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

Jiang, Shaojun; Lv, Meina; Zeng, Zhiwei; Fang, Zuxiang; Chen, Mingrong; Qian, Jiafen; Wang, Tingting; Zhang, Jinhua

doi:10.1007/s11239-021-02630-0

Cited by 8 publications

(4 citation statements)

References 39 publications

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“… 23 Furthermore, the use of computer-assisted warfarin clinical algorithms dosing programs by the clinical pharmacist can improve warfarin dosing. 25 , 26 Combined genetic and clinical factors have proved to predict an algorithm for adjusting individual dosing of warfarin. 27 Some recent African studies have found other diverse variants relevant to predicting pharmacogenetics-based warfarin dosing additionally to those known in CYP2C9 and VKORC1 which indicate the necessity to conduct more pharmacogenomics studies on African population for other potential predictors for warfarin variability in response.…”

Section: Discussionmentioning

confidence: 99%

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

Elnour¹,

Ahmed²,

Khalid³

et al. 2022

PHARMPRACT

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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..

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Section: Discussionmentioning

confidence: 99%

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

Elnour¹,

Ahmed²,

Khalid³

et al. 2022

PHARMPRACT

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“…Telemedicine has shown positive impacts (easier access to information, alerting of caregivers, etc.) in the follow-up of patients treated with anti-vitamin K [ 17 ], or the monitoring of type I diabetes [ 18 ]. An application monitoring the recurrence of bronchial cancer has shown a better follow-up and an increase in life expectancy of patients [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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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.

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“…It has been recognized as a pandemic by the World Health Organization ( World Health Organization, 2021 ). On 23 January 2020, China initiated the Level I response to public health incidents nationwide, which is the highest one ( Jiang et al, 2022 ), and slowed the spread of COVID-19 effectively. However, social distancing and stay-at-home orders, which were adopted to avoid the spread of COVID-19, posed unique challenges for patients on medications, requiring continued monitoring by clinic staff, such as warfarin treatment ( Kish and Lekic, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

“…“Internet + Anticoagulation clinic” (IAC) is a new approach for anticoagulation management, which is undoubtedly attractive to patients and clinical pharmacists, especially during the COVID-19 pandemic. To the best of our knowledge, only one previous study has investigated the effectiveness and safety of anticoagulation management provided by clinical pharmacists through the IAC during the COVID-19 pandemic ( Jiang et al, 2022 ), with small sample size and short-term follow-ups, providing preliminary conclusions that IAC improved anticoagulation quality. Therefore, more studies are encouraged to provide crucial evidence for application of IAC during the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

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

Dai

Zhang

et al. 2022

Front. Pharmacol.

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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.

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

Cited by 8 publications

References 39 publications

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

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

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

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

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