can be drawn about the real value of SpO₂ measurements. Future research could optimize performance of alerts using individualized, time-dependent thresholds or predictive algorithms to account for individual differences and SpO₂ baseline changes. Additionally, the value of performing continuous measurements should be examined. Expert commentary: Standardization of the measurements, data science techniques and advancing technology can still boost performance of telemonitoring applications. All these opportunities should be thoroughly explored to assess the real value of SpO₂ in COPD telemonitoring.