Accuracy of the Sequential Organ Failure Assessment Score for In-Hospital Mortality by Race and Relevance to Crisis Standards of Care

Age and Saving Lives in Crisis Standards of Care: A Multicenter Cohort Study of Triage Score Prognostic Accuracy

IMPORTANCE

Current protocols to triage life support use scores that are biased and inaccurate.

OBJECTIVES

To determine if adding age to triage protocols used in disaster scenarios improves the identification of critically ill patients likely to survive.

DESIGN, SETTING, AND PARTICIPANTS

Observational cohort study from March 1, 2020, to March 1, 2022, at 22 hospitals in three networks, divided into derivation (12 hospitals) and validation cohorts (ten hospitals). Participants were critically ill adults (90% COVID-19 positive) who would have needed life support during an overwhelming case surge. Life support was defined as vasoactive medications for shock, invasive or noninvasive mechanical ventilation, or oxygen therapy with Pao2/Fio2 less than 200.

MAIN OUTCOMES AND MEASURES

The primary outcome was death in the intensive care unit. We fit logistic regression models using a modified Sequential Organ Failure Assessment (SOFA) score with and without age in the derivation cohort and assessed predictive performance in the validation cohort using area under the receiver operating characteristic curves (AUCs) and compared observed and predicted mortality.

RESULTS

The final analysis contained 7,660 patients with 16,711 life-support episodes. In the validation cohort, the AUC for age plus SOFA was significantly higher than the AUC for SOFA alone (0.66 vs. 0.54; p < 0.001). SOFA score substantially overpredicted mortality (13% predicted vs. 5% observed) for younger patients (< 40 yr) and underestimated mortality (14% predicted vs. 31% observed) for older patients (> 80 yr). In contrast, age plus SOFA had good calibration overall and across age groups. The addition of age improved but did not eliminate differences between observed and predicted mortality across racial-ethnic groups.

CONCLUSIONS AND RELEVANCE

Age-inclusive triage better identifies ICU survivors than SOFA alone and is more equitable. Incorporating age into prioritization algorithms could save more lives in a crisis scenario.

Real-world Multi-institutional Data From the Midwest Pediatric Surgery Consortium (MWPSC) to Assess the Effect of Delayed Kasai Procedure on Biliary Drainage in Patients With Biliary Atresia

PURPOSE

Early Kasai portoenterostomy (KPE) for infants with biliary atresia (BA) increases the chance of transplant-free survival (TFS). However, early timing of KPE is not consistently achieved in the United States. Clearance of jaundice at three months is predictive of TFS. Among a cohort of patients with BA, we investigated institutional variability in the initiation of hyperbilirubinemia evaluation and operative timing to identify factors associated with successful jaundice clearance.

METHODS

A multi-institutional, retrospective study was performed at eleven U.S. tertiary children's hospitals. Infants diagnosed with BA between 10/1/2015-10/1/2020 were identified. Age at initiation of diagnostic workup and age at KPE were collected. Adjusted multivariable logistic regression was used to determine factors associated with direct bilirubin normalization at three months following KPE.

RESULTS

In 161 infants, the median age at initiation of jaundice evaluation was 35 days (IQR 8-60). Among 148 patients who underwent KPE, median age at surgery was 53 days (IQR 37.3-67.5). Each 10-day increase in age at KPE was associated with a 18.8 % decrease in odds of normalizing bilirubin at three months (OR 0.81, 95 % CI 0.66-0.99), with infants who underwent KPE ≤50 days significantly more likely to normalize bilirubin (OR 2.6, CI 1.1-6.1) compared to KPE >50 days. There was significant variation among institutions in the time from initiation of workup to KPE (range 0-24.5 days, p = 0.02) and the odds of patients normalizing direct bilirubin at three months (range 0.04-0.89, p = 0.044).

CONCLUSION

Our results confirmed that increasing age at KPE decreases the odds of clearing bilirubin at three months post-KPE. We identified significant institutional variability in the time from workup to KPE that may have impacted the likelihood of successful biliary drainage.

LEVEL OF EVIDENCE

IV (Well-designed case-control or cohort study).

Covert Critical Illness Encephalopathy: Impairments That Escape Detection by Guideline Recommended, Protocolized Assessments

OBJECTIVES

To determine whether cognitive impairments of important severity escape detection by guideline-recommended delirium and encephalopathy screening instruments in critically ill patients.

DESIGN

Cross-sectional study with random patient sampling.

SETTING

ICUs of a large referral hospital with protocols implementing the Society of Critical Care Medicine's ICU Liberation Bundle.

PATIENTS

Patients with a heterogeneous mix of primary organ system conditions leading to critical illness and with no abnormal findings scored in Confusion Assessment Method for the ICU (CAM-ICU) screening, Richmond Agitation-Sedation Scale (RASS) 0, and Glasgow Coma Scale (GCS) 15, indicating they were alert, fully oriented, and following commands with no delirium or findings to indicate subsyndromal delirium.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We evaluated 50 patients, age 54 ± 16 years. Trained critical care nurses assessed patients at regular intervals using the CAM-ICU, RASS, and GCS per a protocol. We performed a battery of psychometric cognitive tests using the NIH Toolbox. Executive functions linked to attention and inhibitory control, and processing speed were 1.5 sd below population norm (both p < 0.01). Working memory and cognitive flexibility were also significantly, but less severely, impaired ( p < 0.01 and p = 0.026). Nearly two-thirds (64%) of the patients scored at least 1.5 sd worse than demographically adjusted means in two or more cognitive domains, a commonly used diagnostic criterion for cognitive impairment.

CONCLUSIONS

Substantial cognitive impairment is present among critically ill patients with no abnormalities detected by standard delirium and encephalopathy assessments.

Minnesota Hospitals' Plans for Implementing Statewide Guidance on Allocation of Scarce Critical Care Resources During the COVID-19 Pandemic

Objectives

To assess hospitals' plans for implementing Minnesota's statewide guidance for allocating scarce critical care resources during the COVID-19 pandemic.

Patients and Methods

Individuals from 23 hospitals across Minnesota were invited to complete a 25-item survey between July 20, 2020, and September 18, 2020 to understand how hospitals in the state intended to operationalize statewide clinical triage instructions for scarce resources (including mechanical ventilation) and written ethics guidance on the allocation of critical care resources in the event crisis standards of care triggered triage.

Results

Of individuals invited from 23 hospitals, 14 hospitals completed the survey (60.9% institutional response rate) and described plans for triage at their respective hospitals. Planned triage team composition and size varied. Hospitals' plans for which individuals should assign a triage score (reflecting patients' illness severity) also differed markedly. Most respondents described plans for staff training to address potential bias in triage.

Conclusion

Despite explicit state guidance to encourage consistency across hospitals, we found considerable heterogeneity in implementation plans. Plans diverged from Minnesota's written ethics guidance on whether to consider race during triage to help mitigate health disparities. Inconsistencies between the state's 2 guidance documents could explain some of these differences. Collaboration between hospitals and committees developing statewide guidance may help identify barriers to effective operationalization. Ongoing review of published guidance and hospital plans can identify issues of clarity and consistency and promote equitable triage.

A Clinician's Guide to Understanding Bias in Critical Clinical Prediction Models

This narrative review focuses on the role of clinical prediction models in supporting informed decision-making in critical care, emphasizing their 2 forms: traditional scores and artificial intelligence (AI)-based models. Acknowledging the potential for both types to embed biases, the authors underscore the importance of critical appraisal to increase our trust in models. The authors outline recommendations and critical care examples to manage risk of bias in AI models. The authors advocate for enhanced interdisciplinary training for clinicians, who are encouraged to explore various resources (books, journals, news Web sites, and social media) and events (Datathons) to deepen their understanding of risk of bias.

Pruning the Way to Reliable Policies: A Multi-Objective Deep Q-Learning Approach to Critical Care

Medical treatments often involve a sequence of decisions, each informed by previous outcomes. This process closely aligns with reinforcement learning (RL), a framework for optimizing sequential decisions to maximize cumulative rewards under unknown dynamics. While RL shows promise for creating data-driven treatment plans, its application in medical contexts is challenging due to the frequent need to use sparse rewards, primarily defined based on mortality outcomes. This sparsity can reduce the stability of offline estimates, posing a significant hurdle in fully utilizing RL for medical decision-making. We introduce a deep Q-learning approach to obtain more reliable critical care policies by integrating relevant but noisy frequently measured biomarker signals into the reward specification without compromising the optimization of the main outcome. Our method prunes the action space based on all available rewards before training a final model on the sparse main reward. This approach minimizes potential distortions of the main objective while extracting valuable information from intermediate signals to guide learning. We evaluate our method in off-policy and offline settings using simulated environments and real health records from intensive care units. Our empirical results demonstrate that our method outperforms common offline RL methods such as conservative Q-learning and batch-constrained deep Q-learning. By disentangling sparse rewards and frequently measured reward proxies through action pruning, our work represents a step towards developing reliable policies that effectively harness the wealth of available information in data-intensive critical care environments.

Social Disparities and Critical Illness during the Coronavirus Disease 2019 Pandemic: A Narrative Review

The coronavirus disease 2019 (COVID-19) pandemic raised new considerations for social disparities in critical illness including hospital capacity and access to personal protective equipment, access to evolving therapies, vaccinations, virtual care, and restrictions on family visitation. This narrative review aims to explore evidence about racial/ethnic and socioeconomic differences in critical illness during the COVID-19 pandemic, factors driving those differences and promising solutions for mitigating inequities in the future. We apply a patient journey framework to identify social disparities at various stages before, during, and after patient interactions with critical care services and discuss recommendations for policy and practice.

Investigating ethical tradeoffs in crisis standards of care through simulation of ventilator allocation protocols

INTRODUCTION

Arguments over the appropriate Crisis Standards of Care (CSC) for public health emergencies often assume that there is a tradeoff between saving the most lives, saving the most life-years, and preventing racial disparities. However, these assumptions have rarely been explored empirically. To quantitatively characterize possible ethical tradeoffs, we aimed to simulate the implementation of five proposed CSC protocols for rationing ventilators in the context of the COVID-19 pandemic.

METHODS

A Monte Carlo simulation was used to estimate the number of lives saved and life-years saved by implementing clinical acuity-, comorbidity- and age-based CSC protocols under different shortage conditions. This model was populated with patient data from 3707 adult admissions requiring ventilator support in a New York hospital system between April 2020 and May 2021. To estimate lives and life-years saved by each protocol, we determined survival to discharge and estimated remaining life expectancy for each admission.

RESULTS

The simulation demonstrated stronger performance for age-sensitive protocols. For a capacity of 1 bed per 2 patients, ranking by age bands saves approximately 29 lives and 3400 life-years per thousand patients. Proposed protocols from New York and Maryland which allocated without considering age saved the fewest lives (~13.2 and 8.5 lives) and life-years (~416 and 420 years). Unlike other protocols, the New York and Maryland algorithms did not generate significant disparities in lives saved and life-years saved between White non-Hispanic, Black non-Hispanic, and Hispanic sub-populations. For all protocols, we observed a positive correlation between lives saved and life-years saved, but also between lives saved overall and inequality in the number of lives saved in different race and ethnicity sub-populations.

CONCLUSION

While there is significant variance in the number of lives saved and life-years saved, we did not find a tradeoff between saving the most lives and saving the most life-years. Moreover, concerns about racial discrimination in triage protocols require thinking carefully about the tradeoff between enforcing equality of survival rates and maximizing the lives saved in each sub-population.

A Common Longitudinal Intensive Care Unit data Format (CLIF) to enable multi-institutional federated critical illness research

Background

Critical illness, or acute organ failure requiring life support, threatens over five million American lives annually. Electronic health record (EHR) data are a source of granular information that could generate crucial insights into the nature and optimal treatment of critical illness. However, data management, security, and standardization are barriers to large-scale critical illness EHR studies.

Methods

A consortium of critical care physicians and data scientists from eight US healthcare systems developed the Common Longitudinal Intensive Care Unit (ICU) data Format (CLIF), an open-source database format that harmonizes a minimum set of ICU Data Elements for use in critical illness research. We created a pipeline to process adult ICU EHR data at each site. After development and iteration, we conducted two proof-of-concept studies with a federated research architecture: 1) an external validation of an in-hospital mortality prediction model for critically ill patients and 2) an assessment of 72-hour temperature trajectories and their association with mechanical ventilation and in-hospital mortality using group-based trajectory models.

Results

We converted longitudinal data from 94,356 critically ill patients treated in 2020-2021 (mean age 60.6 years [standard deviation 17.2], 30% Black, 7% Hispanic, 45% female) across 8 health systems and 33 hospitals into the CLIF format, The in-hospital mortality prediction model performed well in the health system where it was derived (0.81 AUC, 0.06 Brier score). Performance across CLIF consortium sites varied (AUCs: 0.74-0.83, Brier scores: 0.06-0.01), and demonstrated some degradation in predictive capability. Temperature trajectories were similar across health systems. Hypothermic and hyperthermic-slow-resolver patients consistently had the highest mortality.

Conclusions

CLIF facilitates efficient, rigorous, and reproducible critical care research. Our federated case studies showcase CLIF's potential for disease sub-phenotyping and clinical decision-support evaluation. Future applications include pragmatic EHR-based trials, target trial emulations, foundational multi-modal AI models of critical illness, and real-time critical care quality dashboards.

SOFA score performs worse than age for predicting mortality in patients with COVID-19

The use of the Sequential Organ Failure Assessment (SOFA) score, originally developed to describe disease morbidity, is commonly used to predict in-hospital mortality. During the COVID-19 pandemic, many protocols for crisis standards of care used the SOFA score to select patients to be deprioritized due to a low likelihood of survival. A prior study found that age outperformed the SOFA score for mortality prediction in patients with COVID-19, but was limited to a small cohort of intensive care unit (ICU) patients and did not address whether their findings were unique to patients with COVID-19. Moreover, it is not known how well these measures perform across races. In this retrospective study, we compare the performance of age and SOFA score in predicting in-hospital mortality across two cohorts: a cohort of 2,648 consecutive adult patients diagnosed with COVID-19 who were admitted to a large academic health system in the northeastern United States over a 4-month period in 2020 and a cohort of 75,601 patients admitted to one of 335 ICUs in the eICU database between 2014 and 2015. We used age and the maximum SOFA score as predictor variables in separate univariate logistic regression models for in-hospital mortality and calculated area under the receiver operator characteristic curves (AU-ROCs) and area under precision-recall curves (AU-PRCs) for each predictor in both cohorts. Among the COVID-19 cohort, age (AU-ROC 0.795, 95% CI 0.762, 0.828) had a significantly better discrimination than SOFA score (AU-ROC 0.679, 95% CI 0.638, 0.721) for mortality prediction. Conversely, age (AU-ROC 0.628 95% CI 0.608, 0.628) underperformed compared to SOFA score (AU-ROC 0.735, 95% CI 0.726, 0.745) in non-COVID-19 ICU patients in the eICU database. There was no difference between Black and White COVID-19 patients in performance of either age or SOFA Score. Our findings bring into question the utility of SOFA score-based resource allocation in COVID-19 crisis standards of care.

The Impact of Health Care Algorithms on Racial and Ethnic Disparities : A Systematic Review

BACKGROUND

There is increasing concern for the potential impact of health care algorithms on racial and ethnic disparities.

PURPOSE

To examine the evidence on how health care algorithms and associated mitigation strategies affect racial and ethnic disparities.

DATA SOURCES

Several databases were searched for relevant studies published from 1 January 2011 to 30 September 2023.

STUDY SELECTION

Using predefined criteria and dual review, studies were screened and selected to determine: 1) the effect of algorithms on racial and ethnic disparities in health and health care outcomes and 2) the effect of strategies or approaches to mitigate racial and ethnic bias in the development, validation, dissemination, and implementation of algorithms.

DATA EXTRACTION

Outcomes of interest (that is, access to health care, quality of care, and health outcomes) were extracted with risk-of-bias assessment using the ROBINS-I (Risk Of Bias In Non-randomised Studies - of Interventions) tool and adapted CARE-CPM (Critical Appraisal for Racial and Ethnic Equity in Clinical Prediction Models) equity extension.

DATA SYNTHESIS

Sixty-three studies (51 modeling, 4 retrospective, 2 prospective, 5 prepost studies, and 1 randomized controlled trial) were included. Heterogenous evidence on algorithms was found to: a) reduce disparities (for example, the revised kidney allocation system), b) perpetuate or exacerbate disparities (for example, severity-of-illness scores applied to critical care resource allocation), and/or c) have no statistically significant effect on select outcomes (for example, the HEART Pathway [history, electrocardiogram, age, risk factors, and troponin]). To mitigate disparities, 7 strategies were identified: removing an input variable, replacing a variable, adding race, adding a non-race-based variable, changing the racial and ethnic composition of the population used in model development, creating separate thresholds for subpopulations, and modifying algorithmic analytic techniques.

LIMITATION

Results are mostly based on modeling studies and may be highly context-specific.

CONCLUSION

Algorithms can mitigate, perpetuate, and exacerbate racial and ethnic disparities, regardless of the explicit use of race and ethnicity, but evidence is heterogeneous. Intentionality and implementation of the algorithm can impact the effect on disparities, and there may be tradeoffs in outcomes.

PRIMARY FUNDING SOURCE

Agency for Healthcare Quality and Research.

Investigating Ethical Tradeoffs in Crisis Standards of Care through Simulation of Ventilator Allocation Protocols

Introduction

Arguments over the appropriate Crisis Standards of Care (CSC) for public health emergencies often assume that there is a tradeoff between saving the most lives, saving the most life-years, and preventing racial disparities. However, these assumptions have rarely been explored empirically. To quantitatively characterize possible ethical tradeoffs, we aimed to simulate the implementation of five proposed CSC protocols for rationing ventilators in the context of the COVID-19 pandemic.

Methods

A Monte Carlo simulation was used to estimate the number of lives saved and life-years saved by implementing clinical acuity-, comorbidity- and age-based CSC protocols under different shortage conditions. This model was populated with patient data from 3707 adult admissions requiring ventilator support in a New York hospital system between April 2020 and May 2021. To estimate lives and life-years saved by each protocol, we determined survival to discharge and estimated remaining life expectancy for each admission.

Results

The simulation demonstrated stronger performance for age- and comorbidity-sensitive protocols. For a capacity of 1 bed per 2 patients, ranking by age bands saves approximately 28.7 lives and 3408 life-years per thousand patients, while ranking by Sequential Organ Failure Assessment (SOFA) bands saved the fewest lives (13.2) and life-years (416). For all protocols, we observed a positive correlation between lives saved and life-years saved. For all protocols except lottery and the banded SOFA, significant disparities in lives saved and life-years saved were noted between White non-Hispanic, Black non-Hispanic, and Hispanic sub-populations.

Conclusion

While there is significant variance in the number of lives saved and life-years saved, we did not find a tradeoff between saving the most lives and saving the most life-years. Moreover, concerns about racial discrimination in triage protocols require thinking carefully about the tradeoff between enforcing equality of survival rates and maximizing the lives saved in each sub-population.

Do-Not-Resuscitate Orders by COVID-19 Status Throughout the First Year of the COVID-19 Pandemic

BACKGROUND

At the beginning of the COVID-19 pandemic, whether performing CPR on patients with COVID-19 would be effective or increase COVID-19 transmission to health care workers was unclear.

RESEARCH QUESTION

Did the prevalence of do-not-resuscitate (DNR) orders by COVID-19 status change over the first year of the pandemic as risks such as COVID-19 transmission to health care workers improved?

STUDY DESIGN AND METHODS

This cross-sectional study assessed DNR orders for all adult patients admitted to ICUs at two academic medical centers in Chicago, IL, between April 2020 and April 2021. DNR orders by COVID-19 status were assessed using risk-adjusted mixed-effects logistic regression and propensity score matching by patient severity of illness.

RESULTS

The study population of 3,070 critically ill patients were 46% Black, 53% male, with median age (interquartile range [IQR]) 63 (50-73) years. Eighteen percent were COVID-19 positive and 27% had a DNR order. Black and Latinx patients had higher absolute rates of DNR orders than White patients (30% vs 29% vs 23%; P = .006). After adjustment for patient characteristics, illness severity, and hospital location, DNR orders were more likely in patients with COVID-19 in the nonpropensity score-matched (n = 3,070; aOR, 2.01; 95% CI, 1.64-2.38) and propensity score-matched (n = 1,118; aOR, 1.91; 95% CI, 1.45-2.52) cohorts. The prevalence of DNR orders remained higher for patients with COVID-19 than patients without COVID-19 during all months of the study period (difference in prevalence over time, P = .751).

INTERPRETATION

In this multihospital study, DNR orders remained persistently higher for patients with COVID-19 vs patients without COVID-19 with similar severity of illness during the first year of the pandemic. The specific reasons why DNR orders remained persistently elevated for patients with COVID-19 should be assessed in future studies, because these changes may continue to affect COVID-19 patient care and outcomes.

Clinical data mining: challenges, opportunities, and recommendations for translational applications

Clinical data mining of predictive models offers significant advantages for re-evaluating and leveraging large amounts of complex clinical real-world data and experimental comparison data for tasks such as risk stratification, diagnosis, classification, and survival prediction. However, its translational application is still limited. One challenge is that the proposed clinical requirements and data mining are not synchronized. Additionally, the exotic predictions of data mining are difficult to apply directly in local medical institutions. Hence, it is necessary to incisively review the translational application of clinical data mining, providing an analytical workflow for developing and validating prediction models to ensure the scientific validity of analytic workflows in response to clinical questions. This review systematically revisits the purpose, process, and principles of clinical data mining and discusses the key causes contributing to the detachment from practice and the misuse of model verification in developing predictive models for research. Based on this, we propose a niche-targeting framework of four principles: Clinical Contextual, Subgroup-Oriented, Confounder- and False Positive-Controlled (CSCF), to provide guidance for clinical data mining prior to the model's development in clinical settings. Eventually, it is hoped that this review can help guide future research and develop personalized predictive models to achieve the goal of discovering subgroups with varied remedial benefits or risks and ensuring that precision medicine can deliver its full potential.

Defining the Time-limited Trial for Patients with Critical Illness: An Official American Thoracic Society Workshop Report

In critical care, the specific, structured approach to patient care known as a "time-limited trial" has been promoted in the literature to help patients, surrogate decision makers, and clinicians navigate consequential decisions about life-sustaining therapy in the face of uncertainty. Despite promotion of the time-limited trial approach, a lack of consensus about its definition and essential elements prevents optimal clinical use and rigorous evaluation of its impact. The objectives of this American Thoracic Society Workshop Committee were to establish a consensus definition of a time-limited trial in critical care, identify the essential elements for conducting a time-limited trial, and prioritize directions for future work. We achieved these objectives through a structured search of the literature, a modified Delphi process with 100 interdisciplinary and interprofessional stakeholders, and iterative committee discussions. We conclude that a time-limited trial for patients with critical illness is a collaborative plan among clinicians and a patient and/or their surrogate decision makers to use life-sustaining therapy for a defined duration, after which the patient's response to therapy informs the decision to continue care directed toward recovery, transition to care focused exclusively on comfort, or extend the trial's duration. The plan's 16 essential elements follow four sequential phases: consider, plan, support, and reassess. We acknowledge considerable gaps in evidence about the impact of time-limited trials and highlight a concern that if inadequately implemented, time-limited trials may perpetuate unintended harm. Future work is needed to better implement this defined, specific approach to care in practice through a person-centered equity lens and to evaluate its impact on patients, surrogates, and clinicians.

Evaluating Prognostic Bias of Critical Illness Severity Scores Based on Age, Sex, and Primary Language in the United States: A Retrospective Multicenter Study

OBJECTIVES

Although illness severity scoring systems are widely used to support clinical decision-making and assess ICU performance, their potential bias across different age, sex, and primary language groups has not been well-studied.

DESIGN SETTING AND PATIENTS

We aimed to identify potential bias of Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation (APACHE) IVa scores via large ICU databases.

SETTING/PATIENTS

This multicenter, retrospective study was conducted using data from the Medical Information Mart for Intensive Care (MIMIC) and eICU Collaborative Research Database. SOFA and APACHE IVa scores were obtained from ICU admission. Hospital mortality was the primary outcome. Discrimination (area under receiver operating characteristic [AUROC] curve) and calibration (standardized mortality ratio [SMR]) were assessed for all subgroups.

INTERVENTIONS

Not applicable.

MEASUREMENTS AND MAIN RESULTS

A total of 196,310 patient encounters were studied. Discrimination for both scores was worse in older patients compared with younger patients and female patients rather than male patients. In MIMIC, discrimination of SOFA in non-English primary language speakers patients was worse than that of English speakers (AUROC 0.726 vs. 0.783, p < 0.0001). Evaluating calibration via SMR showed statistically significant underestimations of mortality when compared with overall cohort in the oldest patients for both SOFA and APACHE IVa, female patients (1.09) for SOFA, and non-English primary language patients (1.38) for SOFA in MIMIC.

CONCLUSIONS

Differences in discrimination and calibration of two scores across varying age, sex, and primary language groups suggest illness severity scores are prone to bias in mortality predictions. Caution must be taken when using them for quality benchmarking and decision-making among diverse real-world populations.

Race and ethnicity in the COVID-19 Critical Care Consortium: demographics, treatments, and outcomes, an international observational registry study

BACKGROUND

Improving access to healthcare for ethnic minorities is a public health priority in many countries, yet little is known about how to incorporate information on race, ethnicity, and related social determinants of health into large international studies. Most studies of differences in treatments and outcomes of COVID-19 associated with race and ethnicity are from single cities or countries.

METHODS

We present the breadth of race and ethnicity reported for patients in the COVID-19 Critical Care Consortium, an international observational cohort study from 380 sites across 32 countries. Patients from the United States, Australia, and South Africa were the focus of an analysis of treatments and in-hospital mortality stratified by race and ethnicity. Inclusion criteria were admission to intensive care for acute COVID-19 between January 14th, 2020, and February 15, 2022. Measurements included demographics, comorbidities, disease severity scores, treatments for organ failure, and in-hospital mortality.

RESULTS

Seven thousand three hundred ninety-four adults met the inclusion criteria. There was a wide variety of race and ethnicity designations. In the US, American Indian or Alaska Natives frequently received dialysis and mechanical ventilation and had the highest mortality. In Australia, organ failure scores were highest for Aboriginal/First Nations persons. The South Africa cohort ethnicities were predominantly Black African (50%) and Coloured* (28%). All patients in the South Africa cohort required mechanical ventilation. Mortality was highest for South Africa (68%), lowest for Australia (15%), and 30% in the US.

CONCLUSIONS

Disease severity was higher for Indigenous ethnicity groups in the US and Australia than for other ethnicities. Race and ethnicity groups with longstanding healthcare disparities were found to have high acuity from COVID-19 and high mortality. Because there is no global system of race and ethnicity classification, researchers designing case report forms for international studies should consider including related information, such as socioeconomic status or migration background. *Note: "Coloured" is an official, contemporary government census category of South Africa and is a term of self-identification of race and ethnicity of many citizens of South Africa.

Simulation of New York City's Ventilator Allocation Guideline During the Spring 2020 COVID-19 Surge

Importance

The spring 2020 surge of COVID-19 unprecedentedly strained ventilator supply in New York City, with many hospitals nearly exhausting available ventilators and subsequently seriously considering enacting crisis standards of care and implementing New York State Ventilator Allocation Guidelines (NYVAG). However, there is little evidence as to how NYVAG would perform if implemented.

Objectives

To evaluate the performance and potential improvement of NYVAG during a surge of patients with respect to the length of rationing, overall mortality, and worsening health disparities.

Design, Setting, and Participants

This cohort study included intubated patients in a single health system in New York City from March through July 2020. A total of 20 000 simulations were conducted of ventilator triage (10 000 following NYVAG and 10 000 following a proposed improved NYVAG) during a crisis period, defined as the point at which the prepandemic ventilator supply was 95% utilized.

Exposures

The NYVAG protocol for triage ventilators.

Main Outcomes and Measures

Comparison of observed survival rates with simulations of scenarios requiring NYVAG ventilator rationing.

Results

The total cohort included 1671 patients; of these, 674 intubated patients (mean [SD] age, 63.7 [13.8] years; 465 male [69.9%]) were included in the crisis period, with 571 (84.7%) testing positive for COVID-19. Simulated ventilator rationing occurred for 163.9 patients over 15.0 days, 44.4% (95% CI, 38.3%-50.0%) of whom would have survived if provided a ventilator while only 34.8% (95% CI, 28.5%-40.0%) of those newly intubated patients receiving a reallocated ventilator survived. While triage categorization at the time of intubation exhibited partial prognostic differentiation, 94.8% of all ventilator rationing occurred after a time trial. Within this subset, 43.1% were intubated for 7 or more days with a favorable SOFA score that had not improved. An estimated 60.6% of these patients would have survived if sustained on a ventilator. Revising triage subcategorization, proposed improved NYVAG, would have improved this alarming ventilator allocation inefficiency (25.3% [95% CI, 22.1%-28.4%] of those selected for ventilator rationing would have survived if provided a ventilator). NYVAG ventilator rationing did not exacerbate existing health disparities.

Conclusions and Relevance

In this cohort study of intubated patients experiencing simulated ventilator rationing during the apex of the New York City COVID-19 2020 surge, NYVAG diverted ventilators from patients with a higher chance of survival to those with a lower chance of survival. Future efforts should be focused on triage subcategorization, which improved this triage inefficiency, and ventilator rationing after a time trial, when most ventilator rationing occurred.

Linking Sepsis with chronic arterial hypertension, diabetes mellitus, and socioeconomic factors in the United States: A scoping review

RATIONALE

Sepsis is a syndrome of life-threatening organ dysfunction caused by a dysregulated host immune response to infection. Social risk factors including location and poverty are associated with sepsis-related disparities. Understanding the social and biological phenotypes linked with the incidence of sepsis is warranted to identify the most at-risk populations. We aim to examine how factors in disadvantage influence health disparities related to sepsis.

METHODS

A scoping review was performed for English-language articles published in the United States from 1990 to 2022 on PubMed, Web of Science, and Scopus. Of the 2064 articles found, 139 met eligibility criteria and were included for review.

RESULTS

There is consistency across the literature of disproportionately higher rates of sepsis incidence, mortality, readmissions, and associated complications, in neighborhoods with socioeconomic disadvantage and significant poverty. Chronic arterial hypertension and diabetes mellitus also occur more frequently in the same geographic distribution as sepsis, suggesting a potential shared pathophysiology.

CONCLUSIONS

The distribution of chronic arterial hypertension, diabetes mellitus, social risk factors associated with socioeconomic disadvantage, and sepsis incidence, are clustered in specific geographical areas and linked by endothelial dysfunction. Such population factors can be utilized to create equitable interventions aimed at mitigating sepsis incidence and sepsis-related disparities.

Investigating the Utility of the SOFA Score and Creating a Modified SOFA Score for Predicting Mortality in the Intensive Care Units in a Tertiary Hospital in Jordan

Background

The utility of the Sequential Organ Failure Assessment (SOFA) score in predicting mortality in the intensive care unit (ICU) has been demonstrated before, but serial testing in various settings is required to validate and improve the score. This study examined the utility of the SOFA score in predicting mortality in Jordanian ICU patients and aimed to find a modified score that required fewer laboratory tests.

Methods

A prospective observational study was conducted at Jordan University Hospital (JUH). All adult patients admitted to JUH ICUs between June and December 2020 were included in the study. SOFA scores were measured daily during the whole ICU stay. A modified SOFA score (mSOFA) was constructed from the available laboratory, clinical, and demographic data. The performance of the SOFA, mSOFA, qSOFA, and SIRS in predicting ICU mortality was assessed using the area under the receiver operating characteristic curve (AUROC).

Results

194 patients were followed up. SOFA score (mean ± SD) at admission was significantly higher in non-survivors (7.5 ± 3.9) compared to survivors (2.4 ± 2.2) and performed the best in predicting ICU mortality (AUROC = 0.8756, 95% CI: 0.8117-0.9395) compared to qSOFA (AUROC = 0.746, 95% CI: 0.655-0.836) and SIRS (AUROC = 0.533, 95% CI: 0.425-0.641). The constructed mSOFA included points for the hepatic and CNS SOFA scores, in addition to one point each for the presence of chronic kidney disease or the use of breathing support; it performed as well as the SOFA score in this cohort or better than the SOFA score in a subgroup of patients with heart disease.

Conclusion

SOFA score was a good predictor of mortality in a Jordanian ICU population and better than qSOFA, while SIRS could not predict mortality. Furthermore, the proposed mSOFA score which employed fewer laboratory tests could be used after validation from larger studies.

Disparities in Unilateral Do Not Resuscitate Order Use During the COVID-19 Pandemic

OBJECTIVES

A unilateral do-not-resuscitate (UDNR) order is a do-not-resuscitate order placed using clinician judgment which does not require consent from a patient or surrogate. This study assessed how UDNR orders were used during the COVID-19 pandemic.

DESIGN

We analyzed a retrospective cross-sectional study of UDNR use at two academic medical centers between April 2020 and April 2021.

SETTING

Two academic medical centers in the Chicago metropolitan area.

PATIENTS

Patients admitted to an ICU between April 2020 and April 2021 who received vasopressor or inotropic medications to select for patients with high severity of illness.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The 1,473 patients meeting inclusion criteria were 53% male, median age 64 (interquartile range, 54-73), and 38% died during admission or were discharged to hospice. Clinicians placed do not resuscitate orders for 41% of patients ( n = 604/1,473) and UDNR orders for 3% of patients ( n = 51/1,473). The absolute rate of UDNR orders was higher for patients who were primary Spanish speaking (10% Spanish vs 3% English; p ≤ 0.0001), were Hispanic or Latinx (7% Hispanic/Latinx vs 3% Black vs 2% White; p = 0.003), positive for COVID-19 (9% vs 3%; p ≤ 0.0001), or were intubated (5% vs 1%; p = 0.001). In the base multivariable logistic regression model including age, race/ethnicity, primary language spoken, and hospital location, Black race (adjusted odds ratio [aOR], 2.5; 95% CI, 1.3-4.9) and primary Spanish language (aOR, 4.4; 95% CI, 2.1-9.4) had higher odds of UDNR. After adjusting the base model for severity of illness, primary Spanish language remained associated with higher odds of UDNR order (aOR, 2.8; 95% CI, 1.7-4.7).

CONCLUSIONS

In this multihospital study, UDNR orders were used more often for primary Spanish-speaking patients during the COVID-19 pandemic, which may be related to communication barriers Spanish-speaking patients and families experience. Further study is needed to assess UDNR use across hospitals and enact interventions to improve potential disparities.

Triage Procedures for Critical Care Resource Allocation During Scarcity

Importance

During the COVID-19 pandemic, many US states issued or revised pandemic preparedness plans guiding allocation of critical care resources during crises. State plans vary in the factors used to triage patients and have faced criticism from advocacy groups due to the potential for discrimination.

Objective

To analyze the role of comorbidities and long-term prognosis in state triage procedures.

Design, Setting, and Participants

This cross-sectional study used data gathered from parallel internet searches for state-endorsed pandemic preparedness plans for the 50 US states, District of Columbia, and Puerto Rico (hereafter referred to as states), which were conducted between November 25, 2021, and June 16, 2023. Plans available on June 16, 2023, that provided step-by-step instructions for triaging critically ill patients were categorized for use of comorbidities and prognostication.

Main Outcomes and Measures

Prevalence and contents of lists of comorbidities and their stated function in triage and instructions to predict duration of postdischarge survival.

Results

Overall, 32 state-promulgated pandemic preparedness plans included triage procedures specific enough to guide triage in clinical practice. Twenty of these (63%) included lists of comorbidities that excluded (11 of 20 [55%]) or deprioritized (8 of 20 [40%]) patients during triage; one state's list was formulated to resolve ties between patients with equal triage scores. Most states with triage procedures (21 of 32 [66%]) considered predicted survival beyond hospital discharge. These states proposed different prognostic time horizons; 15 of 21 (71%) were numeric (ranging from 6 months to 5 years after hospital discharge), with the remaining 6 (29%) using descriptive terms, such as long-term.

Conclusions and Relevance

In this cross-sectional study of state-promulgated critical care triage policies, most plans restricted access to scarce critical care resources for patients with listed comorbidities and/or for patients with less-than-average expected postdischarge survival. This analysis raises concerns about access to care during a public health crisis for populations with high burdens of chronic illness, such as individuals with disabilities and minoritized racial and ethnic groups.

Bias in artificial intelligence algorithms and recommendations for mitigation

The adoption of artificial intelligence (AI) algorithms is rapidly increasing in healthcare. Such algorithms may be shaped by various factors such as social determinants of health that can influence health outcomes. While AI algorithms have been proposed as a tool to expand the reach of quality healthcare to underserved communities and improve health equity, recent literature has raised concerns about the propagation of biases and healthcare disparities through implementation of these algorithms. Thus, it is critical to understand the sources of bias inherent in AI-based algorithms. This review aims to highlight the potential sources of bias within each step of developing AI algorithms in healthcare, starting from framing the problem, data collection, preprocessing, development, and validation, as well as their full implementation. For each of these steps, we also discuss strategies to mitigate the bias and disparities. A checklist was developed with recommendations for reducing bias during the development and implementation stages. It is important for developers and users of AI-based algorithms to keep these important considerations in mind to advance health equity for all populations.

Circulating extracellular vesicles are associated with the clinical outcomes of sepsis

Introduction

Sepsis is associated with endothelial cell (EC) dysfunction, increased vascular permeability and organ injury, which may lead to mortality, acute respiratory distress syndrome (ARDS) and acute renal failure (ARF). There are no reliable biomarkers to predict these sepsis complications at present. Recent evidence suggests that circulating extracellular vesicles (EVs) and their content caspase-1 and miR-126 may play a critical role in modulating vascular injury in sepsis; however, the association between circulating EVs and sepsis outcomes remains largely unknown.

Methods

We obtained plasma samples from septic patients (n=96) within 24 hours of hospital admission and from healthy controls (n=45). Total, monocyte- or EC-derived EVs were isolated from the plasma samples. Transendothelial electrical resistance (TEER) was used as an indicator of EC dysfunction. Caspase-1 activity in EVs was detected and their association with sepsis outcomes including mortality, ARDS and ARF was analyzed. In another set of experiments, total EVs were isolated from plasma samples of 12 septic patients and 12 non-septic critical illness controls on days 1, and 3 after hospital admission. RNAs were isolated from these EVs and Next-generation sequencing was performed. The association between miR-126 levels and sepsis outcomes such as mortality, ARDS and ARF was analyzed.

Results

Septic patients with circulating EVs that induced EC injury (lower transendothelial electrical resistance) were more likely to experience ARDS (p<0.05). Higher caspase-1 activity in total EVs, monocyte- or EC-derived EVs was significantly associated with the development of ARDS (p<0.05). MiR-126-3p levels in EC EVs were significantly decreased in ARDS patients compared with healthy controls (p<0.05). Moreover, a decline in miR-126-5p levels from day 1 to day 3 was associated with increased mortality, ARDS and ARF; while decline in miR-126-3p levels from day 1 to day 3 was associated with ARDS development.

Conclusions

Enhanced caspase-1 activity and declining miR-126 levels in circulating EVs are associated with sepsis-related organ failure and mortality. Extracellular vesicular contents may serve as novel prognostic biomarkers and/or targets for future therapeutic approaches in sepsis.

The impact of ethnic background on ICU care and outcome in sepsis and septic shock - A retrospective multicenter analysis on 17,949 patients

BACKGROUND

Previous studies have been inconclusive about racial disparities in sepsis. This study evaluated the impact of ethnic background on management and outcome in sepsis and septic shock.

METHODS

This analysis included 17,146 patients suffering from sepsis and septic shock from the multicenter eICU Collaborative Research Database. Generalized estimated equation (GEE) population-averaged models were used to fit three sequential regression models for the binary primary outcome of hospital mortality.

RESULTS

Non-Hispanic whites were the predominant group (n = 14,124), followed by African Americans (n = 1,852), Hispanics (n = 717), Asian Americans (n = 280), Native Americans (n = 146) and others (n = 830). Overall, the intensive care treatment and hospital mortality were similar between all ethnic groups. This finding was concordant in patients with septic shock and persisted after adjusting for patient-level variables (age, sex, mechanical ventilation, vasopressor use and comorbidities) and hospital variables (teaching hospital status, number of beds in the hospital).

CONCLUSION

We could not detect ethnic disparities in the management and outcomes of critically ill septic patients and patients suffering from septic shock. Disparate outcomes among critically ill septic patients of different ethnicities are a public health, rather than a critical care challenge.

Change Management Strategies Towards Dismantling Race-Based Structural Barriers in Radiology

Political momentum for antiracist policies grew out of the collective trauma highlighted during the COVID pandemic. This prompted discussions of root cause analyses for differences in health outcomes among historically underserved populations, including racial and ethnic minorities. Dismantling structural racism in medicine is an ambitious goal that requires widespread buy-in and transdisciplinary collaborations across institutions to establish systematic, rigorous approaches that enable sustainable change. Radiology is at the center of medical care and renewed focus on equity, diversity, and inclusion (EDI) provides an opportune window for radiologists to facilitate an open forum to address racialized medicine to catalyze real and lasting change. The framework of change management can help radiology practices create and maintain this change while minimizing disruption. This article discusses how change management principles can be leveraged by radiology to lead EDI interventions that will encourage honest dialogue, serve as a platform to support institutional EDI efforts, and lead to systemic change.

Overt and Occult Hypoxemia in Patients Hospitalized With COVID-19

Progressive hypoxemia is the predominant mode of deterioration in COVID-19. Among hypoxemia measures, the ratio of the Pao2 to the Fio2 (P/F ratio) has optimal construct validity but poor availability because it requires arterial blood sampling. Pulse oximetry reports oxygenation continuously (ratio of the Spo2 to the Fio2 [S/F ratio]), but it is affected by skin color and occult hypoxemia can occur in Black patients. Oxygen dissociation curves allow noninvasive estimation of P/F ratios (ePFRs) but remain unproven.

OBJECTIVES

Measure overt and occult hypoxemia using ePFR.

DESIGN SETTING AND PARTICIPANTS

We retrospectively studied COVID-19 hospital encounters (n = 5,319) at two academic centers (University of Virginia [UVA] and Emory University).

MAIN OUTCOMES AND MEASURES

We measured primary outcomes (death or ICU transfer within 24 hr), ePFR, conventional hypoxemia measures, baseline predictors (age, sex, race, comorbidity), and acute predictors (National Early Warning Score [NEWS] and Sequential Organ Failure Assessment [SOFA]). We updated predictors every 15 minutes. We assessed predictive validity using adjusted odds ratios (AORs) and area under the receiver operating characteristic curves (AUROCs). We quantified disparities (Black vs non-Black) in empirical cumulative distributions using the Kolmogorov-Smirnov (K-S) two-sample test.

RESULTS

Overt hypoxemia (low ePFR) predicted bad outcomes (AOR for a 100-point ePFR drop: 2.7 [UVA]; 1.7 [Emory]; p < 0.01) with better discrimination (AUROC: 0.76 [UVA]; 0.71 [Emory]) than NEWS (0.70 [both sites]) or SOFA (0.68 [UVA]; 0.65 [Emory]) and similar to S/F ratio (0.76 [UVA]; 0.70 [Emory]). We found racial differences consistent with occult hypoxemia. Black patients had better apparent oxygenation (K-S distance: 0.17 [both sites]; p < 0.01) but, for comparable ePFRs, worse outcomes than other patients (AOR: 2.2 [UVA]; 1.2 [Emory]; p < 0.01).

CONCLUSIONS AND RELEVANCE

The ePFR was a valid measure of overt hypoxemia. In COVID-19, it may outperform multi-organ dysfunction models. By accounting for biased oximetry as well as clinicians' real-time responses to it (supplemental oxygen adjustment), ePFRs may reveal racial disparities attributable to occult hypoxemia.

"Community engagement via restorative justice to build equity-oriented crisis standards of care"

The COVID-19 (SARS-CoV-2) Pandemic has revealed multiple structural inequities within the United States (US), with high social vulnerability index communities shouldering the brunt of death and disability of this pandemic. BIPOC/Latinx people have undergone hospitalizations and death at magnitudes greater than White people in the US. The untold second casualties are health care workers that are suffering from increased risk of infection, death, and mental health crisis. Many health care workers are abandoning the profession all together. Although Crisis Standards of Care (CSC) mean to guide the ethical allocation of scare resources, they frequently use scoring systems that are inherently biased. This raises concern for the application of equity in CSC. Data examining the impact of these protocols on health equity is scarce. Structural maltreatment in healthcare and inequities have led to cumulative harms, physiologic weathering and structural adversities for residents of the US. We propose the use of Restorative Justice (RJ) practices to develop CSC rooted in inclusion and equity. The RJ framework utilizes capacity building, circle process, and conferences to convene groups in a respectful environment for dialogue, healing, accountability, and action plan creation. A phased, non-faith-based facilitated RJ approach for CSC development (or revision) that fosters ethically equitable resource distribution, authentic community engagement, and accountability is shared. This opportunity for local, inclusive decision making and problem solving will both reflect the needs and give agency to community members while supporting the dismantling of structural racism and oppressive, exclusive policies. The authors are asking legislative and health system policy makers to adopt Restorative Justice practices for Crisis Standards of Care development. The US cannot afford to have additional reductions in inhabitant lifespan or the talent pool within healthcare.

Quantifying Utilitarian Outcomes to Inform Triage Ethics: Simulated Performance of a Ventilator Triage Protocol under Sars-CoV-2 Pandemic Surge Conditions

BACKGROUND

Equitable protocols to triage life-saving resources must be specified prior to shortages in order to promote transparency, trust and consistency. How well proposed utilitarian protocols perform to maximize lives saved is unknown. We aimed to estimate the survival rates that would be associated with implementation of the New York State 2015 guidelines for ventilator triage, and to compare them to a first-come-first-served triage method.

METHODS

We constructed a simulation model based on a modified version of the New York State 2015 guidelines compared to a first-come-first-served method under various hypothetical ventilator shortages. We included patients with SARs-CoV-2 infection admitted with respiratory failure requiring mechanical ventilation to three acute care hospitals in New York from 3/01/2020 and 5/27/2020. We estimated (1) survival rates, (2) number of excess deaths, (3) number of patients extubated early or not allocated a ventilator due to capacity constraints, (4) survival rates among patients not allocated a ventilator at triage or extubated early due to capacity constraints.

RESULTS

807 patients were included in the study. The simulation model based on a modified New York State policy did not decrease mortality, excess death or exclusion from ventilators compared to the first-come-first-served policy at every ventilator capacity we tested using COVID-19 surge cohort patients. Survival rates were similar at all the survival probabilities estimated. At the lowest ventilator capacity, the modified New York State policy has an estimated survival of 28.5% (CI: 28.4-28.6), compared to 28.1% (CI: 27.7-28.5) for the first-come-first-served policy.

CONCLUSIONS

This simulation of a modified New York State guideline-based triage protocol revealed limitations in achieving the utilitarian goals these protocols are designed to fulfill. Quantifying these outcomes can inform a better balance among competing moral aims.

Perspectives of Triage Team Members Participating in Statewide Triage Simulations for Scarce Resource Allocation During the COVID-19 Pandemic in Washington State

IMPORTANCE

The COVID-19 pandemic prompted health care institutions worldwide to develop plans for allocation of scarce resources in crisis capacity settings. These plans frequently rely on rapid deployment of institutional triage teams that would be responsible for prioritizing patients to receive scarce resources; however, little is known about how these teams function or how to support team members participating in this unique task.

OBJECTIVE

To identify themes illuminating triage team members' perspectives and experiences pertaining to the triage process.

DESIGN, SETTING, AND PARTICIPANTS

This qualitative study was conducted using inductive thematic analysis of observations of Washington state triage team simulations and semistructured interviews with participants during the COVID-19 pandemic from December 2020 to February 2021. Participants included clinician and ethicist triage team members. Data were analyzed from December 2020 through November 2021.

MAIN OUTCOMES AND MEASURES

Emergent themes describing the triage process and experience of triage team members.

RESULTS

Among 41 triage team members (mean [SD] age, 50.3 [11.4] years; 21 [51.2%] women) who participated in 12 simulations and 21 follow-up interviews, there were 5 Asian individuals (12.2%) and 35 White individuals (85.4%); most participants worked in urban hospital settings (32 individuals [78.0%]). Three interrelated themes emerged from qualitative analysis: (1) understanding the broader approach to resource allocation: participants strove to understand operational and ethical foundations of the triage process, which was necessary to appreciate their team's specific role; (2) contending with uncertainty: team members could find it difficult or feel irresponsible making consequential decisions based on limited clinical and contextual patient information, and they grappled with ethically ambiguous features of individual cases and of the triage process as a whole; and (3) transforming mindset: participants struggled to disentangle narrow determinations about patients' likelihood of survival to discharge from implicit biases and other ethically relevant factors, such as quality of life. They cited the team's open deliberative process, as well as practice and personal experience with triage as important in helping to reshape their usual cognitive approach to align with this unique task.

CONCLUSIONS AND RELEVANCE

This study found that there were challenges in adapting clinical intuition and training to a distinctive role in the process of scarce resource allocation. These findings suggest that clinical experience, education in ethical and operational foundations of triage, and experiential training, such as triage simulations, may help prepare clinicians for this difficult role.

Assessment of a Crisis Standards of Care Scoring System for Resource Prioritization and Estimated Excess Mortality by Race, Ethnicity, and Socially Vulnerable Area During a Regional Surge in COVID-19

IMPORTANCE

Crisis standards of care (CSOC) scores designed to allocate scarce resources during the COVID-19 pandemic could exacerbate racial disparities in health care.

OBJECTIVE

To analyze the association of a CSOC scoring system with resource prioritization and estimated excess mortality by race, ethnicity, and residence in a socially vulnerable area.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort analysis included adult patients in the intensive care unit during a regional COVID-19 surge from April 13 to May 22, 2020, at 6 hospitals in a health care network in greater Boston, Massachusetts. Participants were scored by acute severity of illness using the Sequential Organ Failure Assessment score and chronic severity of illness using comorbidity and life expectancy scores, and only participants with complete scores were included. The score was ordinal, with cutoff points suggested by the Massachusetts guidelines.

EXPOSURES

Race, ethnicity, Social Vulnerability Index.

MAIN OUTCOMES AND MEASURES

The primary outcome was proportion of patients in the lowest priority score category stratified by self-reported race. Secondary outcomes were discrimination and calibration of the score overall and by race, ethnicity, and neighborhood Social Vulnerability Index. Projected excess deaths were modeled by race, using the priority scoring system and a random lottery.

RESULTS

Of 608 patients in the intensive care unit during the study period, 498 had complete data and were included in the analysis; this population had a median (IQR) age of 67 (56-75) years, 191 (38.4%) female participants, 79 (15.9%) Black participants, and 225 patients (45.7%) with COVID-19. The area under the receiver operating characteristic curve for the priority score was 0.79 and was similar across racial groups. Black patients were more likely than others to be in the lowest priority group (12 [15.2%] vs 34 [8.1%]; P = .046). In an exploratory simulation model using the score for ventilator allocation, with only those in the highest priority group receiving ventilators, there were 43.9% excess deaths among Black patients (18 of 41 patients) and 28.6% (58 of 203 patients among all others (P = .05); when the highest and intermediate priority groups received ventilators, there were 4.9% (2 of 41 patients) excess deaths among Black patients and 3.0% (6 of 203) among all others (P = .53). A random lottery resulted in more excess deaths than the score.

CONCLUSIONS AND RELEVANCE

In this study, a CSOC priority score resulted in lower prioritization of Black patients to receive scarce resources. A model using a random lottery resulted in more estimated excess deaths overall without improving equity by race. CSOC policies must be evaluated for their potential association with racial disparities in health care.

Sequential organ failure assessment, ventilator rationing and evolving triage guidance: new evidence underlines the need to recognise and revise, unjust allocation frameworks

We respond to recent comments on our proposal to improve justice in ventilator triage, in which we used as an example New Jersey's (NJ) publicly available and legally binding Directive Number 2020-03. We agree with Bernard Lo and Doug White that equity implications of triage frameworks should be continually reassessed, which is why we offered six concrete options for improvement, and called for monitoring the consequences of adopted triage models. We disagree with their assessment that we mis-characterised their Model Guidance, as included in the NJ Directive, in ways that undermine our conclusions. They suggest we erroneously described their model as a two-criterion allocation framework; that recognising other operant criterion reveals it 'likely mitigate[s] rather than exacerbate[s] racial disparities during triage', and allege that concerns about inequitable outcomes are 'without evidence'. We highlight two major studies robustly demonstrating why concerns about disparate outcomes are justified. We also show that White and Lo seek to retrospectively-and counterfactually-correct the version of the Model Guideline included in the NJ Directive. However, as our facsimile reproductions show, neither the alleged four-criteria form, nor other key changes, such as dropping the Sequential Organ Failure Assessment score, are found in the Directive. These points matter because (1) our conclusions hence stand, (2) because the public version of the Model Guidance had not been updated to reduce the risk of inequitable outcomes until June 2021 and (3) NJ's Directive still does not reflect these revisions, and, hence, represents a less equitable version, as acknowledged by its authors. We comment on broader policy implications and call for ways of ensuring accurate, transparent and timely updates for users of high-stakes guidelines.

Survey of Glasgow Coma Scale and PaO 2 / FIO 2 ratio assessment methods for the Sequential Organ Failure Assessment score in Japanese intensive care units

Aim

Accurately calculating the Sequential Organ Failure Assessment (SOFA) score is essential for medical resource allocation and decision‐making. This study surveyed Japanese intensive care units regarding their assessment of the Glasgow Coma Scale (GCS) and PaO₂/FIO₂ ratio, components of the SOFA score.

Methods

A cross‐sectional, web‐based survey was conducted among healthcare workers. The survey consisted of questions about the intensive care units where they work and questions for respondents. It was distributed to healthcare workers by e‐mail through the Japanese Society of Intensive Care Medicine mailing list and social networking service.

Results

Among 414 responses, we obtained 211 valid responses and 175 survey results from unique intensive care units. When assessing GCS in patients under the influence of sedatives, 45.1% (95% confidence interval, 37.6–52.8) of intensive care units assessed GCS assuming that the sedatives had no influence. For the PaO₂/FIO₂ ratio in the SOFA score, calculation based on the Japanese Intensive Care Patient Database definition document and mechanical ventilator settings were the most common methods in patients with oxygen masks and on extracorporeal membrane oxygenation, respectively. Approximately 60% of respondents indicated that it was difficult to assess GCS assuming that sedatives had no influence.

Conclusion

In patients under the influence of sedatives, approximately half of the intensive care units assessed assumed GCS. There was variation in the methods used to assess the PaO₂/FIO₂ ratio. Standardized assessment methods for GCS and the PaO₂/FIO₂ ratio are needed to obtain valid SOFA score.

Functionality of Scarce Healthcare Resource Triage Teams During the COVID-19 Pandemic: A Multi-Institutional Simulation Study

Plans for allocating scarce healthcare resources during the COVID-19 pandemic commonly involve the activation of institutional triage teams. These teams would be responsible for selecting patients who are most likely to survive to be prioritized to receive scarce resources. However, there is little empirical support for this approach.

DESIGN

High-fidelity triage-team simulation study.

SETTING

Healthcare institutions in Washington state.

SUBJECTS

Triage teams, consisting of at least two senior clinicians and a bioethicist.

INTERVENTIONS

Participants reviewed a limited amount of deidentified information for a diverse sample of critically ill patients. Teams then assigned each patient to one of five prioritization categories defined by likelihood of survival to hospital discharge. The process was refined based on observation and participant feedback after which a second phase of simulations was conducted.

MEASUREMENTS AND MAIN RESULTS

Feasibility was assessed by the time required for teams to perform their task. Prognostic accuracy was assessed by comparing teams' prediction about likelihood of survival to hospital discharge with real-world discharge outcomes. Agreement between the teams on prognostic categorization was evaluated using kappa statistics. Eleven triage team simulations (eight in phase 1 and three in phase 2) were conducted from December 2020 to February 2021. Overall, teams reviewed a median of 23 patient cases in each session (interquartile range [IQR], 17-29) and spent a median of 102 seconds (IQR, 50-268) per case. The concordance between expected survival and real-world survival to discharge was 71% (IQR, 64-76%). The overall agreement between teams for placement of patients into prognostic categories was moderate (weighted kappa = 0.53).

CONCLUSIONS

These findings support the potential feasibility, accuracy, and effectiveness of institutional triage teams informed by a limited set of patient information items as part of a strategy for allocating scarce resources in healthcare emergencies. Additional work is needed to refine the process and adapt it to local contexts.

Ethics of Extracorporeal Membrane Oxygenation under Conventional and Crisis Standards of Care

Extracorporeal membrane oxygenation (ECMO) is a form of life support for cardiac and/or pulmonary failure with unique ethical challenges compared to other forms of life support. Ethical challenges with ECMO exist when conventional standards of care apply, and are exacerbated during periods of absolute ECMO scarcity when "crisis standards of care" are instituted. When conventional standards of care apply, we propose that it is ethically permissible to withhold placing patients on ECMO for reasons of technical futility or when patients have terminal, short-term prognoses that are untreatable by ECMO. Under crisis standards of care, it is ethically permissible to broaden exclusionary criteria to also withhold ECMO from patients who have a low likelihood of recovery, to maximize the overall number of lives saved. Unilateral withdrawal of ECMO against a patient's preferences is unethical under conventional standards of care, but is ethical under crisis standards of care to increase access to ECMO to others in society. ECMO should only be rationed when true scarcity exists, and allocation protocols should be transparent to the public. When rationing must occur under crisis standards of care, it is imperative that oversight bodies assess for inequities in the allocation of ECMO and make frequent changes to improve any inequities.