New telemetric system for daily pulmonary function surveillance of lung transplant recipients

Wagner, Florian; Weber, Andreas; Park, Jai-Wun; Schiemanck, S.; Tugtekin, Sems Malte; Gulielmos, Vassilios; Schüler, Stephan

doi:10.1016/s0003-4975(99)01140-6

Cited by 37 publications

(22 citation statements)

References 7 publications

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“…In the current study, the best overall performance was consistently achieved with FEV 1 and symptom at 80-90% sensitivity. These sensitivities exceeded the reported sensitivity of approximately 60% in previous reported studies 25,26 in which screening was based on clinician review of daily spirometry. As might be expected, as detection sensitivity increases, so does the incidence of false alarms.…”

Section: Discussioncontrasting

confidence: 66%

“…It is well known that spirometry alone does not allow recognition of the etiology of pulmonary dysfunction 26,27 and that symptoms alone could not differentiate pulmonary rejection and infection. 11 Therefore, non-pulmonary events that affect pulmonary functions may not be distinguishable from pulmonary events on the basis of spirometry and symptom surveillance alone.…”

Section: Limitationsmentioning

confidence: 99%

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Automatic Event Detection in Lung Transplant Recipients Based on Home Monitoring of Spirometry and Symptoms

Wang

Finkelstein²,

Hertz

2013

Telemedicine and e-Health

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Objective: The goal of this study was to develop, implement, and test an automated decision system to provide early detection of clinically important bronchopulmonary events in a population of lung transplant recipients following a home monitoring protocol. Subjects and Methods: Spirometry and other clinical data were collected daily at home by lung transplant recipients and transmitted weekly to the study data center. Decision rules were developed using wavelet analysis of declines in spirometry and increases in respiratory symptoms from a learning set of patient home data and validated with an independent patient set. Results: Using forced expiratory volume in 1 s or symptoms, the detection captured the majority of events (sensitivity, 80-90%) at an acceptable level of false alarms. On average, detections occurred 6.6-10.8 days earlier than the known event records. Conclusions: This approach is useful for early discovery of pulmonary events and has the potential to decrease the time required for humans to review large amount of home monitoring data to discover relatively infrequent but clinically important events.

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Section: Discussioncontrasting

confidence: 66%

Section: Limitationsmentioning

confidence: 99%

Automatic Event Detection in Lung Transplant Recipients Based on Home Monitoring of Spirometry and Symptoms

Wang

Finkelstein²,

Hertz

2013

Telemedicine and e-Health

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“…Frequent monitoring of pulmonary function and respiratory symptoms allows for early detection and treatment of problems. [8][9][10][11][12][13] Home monitoring (HM) has been used in a range of clinical contexts, including chronic diseases like hypertension 14,15 and diabetes. 16,17 HM of pulmonary function and symptoms is feasible to follow lung recipients to improve transplant care and clinical status.…”

Section: Introductionmentioning

confidence: 99%

A Randomized Controlled Trial Comparing Health and Quality of Life of Lung Transplant Recipients Following Nurse and Computer-Based Triage Utilizing Home Spirometry Monitoring

Finkelstein

Lindgren²,

Robiner

et al. 2013

Telemedicine and e-Health

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Background: Lung transplantation is now a standard intervention for patients with advanced lung disease. Home monitoring of pulmonary function and symptoms has been used to follow the progress of lung transplant recipients in an effort to improve care and clinical status. The study objective was to determine the relative performance of a computer-based Bayesian algorithm compared with a manual nurse decision process for triaging clinical intervention in lung transplant recipients participating in a home monitoring program. Materials and Methods: This randomized controlled trial had 65 lung transplant recipients assigned to either the Bayesian or nurse triage study arm. Subjects monitored and transmitted spirometry and respiratory symptoms daily to the data center using an electronic spirometer/diary device. Subjects completed the Short Form-36 (SF-36) survey at baseline and after 1 year. End points were change from baseline after 1 year in forced expiratory volume at 1 s (FEV 1 ) and quality of life (SF-36 scales) within and between each study arm. Results: There were no statistically significant differences between groups in FEV 1 or SF-36 scales at baseline or after 1 year.: Results were comparable between nurse and Bayesian system for detecting changes in spirometry and symptoms, providing support for using computer-based triage support systems as remote monitoring triage programs become more widely available. Conclusions: The feasibility of monitoring critical patient data with a computer-based decision system is especially important given the likely economic constraints on the growth in the nurse workforce capable of providing these early detection triage services.

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“…Several studies have suggested that frequent monitoring of pulmonary function can provide such an early detection capability. [4][5][6][7] Such frequent monitoring can be accomplished by patients performing regular pulmonary function monitoring at home and either performing self-assessment of test results or downloading the test data for evaluation at the transplant center. Otulana and colleagues.…”

mentioning

confidence: 99%

“…Bjortuft et al 5 reported that daily home monitoring of spirometry helped in the early detection of rejection in lung transplant recipients. Wagner et al 6 reported that reliable early diagnosis and treatment of infection or rejection in transplanted lungs was made possible by telemetric monitoring. Morlion et al 7 concluded that Internetbased home monitoring of pulmonary function after lung transplantation was feasible and reproducible, but they questioned its usefulness in detecting acute allograft dysfunction.…”

mentioning

confidence: 99%

Decision support for the triage of lung transplant recipients on the basis of home-monitoring spirometry and symptom reporting

et al. 2005

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New telemetric system for daily pulmonary function surveillance of lung transplant recipients

Cited by 37 publications

References 7 publications

Automatic Event Detection in Lung Transplant Recipients Based on Home Monitoring of Spirometry and Symptoms

Automatic Event Detection in Lung Transplant Recipients Based on Home Monitoring of Spirometry and Symptoms

A Randomized Controlled Trial Comparing Health and Quality of Life of Lung Transplant Recipients Following Nurse and Computer-Based Triage Utilizing Home Spirometry Monitoring

Decision support for the triage of lung transplant recipients on the basis of home-monitoring spirometry and symptom reporting

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