Temporal trend analysis of rheumatic heart disease burden in high-income countries between 1990 and 2019.

AIMS: To assesses trends in rheumatic heart disease (RHD) burden in high-income, European Union 15+ (EU15+) countries between 1990 and 2019. METHODS AND RESULTS: Cross-sectional analysis of the incidence and mortality of RHD was conducted using data from the Global Burden of Disease Study (GBD) database. Age-standardized incidence rates (ASIRs) and age-standardized mortality rates (ASMRs) were extracted for EU15 + countries per sex for each of the years from 1990-2019, inclusive, and mortality-to-incidence indices (MII) were computed. Joinpoint regression analysis was used for the description of trends. Over 29 years, an overall declining trend in RHD incidence and mortality across EU 15 + nations were observed. There was significant variability in RHD incidence and mortality rates across high-income countries. However, both RHD incidence and mortality were higher among females compared to males across EU15 + countries over the observed period. The most recent incidence trend, starting predominantly after 2014, demonstrated a rise in RHD incidence in most countries for both sexes. The timing of this RHD resurgence corresponds temporally with an influx of migrants and refugees into Europe. The recent increasing RHD incidence rates ranged from + 0.4% to + 24.7% for males, and + 0.6% to + 11.4% for females. CONCLUSIONS: More than half of EU15 + nations display a recent increase in RHD incidence rate across both sexes. Possible factors associated with this rise are discussed and include increase in global migration from nations with higher RHD prevalence, host nation factors such as migrants' housing conditions, healthcare access and migrant health status on arrival.

Protocol for assessing and predicting acute respiratory decline in hospitalized patients.

This protocol aids both new and experienced researchers in designing retrospective clinical and translational studies of acute respiratory decline in hospitalized patients. This protocol addresses (1) the basics of respiratory failure and electronic health record research, (2) defining patient cohorts as "mild, progressive, or severe" instead of "ICU versus non-ICU", (3) adapting physiological indices, and (4) using biomarker trends. We apply these approaches to inflammatory biomarkers in COVID-19, but this protocol can be applied to any progressive respiratory failure study. For complete details on the use and execution of this protocol, please refer to Mueller et al. (2020).

Empirical Assessment of U.S. Coronavirus Disease 2019 Crisis Standards of Care Guidelines.

To establish the feasibility of empirically testing crisis standards of care guidelines. DESIGN: Retrospective single-center study. SETTING: ICUs at a large academic medical center in the United States. SUBJECTS: Adult, critically ill patients admitted to ICU, with 27 patients admitted for acute respiratory failure due to coronavirus disease 2019 and 37 patients admitted for diagnoses other than coronavirus disease 2019. INTERVENTIONS: Review of electronic health record. MEASUREMENTS AND MAIN RESULTS: Many U.S. states released crisis standards of care guidelines with algorithms to allocate scarce healthcare resources during the coronavirus disease 2019 pandemic. We compared state guidelines that represent different approaches to incorporating disease severity and comorbidities: New York, Maryland, Pennsylvania, and Colorado. Following each algorithm, we calculated priority scores at the time of ICU admission for a cohort of patients with primary diagnoses of coronavirus disease 2019 and diseases other than coronavirus disease 2019 (n = 64). We assessed discrimination of 28-day mortality by area under the receiver operating characteristic curve. We simulated real-time decision-making by applying the triage algorithms to groups of two, five, or 10 patients. For prediction of 28-day mortality by priority scores, area under the receiver operating characteristic curve was 0.56, 0.49, 0.53, 0.66, and 0.69 for New York, Maryland, Pennsylvania, Colorado, and raw Sequential Organ Failure Assessment score algorithms, respectively. For groups of five patients, the percentage of decisions made without deferring to a lottery were 1%, 57%, 80%, 88%, and 95% for New York, Maryland, Pennsylvania, Colorado, and raw Sequential Organ Failure Assessment score algorithms, respectively. The percentage of decisions made without lottery was higher in the subcohort without coronavirus disease 2019, compared with the subcohort with coronavirus disease 2019. CONCLUSIONS: Inclusion of comorbidities does not consistently improve an algorithm's performance in predicting 28-day mortality. Crisis standards of care algorithms result in a substantial percentage of tied priority scores. Crisis standards of care algorithms operate differently in cohorts with and without coronavirus disease 2019. This proof-of-principle study demonstrates the feasibility and importance of empirical testing of crisis standards of care guidelines to understand whether they meet their goals.

Performance of crisis standards of care guidelines in a cohort of critically ill COVID-19 patients in the United States.

Many US states published crisis standards of care (CSC) guidelines for allocating scarce critical care resources during the COVID-19 pandemic. However, the performance of these guidelines in maximizing their population benefit has not been well tested. In 2,272 adults with COVID-19 requiring mechanical ventilation drawn from the Study of the Treatment and Outcomes in Critically Ill Patients with COVID-19 (STOP-COVID) multicenter cohort, we test the following three approaches to CSC algorithms: Sequential Organ Failure Assessment (SOFA) scores grouped into ranges, SOFA score ranges plus comorbidities, and a hypothetical approach using raw SOFA scores not grouped into ranges. We find that area under receiver operating characteristic (AUROC) curves for all three algorithms demonstrate only modest discrimination for 28-day mortality. Adding comorbidity scoring modestly improves algorithm performance over SOFA scores alone. The algorithm incorporating comorbidities has modestly worse predictive performance for Black compared to white patients. CSC algorithms should be empirically examined to refine approaches to the allocation of scarce resources during pandemics and to avoid potential exacerbation of racial inequities.

The association between ACLS guideline deviations and outcomes from in-hospital cardiac arrest.

AIM OF STUDY: In hospital cardiac arrests occur at a rate of 1-5 per 1000 admissions and are associated with significant morbidity and mortality. We aimed to investigate the association between deviations from ACLS protocol and patient outcomes. METHODS: This retrospective review was conducted at a single academic medical center. Data was collected on patients who suffered cardiac arrest from December 2015-November 2019. Our primary endpoint was return of spontaneous circulation. Secondary endpoints included survival to discharge and discharge with favorable neurological outcomes. RESULTS: 108 patients were included, 74 obtained return of spontaneous circulation, and 23 survived to discharge. The median number of deviations from the ACLS protocol per event in ROSC group was 1 (IQR 0-3) compared to 6.5 (IQR 4-12) in non-ROSC group (p < .0001). The probability of obtaining ROSC was 96% with 0-2 deviations per event, 59% with 2-5 deviations per event, and 11% with greater than 6 deviations per event (p < .0001). The median deviation per event in patients who survived to discharge was 0 (IQR 0-1) vs. 3 (IQR 1-6, p < .0001) in those who did not. Lastly, survival to discharge with a favorable neurological outcome may be associated we less deviations per event (p < .006). CONCLUSION: Our findings highlight the importance of adherence to the ACLS protocol. We found that deviations from the algorithm are associated with decreased rates of ROSC and survival to discharge. Additionally, higher rates of protocol deviations may be associated with higher rates of neurological impairments after cardiac arrest.

The Use of Mechanical Cardiopulmonary Resuscitation May Be Associated With Improved Outcomes Over Manual Cardiopulmonary Resuscitation During Inhospital Cardiac Arrests.

We aimed to investigate the impact of mechanical cardiopulmonary resuscitation devices over manual cardiopulmonary resuscitation on outcomes from inhospital cardiac arrests. DESIGN: Restrospective review. SETTING: Single academic medical center. PARTICIPANTS: Data were collected on all patients who suffered cardiac arrest from December 2015 to November 2019. MAIN OUTCOMES AND MEASURES: Primary end point was return of spontaneous circulation. Secondary end points included survival to discharge and survival to discharge with favorable neurologic outcomes. RESULTS: About 104 patients were included in the study: 59 patients received mechanical cardiopulmonary resuscitation and 45 patients received manual cardiopulmonary resuscitation during the enrollment period. Return of spontaneous circulation rate was 83% in the mechanical cardiopulmonary resuscitation group versus 48.8% in the manual group (p = 0.009). Survival-to-discharge rate was 32.2% in the mechanical cardiopulmonary resuscitation group versus 11.1% in those who received manual cardiopulmonary resuscitation (p = 0.02). Of the patients who survived to discharge and received mechanical cardiopulmonary resuscitation, 100% (n = 19) had a favorable neurologic outcome versus 40% (two out of five) of patients who survived and received manual cardiopulmonary resuscitation (p = 0.005). CONCLUSIONS: Our findings demonstrate a significant association of improved outcomes with mechanical cardiopulmonary resuscitation over manual cardiopulmonary resuscitation during inhospital cardiac arrests. Mechanical cardiopulmonary resuscitation may improve rates of return of spontaneous circulation, survival to discharge, and favorable neurologic outcomes.

Initiation and Assessment of Timekeeping Roles During In-Hospital Cardiac Arrests to Track Rhythm Checks and Epinephrine Dosing.

OBJECTIVES: Compliance to advanced cardiac life support algorithm is low and associated with worse outcomes from in-hospital cardiac arrests. This study aims to improve algorithm compliance by delegation of two separate code team members for timing rhythm check and epinephrine administration in accordance to the advanced cardiac life support algorithm. DESIGN: Prospective intervention with historical controls. SETTING: Single academic medical center. PATIENTS: Patients who suffered in-hospital cardiac arrest during study period were considered for inclusion. Patients in which the advanced cardiac life support algorithm or new timekeeper roles were not used were excluded. INTERVENTIONS: Two existing code team members were delegated to time epinephrine and rhythm checks. MEASUREMENTS AND MAIN RESULTS: Primary endpoint was deviations from the 2-minute rhythm check or 3- to 5-minute epinephrine administration. Each deviation outside allotted time intervals was counted as one deviation. However, instances in which multiple intervals passed were counted as multiple deviations. Algorithm adherence was analyzed before and after intervention. Secondary endpoints included return of spontaneous circulation rate, time until first dose of epinephrine, and anonymous survey data. Thirteen pre intervention in-hospital cardiac arrests were compared with 13 in-hospital cardiac arrests post. Prior to intervention, the median deviation per in-hospital cardiac arrest was 5 (interquartile range, 3-7) versus 1 post (interquartile range 0-1; p = 0.0003). The median time until first dose of epinephrine was administered pre intervention was 5 minutes (interquartile range, 0-4) versus post intervention median of 0 (interquartile range, 0-0; p = 0.02). Pre-intervention return of spontaneous circulation rate was 46.1% versus 69.2% post. Surveys demonstrated advanced cardiac life support providers felt time keeping roles made it easier to track epinephrine administration and rhythm checks and improved team communication. CONCLUSIONS: Two separate timekeeper roles during in-hospital cardiac arrests improved algorithm compliance, code team function, and was favored by code team members. Timekeeper roles may be associated with improved rates of return of spontaneous circulation and less time until the first dose of epinephrine was administered. This study is limited by small sample size and single-center design.

Inflammatory Biomarker Trends Predict Respiratory Decline in COVID-19 Patients.

In this single-center, retrospective cohort analysis of hospitalized coronavirus disease 2019 (COVID-19) patients, we investigate whether inflammatory biomarker levels predict respiratory decline in patients who initially present with stable disease. Examination of C-reactive protein (CRP) trends reveals that a rapid rise in CRP levels precedes respiratory deterioration and intubation, although CRP levels plateau in patients who remain stable. Increasing CRP during the first 48 h of hospitalization is a better predictor (with higher sensitivity) of respiratory decline than initial CRP levels or ROX indices (a physiological score of respiratory function). CRP, the proinflammatory cytokine interleukin-6 (IL-6), and physiological measures of hypoxemic respiratory failure are correlated, which suggests a mechanistic link. Our work shows that rising CRP predicts subsequent respiratory deterioration in COVID-19 and may suggest mechanistic insight and a potential role for targeted immunomodulation in a subset of patients early during hospitalization.