Remote Patient Monitoring for the Detection of COPD Exacerbations

References

• American Lung Association. Trends in COPD (Chronic Bronchitis and Emphysema): Morbidity and Mortality. Epidemiology and Statistics Unit Research and Health Education Division; 2013 Available from http://www.lung.org/finding-cures/our-research/trend-reports/copd-trend-report.pdf. Accessed 16, 2014.
   Google Scholar
• Global Initiative for Chronic Obstructive Lung Disease. Global strategy for diagnosis, management, and prevention of chronic obstructive pulmonary disease; 2020 Available from: https://goldcopd.org/wp-content/uploads/2019/11/GOLD-2020-REPORT-ver1.0wms.pdf. Accessed 812, 2020.
   Google Scholar
• World Health Organization. World health statistics 2008; 2008 Available from: http://www.who.int/whosis/whostat/EN_WHS08_Full.pdf. Accessed 16, 2014..
   Google Scholar
• LareauS, MosesonE, SlatoreCG. Exacerbation of COPD. Am J Respir Crit Care Med. 2018;198:21–22. doi:10.1164/rccm.19811P21
   Web of Science ®Google Scholar
• CoteCG, DordellyLJ, CelliBR. Impact of COPD exacerbations on patient-centered outcomes. Chest. 2007;131(3):696–704. doi:10.1378/chest.06-161017356082
   PubMed Web of Science ®Google Scholar
• HalpinDM, DecramerM, CelliB, KestenS, LiuD, TashkinDP. Exacerbation frequency and course of COPD. Int J Chron Obstruct Pulmon Dis. 2012;7:653–661. doi:10.2147/COPD.S3418623055714
   PubMed Web of Science ®Google Scholar
• AnzuetoA, LeimerI, KestenS. Impact of frequency of COPD exacerbations on pulmonary function, health status and clinical outcomes. Int J Chron Obstruct Pulmon Dis. 2009;4:245–251. doi:10.2147/copd.s486219657398
   PubMedGoogle Scholar
• WedzichaJA, DonaldsonGC. Exacerbations of chronic obstructive pulmonary disease. Respir Care. 2003;48(12):1204–1215.14651761
   PubMedGoogle Scholar
• WilkinsonTM, DonaldsonGC, HurstJR, SeemungalTA, WedzichaJA. Early therapy improves outcomes of exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2004;169(12):1298–1303. doi:10.1164/rccm.200310-1443OC14990395
   PubMed Web of Science ®Google Scholar
• RahimiK, WoodwardM, KorshidiR, et al. Home monitoring with IT-supported specialist management versus home monitoring alone in patients with heart failure: design and baseline results of the SUPPORT-HF 2 randomized trial. Am Heart J. 2018;208:55–64.30553130
   PubMed Web of Science ®Google Scholar
• BuiAL, FonarowGC. Home monitoring for heart failure management. J Am Coll Cardiol. 2012;59(2):97–104. doi:10.1016/j.jacc.2011.09.04422222071
   PubMed Web of Science ®Google Scholar
• ClarkRA, InglisSC, McAlisterFA, ClelandJG, StewartS. Telemonitoring or structured telephone support programmes for patients with chronic heart failure: systematic review and meta-analysis. BMJ. 2007;334(7600):942. doi:10.1136/bmj.39156.536968.5517426062
   PubMed Web of Science ®Google Scholar
• TseG, ChanC, GongM, et al. Telemonitoring and hemodynamic monitoring to reduce hospitalization rates in heart failure: a systematic review and meta-analysis of randomized controlled trials and real-world studies. J Geriatr Cardiol. 2018;15(4):298.29915620
   PubMedGoogle Scholar
• PandorA, GomersallT, StevensJW, et al. Remote monitoring after recent hospital discharge in patients with heart failure: a systematic review and network meta-analysis. Heart. 2013;99(23):1717–1726. doi:10.1136/heartjnl-2013-30381123680885
   PubMed Web of Science ®Google Scholar
• MadsenF, UlrikCS, DirksenA, et al. Patient-administered sequential spirometry in healthy volunteers and patients with alpha 1-antitrypsin deficiency. Respir Med. 1996;90(3):131–138. doi:10.1016/S0954-6111(96)90154-78736204
   PubMed Web of Science ®Google Scholar
• LindgrenBR, FinkelsteinSM, PrasadB, et al. Determination of reliability and validity in home monitoring data of pulmonary function tests following lung transplantation. Res Nurs Health. 1997;20(6):539–550. doi:10.1002/(SICI)1098-240X(199712)20:6<539::AID-NUR8>3.0.CO;2-N9397133
   PubMed Web of Science ®Google Scholar
• SeemungalTA, DonaldsonGC, BhowmikA, JeffriesDJ, WedzichaJA. Time course and recovery of exacerbations in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2000;161(5):1608–1613. doi:10.1164/ajrccm.161.5.990802210806163
   PubMed Web of Science ®Google Scholar
• SundZM, PowellT, GreenwoodR, JaradNA. Remote daily real-time monitoring in patients with COPD–a feasibility study using a novel device. Respir Med. 2009;103(9):1320–1328. doi:10.1016/j.rmed.2009.03.01719375294
   PubMed Web of Science ®Google Scholar
• ShahSA, VelardoC, FarmerA, TarassenkoL. Exacerbations in chronic obstructive pulmonary disease: identification and prediction using a digital health system. J Med Internet Res. 2017;19(3):e69. doi:10.2196/jmir.720728270380
   PubMed Web of Science ®Google Scholar
• LanclusM, ClukersJ, Van HolsbekeC, et al. Machine learning algorithms utilizing functional respiratory imaging may predict COPD exacerbations. Acad Radiol. 2019;26(9):1191–1199. doi:10.1016/j.acra.2018.10.02230477949
   PubMed Web of Science ®Google Scholar
• CavaillesA, MelloniB, MotolaS, et al. Identification of patient profiles with high risk of hospital re-admissions for Acute COPD Exacerbations (AECOPD) in France using a machine learning model. Int J Chron Obstruct Pulmon Dis. 2020;15:949–962. doi:10.2147/COPD.S23678732431495
   PubMed Web of Science ®Google Scholar
• LiX, XieY, ZhaoH, ZhangH, YuX, LiJ. Telemonitoring interventions in COPD patients: overview of systematic reviews. Biomed Res Int. 2020;2020:5040521. doi:10.1155/2020/392028432016115
   PubMed Web of Science ®Google Scholar
• CruzJ, BrooksD, MarquesA. Home telemonitoring effectiveness in COPD: a systematic review. Int J Clin Pract. 2014;68(3):369–378. doi:10.1111/ijcp.1234524472009
   PubMed Web of Science ®Google Scholar
• McCabeC, McCannM, BradyAM. Computer and mobile technology interventions for self-management in chronic obstructive pulmonary disease. Cochrane Database Syst Rev. 2017;5:CD011425.28535331
   PubMed Web of Science ®Google Scholar
• CooperCB, SirichanaW, NeufeldEV, TaylorM, WangX, DolezalBA. Statistical process control improves the feasibility of remote physiological monitoring in patients with chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2019;14:2485–2496. doi:10.2147/COPD.S20762632009781
   PubMed Web of Science ®Google Scholar
• ByrtT, BishopJ, CarlinJB. Bias, prevalence and kappa. J Clin Epidemiol. 1993;46(5):423–429. doi:10.1016/0895-4356(93)90018-V8501467
   PubMed Web of Science ®Google Scholar
• VogelmeierCF, CrinerGJ, MartinezFJ, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report. GOLD executive summary. Am J Respir Crit Care Med. 2017;195(5):557–582. doi:10.1164/rccm.201701-0218PP28128970
   PubMed Web of Science ®Google Scholar
• AnthonisenNR, ManfredaJ, WarrenCP, HershfieldES, HardingGK, NelsonNA. Antibiotic therapy in exacerbations of chronic obstructive pulmonary disease. Ann Intern Med. 1987;106(2):196–204. doi:10.7326/0003-4819-106-2-1963492164
   PubMed Web of Science ®Google Scholar
• YañezAM, GuerreroD, de AlejoRP, et al. Monitoring breathing rate at home allows early identification of COPD exacerbations. Chest. 2012;142(6):1524–1529. doi:10.1378/chest.11-272822797131
   PubMed Web of Science ®Google Scholar
• Gálvez-BarrónC, Villar-ÁlvarezF, RibasJ, et al. Effort oxygen saturation and effort heart rate to detect exacerbations of chronic obstructive pulmonary disease or congestive heart failure. J Clin Med. 2019;8(1):42. doi:10.3390/jcm8010042
   PubMed Web of Science ®Google Scholar
• RubioN, ParkerRA, DrostEM, et al. Home monitoring of breathing rate in people with chronic obstructive pulmonary disease: observational study of feasibility, acceptability, and change after exacerbation. Int J Chron Obstruct Pulmon Dis. 2017;12:1221–1231. doi:10.2147/COPD.S12070628458534
   PubMed Web of Science ®Google Scholar
• DecramerM, CelliB, TashkinDP, et al. Clinical trial design considerations in assessing long‐term functional impacts of tiotropium in COPD: the UPLIFT trial. COPD. 2004;1(2):303–312. doi:10.1081/COPD-20002693417136995
   PubMedGoogle Scholar
• WedzichaJA, DecramerM, FickerJH, et al. Analysis of chronic obstructive pulmonary disease exacerbations with the dual bronchodilator QVA149 compared with glycopyrronium and tiotropium (SPARK): a randomised, double-blind, parallel-group study. Lancet Respir Med. 2013;1(3):199–209. doi:10.1016/S2213-2600(13)70052-324429126
   PubMed Web of Science ®Google Scholar
• BurgeS, WedzichaJA. COPD exacerbations: definitions and classifications. Eur Respir J Suppl. 2003;41:46s–53s. doi:10.1183/09031936.03.0007800212795331
   PubMedGoogle Scholar
• O’DonnellDE, ParkerCM. COPD exacerbations 3: pathophysiology. Thorax. 2006;61(4):354–361. doi:10.1136/thx.2005.04183016565268
   PubMed Web of Science ®Google Scholar
• SoJY, LastraAC, ZhaoH, MarchettiN, CrinerGJ. Daily peak expiratory flow rate and disease instability in chronic obstructive pulmonary disease. Chronic Obstr Pulm Dis. 2015;3(1):398–405. doi:10.15326/jcopdf.3.1.2015.014228848862
   PubMedGoogle Scholar
• WhiteP. Spirometry and peak expiratory flow in the primary care management of COPD. Prim Care Respir J. 2004;13(1):5–8. doi:10.1016/j.pcrj.2003.11.00916701628
   PubMedGoogle Scholar
• Al RajehAM, HurstJR. Monitoring of physiological parameters to predict exacerbations of chronic obstructive pulmonary disease (COPD): a systematic review. J Clin Med. 2016;5(12):108. doi:10.3390/jcm5120108
   PubMed Web of Science ®Google Scholar