News Focus

This section offers medical-related news briefs for the year 2023 in the United Kingdom (UK) which includes funding allocated by the Department for Health and Social Care for women's health hubs in England, plan for the spring Covid-19 booster campaign, and areas with highest emergency admissions and death rates for lung conditions.

The Effect of the COVID-19 Pandemic on Use of Select Child Health Services in Kenyan Hospitals

Introduction. Kenya reported its first case of coronavirus disease (COVID-19) in March 2020. Pandemics may disrupt provision of essential health services. This study sought to find out if the COVID-19 outbreak had any effect on reported paediatric workload in Kenya. Methods. Aggregate workload data for 12 months before COVID-19 outbreak and 12 months of the COVID-19 outbreak were extracted from the Kenya Health Information System and negative binomial regression conducted. Results. A significant decline was observed across all indicators. Paediatric clinics attendance declined by 36%, paediatric admissions by 31.4%, outpatient attendance by 28.7%, and child wellness clinics attendance by 10.3%. In outpatient attendance, the five conditions with the highest attendance reported a decline ranging from 17.3% to 33.8%. Conclusion. COVID-19 partially disrupted essential health services among children in Kenya. Children in need of specialized treatment were more disadvantaged.

Association between hospital internal medicine physician workforce and patient admissions during the COVID-19 pandemic in Japan.

BACKGROUND: Hospital physician workforce in Japan is the lowest among developed countries. Many patients with novel coronavirus disease 2019 (COVID-19) with high risk of mortality could not be hospitalized during case surges in Japan and only about 5% of total acute care beds were used as COVID-19 beds nationwide. However, the relationship between the number of hospital physicians and patient admissions remains unclear. Thus, we aimed to evaluate this relationship in areas with the highest incidences during the surges. METHODS: Data collection was performed for teaching hospitals accredited with the specialty of internal medicine in three prefectures which experienced the highest COVID-19 incidences in Japan (Tokyo, Osaka, Okinawa). Association was examined between the number of full-time physicians (internal medicine staff physicians and residents) and admissions of internal medicine patients through ambulance transport from April 2020 to March 2021. Analysis was conducted separately for community hospitals and university hospitals because the latter have roles as research institutions in Japan. Community hospitals included private, public, and semi-public hospitals. RESULTS: Of 117 teaching hospitals in three prefectures, data from 108 teaching hospitals (83 community hospitals and 25 university hospitals) were available. A total of 102,400 internal medicine patients were admitted to these hospitals during the one-year period. Private hospitals received the greatest mean number of patient admissions (290 per 100 beds), followed by public hospitals (227) and semi-public hospitals (201), and university hospitals (94). Among community hospitals, a higher number of resident physicians per 100 beds was significantly associated with a greater number of patient admissions per 100 beds with beta coefficient of 11.6 (95% CI, 1.5 to 21.2, p = 0.025) admissions by one physician increase per 100 beds. There was no such association among university hospitals. CONCLUSIONS: Community hospitals with many resident physicians accepted more internal medicine admissions through ambulance transport during the COVID-19 pandemic. An effective policy to counter physician shortage in hospitals in Japan may be to increase internal medicine resident physicians among community hospitals to save more lives.

The Predictors of in-Hospital Mortality in Hypertensive Elderly Intensive Care Unit Patients with Coronavirus Disease 2019

Introduction: Advanced age is an important prognostic indicator for the mortality of coronavirus disease 2019, especially in patients over 65. Patients with chronic underlying conditions such as hypertension showed the worst outcomes. This study aimed to identify predictors of mortality in elderly hypertensive patients hospitalized in intensive care units. Material(s) and Method(s): Demographic, clinical, treatment, and laboratory data were extracted from electronic medical records and compared between survivors and non-survivors. Univariate and multivariate logistic regression methods were used to explore the indicators of in-hospital mortality. Result(s): One hundred and ninety-eight patients with a median age of 75 years (65-94 years) were included in this study, of whom 95 were discharged from the intensive care units, and 103 died. Shortness of breath [hazard ratio (HR): 1.65, 95% confidence interval (CI): 1.04-2.61, p: 0.034], C-reactive protein (CRP)/albumin ratio (>51.32) (HR: 1.83, 95% CI: 1.12-2.97, p: 0.015), serum creatinine (>1.62 mg/dl) (HR: 2.04, 95% CI: 1.13-3.33, p: 0.001), aspartate transaminase (>34 u/l) (HR: 1.99, 95% CI: 1.28-3.09, p: 0.002), D-dimer (>781 ng/ml) (HR: 1.59, 95% CI: 1.04-2.43, p: 0.031), leukocyte (>12,000' 103/microl) (HR: 1.68, 95% CI: 1.09-2.59, p: 0.018) and lymphocyte count, (<=660' 103/microl) (HR: 1.76, 95% CI: 1.17-2.63, p: 0.006) were independent predictors for mortality in elderly hypertensive patients. Conclusion(s): Using these predictors with cut-off values can identify patients at risk of death and needing aggressive intervention earlier in the disease course. Copyright © 2022, Geriatrics Society. All rights reserved.

Challenges at the front: experiences of professionals in admitting patients to the intensive care unit during the covid-19 pandemic / Desafíos delanteros: experiencias de profesionales en el ingreso de pacientes en la unidad de cuidados intensivos en la pandemia del covid-19 / Desafios do front: experiências de profissionais na admissão de pacientes em unidade de terapia intensiva na pandemia da covid-19

ABSTRACT Objective: to know the perspectives, practices and challenges in decision-making for admitting patients into the Intensive Care Unit during the Covid-19 pandemic. Methods: a qualitative study developed in two public hospitals in Maranhão, Brazil, from November/2020 to January/2021. Data collection took place through individual interviews guided by a script. A total of 22 professionals participated in the study: nurses and doctors who worked in the Intensive Care Unit and Bed Regulation in the first wave of the pandemic. Content Analysis was used in the thematic mode, with support from the Qualitative Data Analysis software program for data categorization. The theory of Responsibility for Reasonableness guided the study. Results: two main categories emerged: "The context of the decision-making process - the paradox of celestial discharges" and "Decision-making for admission". In the scenario of high demand, a lack of beds, and the uncertainties of the "new disease", deciding who would occupy the bed was arduous and conflicting. Clinical and non-clinical criteria such as severity, chance of survival, distance to be covered and transport conditions were considered. It was found that the ambivalence of feelings attributed to death and care at that moment of the pandemic marked the social and technical environment of intensive care. Conclusions: the complexity of the decision-making process for admission to an intensive care unit was evidenced, demonstrating the importance of analyzing the allocation of critical resources in pandemic scenarios. Knowing the perspectives of professionals and their reflections on the experiences in that period can help in planning the allocation of health resources in future emergency scenarios.

RESUMEN Objetivo: conocer perspectivas, prácticas y desafíos en la toma de decisiones para el ingreso de pacientes a camas en Unidades de Cuidados Intensivos en la pandemia de COVID-19. Métodos: un estudio cualitativo, desarrollado en dos hospitales públicos de Maranhão, Brasil, de noviembre/2020 a enero/2021. La recolección de datos se realizó a través de entrevistas individuales guiadas por un guión. Un total de 22 profesionales participaron en el estudio: enfermeros y médicos que actuaban en la Unidad de Cuidados Intensivos y Regulación de Camas en la primera ola de la pandemia. Se utilizó el Análisis de Contenido en la modalidad temática, con apoyo del Software de Análisis Cualitativo de Datos para la categorización de los datos. La teoría de la Responsabilidad por la Razonabilidad guió el estudio. Resultados: surgieron dos categorías principales: "El contexto del proceso de toma de decisiones - la paradoja de los altos celestes" y "Toma de decisiones para la admisión". En el escenario de alta demanda, escasez de camas e incertidumbres de la "nueva enfermedad", decidir quién ocuparía la cama fue arduo y conflictivo. Se consideraron criterios clínicos y no clínicos, como gravedad, probabilidad de supervivencia, distancia a recorrer y condiciones de transporte. Se constató que la ambivalencia de los sentimientos atribuidos a la muerte y al cuidado, en ese momento de la pandemia, marcaron el ambiente social y técnico de la terapia intensiva. Conclusiones: se evidenció la complejidad del proceso de toma de decisiones para el ingreso a una unidad de cuidados intensivos, demostrando la importancia de analizar la asignación de recursos críticos en escenarios de pandemia. Conocer las perspectivas de los profesionales y sus reflexiones sobre las experiencias en ese período puede ayudar en la planificación de la asignación de recursos de salud en futuros escenarios de emergencia.

RESUMO Objetivo: conhecer perspectivas, práticas e desafios na tomada de decisão para admissão de pacientes em leitos de Unidades de Terapia Intensiva na pandemia da Covid-19. Métodos: estudo qualitativo, desenvolvido em dois hospitais públicos do Maranhão, Brasil, de novembro/2020 a janeiro/2021. A coleta de dados ocorreu por meio de entrevistas individuais guiadas por roteiro. Participaram do estudo 22 profissionais: enfermeiros e médicos que atuaram em Unidade de Terapia Intensiva e Regulação de Leitos na primeira onda da pandemia. Empregou-se a Análise de Conteúdo na modalidade temática, com apoio do Qualitative Data Analysis Software para categorização dos dados. A teoria da Responsabilidade pela Razoabilidade norteou o estudo. Resultados: emergiram duas categorias principais: "Contexto do processo decisório - o paradoxo das altas celestiais" e "Tomada de decisão para admissão". No cenário de alta demanda, insuficiência de leitos e de incertezas da "nova doença", decidir quem ocuparia o leito era árduo e conflitante. Critérios clínicos e não clínicos, como gravidade, chance de sobrevivência, distância a ser percorrida e condições do transporte foram considerados. Constatou-se que a ambivalência de sentimentos atribuídos à morte e ao cuidado, naquele momento da pandemia, marcaram o ambiente social e técnico da terapia intensiva. Conclusões: evidenciou-se a complexidade do processo decisório para admissão em unidade de terapia intensiva, demonstrando a importância de analisar a alocação de recursos críticos em cenários pandêmicos. Conhecer as perspectivas dos profissionais e as reflexões deles sobre as experiências naquele período podem auxiliar no planejamento de alocação de recursos de saúde em cenários emergenciais futuros.

MONitoring Knockbacks in EmergencY (MONKEY) - An Audit of Disposition Outcomes in Emergency Patients with Rejected Admission Requests.

Background: Emergency Department (ED) clinicians commonly experience difficulties in referring patients to inpatient teams for hospital admission. There is limited literature reporting on patient outcomes following these complicated referrals, where ED requests for inpatient admission are rejected - which study investigators termed a "knockback". Purpose: To identify disposition outcomes and referral accuracy in ED patients whose admission referral was initially rejected. Secondary objectives were to identify additional patient, clinician and systemic factors associated with knockbacks. Selection and Methodology: Emergency clinicians prospectively nominated a convenience sample of patients identified as having knockbacks over two time periods (Jan-Feb 2020 and Aug 2020 to Jan 2021) at a tertiary Australian ED. Data were analyzed with a mixed-methods approach and subsequent descriptive and thematic analyses were performed. Results: A total of 109 patients were identified as knockbacks. The referrals were warranted, with 89.0% of cases (n = 97) ultimately requiring a hospital admission. In 60.6% (n = 66) of the admissions, patients were admitted under the inpatient team initially referred to by the ED, suggesting referrals were generally accurate. The number of in-hospital units involved in the admission process and ED length of stay were positively correlated (0.409, p < 0.001). Patient factors associated with knockbacks include pre-existing chronic medical conditions and presenting acutely unwell. Analysis of clinicians' perspectives yielded recurring themes of disagreements over admission destination and diagnostic uncertainty. Conclusion: In this patient sample, emergency referrals for admission were mostly warranted and accurate. Knockbacks increase ED length of stay and may adversely affect patient care. Further focused discussion and clearer referral guidelines between ED clinicians and their inpatient colleagues are required.

Cardiac injury on admission linked to worse outcomes in hospitalized COVID-19 patients

Background/Aim. The novel severe acute respiratory syn-drome coronavirus 2 (SARS Cov-2) has triggered a pandem-ic that causes a disease with complex clinical manifestations (coronavirus disease 2019, COVID-19). Soon it became clear that patients who had some comorbidities had a bigger chance of getting the severe form of COVID-19. The aim of the study was to investigate if there was a link between cardiac injury and COVID-19 severity and mortality in pa-tients. Methods. All consecutive patients with laboratory -confirmed COVID-19 were included and followed up until discharge or death from January 30, 2020, to April 5, 2020. Results. A total of 261 COVID-19 patients were included, and 29 (11.1%) had cardiac injury on admission. Patients with cardiac injury were older than those without cardiac in-jury (72.8 vs 55.8 years old) and more likely to be male (82.8% vs 42.2%). Patients with cardiac injury were also more likely to be smokers (31.0% vs 12.5%), more likely to have chronic cardiovascular disease (24.1% vs 7.8%), chron-ic pulmonary disease (17.2% vs 3.0%), and chronic kidney disease (10.3% vs 2.2%) compared to patients without cardi-ac injury. Laboratory findings suggested that patients with cardiac injury were more likely to have leukocyte counts > 10 x 109/L, pronounced lymphopenia, direct bilirubin, myohemoglobin, blood urea nitrogen, C-reactive protein, and pro-B-type natriuretic peptide but lower levels of se-rum total protein and estimated glomerular filtration rates compared to patients without cardiac injury. Patients with cardiac injury experienced more complications (72.4% vs 47.8%), including acute respiratory distress syndrome (20.7% vs 2.7%), acute kidney injury (10.3 vs 0.4%), severe COVID-19 (58.6% vs 11.6%) and death (55.2% vs 3.9%) compared to patients without cardiac injury. Multivariate analyses showed that cardiac injury was associated with an increased risk of severe COVID-19 [hazard ratio (HR) = 8.71, 95% confidence interval (CI) = 2.37-32.04] and death (HR = 20.84, 95% CI = 1.32-328.22). Conclusion. Cardiac injury on admission was associated with a higher risk of disease progression and death in patients with COVID-19.

Admissions to a large tertiary care hospital and Omicron BA.1 and BA.2 SARS-CoV-2 polymerase chain reaction positivity: primary, contributing, or incidental COVID-19.

OBJECTIVES: SARS-CoV-2 Omicron variants BA.1 and BA.2 seem to show reduced clinical severity compared with earlier variants. Therefore, we aimed to assess and classify the cause of hospitalization for patients with COVID-19 identified with these Omicron variants in our hospital. METHODS: A retrospective analysis was performed on all patients identified with the SARS-CoV-2 Omicron variant between December 23, 2021, and February 27, 2022. Patients with a positive SARS-CoV-2 polymerase chain reaction (PCR) upon clinical admission or during clinical admission were classified into four categories: (1) primary COVID-19, (2) admission-contributing COVID-19, (3) incidental COVID-19, and (4) undetermined COVID-19. RESULTS: We classified 172 COVID-19 Omicron patient admissions, including 151 adult and 21 pediatric patients. Of the adult patients, 45% were primary COVID-19 cases, 21% were admission-contributing, 31% were incidental, and 3% were undetermined. Of the pediatric patients, 19% were primary COVID-19 cases, 29% were admission-contributing, 38% were incidental, and 14% were undetermined. CONCLUSION: In the evolving landscape of COVID-19, the number of hospitalized patients with COVID-19 should be interpreted with caution. The different patient categories should be considered in public health policy decision-making and when informing the general public.

Community-acquired pneumonia in adults

Pneumonia is a disease associated with morbidity and mortality around the world. Although the disease can occur at any age, the very young and elderly are those most likely to surfer a poor outcome. There are many causative organisms, and the illness can result in varying degrees of severity, ranging from a mild illness to a more serious one which may result in admission to hospital. This article focuses on community-acquired pneumonia (CAP) in adults and hopes to give nurses and non-medical prescribers greater confidence in assessing patients and enabling earlier recognition and treatment of this potentially fatal disease.

Window-Based Multi-Objective Optimization for Dynamic Patient Scheduling with Problem-Specific Operators

The problem of patient admission scheduling (PAS) is a nondeterministic polynomial time (NP)-hard combinatorial optimization problem with numerous constraints. Researchers have divided the constraints of this problem into hard (i.e., feasible solution) and soft constraints (i.e., quality solution). The majority of research has dealt with PAS using integer linear programming (ILP) and single objective meta-heuristic searching-based approaches. ILP-based approaches carry high computational demand and the risk of non-feasibility for a large dataset. In a single objective optimization, there is a risk of local minima due to the non-convexity of the problem. In this article, we present the first pareto front-based optimization for PAS using set of meta-heuristic approaches. We selected four multi-objective optimization methods. Problem-specific operators were developed for each of them. Next, we compared them with single objective optimization approaches, namely, simulated annealing and particle swarm optimization. In addition, this article also deals with the dynamical aspect of this problem by comparing historical window-based decomposition with day decomposition, as has previously been proposed in the literature. An evaluation of the models proposed in the article and comparison with traditional models reveals the superiority of our proposed multi-objective optimization with window incorporation in terms of optimality.

Clinical Features and Predictors associated with Mortality in Non-Survived Patients of COVID-19 in a Referral Hospital in Rasht, North of Iran

Background and Aim: In December 2019, a new type of Coronavirus (SARS-CoV-2) pneumonia (COVID-19) was reported in Wuhan and quickly spread worldwide. This study was designed to investigate the clinical symptoms of the COVID-19 patients. Materials and Methods: In this retrospective study, we collected data of 132 COVID-19 dead patients. Demographic, epidemiological, and clinical data and laboratory test results were analyzed on days 1, 3, and 6 of admission. Results: Most cases were in the 66-75 age group, 64.39% of which were males. Three days after admission, 55.3% of patients died. The most frequent clinical manifestations were dry cough (70.45%) and fever (54.54%), which increased during hospitalization. Diabetes and blood pressure were reported as the most prevalent underlying diseases. Lymphopenia and an increase in leucocyte number were observed in most patients. ESR (92.5%) and LDH (94.64%) levels were above normal. Furthermore, 42.85% and 44.73% of patients had elevated ALT and AST levels, respectively. Conclusion: The results of this study revealed that males are more likely to be infected with SARS-CoV-19. Underlying diseases were common among patients and clinical and laboratory symptoms aggravated with a rise in hospitalization time.

Dynamic Patient Admission Control With Time-Varying and Uncertain Demands in COVID-19 Pandemic

In the coronavirus epidemic, many Chinese hospitals have established buffer zones to prevent the spread and transmission of the virus. The buffer zone is a monitored and separate area where the patients who need hospitalizations after the quick treatments in the emergency department can temporarily wait for the Covid-19 test and receive some healthcare services to stabilize their conditions. Because the beds in the buffer zones are limited, the managers face the patient admission control problem for the buffer zone. This management and control problem is challenging since the patient arrivals are uncertain, and the patients’ conditions are different. In this paper, we build the infinite- and finite-horizon Markov decision process (MDP) models for this problem. We use the uniformization method to discretize the patient flow. We propose various iteration algorithms to solve the MDP models and obtain the optimal and threshold policies. Numerical experiments validate the advantages of the policies obtained by the algorithms in this paper over the current policies of hospitals. Note to Practitioners—The ongoing COVID-19 pandemic has been causing enormous damage to people’s health, jobs, and well-being. COVID-19 has affected almost all countries globally and has changed the operation mode of the healthcare system, especially the hospitals. The hospitals are the frontlines of healthcare service and the battle with the COVID-19 pandemic. This article is motivated by our collaborations with hospitals in Shanghai, China. In China, many hospitals establish buffer zones: a monitored area where the patients who need hospitalizations after the quick treatments in the emergency department can temporarily wait for the Covid-19 test and receive some healthcare services to stabilize their conditions. Because the zone’s capacity is limited, the managers must make dynamic patient admission control decisions according to multiple factors, such as patients’ health conditions and the usage of beds in the zone. We propose two MDP models to solve this complex problem. Several iteration algorithms are designed to solve the MDP models and obtain the optimal and threshold policies. Based on hospitals’ real-life data, we show the methods presented in this paper can help hospital managers make more reasonable decisions. Although we focus on the hospital’s buffer zone in China, the methodology and approach for this problem can be extended to other practical hospital management scenarios in the coronavirus pandemic. For example, For example, some hospitals have admission control problems for coronavirus patients due to hospital capacity limitations. The hospital has to decide if a patient is accepted as an inpatient or suggested to home quarantine. In such a case, the admission control problem can also be solved by the methodologies in the paper. [ FROM AUTHOR] Copyright of IEEE Transactions on Automation Science & Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

One Year of COVID-19: Lessons Learned in a Hand Trauma Center.

2020 will be remembered worldwide as the year of COVID-19 outbreak. The onset of this pandemic abruptly changed everybody's life and, in a particular manner, doctors' lives. Our hand surgery department became rapidly one of the first COVID-19-specialized wards in Italy, impacting considerably the authors' routines and activities. In this paper, the authors focus on how the demographics of patients with hand trauma changed and how they had to modify their activity. The authors retrospectively took into consideration all patients reaching their emergency department (ED) with hand trauma between 9 March 2020 (the day of the beginning of the first lockdown in Italy) and 8 March 2021 and compared them to those who reached the ED in the three previous years. Authors have analyzed the number of patients, their gender and age, the severity of their trauma, where the trauma occurred, the type of lesion, the percentage of patients who underwent surgery, and the percentage of patients who had an emergency admission. In the last year, the number of patients reaching the ED for a hand trauma has been reduced by two thirds (975 patients during the past year), the mean age of those patients has slightly increased, the severity of cases has increased, places of trauma and type of lesions have changed, and, lastly, the percentage of patients needing surgery who were admitted immediately has increased. This paper shows how the type of patients reaching the ED changed and discusses how surgeons evolved and modified their habits in treating those patients during the first lockdown and the year that followed.

[Apropriateness of hospital admissions due to COVID-19 in the 2nd and 5th phase of the pandemic.]

OBJECTIVE: The increase in the demand for healthcare caused by COVID-19 implies a lower availability of health resources and influences the appropriateness of their use. Due to the variability of demand during the pandemic, the study aimed to compare the appropriateness of hospital admissions between the 2nd and 5th phases of the pandemic according to the criteria of the Hospital Emergency Service (CiHRyC). These results were compared with those obtained according to the Pneumonity Severity Index (FINE) and the Appropriateness Evaluation Protocol (AEP). As a secondary objective, the clinical and sociodemographic characteristics of the patients studied were described. METHODS: 80 patients hospitalized from the Emergency Department were randomly selected in two study periods (2nd and 5th pandemic phase) obtained from the registry of hospitalizations of the Preventive Medicine service of Hospital Ramon y Cajal. Prevalences of inappropriateness were estimated according to the CiHRyC, FINE and AEP and an analysis was performed using univariate logistic regression between epidemiological variables of both periods collected through the electronical medical records. RESULTS: Inappropriateness of admissions were 35% and 45% in the 2nd and 5th phase of the pandemic according with CiHRyC, 25% and 5/% according with FINE and 0% and 5% according with AEP. Median age was 71.4 and 50.0 years in 2nd and 5th phase (p=0.02). 72.5% and 17.5% of the patients in the 2nd and 5th phases had at least one risk factor for COVID-19 severe illness (p<0.01). CONCLUSIONS: The measurement tools used identified more inappropriately cases in the 5th phase of the pandemic than in the 2nd one. CiHRyC coincided with FINE and AEP in the result of their evaluation.

High admission blood glucose independently predicts poor prognosis in COVID-19 patients: A systematic review and dose-response meta-analysis.

AIMS: To investigate the prognostic value of admission blood glucose (BG) in predicting COVID-19 outcomes, including poor composite outcomes (mortality/severity), mortality, and severity. METHODS: Eligible studies evaluating the association between admission fasting BG (FBG) and random BG (RBG) levels with COVID-19 outcomes were included and assessed for risk of bias with the Quality in Prognosis Studies tool. Random-effects dose-response meta-analysis was conducted to investigate potential linear or non-linear exposure-response gradient. RESULTS: The search yielded 35 studies involving a total of 14,502 patients. We discovered independent association between admission FBG and poor COVID-19 prognosis. Furthermore, we demonstrated non-linear relationship between admission FBG and severity (Pnon-linearity < 0.001), where each 1 mmol/L increase augmented the risk of severity by 33% (risk ratio 1.33 [95% CI: 1.26-1.40]). Albeit exhibiting similar trends, study scarcity limited the evidence strength on the independent prognostic value of admission RBG. GRADE assessment yielded high-quality evidence for the association between admission FBG and COVID-19 severity, and moderate-quality evidence for its association with mortality and poor outcomes. CONCLUSION: High admission FBG level independently predicted poor COVID-19 prognosis. Further research to confirm the prognostic value of admission RBG and to ascertain the estimated dose-response risk between admission FBG and COVID-19 severity are required.