Efficacy and safety of app-based remote warfarin management during COVID-19-related lockdown: a retrospective cohort study

Application of eHealth Tools in Anticoagulation Management After Cardiac Valve Replacement: Scoping Review Coupled With Bibliometric Analysis

BACKGROUND

Anticoagulation management can effectively prevent complications in patients undergoing cardiac valve replacement (CVR). The emergence of eHealth tools provides new prospects for the management of long-term anticoagulants. However, there is no comprehensive summary of the application of eHealth tools in anticoagulation management after CVR.

OBJECTIVE

Our objective is to clarify the current state, trends, benefits, and challenges of using eHealth tools in the anticoagulation management of patients after CVR and provide future directions and recommendations for development in this field.

METHODS

This scoping review follows the 5-step framework developed by Arksey and O'Malley. We searched 5 databases such as PubMed, MEDLINE, Web of Science, CINAHL, and Embase using keywords such as "eHealth," "anticoagulation," and "valve replacement." We included papers on the practical application of eHealth tools and excluded papers describing the underlying mechanisms for developing eHealth tools. The search time ranged from the database inception to March 1, 2023. The study findings were reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Additionally, VOSviewer (version 1.6.18) was used to construct visualization maps of countries, institutions, authors, and keywords to investigate the internal relations of included literature and to explore research hotspots and frontiers.

RESULTS

This study included 25 studies that fulfilled the criteria. There were 27,050 participants in total, with the sample size of the included studies ranging from 49 to 13,219. The eHealth tools mainly include computer-based support systems, electronic health records, telemedicine platforms, and mobile apps. Compared to traditional anticoagulation management, eHealth tools can improve time in therapeutic range and life satisfaction. However, there is no significant impact observed in terms of economic benefits and anticoagulation-related complications. Bibliometric analysis suggests the potential for increased collaboration and opportunities among countries and academic institutions. Italy had the widest cooperative relationships. Machine learning and artificial intelligence are the popular research directions in anticoagulation management.

CONCLUSIONS

eHealth tools exhibit promise for clinical applications in anticoagulation management after CVR, with the potential to enhance postoperative rehabilitation. Further high-quality research is needed to explore the economic benefits of eHealth tools in long-term anticoagulant therapy and the potential to reduce the occurrence of adverse events.

Impact of web application support versus standard management on adherence with adjuvant hormone therapy in patients treated for breast cancer: the WEBAPPAC study

BACKGROUND

Non-metastatic breast cancer treatment is mainly based on surgery, with or without chemotherapy, radiotherapy and/or hormone therapy. To reduce the risk of hormone receptor positive (HR+) disease recurrence, hormone therapy is prescribed for at least 5 years. It may induce adverse drug reactions (ADRs) as joint pain, sexual dysfunction, weight increase, fatigue, mood disorders and vasomotor symptoms. Around 30-40% of patients withhold hormone therapy within 5 years after initiation. Based on encouraging results of mobile health in patient follow-up, we developed a web-application addressed for breast cancer patients initiating adjuvant hormonal therapy and aimed to assess its impact on hormone therapy adherence, ADRs management, and health-related quality of life.

METHODS

The WEBAPPAC trial is a randomized, open-label, prospective, single-center phase 3 study aiming to assess the interest of a web-application support as compared to standard management among breast cancer patients initiating hormone therapy. The main endpoint is the proportion of patients with hormone therapy adherence failure within 18 months after treatment start, in each arm. Eligible patients will be 1:1 randomized between the WEBAPPAC web-application support (experimental arm,) or standard support (control arm), with stratification on type of hormone therapy (Aromatase inhibitor or Tamoxifen). We plan to enroll 438 patients overall. Failure to hormone therapy will be assessed using the Morisky 8-item self-questionnaire (MMSA8), patient adherence logbook, and medical consultations. Secondary outcomes include hormone therapy adherence at 6 months, pain (Visual Analogue Scale and Brief Pain Inventory), quality of life (EORTC QLQ-C30 and BR23 self-questionnaires), anxiety and depression (Hospital and Depression Scale), and return to work and/or daily activities. The user experience with the WEBAPPAC web-application will be assessed using the System Usability Scale (SUS) questionnaire.

DISCUSSION

Hormone therapy discontinuation or adherence failure in breast cancer patients may be indirectly related to an increased risk of recurrence. A better control of medication adherence, through the detection of side effects and some proposed actions trying to reduce them, appears therefore essential to limit the risk of disease recurrence. The WEBAPPAC web-application thus aims better monitoring and allowing higher level of responsiveness in case of ADRs, thus improving treatment adherence.

TRIAL REGISTRATION

NCT04554927, registered September 18, 2020.

PROTOCOL VERSION

Version 2.1 dated from December 21, 2021.

Evaluation of a pharmacist-led drive-up anticoagulation clinic during the coronavirus 2019 pandemic

Background

The University of Kentucky HealthCare Anticoagulation Clinic at the Gill Heart and Vascular Institute in Lexington, Kentucky, designed and implemented a drive-up clinic for warfarin management with the goal to minimize person-to-person exposure during the coronavirus disease 2019 (COVID-19) pandemic.

Objective

The purpose of this study was to evaluate the effect on warfarin management in a pharmacist-led anticoagulation service when transitioned from an in-person clinic to a drive-up clinic during the COVID-19 pandemic.

Methods

This is a retrospective observational cohort study of 68 patients seen in the University of Kentucky HealthCare Anticoagulation Clinic on warfarin therapy for any indication. Patients were included if they had scheduled visits at least 3 times in the period 6 months before, during, and after the initiation of the drive-up clinic. The primary outcome is the difference in time in therapeutic range (TTR) before and during the drive-up clinic.

Results

The difference between the mean TTR in period 1 (69.1% ± 23.2%) and period 2 (69.6% ± 19.2%) was not statistically significant (P = 0.882). The mean TTR in period 3 (70.5% ± 20.8%) did not differ in statistical significance from either period 1 (P = 0.688) or period 2 (P = 0.746). Safety outcomes including reported bleeding events and emergency department visits or hospital admissions for bleeding or thrombotic events were consistently low across each period.

Conclusion

The results of this study illustrate that a drive-up clinic for warfarin management may be a reasonable alternative approach to providing care for outpatient anticoagulant management and may support nontraditional clinic models for long-term management of anticoagulation and other chronic disease states.

Warfarin anticoagulation management during the COVID-19 pandemic: The role of internet clinic and machine learning

Background: Patients who received warfarin require constant monitoring by hospital staff. However, social distancing and stay-at-home orders, which were universally adopted strategies to avoid the spread of COVID-19, led to unprecedented challenges. This study aimed to optimize warfarin treatment during the COVID-19 pandemic by determining the role of the Internet clinic and developing a machine learning (ML) model to predict anticoagulation quality.

Methods: This retrospective study enrolled patients who received warfarin treatment in the hospital anticoagulation clinic (HAC) and “Internet + Anticoagulation clinic” (IAC) of the Nanjing Drum Tower Hospital between January 2020 and September 2021. The primary outcome was the anticoagulation quality of patients, which was evaluated by both the time in therapeutic range (TTR) and international normalized ratio (INR) variability. Anticoagulation quality and incidence of adverse events were compared between HAC and IAC. Furthermore, five ML algorithms were used to develop the anticoagulation quality prediction model, and the SHAP method was introduced to rank the feature importance.

Results: Totally, 241 patients were included, comprising 145 patients in the HAC group and 96 patients in the IAC group. In the HAC group and IAC group, 73.1 and 69.8% (p = 0.576) of patients achieved good anticoagulation quality, with the average TTR being 79.9 ± 20.0% and 80.6 ± 21.1%, respectively. There was no significant difference in the incidence of adverse events between the two groups. Evaluating the five ML models using the test set, the accuracy of the XGBoost model was 0.767, and the area under the receiver operating characteristic curve was 0.808, which showed the best performance. The results of the SHAP method revealed that age, education, hypertension, aspirin, and amiodarone were the top five important features associated with poor anticoagulation quality.

Conclusion: The IAC contributed to a novel management method for patients who received warfarin during the COVID-19 pandemic, as effective as HAC and with a low risk of virus transmission. The XGBoost model could accurately select patients at a high risk of poor anticoagulation quality, who could benefit from active intervention.

Validation and comparison between two warfarin dosing clinical algorithms and warfarin fixed dosing in specialized heart center: cross-sectional study

Background

Warfarin is well known as a narrow therapeutic index that has prodigious variability in response which challenges dosing adjustment for the maintenance of therapeutic international normalized ratio. However, an appreciated population not on new oral anticoagulants may still need to be stabilized with warfarin dosing.

Objective

The current study's main objective was to validate and compare two models of warfarin clinical algorithm models namely the Gage and the International Warfarin Pharmacogenetics Consortium (IWPC) with warfarin 5 mg fixed standard dosing strategy in a sample of Sudanese subjects.

Method

We have conducted a cross-sectional study recruited from the out-patient clinic at a tertiary specialized heart center. We included subjects with unchanged warfarin dose (stabilized), and with therapeutic international normalized ratio. The predicted doses of warfarin in the two models were calculated by three different methods (accuracy, clinical practicality, and the clinical safety of the clinical algorithms).

Main outcome measure

The primary outcomes were the measurements of the clinical (accuracy, practicality, and safety) in each of the two clinical algorithms models compared to warfarin 5 mg fixed standard dose strategy.

Results

We have enrolled 71 Sudanese subjects with mean age (51.7 ± 14 years), of which (49, 69.0%) were females. There was no significant difference between the warfarin 5 mg fixed standard dose strategy and the predicted doses of the two clinical algorithm models (MAE 1.44, 1.45, and 1.49 mg/day [P =0.4]) respectively. In the clinical practicality, all of the three models had a high percent of subjects (95.0%, 51.9%, and 66.7%) in the ideal dose range in middle dose group (3-7 mg/ day) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithm models respectively. However, a small percent of subjects was exhibited in the warfarin low dose group ≤ 3 mg/day (0.0%, 15.0%, and 10.0%) and warfarin high dose group ≥ 7 mg/day (0.0%, 33.3%, and 33.3%) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithms respectively. In terms of clinical safety, the percent of subjects with severely over-prediction were 28.2%, 22.5%, and 22.5% for warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively. While the percent of severely under-prediction was 12.7%, 7.0%, and 5.6% for the warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively.

Conclusion

The Gage and IWPC clinical algorithm models were accurate, more clinically practical, and clinically safe than warfarin 5 mg standard dosing in the study population. The cardiologist can use either models (Gage and IWPC) to stratify subjects for accurate, practical, and clinically safe warfarin dosing..