Development and Validation of a Risk Score Predicting Death Without Transplant in Adult Heart Transplant Candidates.

Importance: The US heart allocation system prioritizes medically urgent candidates with a high risk of dying without transplant. The current therapy-based 6-status system is susceptible to manipulation and has limited rank ordering ability. Objective: To develop and validate a candidate risk score that incorporates current clinical, laboratory, and hemodynamic data. Design, Setting, and Participants: A registry-based observational study of adult heart transplant candidates (aged ≥18 years) from the US heart allocation system listed between January 1, 2019, and December 31, 2022, split by center into training (70%) and test (30%) datasets. Adult candidates were listed between January 1, 2019, and December 31, 2022. Main Outcomes and Measures: A US candidate risk score (US-CRS) model was developed by adding a predefined set of predictors to the current French Candidate Risk Score (French-CRS) model. Sensitivity analyses were performed, which included intra-aortic balloon pumps (IABP) and percutaneous ventricular assist devices (VAD) in the definition of short-term mechanical circulatory support (MCS) for the US-CRS. Performance of the US-CRS model, French-CRS model, and 6-status model in the test dataset was evaluated by time-dependent area under the receiver operating characteristic curve (AUC) for death without transplant within 6 weeks and overall survival concordance (c-index) with integrated AUC. Results: A total of 16 905 adult heart transplant candidates were listed (mean [SD] age, 53 [13] years; 73% male; 58% White); 796 patients (4.7%) died without a transplant. The final US-CRS contained time-varying short-term MCS (ventricular assist-extracorporeal membrane oxygenation or temporary surgical VAD), the log of bilirubin, estimated glomerular filtration rate, the log of B-type natriuretic peptide, albumin, sodium, and durable left ventricular assist device. In the test dataset, the AUC for death within 6 weeks of listing for the US-CRS model was 0.79 (95% CI, 0.75-0.83), for the French-CRS model was 0.72 (95% CI, 0.67-0.76), and 6-status model was 0.68 (95% CI, 0.62-0.73). Overall c-index for the US-CRS model was 0.76 (95% CI, 0.73-0.80), for the French-CRS model was 0.69 (95% CI, 0.65-0.73), and 6-status model was 0.67 (95% CI, 0.63-0.71). Classifying IABP and percutaneous VAD as short-term MCS reduced the effect size by 54%. Conclusions and Relevance: In this registry-based study of US heart transplant candidates, a continuous multivariable allocation score outperformed the 6-status system in rank ordering heart transplant candidates by medical urgency and may be useful for the medical urgency component of heart allocation.

Implicit rationing of nursing care reported by nurses from different types of hospitals and hospital units.

AIMS AND OBJECTIVES: The study aimed to investigate differences in assessing implicit rationing of nursing care by Czech nurses with respect to the type of unit and type of hospital. BACKGROUND: Implicit rationing of nursing care may differ across different types of hospitals and hospital units. DESIGN: This study used a multicentre cross-sectional study design. METHODS: The STROBE checklist for observational cross-sectional studies was followed for reporting of the research study. The sample included 8209 nurses providing direct care to medical and surgical patients in 14 acute care Czech hospitals. The main outcome was implicit rationing of nursing care as measured with a Czech version of the Perceived Implicit Rationing of Nursing Care (PIRNCA) instrument. Data were collected from September 2019 to October 2020. RESULTS: The most frequently rationed nursing care activity was timely response to patient or family request/need, followed by emotional or psychological support and adequate supervision of delegated tasks. More implicitly rationed nursing care was reported in medical units. Statistical differences were found in rating 25 items and the PIRNCA total score. Nurses from middle-sized hospitals reported implicitly rationed care more frequently than those from large hospitals. CONCLUSION: More rationed care was reported by nurses from medical units and nurses from middle-sized hospitals. Organisational variables (the type of unit and type of hospital) influence the implicit rationing of nursing care in our study. RELEVANCE TO CLINICAL PRACTICE: The findings call for nursing managers to pay attention to organisational variables which may affect the implicit rationing of nursing care.

CROATIAN ADAPTATION AND VALIDATION OF THE PERCEIVED IMPLICIT RATIONING OF NURSING CARE (PIRNCA) QUESTIONNAIRE: A CROSS-SECTIONAL STUDY.

The aim was to perform adaptation and validation of the Perceived Implicit Rationing of Nursing Care. Implicit delaying of nursing care is an intermediate step, linking nurses with the quality of outcomes for patients and nurses, and it is the result of prioritization of health care measures within the assigned group of patients cared for by nurses. The Perceived Implicit Rationing of Nursing Care instrument is a tool used to assess the rationing of care in nursing practice. Study participants were nurses working at hospital wards in 4 university hospitals in the Republic of Croatia. The questionnaire was filled-in by 438 nurses. Data were collected between April and November 2018. After principal axis factoring, a single factor solution based on the correlation matrix was adopted. The measured construct is one-dimensional, and the extracted factor explains 47.2% of its variance. Additionally, the reliability of the whole questionnaire was determined by using the internal consistency coefficient Cronbach alpha on the Perceived Implicit Rationing of Nursing Care with 31 of 0.96 particles, which is extremely high internal consistency reliability. In conclusion, the study found a high level of reliability and validity of the translated Perceived Implicit Rationing of Nursing Care questionnaire, fully comparable to that of the original. The questionnaire can be used to assess the phenomenon of implicit care rationing in Croatian hospitals.

Cardiac surgery outcomes in patients with coronavirus disease 2019 (COVID-19): A case-series report.

OBJECTIVE: The impact of coronavirus disease 2019 (COVID-19) on the postoperative course of patients after cardiac surgery is unknown. We experienced a major severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak in our cardiac surgery unit, with several patients who tested positive early after surgery. Here we describe the characteristics, postoperative course, and laboratory findings of these patients, along with the fate of the health care workers. We also discuss how we reorganize and reallocate hospital resources to resume the surgical activity without further positive patients. METHODS: After diagnosis of the first symptomatic patient, surgery was suspended. Nasopharyngeal swabs were performed in all patients and health care workers. Patients who were positive for SARS-CoV-2 were isolated and monitored throughout the in-hospital stay and followed up after discharged until death or clinical recovery. RESULTS: Twenty patients were found to be positive for SARS-CoV-2 sometime after cardiac surgery (mean age 69 ± 10.4 years; median European System for Cardiac Operative Risk Evaluation II score 3 [interquartile range, 5.1]); the median time from surgery to diagnosis was 15 days (interquartile range, 11). Among the patients, 18 had undergone cardiac surgery and 2 of them transcatheter aortic valve replacement. Overall mortality was 15%. Specific COVID-19-related symptoms were identified in 7 patients (35%). Among the 12 health care workers infected, 1 developed a bilateral mild-grade interstitial pneumonia. CONCLUSIONS: COVID-19 infection after cardiac surgery, regardless the time of the onset, is a serious condition. The systemic inflammatory state that follows extracorporeal circulation may mask the typical COVID-19 laboratory findings, making the diagnosis more difficult. A strict reorganization of the hospital resources is necessary to safely resume the cardiac surgical activity.

Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization.

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.

Time-varying optimization of COVID-19 vaccine prioritization in the context of limited vaccination capacity.

Dynamically adapting the allocation of COVID-19 vaccines to the evolving epidemiological situation could be key to reduce COVID-19 burden. Here we developed a data-driven mechanistic model of SARS-CoV-2 transmission to explore optimal vaccine prioritization strategies in China. We found that a time-varying vaccination program (i.e., allocating vaccines to different target groups as the epidemic evolves) can be highly beneficial as it is capable of simultaneously achieving different objectives (e.g., minimizing the number of deaths and of infections). Our findings suggest that boosting the vaccination capacity up to 2.5 million first doses per day (0.17% rollout speed) or higher could greatly reduce COVID-19 burden, should a new wave start to unfold in China with reproduction number ≤1.5. The highest priority categories are consistent under a broad range of assumptions. Finally, a high vaccination capacity in the early phase of the vaccination campaign is key to achieve large gains of strategic prioritizations.

Determinants of access to the SARS-CoV-2 vaccine: a preliminary approach.

BACKGROUND: The determinants of access to immunizers are still poorly understood, leading to questions about which criteria were considered in this distribution. Given the above, the present study aimed to analyze the determinants of access to the SARS-CoV-2 vaccine by different countries. METHODS: The study covered 189 countries using data from different public databases, and collected until February 19, 2021. We used eight explanatory variables: gross domestic product (GDP), extreme poverty, human development index (HDI), life expectancy, median age, coronavirus disease 2019 (COVID-19) cases, COVID-19 tests, and COVID-19 deaths. The endogenous variables were total vaccine doses, vaccine doses per thousand, and days of vaccination. The structural equation modeling (SEM) technique was applied to establish the causal relationship between the country's COVID-19 impact, socioeconomic variables, and vaccine access. To support SEM, we used confirmatory factor analysis, t-test, and Pearson's correlation. RESULTS: We collected the sample on February 19, and to date, 80 countries (42.1%) had already received a batch of immunizers against COVID-19. The countries with first access to the vaccine (e.g., number of days elapsed since they took the first dose) were the United Kingdom (68), China (68), Russia (66), and Israel (62). The countries receiving the highest doses were the United States, China, India, and Israel. The countries with extreme poverty had lower access to vaccines and the richer countries gained priority access. Countries most affected by COVID (deaths and cases) also received immunizers earlier and in greater volumes. Unfortunately, similar to other vaccines, indicators, such as income, poverty, and human development, influence vaccines' access. Thus affecting the population of vulnerable and less protected countries. Therefore, global initiatives for the equitable distribution of COVID need to be discussed and encouraged. CONCLUSIONS: Determinants of vaccine distribution consider the impact of the disease in the country and are also affected by favorable socioeconomic indicators. The COVID-19 vaccines need to be accessible to all affected countries, regardless of their social hands.

COVID-19 Vaccine Administration, by Race and Ethnicity - North Carolina, December 14, 2020-April 6, 2021.

COVID-19 has disproportionately affected non-Hispanic Black or African American (Black) and Hispanic persons in the United States (1,2). In North Carolina during January-September 2020, deaths from COVID-19 were 1.6 times higher among Black persons than among non-Hispanic White persons (3), and the rate of COVID-19 cases among Hispanic persons was 2.3 times higher than that among non-Hispanic persons (4). During December 14, 2020-April 6, 2021, the North Carolina Department of Health and Human Services (NCDHHS) monitored the proportion of Black and Hispanic persons* aged ≥16 years who received COVID-19 vaccinations, relative to the population proportions of these groups. On January 14, 2021, NCDHHS implemented a multipronged strategy to prioritize COVID-19 vaccinations among Black and Hispanic persons. This included mapping communities with larger population proportions of persons aged ≥65 years among these groups, increasing vaccine allocations to providers serving these communities, setting expectations that the share of vaccines administered to Black and Hispanic persons matched or exceeded population proportions, and facilitating community partnerships. From December 14, 2020-January 3, 2021 to March 29-April 6, 2021, the proportion of vaccines administered to Black persons increased from 9.2% to 18.7%, and the proportion administered to Hispanic persons increased from 3.9% to 9.9%, approaching the population proportion aged ≥16 years of these groups (22.3% and 8.0%, respectively). Vaccinating communities most affected by COVID-19 is a national priority (5). Public health officials could use U.S. Census tract-level mapping to guide vaccine allocation, promote shared accountability for equitable distribution of COVID-19 vaccines with vaccine providers through data sharing, and facilitate community partnerships to support vaccine access and promote equity in vaccine uptake.

Phase- and gender-specific, lifetime, and future costs of cancer: A retrospective population-based registry study.

ABSTRACT: Valid estimates of cancer treatment costs are import for priority setting, but few studies have examined costs of multiple cancers in the same setting.We performed a retrospective population-based registry study to evaluate phase-specific (initial, continuing, and terminal phase) direct medical costs and lifetime costs for 13 cancers and all cancers combined in Norway. Mean monthly cancer attributable costs were estimated using nationwide activity data from all Norwegian hospitals. Mean lifetime costs were estimated by combining phase-specific monthly costs and survival times from the national cancer registry. Scenarios for future costs were developed from the lifetime costs and the expected number of new cancer cases toward 2034 estimated by NORDCAN.For all cancers combined, mean discounted per patient direct medical costs were Euros (EUR) 21,808 in the initial 12 months, EUR 4347 in the subsequent continuing phase, and EUR 12,085 in the terminal phase (last 12 months). Lifetime costs were higher for cancers with a 5-year relative survival between 50% and 70% (myeloma: EUR 89,686, mouth/pharynx: EUR 66,619, and non-Hodgkin lymphoma: EUR 65,528). The scenario analyses indicate that future cancer costs are highly dependent on future cancer incidence, changes in death risk, and cancer-specific unit costs.Gender- and cancer-specific estimates of treatment costs are important for assessing equity of care and to better understand resource consumption associated with different cancers.Cancers with an intermediate prognosis (50%-70% 5-year relative survival) are associated with higher direct medical costs than those with relatively good or poor prognosis.

[Consensus of the Genetics Branch of the Chilean Society of Pediatrics on the prioritization of people with Down syndrome and rare diseases for vaccination against SARS-CoV-2]. / Consenso de la Rama de Genética de la Sociedad Chilena de Pediatría sobre priorización de personas con Síndrome de Down y otras condiciones poco frecuentes en la Campaña de Vacunación COVID-19.

In the framework of the vaccination campaign against the SARS-CoV-2 virus, the Chilean Ministry of Health requested advice from the Genetics Branch of the Chilean Society of Pediatrics, to define the level of prioritization for people with Down Syndrome . A panel of geneticists worked on the development of this consensus, in which not only patients with Down syndrome were included, but the search was extended to patients with other types of disabilities, in both pediatric and adult ages in or der to contribute to the development of public health measures against the COVID-19 pandemic. The consensus concludes that, given the prevalence of comorbidities associated with Down syndrome, the higher incidence of cases with severe COVID-19 in this population group and a higher mortality, individuals with trisomy 21 should be considered as a high-risk population, and therefore, vaccina tion against SARS-CoV-2 should have a high priority for all people with Down syndrome regardless of their age (except for the age limit established by the clinical trials of each vaccine), and should be preceded only by the groups of health personnel and adults aged > 60-65 years. Likewise, this group of experts urges health authorities to include people with intellectual disabilities and related conditions as a priority population (other chromosomal abnormalities other than Down syndrome, intellectual disability, congenital anomalies and conditions that cause disability with microcephaly), as well as the caregivers of people with this type of conditions. Vaccination in children with this type of disorders should be considered as part of the first priority group, once safe vaccines against SARS-CoV-2 are available for use in children and adolescents.

Examining hospital staff members' preferences for allocating a ventilator to a COVID-19 patient with and without Alzheimer's disease.

The COVID 19 pandemic has led to an increase in the number of patients in need of ventilation. Limitations in the number of respirators may cause an ethical problem for the medical and nursing staff in deciding who should be connected to the available respirators.  We conducted a cross-sectional survey among a convenience sample of 278 healthcare professionals at one medical center. They were asked to rank their preference in respirator allocation to three COVID-19 patients, one 80 years old with no cognitive illness, one 50 years old with Alzheimer's disease (AD), and one 80 years old with AD. Most respondents (75%) chose the 80-year-old AD patient as last preference, but were evenly divided on how to rank the other two patients. Medical staff have difficulty deciding whether age or cognitive status should be the deciding factor ventilator allocation. Determination of a set policy would help professionals with these decisions.

Allocation of scarce resources in a pandemic: rapid systematic review update of strategies for policymakers.

OBJECTIVE: In pandemics like COVID-19, the need for medical resources quickly outpaces available supply. policymakers need strategies to inform decisions about allocating scarce resources. STUDY DESIGN AND SETTING: We updated a systematic review on evidence-based approaches and searched databases through May 2020 for evaluation of strategies for policymakers. RESULTS: The 201 identified studies evaluated reducing demand for healthcare, optimizing existing resources, augmenting resources, and adopting crisis standards of care. Most research exists to reduce demand (n = 149); 39 higher quality studies reported benefits of contact tracing, school closures, travel restrictions, and mass vaccination. Of 28 strategies to augment resources, 6 higher quality studies reported effectiveness of establishing temporary facilities, use of volunteers, and decision support software. Of 23 strategies to optimize existing resources, 12 higher quality studies reported successful scope of work expansions and building on existing interagency agreements. Of 15 COVID-19 studies, 5 higher quality studies reported on combinations of policies and benefits of community-wide mask policies. CONCLUSION: Despite the volume, the evidence base is limited; few strategies were empirically tested in robust study designs. The review provides a comprehensive overview of the effects of strategies to allocate resources and provides critical appraisal to identify the best available evidence.

Equitable allocation of COVID-19 vaccines in the United States.

Many vaccine rationing guidelines urge planners to recognize, and ideally reduce, inequities. In the United States, allocation frameworks are determined by each of the Centers for Disease Control and Prevention's 64 jurisdictions (50 states, the District of Columbia, five cities and eight territories). In this study, we analyzed vaccine allocation plans published by 8 November 2020, tracking updates through to 30 March 2021. We evaluated whether jurisdictions adopted proposals to reduce inequity using disadvantage indices and related place-based measures. By 30 March 2021, 14 jurisdictions had prioritized specific zip codes in combination with metrics such as COVID-19 incidence, and 37 jurisdictions (including 34 states) had adopted disadvantage indices, compared to 19 jurisdictions in November 2020. Uptake of indices doubled from 7 to 14 among the jurisdictions with the largest shares of disadvantaged communities. Five applications were distinguished: (1) prioritizing disadvantaged groups through increased shares of vaccines or vaccination appointments; (2) defining priority groups or areas; (3) tailoring outreach and communication; (4) planning the location of dispensing sites; and (5) monitoring receipt. To ensure that equity features centrally in allocation plans, policymakers at the federal, state and local levels should universalize the uptake of disadvantage indices and related place-based measures.

Coronavirus Vaccine Distribution: Moving to a Race Conscious Approach for a Racially Disparate Problem.

Strikingly ignoring the critical impact of systemic racism in vulnerabilities to the deadly coronavirus, phase one of the vaccine rollout is not reaching the Black population that has suffered the most from COVID. An urgent need exists for a race-conscious approach that ensures equitable opportunities to both access and receive the vaccines.

Developing the COVID-19 intensive care medical equipment distribution platform: outcomes and lessons learned.

During the first wave of the coronavirus pandemic, the UK government took the decision to centralise the procurement, allocation and distribution of mission-critical intensive care unit (ICU) medical equipment. Establishing new supply chains in the context of global shortages presented significant challenges. This report describes the development of an innovative platform developed rapidly and voluntarily by clinical engineers, to mobilise the UK's shared medical equipment inventory, in order to match ICU capacity to dynamically evolving clinical demand. The 'Coronavirus ICU Medical Equipment Distribution' platform was developed to optimise ICU equipment allocation, distribution, collection, redeployment and traceability across the National Health Service. Although feedback on the platform has largely been very positive, the platform was built for a scenario that did not fully materialise in the UK and this affected the implementation approach. As such, it was not used to its full potential. Nonetheless, the platform and the insights derived and disseminated in its development have been extremely valuable. It provides a prototype for not only optimising system capacity in future pandemic scenarios but also a means for maximally exploiting the large amount of new equipment in the UK health system, as a result of the coronavirus pandemic. This early stage innovation has demonstrated that a system-wide pooled information resource can benefit the operations of individual organisations. It has also generated numerous lessons to be borne in mind in innovation projects.