Direct bilirubin and the neutrophil-to-monocyte ratio timely predict intensive care unit admission in patients with severe acute respiratory syndrome coronavirus-2 infection (COVID-19)

Objective: Intensive care units (ICUs) collapsed under the global wave of coronavirus disease 2019 (COVID-19). Thus, we designed a clinical decision-making model that can help predict at hospital admission what patients with COVID-19 are at higher risk of requiring critical care. Method(s): This was a cross-sectional study in 119 patients that met hospitalization criteria for COVID-19 including less than 30 breaths per minute, peripheral oxygen saturation < 93%, and/or >= 50% lung involvement on imaging. Depending on the need for critical care, patients were retrospectively assigned to ICU and non-ICU groups. Demographic, clinical, and laboratory parameters were collected at admission and analyzed by classification and regression tree (CRT). Result(s): Forty-five patients were admitted to ICU and 80% of them were men older than 57.13 +/- 12.80 years on average. The leading comorbidity in ICU patients was hypertension. The CRT revealed that direct bilirubin (DB) > 0.315 mg/dl together with the neutrophil-to-monocyte ratio (NMR) > 15.90 predicted up to correctly in 92% of the patients the requirement of intensive care management, with sensitivity of 93.2%. Preexisting comorbidities did not influence on the tree growing. Conclusion(s): At hospital admission, DB and NMR can help identify nine in 10 patients with COVID-19 at higher risk of ICU admission.Copyright © 2022 Sociedad Medica del Hospital General de Mexico.

Management of lung cancer in the COVID-19 pandemic: A review

Since its inception, the COVID-19 pandemic has affected health care as a whole. Cancer patients in general and those suffering from lung cancer in particular are a vulnerable group because of their many intrinsic characteristics and care needs. How SARS-CoV-2 (COVID-19) infection affects these patients regarding their risk of infection and outcome in this patient cohort is still to be determined. In this review, we tried to summarize our main concerns regarding COVID-19 in the context of cancer patients from a clinical and multidisciplinary approach. Different types of lung cancer treatments (chemotherapy, radiation therapy and immunotherapy) may also influence the risk of infection and condition the patient's risk of having a worse outcome. Lung cancer patients require frequent radiologic study follow-ups, which may be affected by COVID-19 pandemic. COVID-19 related incidental radiologic findings can appear in routinely scheduled radiology tests, which may be difficult to interpret. Also cancer treatment induced pneumonitis may have similar radiologic features similar to those in acute SARS-CoV-2 pneumonia and lead to a wrong diagnosis. The different health care needs, the requirement for continuous health care access and follow-ups, and the clinical traials in which this patient population might be enrrolled are all being affected by the current COVID-19 health crisis. The COVID-19 pandemic has put health care providers and institutions in difficult situations and obliged them to face challenging ethical scenarios. These issues, in turn, have also affected the psychological well-being of health care workers.Copyright © The Author(s) 2021.

AI and Dynamic Prediction of Deterioration in Covid-19

During the COVID-19 pandemic it became evident that outcome prediction of patients is crucial for triaging, when resources are limited and enable early start or increase of available therapeutic support. COVID-19 demographic risk factors for severe disease and death were rapidly established, including age and sex. Common Clinical Decision Support Systems (CDSS) and Early Warning Systems (EWS) have been used to triage based on demographics, vital signs and laboratory results. However, all of these have limitations, such as dependency of laboratory investigations or set threshold values, were derived from more or less specific cohort studies. Instead, individual illness dynamics and patterns of recovery might be essential characteristics in understanding the critical course of illness.The pandemic has been a game changer for data, and the concept of real-time massive health data has emerged as one of the important tools in battling the pandemic. We here describe the advantages and limitations of established risk scoring systems and show how artificial intelligence applied on dynamic vital parameter changes, may help to predict critical illness, adverse events and death in patients hospitalized with COVID-19.Machine learning assisted dynamic analysis can improve and give patient-specific prediction in Clinical Decision Support systems that have the potential of reducing both morbidity and mortality. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Artificial intelligence and machine learning in clinical trial design and application

In 2020, COVID-19 changed how health care was approached both in the United States and globally. In the early phases, the vast majority of energy and attention was devoted to containing the pandemic and treating the infected. Toward the end of 2020, that attention expanded to vaccinating people across the globe. What was not being considered at the time were challenges to future health and clinical trials that power new treatments for COVID-19 and non-COVID-19 treatments. © 2023 Elsevier Inc. All rights reserved.

Monoclonal antibodies to the interleukin-6 receptor in the treatment of COVID-19 in patients with chronic kidney disease

Interleukin-6 (IL-6) plays a key role in the pathogenesis of COVID-19, which determines the indications for the therapeutic use of its antagonists. However, data on their effectiveness and optimal timing of appointment are contradictory. The question of the possibility of their use in patients with impaired kidney function has not been studied. The aim of the study is to evaluate the efficacy and safety of the use of monoclonal antibodies to IL-6 receptors in COVID-19 in patients with chronic kidney disease (CKD) of stages 2-5 (predialysis) who do not need renal replacement therapy. Material and methods. A clinical retrospective uncontrolled single-center study included 45 patients (60% of men) with CKD stages 2-5 aged 22-95 years (median - 58 years) hospitalized with predominantly severe uncritical COVID-19 infection. Treatment of COVID-19 was carried out in accordance with the Interim guidelines for the prevention and treatment of new coronavirus infection of the Ministry of Health of Russian Federation. Results. The majority of patients (n=36;73.3%) had CKD stage 3b-5, CKD stage 2 was in 7 (15.5%) and stage 3a - in 5 (11.1%) patients. The median serum creatinine level (Cr) was 164 [131;292] mumol/l, glomerular filtration rate (GFR) was 30 [13;49] ml/min/1.73 m2, CRP 67.5 [37.2;106.75] mg/l. The introduction of monoclonal antibody to IL-6 receptors led to a decrease in the activity of the infectious process (CRP 1.55 [0.33;4.15] mg/l, p<0.001), regression of pneumonia, which did not require mechanical ventilation and hospitalization in the intensive care unit. According to the decision of the medical commission, patients were injected with monoclonal antibodies to IL-6 receptors: tocilizumab (n=36;80%), levilimab (n=2;4.4%), combined therapy with two drugs (n=7;15.5%). Therapy with IL-6 antagonists did not have a negative effect on kidney function. The levels of Cr decreased on average from 224.3+/-145.2 mmol/l at admission to 160+/-92.55 mmol/l at discharge (p<0.001), GFR increased from 32.6+/-20.9 ml/min/1.73 m2 at admission to 53+/-31.7 ml/min/1.73 m2 at discharge (p<0.001). In the majority of patients (n=36, 80%) GFR has risen, and only in 9 (20%) cases it remained approximately at the same low level. No serious adverse events have been reported with the use of IL-6 antagonists, as well as concomitant infectious complications. No deaths have been reported. The median length of stay in bed was 14 [10;19] days. Conclusion. The results of the study allow us to state that in patients with CKD, monoclonal antibodies to IL-6 receptors have a good safety profile and can be successfully used in moderate and severe forms of COVID-19, regardless of the state of kidney function.Copyright © 2022 by the authors.

Cognitive bias in the context of epidemic

In connection with the scope and duration of the COVID-19 pandemic, the clinical judgement of clinicians and medical practitioners could be influenced such that diagnostic errors (delays and inaccuracies) may ensue. We hereby recall through two clinical scenarios the constant need for practitioners to take a step back in reflecting of the diagnostic process to avoid the <<tunnel effect>> which may result in delaying common and frequent infectious diseases. The flu-like symptoms presented by these patients (fever, myalgia and asthenia...) quickly prompted our emergency room colleagues to suspect SARS-CoV-2 infection. However, further investigations including imagery and blood cultures revealed completely different but common infectious disease conditions, which are potentially fatal.Copyright © 2020 Editions Medecine et Hygiene. All rights reserved.

Patient Experience of Remote Healthcare during the Pandemic in Rheumatoid Arthritis and Adult Juvenile Idiopathic Arthritis

Background/Aims COVID-19 challenged traditional care models and necessitated introduction of remote consultations. We wanted to understand the experiences of people with rheumatoid arthritis (RA)/adult juvenile idiopathic arthritis (AJIA) on accessing healthcare remotely, and how well people understood their condition and treatment. Methods This collaborative work between the National Rheumatoid Arthritis Society (NRAS) and clinicians in Oxford led to the development of an electronic questionnaire that was disseminated in July 2021 for four weeks through e-newsletters and all NRAS social media platforms. Those living in the UK with RA and AJIA aged 18 and over were eligible. Analyses of data were performed in Microsoft Excel and IBM SPSSv28. Results We analysed 316 responses. There was a middle-aged (ages 46 to 54, 54.1%, n=171), Caucasian (97.5%, n=306), female (92.4%, n=292) preponderance. Most had RA (93%, n=294) followed by another inflammatory arthritis (4.1%, n=13) and AJIA (2.8%, n=9). The majority had their condition for >10 years (43.4%, n=137) but some were diagnosed <12 months ago (3.2%, n=10). Two thirds of participants (66.5%, n=210) did not know their DAS28 score. Of the remaining third, the most commonly reported measure was moderate disease activity (12%, n=38). Those with higher self-reported DAS28 scores were using analgesia more regularly (p<0.01) but we found no difference in NSAID, DMARD or steroid use. Age did not influence steroid usage (p=0.35), but those who had their condition for longer used more steroids and regular analgesia. Only 33.9% (n=107) of responders felt their condition had been managed adequately in the pandemic, with more reporting poor status (40.8%, n=129) rather than good (16.8%, n=53). Those living in the South of England reported statistically better disease control than those from the North, despite having more virtual assessments (p=0.02). Travelling and fear of Covid appeared more important than consultation skills. Just over a fifth (20.3%, n=64) felt greater focus should be given to patient concerns. Of the 9.1% of patients (n=29) with a new diagnosis made during the pandemic, 24.1% (n=7) unable to book a GP appointment easily. Patients experienced a median symptom time of 4-10 weeks before consulting GPs. Once assessed, 31% (n=9) were referred immediately while the median time was 4-8 weeks. We found 58.6% (n=17) of patients received their diagnosis within their initial rheumatology consultation and 76.5% (n=13) of these started a DMARD immediately. Conclusion Despite a greater emphasis on patient education and PROMs influencing clinical decision-making, it is staggering that two-thirds did not know their DAS28 score. Analgesia and steroid use were common in patients with well-established disease which remains a concern. Accessing appointments was a significant barrier to patients and delays in care were experienced at every step in the NHS management pathways. Remote consultations need greater emphasis on patient concerns.

Forecasting COVID-19 cases in Egypt using ARIMA-based time-series analysis

Objectives: The World Health Organization declared the novel coronavirus (COVID-19) outbreak a public health emer-gency of international concern on January 30, 2020. Since it was first identified, COVID-19 has infected more than one hundred million people worldwide, with more than two million fatalities. This study focuses on the interpretation of the distribution of COVID-19 in Egypt to develop an effective forecasting model that can be used as a decision-making mechanism to administer health interventions and mitigate the transmission of COVID-19. Method(s): A model was developed using the data collected by the Egyptian Ministry of Health and used it to predict possible COVID-19 cases in Egypt. Result(s): Statistics obtained based on time-series and kinetic model analyses suggest that the total number of CO-VID-19 cases in mainland Egypt could reach 11076 per week (March 1, 2020 through January 24, 2021) and the number of simple regenerations could reach 12. Analysis of the ARIMA (2, 1, 2) and (2, 1, 3) sequences shows a rise in the number of COVID-19 events. Conclusion(s): The developed forecasting model can help the government and medical personnel plan for the imminent conditions and ensure that healthcare systems are prepared to deal with them.Copyright © 2021 by Eurasian Journal of Medicine and Oncology.

Defining ready for discharge from sub-acute care: a qualitative exploration from multiple stakeholder perspectives.

BACKGROUND: Planning discharges from subacute care facilities is becoming increasingly complex due to an ageing population and a high demand on services. The use of non-standardised assessments to determine a patient's readiness for discharge places a heavy reliance on a clinician's judgement which can be influenced by system pressures, past experiences and team dynamics. The current literature focusses heavily on discharge-readiness from clinicians' perspectives and in the acute care setting. This paper aimed to explore the perceptions of discharge-readiness from the perspectives of key stakeholders in subacute care: inpatients, family members, clinicians and managers. METHODS: A qualitative descriptive study was conducted, exploring the views of inpatients (n = 16), family members (n = 16), clinicians (n = 17) and managers (n = 12). Participants with cognitive deficits and those who did not speak English were excluded from this study. Semi-structured interviews and focus groups were conducted and audio-recorded. Following transcription, inductive thematic analysis was completed. RESULTS: Participants identified that there are both patient-related and environmental factors that influence discharge-readiness. Patient-related factors discussed included continence, functional mobility, cognition, pain and medication management skills. Environmental factors centred around the discharge (home) environment, and were suggested to include a safe physical environment alongside a robust social environment which was suggested to assist to fill any gaps in functional capabilities (i.e. patient-related factors). CONCLUSIONS: These findings make a unique contribution to the literature by providing a thorough exploration of determining discharge-readiness as a combined narrative from the perspectives from key stakeholders. Findings from this qualitative study identified key personal and environmental factors influencing patients' discharge-readiness, which may allow health services to streamline the determination of discharge-readiness from subacute care. Understanding how these factors might be assessed within a discharge pathway warrants further attention.

PDSS: A Pharmacological Decision Support System for Diabetics Patients with COVID-19.

With the advent of SARS-CoV-2, several studies have shown that there is a higher mortality rate in patients with diabetes and, in some cases, it is one of the side effects of overcoming the disease. However, there is no clinical decision support tool or specific treatment protocols for these patients. To tackle this issue, in this paper we present a Pharmacological Decision Support System (PDSS) providing intelligent decision support for COVID-19 diabetic patient treatment selection, based on an analysis of risk factors with data from electronic medical records using Cox regression. The goal of the system is to create real world evidence including the ability to continuously learn to improve clinical practice and outcomes of diabetic patients with COVID-19.

Development and validation of multivariable prediction models of serological response to SARS-CoV-2 vaccination in kidney transplant recipients.

Repeated vaccination against SARS-CoV-2 increases serological response in kidney transplant recipients (KTR) with high interindividual variability. No decision support tool exists to predict SARS-CoV-2 vaccination response to third or fourth vaccination in KTR. We developed, internally and externally validated five different multivariable prediction models of serological response after the third and fourth vaccine dose against SARS-CoV-2 in previously seronegative, COVID-19-naïve KTR. Using 20 candidate predictor variables, we applied statistical and machine learning approaches including logistic regression (LR), least absolute shrinkage and selection operator (LASSO)-regularized LR, random forest, and gradient boosted regression trees. For development and internal validation, data from 590 vaccinations were used. External validation was performed in four independent, international validation cohorts comprising 191, 184, 254, and 323 vaccinations, respectively. LASSO-regularized LR performed on the whole development dataset yielded a 20- and 10-variable model, respectively. External validation showed AUC-ROC of 0.840, 0.741, 0.816, and 0.783 for the sparser 10-variable model, yielding an overall performance 0.812. A 10-variable LASSO-regularized LR model predicts vaccination response in KTR with good overall accuracy. Implemented as an online tool, it can guide decisions whether to modulate immunosuppressive therapy before additional active vaccination, or to perform passive immunization to improve protection against COVID-19 in previously seronegative, COVID-19-naïve KTR.

Improving guideline-concordant thromboprophylaxis prescribing for children admitted to hospital with COVID-19.

BACKGROUND: The incidence of venous thrombo-embolism (VTE) in hospitalized children has increased by 130%-200% over the last two decades. Given this increase, many centers utilize electronic clinical decision support (CDS) to prognosticate VTE risk and recommend prophylaxis. SARS-CoV-2 infection (COVID-19) is a risk factor for VTE; however, CDS developed before the COVID-19 pandemic may not accurately prognosticate VTE risk in children with COVID-19. This study's objective was to identify areas to improve thromboprophylaxis recommendations for children with COVID-19. METHODS: Inpatients with a positive COVID-19 test at admission were identified at a quaternary-care pediatric center between March 1, 2020 and January 20, 2022. The results of the institution's automated CDS thromboprophylaxis recommendations were compared to institutional COVID-19 thromboprophylaxis guidelines and to the actual thromboprophylaxis received. CDS optimization was performed to improve adherence to COVID-19 thromboprophylaxis recommendations. RESULTS: Of the 329 patients included in this study, 106 (28.2%) were prescribed pharmaco-prophylaxis, 167 (50.8%) were identified by the institutional COVID-19 guidelines as requiring pharmaco-prophylaxis, and 45 (13.2%) were identified by the CDS as needing pharmaco-prophylaxis. On univariate analysis, only age 12 years or more was associated with recipient of appropriate prophylaxis (OR 1.78, 95% CI: 1.13-2.82, p = .013). Five patients developed VTEs; three had symptoms at presentation, two were identified as high risk for VTE by both the automated and best practice assessments but were not prescribed pharmaco-prophylaxis. CONCLUSION: Automated thromboprophylaxis recommendations developed prior to the COVID-19 pandemic may not identify all COVID-19 patients needing pharmaco-prophylaxis. Existing CDS tools need to be updated to reflect COVID-19-specific risk factors for VTEs.

Thinking about the development of rapid recommendation based on the status of covid-19 evidence.

With the outbreak and rapid spread of the COVID-19 worldwide, a large amount of relevant research evidence has quickly emerged. However, due to the uneven quality of evidence, poor quality and slow speed of evidence translation, it is a big challenge for health decision-makers, clinicians, and patients to make evidence-based decisions. Based on rapid systematic review of evidence, the rapid advice-guidelines can promptly and effectively transform the latest current evidence into recommendations guiding clinical practice. In the face of global public health emergencies, by building a new type of evidence ecosystem, a completely closed loop of evidence from production and evaluation to application and transformation is formed to improve the level of medical practice and reduce the waste of health resources.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

L-Ornithine-L-Aspartate and Intermittent Renal Replacement Therapy in Fulminant Hepatitis A: A Case Report

Hepatitis A is a common viral infection worldwide that is transmitted via the fecal-oral route. Since the introduction of an efficient vaccine, the incidence of infection has decreased but the number of cases has risen due to widespread community outbreaks among unimmunized individuals. Classic symptoms include fever, malaise, dark urine, and jaundice, and are more common in older children and adults. People are often most infectious 14 days prior to and 7 days following the onset of jaundice. We will discuss the case of a young male patient, diagnosed with acute hepatitis A, leading to fulminant hepatitis refractory to conventional therapy and the development of subsequent kidney injury. The medical treatment through the course of hospitalization was challenging and included the use of L-ornithine-L-aspartate and prolonged intermittent hemodialysis, leading to a remarkable outcome. Hepatitis A is usually self-limited and vaccine-preventable;supportive care is often sufficient for treatment, and chronic infection or chronic liver disease rarely develops. However, fulminant hepatitis, although rare, can be very challenging to manage as in the case of our patient.Copyright © 2023 The Author(s).

Quality Improvement in the Placental Pathology Process: An Interdisciplinary Approach

Background: The placenta functions to provide fetal nutrients, adapt its nutrient supply to match extraction, and mount key inflammatory responses. Placental pathology exams can offer insights and explain long- and short-term adverse events for both birther and fetus. The combination of recent indication developments (i.e. COVID-19) and varying education around pathology reports is resulting in increased pathology workload, result turnaround times, and timing of family consults. For placental pathology to guide clinical decision-making, order indications must be informative to decrease pathologist workloads reviewing electronic record, and timely reports must be returned. The objective of the study is to identify gaps in the workflow of placental pathology processing to facilitate informative orders, improve interdepartmental communication, and educate for better clinical counseling. Method(s): Quality improvement (QI) fishbone diagrams outlined problems and solutions for timely pathology report turnarounds. 3 mixed-methods surveys were sent to UW pathology and general obstetrics (Ob) residents, maternalfetal medicine (MFM) and neonatal intensive care (NICU) fellows, and attending Ob and MFM providers to identify knowledge gaps, preferred educational tools, and free text thoughts about interdepartmental communication around placental pathology. Rates were compared by Chi2, Likert scale data were compared by Mann-Whitney. Result(s): Survey response rates from pathology trainees, combined Ob, MFM, and NICU trainees, and the Ob attendings were 23.8%, 27.2%, and 50%, respectively. Sufficiency of placental education for Ob and MFM trainees and attendings was rated 1.95/10 (n=21) and 5.5/10 (n=8), respectively. Delivery attending Ob/MFM providers rated their confidence family counseling as 4.86/10 (n=14), with MFM providers' expressed rating higher (7/10, n=5) than Ob (3.67/10, n=9). Overall, interdepartmental communication surrounding placentas was rated an average of 1.9/10 (n=30). 4 Ob residents reported receiving no training on the topic. 3 Ob providers expressed that reports often provided no clinically relevant data. Conclusion(s): Utilizing survey responses, 4 interventions were chosen to improve education and communication, including the use of a .placentalpath SmartPhrase, a teaching tool, updated indication guidelines, and regular joint interdisciplinary perinatal case conferences on relevant topics. Future directions include implementing, following, and assessing the effectiveness of these instruments.

Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges

Federated learning is the process of developing machine learning models over datasets distributed across data centers such as hospitals, clinical research labs, and mobile devices while preventing data leakage. This survey examines previous research and studies on federated learning in the healthcare sector across a range of use cases and applications. Our survey shows what challenges, methods, and applications a practitioner should be aware of in the topic of federated learning. This paper aims to lay out existing research and list the possibilities of federated learning for healthcare industries.© 2022 Copyright held by the owner/author(s).

Prognosis Score for Overall Survival with CAR-T Therapy in Aggressive Lymphoma

Background: Despite the transformative potential of chimeric antigen receptor T (CAR-T) therapy, more tools to assist with identifying patients with increased likelihood of benefitting from this therapy will be helpful, particularly given the logistical complexity and socio-economic demands for CAR-T relative to other therapies. Health care resource restriction during the COVID-19 pandemic highlights the need for these tools. We present a simple survival score that uses 3 readily available clinical labs: platelet (plt), absolute lymphocyte count (ALC), and Lactate dehydrogenase (LDH), to predict the risk of dying within 6 months of CAR-T therapy in patients with aggressive lymphoma. Method(s): We conducted a retrospective chart review of patients with aggressive non-Hodgkin lymphoma (NHL) who received FDA-approved CAR-T between Jan 2018 to Jan 2022 at Mayo Clinic Rochester.(Table Presented)Results: Among a total of 110 pts who received CAR-T, 27 (25%) pts died within the first 6 months post CAR-T infusion (OS <= 6 months). Disease progression was the main cause of death (18/25, 72%), followed by infection (4/25, 16%), CAR-T related (HLH/MAS, 2/25, 8%), second primary malignancy (1/25, 4%) and unknown (2/25, 8%).Baseline demographics were comparable between the OS>6months and <=6months groups (Table 1). Patients' ECOG, Karnofsky performance status and 11 labs at the time of evaluation for CAR-T therapy (initial eligibility assessment, prior to leukapheresis) were compared between those who died from any cause within 6 months of CAR-T infusion and those who did not. Hemoglobin, plt, ALC, absolute monocyte count, CRP, ferritin, and LDH were selected as clinically and/or statistically significant variables for multivariate testing. Multivariate regression with boot-strap testing identified plt, ALC, and LDH as the most predictive variables with 80.9+/-11.7% accuracy for predicting death within 6 months of CAR-T infusion. Patients were scored 0-3 using these 3 labs, with 1 point assigned for plt <= 100 X109/L, ALC <= 0.4 X109/L, or LDH > 222 U/L (upper limit of normal). OS by this survival score is shown in Figure 1.(Figure Presented)Discussion: Due to the curative potential of CAR-T, patients with broader characteristics than those treated on registration studies have been treated in standard of care practice. While an estimated 5%-10% risk of CAR-T associated deaths in the first 3 months is seen across all patients in clinical trials, predictors for early death after CAR-T in real-world patient populations can provide additional context for pts and providers when selecting treatment. This survival score is important proof of concept that a simple model using readily accessible clinical labs at the time of CAR-T evaluation could provide additional context to help with additional clinical decision-making. Multicenter prospective studies will help define and validate the definitive survival scoring system.Copyright © 2023 American Society for Transplantation and Cellular Therapy

Predicting COVID-19 Severity Integrating RNA-Seq Data Using Machine Learning Techniques

A fundamental challenge in the fight against COVID-19 is the development of reliable and accurate tools to predict disease progression in a patient. This information can be extremely useful in distinguishing hospitalized patients at higher risk for needing UCI from patients with low severity. How SARS-CoV-2 infection will evolve is still unclear. Method(s): A novel pipeline was developed that can integrate RNA-Seq data from different databases to obtain a genetic biomarker COVID-19 severity index using an artificial intelligence algorithm. Our pipeline ensures robustness through multiple cross-validation processes in different steps. Result(s): CD93, RPS24, PSCA, and CD300E were identified as COVID-19 severity gene signatures. Furthermore, using the obtained gene signature, an effective multi-class classifier capable of discrimi-nating between control, outpatient, inpatient, and ICU COVID-19 patients was optimized, achieving an accuracy of 97.5%. Conclusion(s): In summary, during this research, a new intelligent pipeline was implemented to develop a specific gene signature that can detect the severity of patients suffering COVID-19. Our approach to clinical decision support systems achieved excellent results, even when processing unseen samples. Our system can be of great clinical utility for the strategy of planning, organizing and managing human and material resources, as well as for automatically classifying the severity of patients affected by COVID-19.Copyright © 2023 Bentham Science Publishers.

What is moral injury and how does it affect nurses?: When healthcare staff have to make care decisions that go against their values, a conflict of conscience can arise

The concepts of moral injury and moral distress came to the fore in nursing during the COVID-19 pandemic when, says mental health nurse researcher Emily Wood, healthcare professionals were being placed in difficult circumstances. They were, for example, having to make decisions about which of the sickest patients could be admitted to a limited number of intensive care beds.

Companion restrictions in the emergency department during COVID-19: physician perceptions from the Western Cape, South Africa.

OBJECTIVES: To determine emergency department (ED) physicians' perceptions regarding hospital companions being prohibited from accompanying the patient during COVID-19. DESIGN: Two qualitative datasets were combined. Data collected included voice recordings, narrative interviewing and semistructured interviews. A reflexive thematic analysis was conducted and guided by the Normalisation Process Theory. SETTING: Six hospital EDs in the Western Cape, South Africa. PARTICIPANTS: Convenience sampling was used to recruit a total of eight physicians working full time in the ED during COVID-19. RESULTS: The lack of physical companions provided an opportunity for physicians to assess and reflect on a companion's role in efficient patient care. Physicians perceived that the COVID-19 restrictions illuminated that patient companions engaged in the ED as providers contributing to patient care by providing collateral information and patient support, while simultaneously engaging as consumers detracting physicians from their priorities and patient care. These restrictions prompted the physicians to consider how they understand their patients largely through the companions. When companions became virtual, the physicians were forced to shift how they perceive their patient, which included increased empathy. CONCLUSION: The reflections of providers can feed into discussions about values within the healthcare system and can help explore the balance between medical and social safety, especially with companion restrictions still being practised in some hospitals. These perceptions illuminate various tradeoffs physicians had to consider throughout the pandemic and may be used to improve companion policies when planning for the continuation of the COVID-19 pandemic and future disease outbreaks.