METHODS: Based on the best available clinical knowledge and best practices, an eight member multidisciplinary group of clinical and quality experts undertook the development of a clinical algorithm-based toolkit to guide training and practice for the management of patients with COVID-19. The team followed Horabin and Lewis' seven-step approach in developing the algorithms and a five-step method in writing them. Moreover, we applied Rosenfeld et al's five points to each algorithm.
RESULTS: A set of seven clinical algorithms and one illustrative layout diagram were developed. The algorithms were augmented with documentation forms, data-collection online forms and spreadsheets and an indicators' reference sheet to guide implementation and performance measurement. The final version underwent several revisions and amendments prior to approval.
CONCLUSIONS: A large volume of published literature on the topic of COVID-19 pandemic was translated into a user-friendly, algorithm-based toolkit for the management of patients with COVID-19. This toolkit can be used for training and decision-making to improve the quality of care provided to patients with COVID-19.
AREAS COVERED: There is no specific contraindication or caution related to COVID-19 on the use of antihypertensives unless patients develop severe hypotension from septic shock where all antihypertensives should be discontinued or severe hyperkalemia in which continuation of renin-angiotensin system inhibitors is not desired. The continuation of antiplatelet or statin is not desired when severe thrombocytopenia or severe transminitis develop, respectively. Patients with atrial fibrillation receiving oral anticoagulants, particularly those who are critically ill, should be considered for substitution to parenteral anticoagulants.
EXPERT OPINION: An individualized approach to medication management among hospitalized COVID-19 patients with concurrent CVDs would seem prudent with attention paid to changes in clinical conditions and medications intended for COVID-19. The decision to modify prescribed long-term CV medications should be entailed by close follow-up to check if a revision on the decision is needed, with resumption of any long-term CV medication before discharge if it is discontinued during hospitalization for COVID-19, to ensure continuity of care.
OBJECTIVE: This paper presents a rescue framework for the transfusion of the best CP to the most critical patients with COVID-19 on the basis of biological requirements by using machine learning and novel MCDM methods.
METHOD: The proposed framework is illustrated on the basis of two distinct and consecutive phases (i.e. testing and development). In testing, ABO compatibility is assessed after classifying donors into the four blood types, namely, A, B, AB and O, to indicate the suitability and safety of plasma for administration in order to refine the CP tested list repository. The development phase includes patient and donor sides. In the patient side, prioritisation is performed using a contracted patient decision matrix constructed between 'serological/protein biomarkers and the ratio of the partial pressure of oxygen in arterial blood to fractional inspired oxygen criteria' and 'patient list based on novel MCDM method known as subjective and objective decision by opinion score method'. Then, the patients with the most urgent need are classified into the four blood types and matched with a tested CP list from the test phase in the donor side. Thereafter, the prioritisation of CP tested list is performed using the contracted CP decision matrix.
RESULT: An intelligence-integrated concept is proposed to identify the most appropriate CP for corresponding prioritised patients with COVID-19 to help doctors hasten treatments.
DISCUSSION: The proposed framework implies the benefits of providing effective care and prevention of the extremely rapidly spreading COVID-19 from affecting patients and the medical sector.
METHODS: Electronic databases and country-specific healthcare databases were searched to identify relevant studies/reports. The quality assessment of individual studies was conducted using the Newcastle-Ottawa Scale. Country-specific proportion of individuals with COVID-19 who developed ARDS and reported death were combined in a random-effect meta-analysis to give a pooled mortality estimate of ARDS.
RESULTS: The overall pooled mortality estimate among 10,815 ARDS cases in COVID-19 patients was 39% (95% CI: 23-56%). The pooled mortality estimate for China was 69% (95% CI: 67-72%). In Europe, the highest mortality estimate among COVID-19 patients with ARDS was reported in Poland (73%; 95% CI: 58-86%) while Germany had the lowest mortality estimate (13%; 95% CI: 2-29%) among COVID-19 patients with ARDS. The median crude mortality rate of COVID-19 patients with reported corticosteroid use was 28.0% (lower quartile: 13.9%; upper quartile: 53.6%).
CONCLUSIONS: The high mortality in COVID-19 associated ARDS necessitates a prompt and aggressive treatment strategy which includes corticosteroids. Most of the studies included no information on the dosing regimen of corticosteroid therapy, however, low-dose corticosteroid therapy or pulse corticosteroid therapy appears to have a beneficial role in the management of severely ill COVID-19 patients.
METHOD: A systematic review and metanalysis was conducted in accordance with the PRISMA criteria. The PubMed, Scopus, Science direct, Web of science, CINHAL, Medline, and Google Scholar databases were searched with no lower time-limt and until 24 June 2020. The heterogeneity of the studies was measured using I2 test and the publication bias was assessed by the Egger's test at the significance level of 0.05.
RESULTS: The I2 test was used to evaluate the heterogeneity of the selected studies, based on the results of I2 test, the prevalence of sleep disturbances in nurses and physicians is I2: 97.4% and I2: 97.3% respectively. After following the systematic review processes, 7 cross-sectional studies were selected for meta-analysis. Six studies with the sample size of 3745 nurses were examined in and the prevalence of sleep disturbances was approximated to be 34.8% (95% CI: 24.8-46.4%). The prevalence of sleep disturbances in physicians was also measured in 5 studies with the sample size of 2123 physicians. According to the results, the prevalence of sleep disturbances in physicians caring for the COVID-19 patients was reported to be 41.6% (95% CI: 27.7-57%).
CONCLUSION: Healthcare workers, as the front line of the fight against COVID-19, are more vulnerable to the harmful effects of this disease than other groups in society. Increasing workplace stress increases sleep disturbances in the medical staff, especially nurses and physicians. In other words, increased stress due to the exposure to COVID-19 increases the prevalence of sleep disturbances in nurses and physicians. Therefore, it is important for health policymakers to provide solutions and interventions to reduce the workplace stress and pressures on medical staff.