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1.
Front Public Health ; 9: 730150, 2021.
Article in English | MEDLINE | ID: covidwho-1775857

ABSTRACT

Survival prediction is highly valued in end-of-life care clinical practice, and patient performance status evaluation stands as a predominant component in survival prognostication. While current performance status evaluation tools are limited to their subjective nature, the advent of wearable technology enables continual recordings of patients' activity and has the potential to measure performance status objectively. We hypothesize that wristband actigraphy monitoring devices can predict in-hospital death of end-stage cancer patients during the time of their hospital admissions. The objective of this study was to train and validate a long short-term memory (LSTM) deep-learning prediction model based on activity data of wearable actigraphy devices. The study recruited 60 end-stage cancer patients in a hospice care unit, with 28 deaths and 32 discharged in stable condition at the end of their hospital stay. The standard Karnofsky Performance Status score had an overall prognostic accuracy of 0.83. The LSTM prediction model based on patients' continual actigraphy monitoring had an overall prognostic accuracy of 0.83. Furthermore, the model performance improved with longer input data length up to 48 h. In conclusion, our research suggests the potential feasibility of wristband actigraphy to predict end-of-life admission outcomes in palliative care for end-stage cancer patients. Clinical Trial Registration: The study protocol was registered on ClinicalTrials.gov (ID: NCT04883879).


Subject(s)
Deep Learning , Neoplasms , Wearable Electronic Devices , Actigraphy/methods , Hospital Mortality , Humans , Neoplasms/therapy
2.
Vaccines (Basel) ; 10(2)2022 Feb 17.
Article in English | MEDLINE | ID: covidwho-1708024

ABSTRACT

BACKGROUND: The ChAdOx1 nCoV-19 vaccine has been widely administered against SARS-CoV-2 infection; however, data regarding its immunogenicity, reactogenicity, and potential differences in responses among Asian populations remain scarce. METHODS: 270 participants without prior COVID-19 were enrolled to receive ChAdOx1 nCoV-19 vaccination with a prime-boost interval of 8-9 weeks. Their specific SARS-CoV-2 antibodies, neutralizing antibody titers (NT50), platelet counts, and D-dimer levels were analyzed before and after vaccination. RESULTS: The seroconversion rates of anti-RBD and anti-spike IgG at day 28 after a boost vaccination (BD28) were 100% and 95.19%, respectively. Anti-RBD and anti-spike IgG levels were highly correlated (r = 0.7891), which were 172.9 ± 170.4 and 179.3 ± 76.88 BAU/mL at BD28, respectively. The geometric mean concentrations (GMCs) of NT50 for all participants increased to 132.9 IU/mL (95% CI 120.0-147.1) at BD28 and were highly correlated with anti-RBD and anti-spike IgG levels (r = 0.8248 and 0.7474, respectively). Body weight index was statistically significantly associated with anti-RBD IgG levels (p = 0.035), while female recipients had higher anti-spike IgG levels (p = 0.038). The GMCs of NT50 declined with age (p = 0.0163) and were significantly different across age groups (159.7 IU/mL for 20-29 years, 99.4 IU/mL for ≥50 years, p = 0.0026). Injection-site pain, fever, and fatigue were the major reactogenicity, which were more pronounced after prime vaccination and in younger participants (<50 years). Platelet counts decreased and D-dimer levels increased after vaccination but were not clinically relevant. No serious adverse events or deaths were observed. CONCLUSION: The vaccine is well-tolerated and elicited robust humoral immunity against SARS-CoV-2 after standard prime-boost vaccination in Taiwanese recipients.

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