Quality of life and adherence to therapy in patients with chronic heart failure who were remotely monitored by chatbot compared to the standard follow-up group for 3 months

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BACKGROUND: Chronic heart failure (CHF) is one of the leading causes of death. Telemedicine and remote monitoring (RM) are a way to increase life expectancy and quality of life in patients with CHF. Methods based on messengers familiar to patients promote adherence and do not require additional training.

AIM: To compare quality of life and adherence to therapy in patients with CHF who were on RM using a chatbot compared to the standard follow-up (SFU) group for 3 months.

METHODS: Patients with CHF on optimal drug therapy discharged from the hospital were included in the study. Comparison groups were formed according to the method of observation, particularly, RM and SFU. A chatbot was set up for patients in the RM group. Monitoring was done using a seven-question survey sent daily. The signs of decompensation (red flags [RF]) were increased edema, dyspnea, body weight ≥2 kg per week, and changes in individual parameters of heart rate and blood pressure. If a RF was detected, telephone contact was made, and the therapy was corrected if necessary. Quality of life was assessed according to the Minnesota Quality of Life Questionnaire for patients with CHF (highest, 0 points; lowest, 105 points), and adherence was assessed using the Adherence Scale of the National Society for Evidence-based Pharmacotherapy.

RESULTS: A total of 60 patients were included in the study; 37 patients completed a 3-month follow-up. The RM group (n=17, 13 men, 76.5%; median age 61 [51; 62]) and comparison group (n=20, 14 men, 70%; mean age 64.9±8.9) were comparable according to the functional class (New York Heart Association), but differed in ejection fraction (42.8±13% versus 53.2±10.4% [p <0.05]). Adherence to the chat-bot was 67.2%. Adherence to therapy was not significantly different between the RM and SFU groups accounting for (17 [100%]) and (18 [90%], respectively, (p=0.62). In the RM group, RF was detected in 7 (41%) patients. Only one patient required correction of therapy. Patients in the RM group required no referral to a medical facility, whereas 2 patients in the SFU group required medical care. Quality of life was statistically significantly higher in the RM group, reaching 28.7±13.9 points compared to 37.7±17.9 points in the SFU group (p=0.04).

CONCLUSIONS: After 3 months, patients in the RM group were committed to the chatbot, with adherence to therapy comparable to the SFU group. Quality of life was statistically significantly higher in the RM group. Patients in the RM group did not go to medical facilities, in contrast to the SFU group. The limitations of the study were the small sample size and short follow-up period. The results require further research to obtain additional data.

全文:

BACKGROUND: Chronic heart failure (CHF) is one of the leading causes of death. Telemedicine and remote monitoring (RM) are a way to increase life expectancy and quality of life in patients with CHF. Methods based on messengers familiar to patients promote adherence and do not require additional training.

AIM: To compare quality of life and adherence to therapy in patients with CHF who were on RM using a chatbot compared to the standard follow-up (SFU) group for 3 months.

METHODS: Patients with CHF on optimal drug therapy discharged from the hospital were included in the study. Comparison groups were formed according to the method of observation, particularly, RM and SFU. A chatbot was set up for patients in the RM group. Monitoring was done using a seven-question survey sent daily. The signs of decompensation (red flags [RF]) were increased edema, dyspnea, body weight ≥2 kg per week, and changes in individual parameters of heart rate and blood pressure. If a RF was detected, telephone contact was made, and the therapy was corrected if necessary. Quality of life was assessed according to the Minnesota Quality of Life Questionnaire for patients with CHF (highest, 0 points; lowest, 105 points), and adherence was assessed using the Adherence Scale of the National Society for Evidence-based Pharmacotherapy.

RESULTS: A total of 60 patients were included in the study; 37 patients completed a 3-month follow-up. The RM group (n=17, 13 men, 76.5%; median age 61 [51; 62]) and comparison group (n=20, 14 men, 70%; mean age 64.9±8.9) were comparable according to the functional class (New York Heart Association), but differed in ejection fraction (42.8±13% versus 53.2±10.4% [p <0.05]). Adherence to the chat-bot was 67.2%. Adherence to therapy was not significantly different between the RM and SFU groups accounting for (17 [100%]) and (18 [90%], respectively, (p=0.62). In the RM group, RF was detected in 7 (41%) patients. Only one patient required correction of therapy. Patients in the RM group required no referral to a medical facility, whereas 2 patients in the SFU group required medical care. Quality of life was statistically significantly higher in the RM group, reaching 28.7±13.9 points compared to 37.7±17.9 points in the SFU group (p=0.04).

CONCLUSIONS: After 3 months, patients in the RM group were committed to the chatbot, with adherence to therapy comparable to the SFU group. Quality of life was statistically significantly higher in the RM group. Patients in the RM group did not go to medical facilities, in contrast to the SFU group. The limitations of the study were the small sample size and short follow-up period. The results require further research to obtain additional data.

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作者简介

Aleksei Emelianov

I.M. Sechenov First Moscow State Medical University

Email: emelyanow.alexei@yandex.ru
ORCID iD: 0000-0002-4748-8029
俄罗斯联邦, Moscow

Elena Zheleznykh

I.M. Sechenov First Moscow State Medical University

Email: elenavlvp@gmail.com
ORCID iD: 0000-0002-2596-192X
俄罗斯联邦, Moscow

Maria Kozhevnikova

I.M. Sechenov First Moscow State Medical University

编辑信件的主要联系方式.
Email: kozhevnikova-m@inbox.ru
ORCID iD: 0000-0003-4778-7755
俄罗斯联邦, Moscow

Anton Ageev

I.M. Sechenov First Moscow State Medical University

Email: antonageev1945@gmail.com
ORCID iD: 0000-0002-2161-2140
俄罗斯联邦, Moscow

Vita Zektser

I.M. Sechenov First Moscow State Medical University

Email: zektservita@mail.ru
ORCID iD: 0000-0002-8547-8673
俄罗斯联邦, Moscow

Yuri Belenkov

I.M. Sechenov First Moscow State Medical University

Email: ynbelenkov@gmail.com
ORCID iD: 0000-0002-3014-6129
俄罗斯联邦, Moscow

参考

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  2. Clinical practice guidelines for Chronic heart failure. Russian Journal of Cardiology. 2020;25(11):4083. (In Russ). doi: 10.15829/1560-4071-2020-4083
  3. McAlister F, Stewart S, Ferrua S, et al. Multi-disciplinary strategies for the management of heart failure patients at high risk of admission: A systematic review of randomized trials. J Am Coll Cardiol. 2004;44(4):810–819.
  4. Zhu Y., Gu X., Xu, C. Effectiveness of telemedicine systems for adults with heart failure: a meta-analysis of randomized controlled trials. Heart Fail Rev. 2020;25:231–243.
  5. Koehler F., Koehler K., Deckwart O., et al. Efficacy of telemedical interventional management in patients with heart failure (TIM-HF2): a randomised, controlled, parallel-group, unmasked trial. Lancet. 2018;392:1047–1057. doi: 10.1016/S0140-6736(18)31880-4
  6. Shara N, Bjarnadottir MV, Falah N, et al. Voice activated remote monitoring technology for heart failure patients: Study design, feasibility and observations from a pilot randomized control trial. PLoS ONE. 2022;17(5):e0267794. doi: 10.1371/journal
  7. Boitsov S.A., Ageev F.T., Blankova Z.N., Svirida O.N., Begrambekova Yu.L. Metodicheskie rekomendatsii dlya meditsinskikh sester kabineta bol’nykh khronicheskoi serdechnoi nedostatochnost’yu. Moscow: FGBU “Natsional’nyi meditsinskii issledovatel’skii tsentr kardiologii” of Ministry of Health of Russia: “Obshchestvo spetsialistov po serdechnoi nedostatochnosti” LLC; 2020. 36 p. (In Russ).
  8. Libis RA, Kots YaI, Ageev FT, Mareev VYu. Kachestvo zhizni kak kriterii uspeshnoi terapii bol’nykh s khronicheskoi serdechnoi nedostatochnost’yu. Russkii meditsinskii zhurnal. 1999; 2:8. (In Russ).
  9. Lukina Y.V., Kutishenko N.P., Martsevich S.Y., Drapkina O.M. The Questionnaire Survey Method in Medicine on the Example of Treatment Adherence Scales. Rational Pharmacotherapy in Cardiology. 2020;17(4):576–583. doi: 10.20996/1819-6446-2021-08-02

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