Inflammatory response after prehospital high-dose glucocorticoid to patients resuscitated from out-of-hospital cardiac arrest: A sub-study of the STEROHCA trial.

BACKGROUND: The post-cardiac arrest syndrome (PCAS) after out-of-hospital cardiac arrest (OHCA) is characterized by a series of pathological events, including inflammation. In the randomized "STERoid for OHCA" (STEROHCA) trial, prehospital high-dose glucocorticoid decreased interleukin (IL) 6 and C-reactive protein levels following resuscitated OHCA. The aim of this predefined sub-study was to assess the inflammatory response the first three days of admission. METHODS: The STEROHCA trial enrolled 137 OHCA patients randomized to either a single prehospital injection of methylprednisolone 250 mg or placebo. Inflammatory markers, including pro- and anti-inflammatory cytokines, were analyzed in plasma samples, from 0-, 24-, 48-, and 72 h post-admission. Mixed-model analyses were applied using log-transformed data to assess group differences. RESULTS: The 137 patients included in this sub-study had a median age of 67 years (57 to 74), and the 180-day survival rates were 75% (n = 51/68) and 64% (n = 44/69) in the glucocorticoid and placebo group, respectively. A total of 130 (95%) patients had at least one plasma sample available. The anti-inflammatory cytokine IL-10 was increased at hospital admission in the glucocorticoid group (ratio 2.74 (1.49-5.05), p = 0.006), but the intervention showed the strongest effect after 24 h, decreasing pro-inflammatory levels of IL-6 (ratio 0.06 (0.03-0.10), p < 0.001), IL-8 (ratio 0.53 (0.38-0.75), p < 0.001), macrophage chemokine protein-1 (MCP-1, ratio 0.02 (0.13-0.31), p < 0.001), macrophage inflammatory protein-1-beta (MIP-1b, ratio 0.28 (0.18-0.45), p < 0.001), and tumor necrosis factor-α (TNF-α, ratio 0.6 (0.4-0.8), p = 0.01). CONCLUSION: Administering high-dose glucocorticoid treatment promptly after resuscitation from OHCA influenced the inflammatory response with a reduction in several systemic proinflammatory cytokines after 24 h. TRIAL REGISTRATION: EudraCT number: 2020-000855-11; submitted March 30, 2020. URL: https://www. CLINICALTRIALS: gov; Unique Identifier: NCT04624776.

Prehospital high-dose methylprednisolone in resuscitated out-of-hospital cardiac arrest patients (STEROHCA): a randomized clinical trial.

PURPOSE: Patients who are successfully resuscitated following out-of-hospital cardiac arrest (OHCA) are still at a high risk of neurological damage and death. Inflammation and brain injury are components of the post-cardiac arrest syndrome, and can be assessed by systemic interleukin 6 (IL-6) and neuron-specific enolase (NSE). Anti-inflammatory treatment with methylprednisolone may dampen inflammation, thereby improving outcome. This study aimed to determine if prehospital high-dose methylprednisolone could reduce IL-6 and NSE in comatose OHCA patients. METHODS: The STEROHCA trial was a randomized, blinded, placebo-controlled, phase II prehospital trial performed at two cardiac arrest centers in Denmark. Resuscitated comatose patients with suspected cardiac etiology were randomly assigned 1:1 to a single intravenous injection of 250 mg methylprednisolone or placebo. The co-primary outcome was reduction of IL-6 and NSE-blood levels measured daily for 72 h from admission. The main secondary outcome was survival at 180 days follow-up. RESULTS: We randomized 137 patients to methylprednisolone (n = 68) or placebo (n = 69). We found reduced IL-6 levels (p < 0.0001) in the intervention group, with median (interquartile range, IQR) levels at 24 h of 2.1 pg/ml (1.0; 7.1) and 30.7 pg/ml (14.2; 59) in the placebo group. We observed no difference between groups in NSE levels (p = 0.22), with levels at 48 h of 18.8 ug/L (14.4; 24.6) and 14.8 ug/L (11.2; 19.4) in the intervention and placebo group, respectively. In the intervention group, 51 (75%) patients survived and 44 (64%) in the placebo group. CONCLUSION: Prehospital treatment with high-dose methylprednisolone to resuscitated comatose OHCA patients, resulted in reduced IL-6 levels after 24 h, but did not reduce NSE levels.

Assessing optimal methods for transferring machine learning models to low-volume and imbalanced clinical datasets: experiences from predicting outcomes of Danish trauma patients.

Introduction: Accurately predicting patient outcomes is crucial for improving healthcare delivery, but large-scale risk prediction models are often developed and tested on specific datasets where clinical parameters and outcomes may not fully reflect local clinical settings. Where this is the case, whether to opt for de-novo training of prediction models on local datasets, direct porting of externally trained models, or a transfer learning approach is not well studied, and constitutes the focus of this study. Using the clinical challenge of predicting mortality and hospital length of stay on a Danish trauma dataset, we hypothesized that a transfer learning approach of models trained on large external datasets would provide optimal prediction results compared to de-novo training on sparse but local datasets or directly porting externally trained models. Methods: Using an external dataset of trauma patients from the US Trauma Quality Improvement Program (TQIP) and a local dataset aggregated from the Danish Trauma Database (DTD) enriched with Electronic Health Record data, we tested a range of model-level approaches focused on predicting trauma mortality and hospital length of stay on DTD data. Modeling approaches included de-novo training of models on DTD data, direct porting of models trained on TQIP data to the DTD, and a transfer learning approach by training a model on TQIP data with subsequent transfer and retraining on DTD data. Furthermore, data-level approaches, including mixed dataset training and methods countering imbalanced outcomes (e.g., low mortality rates), were also tested. Results: Using a neural network trained on a mixed dataset consisting of a subset of TQIP and DTD, with class weighting and transfer learning (retraining on DTD), we achieved excellent results in predicting mortality, with a ROC-AUC of 0.988 and an F2-score of 0.866. The best-performing models for predicting long-term hospitalization were trained only on local data, achieving an ROC-AUC of 0.890 and an F1-score of 0.897, although only marginally better than alternative approaches. Conclusion: Our results suggest that when assessing the optimal modeling approach, it is important to have domain knowledge of how incidence rates and workflows compare between hospital systems and datasets where models are trained. Including data from other health-care systems is particularly beneficial when outcomes are suffering from class imbalance and low incidence. Scenarios where outcomes are not directly comparable are best addressed through either de-novo local training or a transfer learning approach.

Out-of-Hospital Cardiac Arrest in Individuals With Human Immunodeficiency Virus: A Nationwide Population-Based Cohort Study.

BACKGROUND: Little data exist on the risk and outcomes of out-of-hospital cardiac arrest (OHCA) in people with HIV (PWH). We aimed to describe OHCA in PWH as compared with the general population in terms of incidence, characteristics, and survival. METHODS: This nationwide study assessed all individuals aged 18-85 years between 2001 and 2019 in Denmark. The cumulative incidence of OHCA was computed using cause-specific Cox models accounting for competing risk of death. RESULTS: Among 6 565 309 individuals, 6 925 (median age: 36; interquartile range [IQR]: 28-44 y; 74% males) were infected at some point with HIV. The incidence of OHCA was 149 (95% CI: 123-180)/100 000 person-years in PWH versus 64 (95% CI: 64-65)/100 000 person-years in people without HIV (P < .001). Age at the time of cardiac arrest was 52 (IQR: 44-61) years in PWH versus 69 (IQR: 59-77) years in individuals without HIV (P < .001). In a multivariable model adjusted for age, sex, hypertension, diabetes, heart failure, ischemic heart disease, atrial fibrillation, chronic obstructive pulmonary disease, cancer, and renal failure, PWH had a 2-fold higher risk of OHCA (hazard ratio: 2.84; 95% CI: 2.36-3.43; P < .001). Thirty-day mortality (89% vs 88%; P = .80) was comparable to individuals without HIV. CONCLUSIONS: HIV is an independent risk factor for OHCA, and those who experience OHCA with HIV are much younger than those without HIV. Almost 90% of PWH died 1 month after OHCA. Further research should strive to find out how to reduce OHCA occurrence in this population.

Steroid treatment as anti-inflammatory and neuroprotective agent following out-of-hospital cardiac arrest: a randomized clinical trial.

BACKGROUND: Patients resuscitated from out-of-hospital cardiac arrest (OHCA) have a high morbidity and mortality risk and often develop post-cardiac arrest syndrome (PCAS) involving systemic inflammation. The severity of the inflammatory response is associated with adverse outcome, with anoxic irreversible brain injury as the leading cause of death following resuscitated OHCA. The study aimed to investigate the anti-inflammatory and neuroprotective effect of pre-hospital administration of a high-dose glucocorticoid following OHCA. METHODS: The study is an investigator-initiated, randomized, multicenter, single-blinded, placebo-controlled, clinical trial. Inclusion will continue until one hundred twenty unconscious OHCA patients surviving a minimum of 72 h are randomized. Intervention is a 1:1 randomization to an infusion of methylprednisolone 250 mg following a minimum of 5 min of sustained return of spontaneous circulation in the pre-hospital setting. Methylprednisolone will be given as a bolus infusion of 1 × 250 mg (1 × 4 mL) over a period of 5 min. Patients allocated to placebo will receive 4 mL of isotonic saline (NaCl 0.9%). Main eligibility criteria are OHCA of presumed cardiac cause, age ≥ 18 years, Glasgow Coma Scale ≤ 8, and sustained ROSC for at least 5 min. Co-primary endpoint: Reduction of interleukin-6 and neuron-specific-enolase. Secondary endpoints: Markers of inflammation, brain, cardiac, kidney and liver damage, hemodynamic and hemostatic function, safety, neurological function at follow-up, and mortality. A research biobank is set up with blood samples taken daily during the first 72 h from hospitalization to evaluate primary and secondary endpoints. DISCUSSION: We hypothesize that early anti-inflammatory steroid treatment in the pre-hospital setting can mitigate the progression of PCAS following resuscitated OHCA. Primary endpoints will be assessed through analyses of biomarkers for inflammation and neurological damage taken during the first 72 h of admission. TRIAL REGISTRATION: EudraCT number: 2020-000855-11 ; submitted March 30, 2020 ClinicalTrials.gov Identifier: NCT04624776; submitted October 12, 2020, first posted November 10, 2020.