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Abstract Background Predicting mortality in the emergency department (ED) is imperative to guide palliative care and end-of-life decisions. However, the clinical usefulness of utilizing the existing screening tools still leaves something to be desired. Methods We advanced the screening tool with the A-qCPR (Age, qSOFA (quick sepsis-related organ failure assessment), cancer, Performance Status Scale, and DNR (Do-Not-Resuscitate) risk score model for predicting one-year mortality in the emergency department of Taipei City Hospital of Taiwan with the potential of hospice need and evaluated its performance compared with the existing screening model. We adopted a large retrospective cohort in conjunction with in-time (the trained and the holdout validation cohort) for the development of the A-qCPR model and out-of-time validation sample for external validation and model robustness to variation with the calendar year. Results A total of 10,474 patients were enrolled in the training cohort and 33,182 patients for external validation. Significant risk scores included age (0.05 per year), qSOFA ≥ 2 (4), Cancer (5), Eastern Cooperative Oncology Group (ECOG) Performance Status score ≥ 2 (2), and DNR status (2). One-year mortality rates were 13.6% for low (score ≦ 3 points), 29.9% for medium (3 9 points). The AUROC curve for the in-time validation sample was 0.76 (0.74–0.78). However, the corresponding figure was slightly shrunk to 0.69 (0.69–0.70) based on out-of-time validation. The accuracy with our newly developed A-qCPR model was better than those existing tools including 0.57 (0.56–0.57) by using SQ (surprise question), 0.54 (0.54–0.54) by using qSOFA, and 0.59 (0.59–0.59) by using ECOG performance status score. Applying the A-qCPR model to emergency departments since 2017 has led to a year-on-year increase in the proportion of patients or their families signing DNR documents, which had not been affected by the COVID-19 pandemic. Conclusions The A-qCPR model is not only effective in predicting one-year mortality but also in identifying hospice needs. Advancing the screening tool that has been widely used for hospice in various scenarios is particularly helpful for facilitating the end-of-life decision-making process in the ED.

Abstract Background Asia’s elderly Baby Boomer demographic (born between 1946 and 1964) faced a huge problem during the COVID-19 pandemic due to increased all-cause mortality. We aimed to provide a unique Taiwan situation regarding the impact of Baby Boomers on excess mortalities from all causes relative to non-Baby Boomers throughout distinct times of SARS-CoV-2 mutations during the COVID-19 pandemic. Methods We used the Poisson time series design with a Bayesian directed acyclic graphic approach to build the background mortality prior to the COVID-19 pandemic between 2015 and 2019. It was then used for predicting the expected all-cause deaths compared to the reported figures during the COVID-19 pandemic period based on Taiwan residents, an Omicron-naïve cohort. Results Baby Boomers experienced a 2% negative excess mortality in 2020 (Wuhan/D614G) and a 4% excess mortality in 2021 (Alpha/Delta) with a rising background mortality trend whereas non-Baby Boomers showed the corresponding figures of 4% negative excess and 1% excess with a stable trend. Baby Boomer and non-Baby Boomer excess mortality soared to 9% (95% CI: 7-10%) and 10% (95% CI: 9-11%), respectively, during the epidemic Omicron period from January to June 2022. Surprisingly, Baby Boomers aged 58–76 experienced the same 9% excess mortality as non-Baby Boomers aged 77 and beyond. Non-COVID-19 deaths were more prevalent among Baby Boomers than non-Baby Boomers (33% vs. 29%). Conclusion Baby Boomers were more likely to die from COVID-19 in early pandemic and had more non-COVID-19 deaths in late pandemic than older non-Baby Boomers demonstrated in Taiwan Omicron-naïve cohort. For this vulnerable population, adequate access to medical care and medical capacity require more consideration.

Background: The trajectories of all-cause deaths linked to omicron infections are rarely studied, especially in relation to the efficacy of booster shots. For assessing three epidemiological death trajectories, including dying from COVID-19, dying with COVID-19, and non-COVID-19 death, we offer a new COVID-19-and-death competing risk model that deals with the primary pathway (e.g., dying from COVID-19) competing with two other pathways. Methods: We applied this model to track three trajectories: deaths directly from COVID-19, deaths with COVID-19 as a contributing factor, and indirect non-COVID-19 deaths. The study used data from a Taiwanese cohort, covering periods of Omicron subvariants BA.2, BA.5, and BA.2.75. It focused on the effectiveness of monovalent and bivalent booster vaccines against these death trajectories. Results: The highest mortality was observed during the BA.2 phase, which decreased in the BA.5 period and increased again in the BA.2.75 period. Analyzing each trajectory, we noted similar trends in deaths directly from and with COVID-19, while non-COVID-19 deaths remained stable across subvariants. Booster vaccines reduced all-cause mortality by 58% (52%−62%) for BA.2, 70% (65%−75%) for BA.5%, and 75% (70%−80%) for BA.2.75, compared to incomplete vaccination. The reduction in deaths directly from COVID-19 was 66% (61%−72%) for BA.2, 78% (72%−84%) for BA.5%, and 85% (76%−93%) for BA.2.75. For deaths with COVID-19, the figures were 46% (36%−55%), 76% (68%−84%), and 90% (86%−95%). Additionally, the booster shots decreased non-COVID-19 deaths by 64% (63%−66%) for BA.2, 38% (36%−40%) for BA.5, and 19% (17%−21%) for BA.2.75. Conclusion: Our competing risk analysis is effective for monitoring all-cause death trajectories amidst various Omicron infections. It provides insights into the impact of booster vaccines, especially bivalent ones, and highlights the consequences of inadequate healthcare for vulnerable groups.

BackgroundPrevious studies have highlighted the importance of viral shedding using cycle threshold (Ct) values obtained via reverse transcription polymerase chain reaction to understand the epidemic trajectories of SARS-CoV-2 infections. However, it is rare to elucidate the transition kinetics of Ct values from the asymptomatic or presymptomatic phase to the symptomatic phase before recovery using individual repeated Ct values. ObjectiveThis study proposes a novel Ct-enshrined compartment model to provide a series of quantitative measures for delineating the full trajectories of the dynamics of viral load from infection until recovery. MethodsThis Ct-enshrined compartment model was constructed by leveraging Ct-classified states within and between presymptomatic and symptomatic compartments before recovery or death among people with infections. A series of recovery indices were developed to assess the net kinetic movement of Ct-up toward and Ct-down off recovery. The model was applied to (1) a small-scale community-acquired Alpha variant outbreak under the “zero-COVID-19” policy without vaccines in May 2021 and (2) a large-scale community-acquired Omicron variant outbreak with high booster vaccination rates following the lifting of the “zero-COVID-19” policy in April 2022 in Taiwan. The model used Bayesian Markov chain Monte Carlo methods with the Metropolis-Hastings algorithm for parameter estimation. Sensitivity analyses were conducted by varying Ct cutoff values to assess the robustness of the model. ResultsThe kinetic indicators revealed a marked difference in viral shedding dynamics between the Alpha and Omicron variants. The Alpha variant exhibited slower viral shedding and lower recovery rates, but the Omicron variant demonstrated swifter viral shedding and higher recovery rates. Specifically, the Alpha variant showed gradual Ct-up transitions and moderate recovery rates, yielding a presymptomatic recovery index slightly higher than 1 (1.10), whereas the Omicron variant had remarkable Ct-up transitions and significantly higher asymptomatic recovery rates, resulting in a presymptomatic recovery index much higher than 1 (152.5). Sensitivity analysis confirmed the robustness of the chosen Ct values of 18 and 25 across different recovery phases. Regarding the impact of vaccination, individuals without booster vaccination had a 19% higher presymptomatic incidence rate compared to those with booster vaccination. Breakthrough infections in boosted individuals initially showed similar Ct-up transition rates but higher rates in later stages compared to nonboosted individuals. Overall, booster vaccination improved recovery rates, particularly during the symptomatic phase, although recovery rates for persistent asymptomatic infection were similar regardless of vaccination status once the Ct level exceeded 25. ConclusionsThe study provides new insights into dynamic Ct transitions, with the notable finding that Ct-up transitions toward recovery outpaced Ct-down and symptom-surfacing transitions during the presymptomatic phase. The Ct-up against Ct-down transition varies with variants and vaccination status. The proposed Ct-enshrined compartment model is useful for the surveillance of emerging infectious diseases in the future to prevent community-acquired outbreaks.

Introduction: Despite the serious risks of diabetes with hepatitis C virus (HCV) infection, this preventable comorbidity is rarely a priority for HCV elimination. We aim to examine how a shared care model could eliminate HCV in patients with diabetes (PwD) in primary care., Methods: There were 27 community-based Diabetes Health Promotion Institutes in each township/city of Changhua, Taiwan. PwD from these institutes from January 2018 to December 2020 were enrolled. HCV screening and treatment were integrated into diabetes structured care through collaboration between diabetes care and HCV care teams. Outcome measures included HCV care continuum indicators. Township/city variation in HCV infection prevalence and care cascades were also examined., Results: Of the 10,684 eligible PwD, 9,984 (93.4%) underwent HCV screening, revealing a 6.18% (n = 617) anti-HCV seroprevalence. Among the 597 eligible seropositive individuals, 507 (84.9%) completed the RNA test, obtaining 71.8% positives. Treatment was initiated by 327 (89.8%) of 364 viremic patients, and 315 (86.5%) completed it, resulting in a final cure rate of 79.4% (n = 289). Overall, with the introduction of antivirals in this cohort, the prevalence of viremic HCV infection dropped from 4.44% to 1.34%, yielding a 69.70% (95% credible interval 63.64%-77.03%) absolute reduction., Discussion: Although HCV prevalence varied, the care cascades achieved consistent results across townships/cities. We have further successfully implemented the model in county-wide hospital-based diabetes clinics, eventually treating 89.6% of the total PwD. A collaborative effort between diabetes care and HCV elimination enhanced the testing and treatment in PwD through an innovative shared care model., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The American College of Gastroenterology.)