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We sought to evaluate the utility and validity of ICU-free days and ventilator-free days as candidate outcomes for OHCA trials.We conducted a secondary analysis of the Pragmatic Airway Resuscitation Trial. We determined ICU-free (days alive and out of ICU during the first 30 days) and ventilator-free days (days alive and without mechanical ventilation). We determined ICU-free and ventilator-free day distributions and correlations with Modified Rankin Scale (MRS). We tested associations with trial interventions (laryngeal tube (LT), endotracheal intubation (ETI)) using continuous (t-test), non-parametric (Wilcoxon Rank-Sum test - WRS), count (negative binomial - NB) and survival models (Cox proportional hazards (CPH) and competing risks regression (CRR)). We conducted bootstrapped simulations to estimate statistical power.ICU-free days was skewed; median 0 days (IQR 0, 0), survivors only 24 (18, 27). Ventilator-free days was skewed; median 0 (IQR 0, 0) days, survivors only 27 (IQR 23, 28). ICU-free and ventilator-free days correlated with MRS (Spearman's ρ = -0.95 and -0.97). LT was associated with higher ICU-free days using t-test (p = 0.001), WRS (p = 0.003), CPH (p = 0.02) and CRR (p = 0.04), but not NB (p = 0.13). LT was associated with higher ventilator-free days using t-test (p = 0.001), WRS (p = 0.001) and CRR (p = 0.03), but not NB (p = 0.13) or CPH (p = 0.13). Simulations suggested that t-test and WRS would have had the greatest power to detect the observed ICU- and ventilator-free days differences.ICU-free and ventilator-free days correlated with MRS and differentiated trial interventions. ICU-free and ventilator-free days may have utility in the design of OHCA trials.

To evaluate the impact of community level information on the predictability of out-of-hospital cardiac arrest (OHCA) survival.We used the Cardiac Arrest Registry to Enhance Survival (CARES) to geocode 9,595 Chicago incidents from 2014 to 2019 into community areas. Community variables including crime, healthcare, and economic factors from public data were merged with CARES. The merged data were used to develop ML models for OHCA survival. Models were evaluated using Area Under the Receiver Operating Characteristic curve (AUROC) and features were analyzed using SHapley Additive exPansion (SHAP) values.Baseline results using CARES data achieved an AUROC of 84%. The final model utilizing community variables increased the AUROC to 88%. A SHAP analysis between high and low performing community area clusters showed the high performing cluster is positively impacted by good health related features and good community safety features positively impact the low performing cluster.Utilizing community variables helps predict neurologic outcomes with better performance than only CARES data. Future studies will use this model to perform simulations to identify interventions to improve OHCA survival.

Background: Italy, France and New York City have reported an increase in out-of-hospital cardiac arrest (OHCA) incidence during the COVID-19 pandemic. The purpose of our study was to assess the effect of COVID-19 on OHCA cases in Chicago. Method: Cardiac Arrest Registry to Enhance Survival (CARES) database was used. Bivariate analysis was conducted to assess changes in demographic and other characteristics. We excluded the cases that occurred in a healthcare facility or a nursing home. We compared the cases reported in 2020 to 2019 (and prior years). ArcGIS was used to geocode incident addresses and to show the temporal distribution by community areas. Bivariate analysis was done using chi-square tests. Results: A total of 3221 OHCA cases were reported in Chicago in 2020, which is 31.5% higher than those reported in 2019 (n=2450 cases). This increase was higher than what has been noticed historically (for instance, the increase from 2018 to 2019 was only 17%). There was an increase in Hispanic OHCA cases (17.3% in 2020 vs. 13.5% in 2019, p Conclusion: A better understanding of the causes of the excess cardiac arrest numbers will be important to help plan and better prepare for future public health interventions. The effect of COVID-19 on OHCA survival needs to be examined further in future studies.

Objective: Compared with traditional out-of-hospital cardiac arrest (OHCA) trial outcomes such as hospital survival, alternative outcomes such as intensive care unit-free (IFD) and ventilator-free days (VFD) have potential advantages including requiring smaller sample sizes to detect significant differences. Few studies have evaluated these outcomes in OHCA. We sought to evaluate the utility and validity of IFD and VFD as candidate outcomes for OHCA trials. Methods: We analyzed data from the Pragmatic Airway Resuscitation Trial (PART), which tested laryngeal tube (LT) vs. endotracheal intubation (ETI) airway strategies in adult OHCA. We defined IFD as the number of days alive and permanently out of ICU during the first 30 days after the OHCA event. We examined IFD distribution and correlation with Modified Rankin Scale (MRS). To test associations with trial interventions, we applied a range of analytic strategies, including modeling IFD as continuous (Generalized Estimating Equations - GEE), non-parametric (Wilcoxon Rank-Sum test - WRS) and count (zero-inflated negative binomial regression - ZINB) data. We also modeled time-to-ICU discharge using a survival model with death as a competing risk. We repeated the analysis assessing VFD. Results: IFD was available for 2,898 of 3,004 patients. IFD was skewed and J-shaped; 91% IFD=0 and 5.3% IFD≥22. Mean (±SD) IFD was 2.0±6.6 days; 21.2±7.5 days for survivors. IFD varied by intervention (LT 2.4±7.2, ETI 1.6±5.8 days). IFD and VFD strongly correlated with MRS (ρ= -0.88, -0.89). LT was associated with increased IFD using GEE, WRS, and ZINB, but not competing risks model. (Table) LT was associated with increased VFD using GEE and WRS, but not ZINB or competing risks models. Conclusion: IFD and VFD differentiated OHCA interventions, suggesting their utility. IFD and VFD were highly correlated with MRS, suggesting validity. IFD and VFD have important features that may influence OHCA trial design.

BACKGROUND During the COVID-19 pandemic, novel digital health technologies have the potential to improve our understanding of SARS-CoV-2 and COVID-19, improve care delivery, and produce better health outcomes. The National Institutes of Health called on digital health leaders to contribute to a high-quality data repository that will support researchers to make discoveries that are otherwise not possible with small, limited data sets. OBJECTIVE To this end, we seek to develop a COVID-19 digital biomarker for early detection of physiological exacerbation or decompensation. We propose the development and validation of a COVID-19 decompensation Index (CDI) in a 2-phase study that builds on existing wearable biosensor-derived analytics generated by physIQ’s end-to-end cloud platform for continuous physiological monitoring with wearable biosensors. This effort serves to achieve two primary objectives: (1) to collect adequate data to help develop the CDI and (2) to collect rich deidentified clinical data correlating with outcomes and symptoms related to COVID-19 progression. Our secondary objectives include evaluation of the feasibility and usability of pinpointIQ, a digital platform through which data are gathered, analyzed, and displayed. METHODS This is a prospective, nonrandomized, open-label, 2-phase study. Phase I will involve data collection for the digital data hub of the National Institutes of Health as well as data to support the preliminary development of the CDI. Phase II will involve data collection for the hub and contribute to continued refinement and validation of the CDI. While this study will focus on the development of a CDI, the digital platform will also be evaluated for feasibility and usability while clinicians deliver care to continuously monitored patients enrolled in the study. RESULTS Our target CDI will be a binary classifier trained to distinguish participants with and those without decompensation. The primary performance metric for CDI will be the area under the receiver operating characteristic curve with a minimum performance criterion of ≥0.75 (α=.05; power [1–β]=0.80). Furthermore, we will determine the sex or gender and race or ethnicity of the participants, which would account for differences in the CDI performance, as well as the lead time—time to predict decompensation—and its relationship with the ultimate disease severity based on the World Health Organization COVID-19 ordinal scale. CONCLUSIONS Using machine learning techniques on a large data set of patients with COVID-19 could provide valuable insights into the pathophysiology of COVID-19 and a digital biomarker for COVID-19 decompensation. Through this study, we intend to develop a tool that can uniquely reflect physiological data of a diverse population and contribute to high-quality data that will help researchers better understand COVID-19. CLINICALTRIAL ClinicalTrials.gov NCT04575532; https://www.clinicaltrials.gov/ct2/show/NCT04575532 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/27271

Introduction: Active cooling is more effective than targeted temperature management in improving sudden cardiac arrest (SCA) survival, but can be difficult to implement clinically. We are developing drugs that mimic cooling effects without the need for physical cooling. Cooling protection is mediated by Akt activation. PH domain and Leucine rich repeat Protein Phosphatases (PHLPP) is a phosphatase that negatively regulates Akt. We developed a cell-permeable peptide TAT-PHLPP9c that inhibits PHLPP and reaches heart and brain within 5 min of intravenous administration. Hypothesis: We hypothesize that TAT-PHLPP9c improves outcomes following SCA. This protection involves the improved early metabolic recovery. Methods: C57BL6 mice (n=20) were randomized to receive peptide treatment and appropriate blinding was ensured. A 12 min asystolic arrest was induced with KCl. CPR was started along with TAT-PHLPP9c (7.5 mg/kg) via i.v. Survival was evaluated. Cerebral blood flow (CBF) and metabolic chemical exchange saturation transfer (CEST) contrast were measured with endogenous and dynamic arterial spin labeling (ASL) and CEST MRI respectively. Glucose utilization was assessed by pyruvate dehydrogenase (PDH) phosphorylation and ATP generation. Further, blood taurine and glutamate were measured. Results: Compared to control, TAT-PHLPP9c significantly improved ROSC rates. 3 ROSC mice in the control group died within 10 min while 8 out of 10 ROSC mice in the treatment group survived over 1 h and 4 mice survived to 4 h despite a 12-min arrest. Progressively increased CBF and metabolic CEST contrast were observed in the treated mice compared to controls. p-PDH was decreased by TAT-PHLPP9c (increased activity) at 15 min post-ROSC in both heart and brain. ATP generation was replenished with the peptide treatment. Plasma taurine and glutamate concentrations was reduced by TAT-PHLPP9c as early as 5 min post-ROSC. Further, higher levels of taurine and glutamate were detected in the non-survivors than the survivors. Conclusions: This novel treatment strategy may have a high translational potential to reproduce critical outcomes of CPR cooling without physical cooling.

The aqueous outflow pathway of adult rabbit eyes with congenital glaucoma (buphthalmos) was examined by light microscopy and by scanning and transmission electron microscopy. The morphology of the buphthalmic rabbit aqueous outflow pathway was markedly abnormal when examined at 6 months, 1 yr, and 2 yr displaying apparent loss and/or compression of the iris pillars, dilation of the intertrabecular spaces, loss of endothelial cell-to-cell association and disorganization of trabecular lamellae, and posterior displacement of the aqueous plexus. In addition, the trabecular meshwork lamellae were observed only adjacent to the sclera and the inner portion of the trabecular meshwork was limited to swirls of collagen with scattered cells. These morphological findings suggest that the disease process in the rabbit principally involves an alteration in the differentiation and maintenance of the structural integrity of the trabecular meshwork. The loss of structural support of the buphthalmic trabecular meshwork may be a factor in the wide variation in intraocular pressure and may allow for compression of the trabecular meshwork against the aqueous plexus.