Remote Outpatient Management During COVID-19 Lockdown: Patient-Derived Quality Assessment

Comparing rehabilitation outcomes for patients admitted to the intensive care unit with COVID-19 requiring mechanical ventilation during the first two waves of the pandemic: A service evaluation

OBJECTIVES

To compare rehabilitation outcomes of patients admitted to the intensive care unit with COVID-19 and mechanically ventilated during wave 1 and 2, receiving two different models of physiotherapy delivery.

METHODS

Adults admitted to the intensive care unit between October-March 2021 (wave 2) with a confirmed diagnosis of COVID-19 and mechanically ventilated for >24 hours were included. During wave 2, rehabilitation was provided by physiotherapists over five days, with only emergency respiratory physiotherapy delivered at weekends. Rehabilitation status was measured daily using the Manchester Mobility Score to identify time taken to first mobilise and highest level of mobility achieved at ICU discharge. Outcomes were compared to data previously published from the same ICU during 'wave 1' (March-April 2020) when a seven-day rehabilitation physiotherapy service was provided.

RESULTS

A total of n = 291 patients were included in analysis; 110 from wave 1, and 181 from wave 2. Patient characteristics and medical management were similar between waves. Mean ± SD time to first mobilise was slower in wave 2 (15 ± 11 days vs 14 ± 7 days), with overall mobility scores lower at both ICU (MMS 5 (Step transferring) vs MMS 4 (standing practice) (4), p < 0.05) and hospital (MMS 7 (Mobile > 30 m MMS) vs MMS 6 (Mobile < 30 m MMS), p < 0.0001) discharge. Significantly more patients in wave 2 required ongoing rehabilitation either at home or as an inpatient compared to wave 1 (81 % vs 49 %, p = 0.003).

CONCLUSION

The change in physiotherapy staff provision from a seven-day rehabilitation service during wave 1 to a five day rehabilitation service with emergency respiratory physio only at weekends in wave 2 was associated with delayed time to first mobilise, lower levels of mobility at both intensive care unit and hospital discharge and higher requirement for ongoing rehabilitation at the point of hospital discharge.

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.

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

This study aimed to explore the effectiveness, and safety of internet-based warfarin management during the pandemic. In this single-center retrospective cohort study, we compared the safety and efficacy of online warfarin management using a smartphone app (the Alfalfa app) versus conventional outpatient clinic management from January 1, 2020 to March 31, 2020. Patients in the online management group used the Alfalfa app to communicate coagulation test results and other relevant information to a doctor or clinical pharmacist, who then responded with the dose adjustment plan and the date of the next blood test. The outcomes examined were the time in therapeutic range (TTR), incidence of clinical events (i.e., bleeding events, thrombotic events, warfarin-related emergency department visits, and warfarin-related hospital admissions), and the distribution of international normalized ratio (INR) values. Data from 117 patients were analyzed in this study. TTR was significantly higher in the online group than in the offline group (61.0% vs. 39.6%, P < 0.01). Incidence of major bleeding events, thrombotic events, and warfarin-related hospital admissions were comparable between the online and offline groups. However, minor bleeds (5.3% vs. 28.3%, P < 0.01) and warfarin-related emergency department visits (1.8% vs. 23.3%, P = 0.02) were significantly fewer in the online group than in the offline group. The proportion of INR values in the therapeutic range (53.8% vs. 40.1%, P < 0.01) was significantly higher in the online group. Warfarin management using the Alfalfa app appears to be a safe and effective method for warfarin management when patients cannot physically visit hospitals for follow-up.