Ethical Criteria for the Admission and Management of Patients in the ICU Under Conditions of Limited Medical Resources: A Shared International Proposal in View of the COVID-19 Pandemic

Critical Bias in Critical Care Devices

Critical care data contain information about the most physiologically fragile patients in the hospital, who require a significant level of monitoring. However, medical devices used for patient monitoring suffer from measurement biases that have been largely underreported. This article explores sources of bias in commonly used clinical devices, including pulse oximeters, thermometers, and sphygmomanometers. Further, it provides a framework for mitigating these biases and key principles to achieve more equitable health care delivery.

Leveraging electronic health records for data science: common pitfalls and how to avoid them

Analysis of electronic health records (EHRs) is an increasingly common approach for studying real-world patient data. Use of routinely collected data offers several advantages compared with other study designs, including reduced administrative costs, the ability to update analysis as practice patterns evolve, and larger sample sizes. Methodologically, EHR analysis is subject to distinct challenges because data are not collected for research purposes. In this Viewpoint, we elaborate on the importance of in-depth knowledge of clinical workflows and describe six potential pitfalls to be avoided when working with EHR data, drawing on examples from the literature and our experience. We propose solutions for prevention or mitigation of factors associated with each of these six pitfalls-sample selection bias, imprecise variable definitions, limitations to deployment, variable measurement frequency, subjective treatment allocation, and model overfitting. Ultimately, we hope that this Viewpoint will guide researchers to further improve the methodological robustness of EHR analysis.

Predicting the Need for Intubation among COVID-19 Patients Using Machine Learning Algorithms: A Single-Center Study

Background: Owing to the shortage of ventilators, there is a crucial demand for an objective and accurate prognosis for 2019 coronavirus disease (COVID-19) critical patients, which may necessitate a mechanical ventilator (MV). This study aimed to construct a predictive model using machine learning (ML) algorithms for frontline clinicians to better triage endangered patients and priorities who would need MV.

Methods: In this retrospective single-center study, the data of 482 COVID-19 patients from February 9, 2020, to December 20, 2020, were analyzed by several ML algorithms including, multi-layer perception (MLP), logistic regression (LR), J-48 decision tree, and Naïve Bayes (NB). First, the most important clinical variables were identified using the Chi-square test at P < 0.01. Then, by comparing the ML algorithms' performance using some evaluation criteria, including TP-Rate, FP-Rate, precision, recall, F-Score, MCC, and Kappa, the best performing one was identified.

Results: Predictive models were trained using 15 validated features, including cough, contusion, oxygen therapy, dyspnea, loss of taste, rhinorrhea, blood pressure, absolute lymphocyte count, pleural fluid, activated partial thromboplastin time, blood glucose, white cell count, cardiac diseases, length of hospitalization, and other underline diseases. The results indicated the J-48 with F-score = 0.868 and AUC = 0.892 yielded the best performance for predicting intubation requirement.

Conclusion: ML algorithms are potentials to improve traditional clinical criteria to forecast the necessity for intubation in COVID-19 in-hospital patients. Such ML-based prediction models may help physicians with optimizing the timing of intubation, better sharing of MV resources and personnel, and increase patient clinical status.

The patient safety in extracorporeal blood purification treatments of critical patients

Today, health systems are complex due to both the technological development in diagnostic and therapeutic procedures and the complexity of the patients that are increasingly older with several comorbidities. In any care setting, latent, organizational, and systematic errors can occur causing critical incident harmful for patients. Management of patients with acute kidney injury (AKI) requires a multidisciplinary approach for the diagnostic-therapeutic-rehabilitative path that can also require an extracorporeal blood purification treatment (EBPT). The complexity of these patients and EBPT require a clinical risk analysis and the introduction of protocols, procedures, operating instructions, and checklists to reduce clinical risk through promotion of the safety culture for all care providers. Caregivers must acquire a series of tools to evaluate the clinical risk in their reality to prevent incidents and customize patient safety in a proactive and reactive way. Established procedures that are made more needed by the COVID-19 pandemic can help to better manage patients in critical care area with intrinsic higher clinical risk. This review analyzes the communication and organizational aspects that need to be taken into consideration in the management of EBPT in a critical care setting by providing tools that can be used to reduce the clinical risk. This review is mostly addressed to all the caregivers involved in the EBPT in Critical Care Nephrology and in the Intensive Care Units.

Bioethics and COVID-19: Considering the Social Determinants of Health

In this paper, we focus on a novel bioethical approach concerning the ethical implications of the Social Determinants of Health (SDs) in the time of COVID-19, offering a fresh interpretation of our agency and responsibility in the current pandemic era. Our interpretation is grounded on the idea that our health basically depends on factors that go beyond our organism. In this sense, we stress the radical importance of circumstances to ethically assess an action, in the current pandemic context. Moreover, due the centrality of the SDs in our bioethical assessments-that implies that our health does not exclusively depend on our choices, behaviors, and lifestyle-we can affirm that we are not entirely responsible for our wellness or diseases. As health depends on economic, social, cultural, and environmental factors, we argue that the analysis of personal responsibility facing personal health status should receive further consideration. In this sense, following the "social connection model," we stress the importance of the concept of "shared responsibility" in collective decisions: if we make many decisions collectively, we are also collectively responsible of these decisions. Furthermore, to responsibly tackle the social inequalities that are the underlying cause of disparities in health outcomes, we propose two main strategies based on the Capability Approach: 1. empowering the individuals, especially the most vulnerable ones; and 2. designing preventive policies and interventions that provides an opportunity to address the disparities moving forward. This will help us going beyond the "individualistic medical ethics paradigm" and integrating our concept of health with social factors (e.g., the SDs), based on a more relational and interdependent anthropological thought.

Supporting Decision Making in Intensive Care: Ethical Principles for Managing Access to Care During the COVID-19 Pandemic

The pandemic from COVID-19 causes a health threat for many countries and requires an internationally coordinated response due to the high spread of the infection. The current local and international situation gives rise to logistical and ethical considerations regarding the imbalance between needs for assistance and availability of health resources in the continuation of the emergency. A shortage condition will require healthcare professionals to choose between patients who will have access to respiratory support and those who will have to continue without. The sharing of criteria for the introduction of patients to the different therapeutic paths is fundamental to prevent the onset of ethical issues. The present paper analyzes the critical issues related to the scarcity of healthcare resources and the limitation of access to intensive care with the aim of proposing ethically sustainable principles for the management of the current pandemic situation.

From Syndemic Lesson after COVID-19 Pandemic to a "Systemic Clinical Risk Management" Proposal in the Perspective of the Ethics of Job Well Done

The syndemic framework proposed by the 2021-2030 World Health Organization (WHO) action plan for patient safety and the introduction of enabling technologies in health services involve a more effective interpretation of the data to understand causation. Based on the Systemic Theory, this communication proposes the "Systemic Clinical Risk Management" (SCRM) to improve the Quality of Care and Patient Safety. This is a new Clinical Risk Management model capable of developing the ability to observe and synthesize different elements in ways that lead to in-depth interventions to achieve solutions aligned with the sustainable development of health services. In order to avoid uncontrolled decision-making related to the use of enabling technologies, we devised an internal Learning Algorithm Risk Management (LARM) level based on a Bayesian approach. Moreover, according to the ethics of Job Well Done, the SCRM, instead of giving an opinion on events that have already occurred, proposes a bioethical co-working because it suggests the best way to act from a scientific point of view.

Specific Risk Factors for Fatal Outcome in Critically Ill COVID-19 Patients: Results from a European Multicenter Study

(1) Background: The aim of our study was to identify specific risk factors for fatal outcome in critically ill COVID-19 patients. (2) Methods: Our data set consisted of 840 patients enclosed in the LEOSS registry. Using lasso regression for variable selection, a multifactorial logistic regression model was fitted to the response variable survival. Specific risk factors and their odds ratios were derived. A nomogram was developed as a graphical representation of the model. (3) Results: 14 variables were identified as independent factors contributing to the risk of death for critically ill COVID-19 patients: age (OR 1.08, CI 1.06–1.10), cardiovascular disease (OR 1.64, CI 1.06–2.55), pulmonary disease (OR 1.87, CI 1.16–3.03), baseline Statin treatment (0.54, CI 0.33–0.87), oxygen saturation (unit = 1%, OR 0.94, CI 0.92–0.96), leukocytes (unit 1000/μL, OR 1.04, CI 1.01–1.07), lymphocytes (unit 100/μL, OR 0.96, CI 0.94–0.99), platelets (unit 100,000/μL, OR 0.70, CI 0.62–0.80), procalcitonin (unit ng/mL, OR 1.11, CI 1.05–1.18), kidney failure (OR 1.68, CI 1.05–2.70), congestive heart failure (OR 2.62, CI 1.11–6.21), severe liver failure (OR 4.93, CI 1.94–12.52), and a quick SOFA score of 3 (OR 1.78, CI 1.14–2.78). The nomogram graphically displays the importance of these 14 factors for mortality. (4) Conclusions: There are risk factors that are specific to the subpopulation of critically ill COVID-19 patients.

Antibiotic resistance during and beyond COVID-19

Antibiotics underpin the 'modern medicine' that has increased life expectancy, leading to societies with sizeable vulnerable elderly populations who have suffered disproportionately during the current COVID-19 pandemic. Governments have responded by shuttering economies, limiting social interactions and refocusing healthcare. There are implications for antibiotic resistance both during and after these events. During spring 2020, COVID-19-stressed ICUs relaxed stewardship, perhaps promoting resistance. Counterpoised to this, more citizens died at home and total hospital antibiotic use declined, reducing selection pressure. Restricted travel and social distancing potentially reduced community import and transmission of resistant bacteria, though hard data are lacking. The future depends on the vaccines now being deployed. Unequivocal vaccine success should allow a swift return to normality. Vaccine failure followed by extended and successful non-pharmaceutical suppression may lead to the same point, but only after some delay, and with indefinite travel restrictions; sustainability is doubtful. Alternatively, failure of vaccines and control measures may prompt acceptance that we must live with the virus, as in the prolonged 1889-94 'influenza' (or coronavirus OC43) pandemic. Vaccine failure scenarios, particularly those accepting 'learning to live with the virus', favour increased outpatient management of non-COVID-19 infections using oral and long t ½ antibiotics. Ultimately, all models-except those envisaging societal collapse-suggest that COVID-19 will be controlled and that hospitals will revert to pre-2020 patterns with a large backlog of non-COVID-19 patients awaiting treatment. Clearing this will increase workloads, stresses, nosocomial infections, antibiotic use and resistance. New antibiotics, including cefiderocol, are part of the answer.

Died with or Died of? Development and Testing of a SARS CoV-2 Significance Score to Assess the Role of COVID-19 in the Deaths of Affected Patients

Since December 2019, a new form of coronavirus, SARS-CoV-2, has spread from China to the whole word, raising concerns regarding Coronavirus Disease 2019 (COVID-19) endangering public health and life. Over 1.5 million deaths related with COVID-19 have been recorded worldwide, with wide variations among countries affected by the pandemic and continuously growing numbers. The aim of this paper was to provide an overview of the literature cases of deaths involving COVID-19 and to evaluate the application of the COVID-19 Significance Score (CSS) in the classification of SARS CoV-2-related fatalities, comparing it with the Hamburg rating scale. The results obtained allowed us to highlight that CSS used after a complete accurate post-mortem examination, coupled to the retrieval of in vivo data, post-mortem radiology, histology and toxicology, as well as to additional required analyses (e.g., electronic microscopy) is a useful and concise tool in the assessment of the cause of death and the role played by this virus. A shared use of this scale might hopefully lower the inhomogeneities in forensic evaluation of SARS CoV-2-related fatalities.

Risk of in-hospital death associated with Covid-19 lung consolidations on chest computed tomography - A novel translational approach using a radiation oncology contour software

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Each unit percent of lung involved resulted in a 3.6 % increase in the chance of in-hospital mortality (OR 1.036, P = 0.007).

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The quantitative lung consolidation was also associated with ocurrence of major adverse hospital events (OR 1.025. P = 0.002).

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These associations between lung involvement and outcomes were statistically significant after adjusting for relevant clinical parameters.

Purpose

To determine whether the percentage of lung involvement at the initial chest computed tomography (CT) is related to the subsequent risk of in-hospital death in patients with coronavirus disease-2019 (Covid-19).

Materials and methods

Using a cohort of 154 laboratory-confirmed Covid-19 pneumonia cases that underwent chest CT between February and April 2020, we performed a volumetric analysis of the lung opacities. The impact of relative lung involvement on outcomes was evaluated using multivariate logistic regression. The primary endpoint was the in-hospital mortality rate. The secondary endpoint was major adverse hospitalization events (intensive care unit admission, use of mechanical ventilation, or death).

Results

The median age of the patients was 65 years: 50.6 % were male, and 36.4 % had a history of smoking. The median relative lung involvement was 28.8 % (interquartile range 9.5–50.3). The overall in-hospital mortality rate was 16.2 %. Thirty-six (26.3 %) patients were intubated. After adjusting for significant clinical factors, there was a 3.6 % increase in the chance of in-hospital mortality (OR 1.036; 95 % confidence interval, 1.010–1.063; P = 0.007) and a 2.5 % increase in major adverse hospital events (OR 1.025; 95 % confidence interval, 1.009–1.042; P = 0.002) per percentage unit of lung involvement. Advanced age (P = 0.013), DNR/DNI status at admission (P < 0.001) and smoking (P = 0.008) also increased in-hospital mortality. Older (P = 0.032) and male patients (P = 0.026) had an increased probability of major adverse hospitalization events.

Conclusions

Among patients hospitalized with Covid-19, more lung consolidation on chest CT increases the risk of in-hospital death, independently of confounding clinical factors.

Take-Home Messages from the COVID-19 Pandemic: Strengths and Pitfalls of the Italian National Health Service from a Medico-Legal Point of View

The World Health Organization (WHO) declared the outbreak of the Coronavirus disease-2019 (COVID-19) infection a pandemic on 11 March 2020. As of the end of October 2020, there were 50 million cases of infection and over one million deaths recorded worldwide, over 45,000 of which occurred in Italy. In Italy, the demand for intensive care over the course of this pandemic crisis has been exceptionally high, resulting in a severe imbalance between the demand for and availability of the necessary resources. This paper focuses on elements of preventive medicine and medical treatments in emergency and non-emergency situations which, based on the international scientific literature, may prove to be useful to physicians on a behavioral level and avert professional liability problems. In order to achieve this objective, we have performed a search on MEDLINE to find published articles related to the risks associated with the pandemic that contain useful suggestions and strategies for mitigating risks and protecting the safety of the population. The results have been collocated in line with these specific study areas.

Allocation of intensive care resources during an infectious disease outbreak: a rapid review to inform practice

BACKGROUND

The COVID-19 pandemic has placed sustained demand on health systems globally, and the capacity to provide critical care has been overwhelmed in some jurisdictions. It is unknown which triage criteria for allocation of resources perform best to inform health system decision-making. We sought to summarize and describe existing triage tools and ethical frameworks to aid healthcare decision-making during infectious disease outbreaks.

METHODS

We conducted a rapid review of triage criteria and ethical frameworks for the allocation of critical care resources during epidemics and pandemics. We searched Medline, EMBASE, and SCOPUS from inception to November 3, 2020. Full-text screening and data abstraction were conducted independently and in duplicate by three reviewers. Articles were included if they were primary research, an adult critical care setting, and the framework described was related to an infectious disease outbreak. We summarized each triage tool and ethical guidelines or framework including their elements and operating characteristics using descriptive statistics. We assessed the quality of each article with applicable checklists tailored to each study design.

RESULTS

From 11,539 unique citations, 697 full-text articles were reviewed and 83 articles were included. Fifty-nine described critical care triage protocols and 25 described ethical frameworks. Of these, four articles described both a protocol and ethical framework. Sixty articles described 52 unique triage criteria (29 algorithm-based, 23 point-based). Few algorithmic- or point-based triage protocols were good predictors of mortality with AUCs ranging from 0.51 (PMEWS) to 0.85 (admitting SOFA > 11). Most published triage protocols included the substantive values of duty to provide care, equity, stewardship and trust, and the procedural value of reason.

CONCLUSIONS

This review summarizes available triage protocols and ethical guidelines to provide decision-makers with data to help select and tailor triage tools. Given the uncertainty about how the COVID-19 pandemic will progress and any future pandemics, jurisdictions should prepare by selecting and adapting a triage tool that works best for their circumstances.

Negative Impact of the COVID-19 Pandemic on Admissions for Intracranial Hemorrhage

Background: The COVID-19 pandemic has seriously impacted healthcare systems worldwide. Admissions for various non-COVID-19 emergencies have significantly decreased. We sought to determine the impact of COVID-19 on admissions for intracranial hemorrhage to a German University Hospital emergency department. Methods: In a retrospective analysis of admissions to the emergency department of the University Hospital Mannheim from January to June 2020 and the corresponding time period in 2019, all patients admitted for either traumatic or non-traumatic intracranial hemorrhage were evaluated. Poisson regression was performed to analyze changes in admission rates as a function of year, epoch (COVID-19-epoch, March to April 2020 and corresponding months 2019; non-COVID-19-epoch, January to February and May to June 2019/2020) and the interaction of year and epoch (reflecting the impact of the pandemic and subsequent lockdown measures). Results: Overall, 320 patients were included in the study. During the COVID-19-epoch, admission rates for spontaneous intracranial hemorrhage decreased significantly by 42.1% (RR 0.579, p = 0.002, 95% confidence interval 0.410-0.818). Likewise, admission rates for traumatic intracranial hemorrhage decreased significantly by 53.7% [RR = 0.463, p < 0.001, 95% confidence interval (CI) 0.358-0.599]. Conclusion: The decrease of spontaneous intracranial hemorrhages may be a consequence of underutilization of the healthcare system whereas decreasing rates of traumatic intracranial hemorrhage admissions may predominantly reflect a decrease in true incidence rates due to lockdown measures with restricted mobility. Raising patient awareness to seek emergency healthcare for acute neurological deficits during lockdown measures is important to ensure appropriate emergency care for patients with intracranial hemorrhage.