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1.
J Med Internet Res ; 25: e44820, 2023 01 26.
Article in English | MEDLINE | ID: covidwho-2231997

ABSTRACT

This article focuses on how Japan experienced the COVID-19 pandemic. It delineates the various challenges the country faced and the measures the national government took to stop the spread of the infection. The article begins with the author's personal experience of COVID-19. The second section explains how the Japanese government lacked the legal sanctions to enforce a state of emergency. The third section deals with the current pandemic response as characterized by the increased use of digital technologies to control the spread of the virus. I argue that the lack of effective governance hampered Japan's timely use of digital technologies. The fourth section will touch on the issues created by the rapid spread of the infection and an increase in the hospitalization rate, focusing on intensive care unit triage and the ethical debates that ensued in Japan. The fifth section discusses the pandemic from the perspective of disaster preparedness and management, exploring the ways the pandemic responses share ethical challenges with responses to other disasters such as earthquakes and typhoons.


Subject(s)
COVID-19 , Pandemics , Humans , Disasters , Japan , Pandemics/prevention & control , Triage
2.
Critical Care Medicine ; 51(1 Supplement):482, 2023.
Article in English | EMBASE | ID: covidwho-2190648

ABSTRACT

INTRODUCTION: Patients are admitted to intensive care units (ICU) either for ICU-level treatments (mechanical ventilation, vasopressors, et cetera) or ICU-level monitoring (often institution dependent, such every hour neuro checks, or diabetic ketoacidosis with serum pH < 7.10, et cetera). Determining which LRM patients should be admitted to ICUs and which can be monitored on wards or intermediate care units and if bringing more LRM patients to the ICUs actually improves/worsens outcomes has always be a subject of much debate between ICU and floor providers, however data in said outcomes has always been sparse. We hypothesized that during various COVID-19 surges where ICUs were under particularly high strain, ICU triaging providers would (out of simple staffing / bed necessity) admit less LRM patients who would ordinarily meet ICU-admission criteria. METHOD(S): Anonymized data captured in the hospital's APACHE database from 3/1/2020 - 3/31/2022 was used to assess the monthly relationship between percentage of COVID ICU admissions and LRM ICU admission. 1/1/2018 - 2/28/20 data was used for baseline rates. RESULT(S): Baseline LRM as a percentage of total ICU admissions was 18.4% in 2018-19 and 20.2% in Jan/Feb 2020. A total of 6196 patients were admitted to the ICU 3/1/20-3/31/22. LRM fell to 13.6% as COVID hit 25% in 3/20, with inverse correlation (Pearson's r=-63.2). Peak COVID at 56.8% in 12/20 resulted in LRM of 14%. ICU SMR, vent days and LOS ratio all increased from baseline during each surge, and approached but did not return to baseline in between waves. CONCLUSION(S): LRM admissions decreased dramatically during each COVID-19 surge, suggesting elasticity in ICU triage criteria. Mortality, LOS and ventilator day ratios increased from baseline possibly indicating capacity strain, most notably 5/2020-7/2020, 1/2021 and 12/2021-1/2022 reflecting the original, alpha and omicron surges. We will use this data to study the hospital course and outcomes in those LRM patients who were not admitted to the ICU and if there are any statistically and clinically significant changes that could potentially be made to our ICU admission criteria in the future.

3.
Critical Care Medicine ; 51(1 Supplement):117, 2023.
Article in English | EMBASE | ID: covidwho-2190501

ABSTRACT

INTRODUCTION: ICU admission occurs for active treatment (ventilation, vasopressors) and to monitor patients at risk. The Acute Physiology and Chronic Health Evaluation (APACHE) IVb defines Low Risk Monitor (LRM) as not actively treated on ICU day 1 and < 10% prospective risk of ever needing active treatment. LRM patients potentially fill ICU beds required by acutely ill patients. We investigated if unprecedented ICU demand during the COVID-19 pandemic decreased LRM admissions during COVID surges. METHOD(S): Retrospective analysis of hospitals tracking COVID-19 status and consistently contributing to the APACHE database March 23, 2020 to December 31, 2021. Baseline pre-pandemic data was also assessed. Patients with primary surgical and trauma diagnoses were removed to eliminate incidental COVID diagnoses. Pearson's correlation coefficient (r) assessed the weekly relationship between %COVID and LRM patients. RESULT(S): 117,004 patients were admitted to ICU at 43 hospitals. Baseline LRM averaged 28.6% pre-COVID. During successive COVID peaks in April, July and December 2020 and April, August and December 2021, there was high inverse correlation (r=-0.90) between COVID census and LRM percentage. For example, in September 2020 COVID% was 7.81 and LRM was 28.2%. In December 2020, COVID surged to 31.1% and LRM dropped to 21.3%. These percentages returned to COVID 9.5% and LRM 28.2% during the March 2021 trough. Hospital mortality was 10.9% pre-pandemic, and 14.69% actual/13.66 predicted (SMR=1.08) from April 2020 through December 2021. Mean ventilator days were 4.08 pre- and 5.58 pandemic. ICU LOS increased from 3.52 to 4.16 days (ratio 1.11). CONCLUSION(S): LRM admissions decreased dramatically during successive COVID-19 surges, demonstrating considerable elasticity in ICU triage decisions. Mortality, ventilator days and ICU LOS all increased during the pandemic compared to baseline. Consistent measurement of % LRM may be helpful in recognizing opportunities to reduce inappropriate ICU bed utilization and as a marker of strained capacity.

4.
Nephrology Dialysis Transplantation ; 37(SUPPL 3):i648-i649, 2022.
Article in English | EMBASE | ID: covidwho-1915776

ABSTRACT

BACKGROUND AND AIMS: during the COVID-19 pandemic, several guidelines have recommended the use of the Clinical Frailty Scale (CFS) for triage of critically ill patients with COVID-19 in case of shortage in ICU resources. However, no data on using CFS assessment for ICU triage for dialysis patients is yet available. This study evaluates whether CFS is associated with mortality rates in a cohort of hospitalized dialysis patients with COVID-19. METHOD: the analyses are based on data of the European Renal Association COVID-19 Database (ERACODA). Dialysis patients who presented with COVID-19 between 1 February 2020 and 30 April 2021 and with complete information on CFS and vital status at 3 months were included. Study outcomes were hospital and ICU admission rates and hospital and ICU mortality at 3 months after hospital admission. Cox regression analyses were performed to assess the association of CFS category (≤5 versus ≥ 6) and study outcomes in line with Dutch ICU triage guidelines for COVID-19. Furthermore, additional subgroup analyses were performed to assess the association between CFS and 3-month mortality by age category (<65, 65-75 and >75 years). RESULTS: among a total of 2206 dialysis patients (mean age = 67.2 (14.1) years, male sex = 61%), 1694 (77%) had CFS ≤ 5 and 514 (23%) had CFS ≥ 6. Hospitalization rate was comparable in patients with CFS ≤ 5 and in patients with CFS ≥ 6 (67 and 71%, respectively), whereas the rate of ICU admission was higher in patients with CFS ≤ 5 than in patients with CFS ≥ 6 (16 versus 9%, p = 0.001). Among 1501 hospitalized patients, 3-month mortality was 26% of patients with CFS ≤ 5 and 59% in patients with CFS ≥ 6 (P < 0.001). Multivariate analysis with adjustment for patient demographics, smoking status and BMI revealed that CFS ≥ 6 was associated with hospital mortality [aHR 2.27 (1.88-2.74) versus CFS ≤ 5;P < 0.001) with a significant interaction for age (P = 0.029). aHR was 4.00 (2.56-6.37;CFS ≥ 6 versus CFS ≤ 5;P < 0.001) in patients < 65 years, aHR was 1.87 (1.33-2.64;CFS ≥ 6 versus CFS ≤ 5;P < 0.001) in patients 65-75 years and aHR was 2.12 (1.64-2.75;CFS ≥ 6 versus CFS ≤ 5;P < 0.001) in patients >75 years. Among 219 ICU admitted patients, 3-month mortality was 60% of the patients with CFS ≤ 5 and 91% in the patients with CFS ≥ 6, respectively. Multivariate analysis with adjustment for patient demographics, smoking status and BMI revealed that CFS ≥ 6 was associated with ICU mortality [aHR 1.80 (1.17-2.77);CFS ≥ 6 versus CFS ≤ 5;P = 0.002]. CONCLUSION: more frail dialysis patients with CFS ≥ 6 who are hospitalized for COVID-19 were less often admitted to the ICU, but in case they were admitted to the ICU they have a very high mortality of 91% in this cohort study. In fit to mildly frail dialysis, patients who were admitted to the ICU, mortality rates are lower. The association between frailty and hospital mortality is interacted by age with the strongest association in patients younger than 65 years. These findings suggest that CFS may be a useful complementary triage tool for ICU admission of dialysis patients during the ongoing COVID-19 pandemic.

5.
Acta Clinica Belgica: International Journal of Clinical and Laboratory Medicine ; 77(sup1):1-33, 2022.
Article in English | EMBASE | ID: covidwho-1886341
6.
Br Med Bull ; 138(1): 5-15, 2021 06 10.
Article in English | MEDLINE | ID: covidwho-1246698

ABSTRACT

INTRODUCTION: The coronavirus disease 2019 pandemic has placed intensive care units (ICU) triage at the center of bioethical discussions. National and international triage guidelines emerged from professional and governmental bodies and have led to controversial discussions about which criteria-e.g. medical prognosis, age, life-expectancy or quality of life-are ethically acceptable. The paper presents the main points of agreement and disagreement in triage protocols and reviews the ethical debate surrounding them. SOURCES OF DATA: Published articles, news articles, book chapters, ICU triage guidelines set out by professional societies and health authorities. AREAS OF AGREEMENT: Points of agreement in the guidelines that are widely supported by ethical arguments are (i) to avoid using a first come, first served policy or quality-adjusted life-years and (ii) to rely on medical prognosis, maximizing lives saved, justice as fairness and non-discrimination. AREAS OF CONTROVERSY: Points of disagreement in existing guidelines and the ethics literature more broadly regard the use of exclusion criteria, the role of life expectancy, the prioritization of healthcare workers and the reassessment of triage decisions. GROWING POINTS: Improve outcome predictions, possibly aided by Artificial intelligence (AI); develop participatory approaches to drafting, assessing and revising triaging protocols; learn from experiences with implementation of guidelines with a view to continuously improve decision-making. AREAS TIMELY FOR DEVELOPING RESEARCH: Examine the universality vs. context-dependence of triaging principles and criteria; empirically test the appropriateness of triaging guidelines, including impact on vulnerable groups and risk of discrimination; study the potential and challenges of AI for outcome and preference prediction and decision-support.


Subject(s)
COVID-19/therapy , Critical Care/ethics , Triage/ethics , COVID-19/epidemiology , COVID-19/transmission , Clinical Protocols , Humans
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