Treatment effects of blood pressure targets and hemodynamics according to initial blood lactate levels in comatose out-of-hospital cardiac arrest patients - A sub study of the BOX trial.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) survivors remaining comatose are often circulatory unstable with high mortality in the first days following resuscitation. Elevated lactate will reflect the severity and duration of hypoperfusion in cardiac arrest. Further, the severity of hypoperfusion could modify the effect on survival of different mean arterial blood pressure (MAP) targets. METHODS: In this sub-study of the BOX trial, adult successfully resuscitated comatose OHCA patients (n = 789) with a presumed cardiac cause were randomized to a MAP target of 63 mmHg vs. 77 mmHg. Patients were arbitrarily grouped in low-lactate: <25% of sample, medium-lactate: 25%-75%, and high >75 percentile according to blood lactate levels at hospital arrival as a surrogate of the severity of hypoperfusion. Invasive hemodynamic evaluations were performed using an arterial catheter and pulmonary artery catheter (PAC), and data from admission to 48 hours (h) were recorded. Logistic regression analysis evaluated whether lactate levels (as continuous and categorical) modify the effect of MAP targets on mortality at 365 days. RESULTS: The three lactate groups had initial lactate levels of low-lactate: <2.9 mmol/L, medium-lactate: 2.9-7.9 mmol/L, and high-lactate > 7.9 mmol/L. All patients were randomized to a 63 mmHg or 77 mmHg MAP target. The proportion of patients in the high-MAP target group was 100/201 (50%), 178/388 (46%), and 114/197 (58%) for low, medium, and high-lactate groups respectively. At admission, the high-lactate groups had a lower MAP compared to the medium-lactate (2.6 mmHg (95% CI: 0.1-5.0 mmHg, p = 0.02), and the low-lactate group, (3.6 mmHg (95% CI: 0.8-6.5 mmHg, p < 0.01). Accordingly, the vasoactive inotropic score was 79% (95%CI: 42%-124%%) higher with increasing initial lactate level (High-lactate vs. low-lactate) with the largest difference at 6 hours (110.6% (95%CI: 54.4%-187.2%) higher in high-lactate patients). No difference in the cardiac index or systemic vascular resistance was observed between lactate groups. The initial lactate level (continuous) modified the effect of the two MAP targets (p = 0.04). In the highest lactate group, the mortality was 100/197 (51%), and with an odds ratio (OR): 1.7 (95%CI: 0.9-3.0) if randomized to MAP 77 mmHg compared to MAP 63 mmHg. In the lowest lactate group, the mortality was 35/201(17%) and similar if randomized to a MAP target of 77 mmHg (OR: 1.1 (95% CI: 0.5-2.3)). CONCLUSION: Comatose OHCA patients with high initial lactate levels required more vasoactive drugs on the first two days of ICU admission to meet the blood pressure target and had a poorer prognosis. No indication that aiming for a higher MAP target is beneficial in patients with an initial high lactate level was found, however, given the post-hoc nature of this study, these results should be considered hypothesis-generating.

Survival and neurological outcome after bystander versus lay responder defibrillation in out-of-hospital cardiac arrest: A sub-study of the BOX trial.

BACKGROUND AND AIM: Bystander defibrillation is associated with increased survival with good neurological outcome after out-of-hospital cardiac arrest (OHCA). Dispatch of lay responders could increase defibrillation rates, however, survival with good neurological outcome in these remain unknown. The aim was to compare long-term survival with good neurological outcome in bystander versus lay responder defibrillated OHCAs. METHODS: This is a sub-study of the BOX trial, which included OHCA patients from two Danish tertiary cardiac intensive care units from March 2017 to December 2021. The main outcome was defined as 3-month survival with good neurological performance (Cerebral Performance Category of 1or 2, on a scale from 1 (good cerebral performance) to 5 (death or brain death)). For this study EMS witnessed OHCAs were excluded. RESULTS: Of the 715 patients, a lay responder arrived before EMS in 125 cases (16%). In total, 81 patients were defibrillated by a lay responder (11%), 69 patients by a bystander (10%) and 565 patients by the EMS staff (79%). The 3-month survival with good neurological outcome was 65% and 81% in the lay responder and bystander defibrillated groups, respectively (P = 0.03). CONCLUSION: In patients with OHCA, 3-month survival with good neurological outcome was higher in bystander defibrillated patients compared with lay responder defibrillated patients.

Duration of Device-Based Fever Prevention after Cardiac Arrest.

BACKGROUND: Guidelines recommend active fever prevention for 72 hours after cardiac arrest. Data from randomized clinical trials of this intervention have been lacking. METHODS: We randomly assigned comatose patients who had been resuscitated after an out-of-hospital cardiac arrest of presumed cardiac cause to device-based temperature control targeting 36°C for 24 hours followed by targeting of 37°C for either 12 or 48 hours (for total intervention times of 36 and 72 hours, respectively) or until the patient regained consciousness. The primary outcome was a composite of death from any cause or hospital discharge with a Cerebral Performance Category of 3 or 4 (range, 1 to 5, with higher scores indicating more severe disability; a category of 3 or 4 indicates severe cerebral disability or coma) within 90 days after randomization. Secondary outcomes included death from any cause and the Montreal Cognitive Assessment score (range, 0 to 30, with higher scores indicating better cognitive ability) at 3 months. RESULTS: A total of 393 patients were randomly assigned to temperature control for 36 hours, and 396 patients were assigned to temperature control for 72 hours. At 90 days after randomization, a primary end-point event had occurred in 127 of 393 patients (32.3%) in the 36-hour group and in 133 of 396 patients (33.6%) in the 72-hour group (hazard ratio, 0.99; 95% confidence interval, 0.77 to 1.26; P = 0.70) and mortality was 29.5% in the 36-hour group and 30.3% in the 72-hour group. At 3 months, the median Montreal Cognitive Assessment score was 26 (interquartile range, 24 to 29) and 27 (interquartile range, 24 to 28), respectively. There was no significant between-group difference in the incidence of adverse events. CONCLUSIONS: Active device-based fever prevention for 36 or 72 hours after cardiac arrest did not result in significantly different percentages of patients dying or having severe disability or coma. (Funded by the Novo Nordisk Foundation; BOX ClinicalTrials.gov number, NCT03141099.).

Blood-Pressure Targets in Comatose Survivors of Cardiac Arrest.

BACKGROUND: Evidence to support the choice of blood-pressure targets for the treatment of comatose survivors of out-of-hospital cardiac arrest who are receiving intensive care is limited. METHODS: In a double-blind, randomized trial with a 2-by-2 factorial design, we evaluated a mean arterial blood-pressure target of 63 mm Hg as compared with 77 mm Hg in comatose adults who had been resuscitated after an out-of-hospital cardiac arrest of presumed cardiac cause; patients were also assigned to one of two oxygen targets (reported separately). The primary outcome was a composite of death from any cause or hospital discharge with a Cerebral Performance Category (CPC) of 3 or 4 within 90 days (range, 0 to 5, with higher categories indicating more severe disability; a category of 3 or 4 indicates severe disability or coma). Secondary outcomes included neuron-specific enolase levels at 48 hours, death from any cause, scores on the Montreal Cognitive Assessment (range, 0 to 30, with higher scores indicating better cognitive ability) and the modified Rankin scale (range, 0 to 6, with higher scores indicating greater disability) at 3 months, and the CPC at 3 months. RESULTS: A total of 789 patients were included in the analysis (393 in the high-target group and 396 in the low-target group). A primary-outcome event occurred in 133 patients (34%) in the high-target group and in 127 patients (32%) in the low-target group (hazard ratio, 1.08; 95% confidence interval [CI], 0.84 to 1.37; P = 0.56). At 90 days, 122 patients (31%) in the high-target group and 114 patients (29%) in the low-target group had died (hazard ratio, 1.13; 95% CI, 0.88 to 1.46). The median CPC was 1 (interquartile range, 1 to 5) in both the high-target group and the low-target group; the corresponding median modified Rankin scale scores were 1 (interquartile range, 0 to 6) and 1 (interquartile range, 0 to 6), and the corresponding median Montreal Cognitive Assessment scores were 27 (interquartile range, 24 to 29) and 26 (interquartile range, 24 to 29). The median neuron-specific enolase level at 48 hours was also similar in the two groups. The percentages of patients with adverse events did not differ significantly between the groups. CONCLUSIONS: Targeting a mean arterial blood pressure of 77 mm Hg or 63 mm Hg in patients who had been resuscitated from cardiac arrest did not result in significantly different percentages of patients dying or having severe disability or coma. (Funded by the Novo Nordisk Foundation; BOX ClinicalTrials.gov number, NCT03141099.).

Oxygen Targets in Comatose Survivors of Cardiac Arrest.

BACKGROUND: The appropriate oxygenation target for mechanical ventilation in comatose survivors of out-of-hospital cardiac arrest is unknown. METHODS: In this randomized trial with a 2-by-2 factorial design, we randomly assigned comatose adults with out-of-hospital cardiac arrest in a 1:1 ratio to either a restrictive oxygen target of a partial pressure of arterial oxygen (Pao2) of 9 to 10 kPa (68 to 75 mm Hg) or a liberal oxygen target of a Pao2 of 13 to 14 kPa (98 to 105 mm Hg); patients were also assigned to one of two blood-pressure targets (reported separately). The primary outcome was a composite of death from any cause or hospital discharge with severe disability or coma (Cerebral Performance Category [CPC] of 3 or 4; categories range from 1 to 5, with higher values indicating more severe disability), whichever occurred first within 90 days after randomization. Secondary outcomes were neuron-specific enolase levels at 48 hours, death from any cause, the score on the Montreal Cognitive Assessment (ranging from 0 to 30, with higher scores indicating better cognitive ability), the score on the modified Rankin scale (ranging from 0 to 6, with higher scores indicating greater disability), and the CPC at 90 days. RESULTS: A total of 789 patients underwent randomization. A primary-outcome event occurred in 126 of 394 patients (32.0%) in the restrictive-target group and in 134 of 395 patients (33.9%) in the liberal-target group (hazard ratio, 0.95; 95% confidence interval, 0.75 to 1.21; P = 0.69). At 90 days, death had occurred in 113 patients (28.7%) in the restrictive-target group and in 123 (31.1%) in the liberal-target group. On the CPC, the median category was 1 in the two groups; on the modified Rankin scale, the median score was 2 in the restrictive-target group and 1 in the liberal-target group; and on the Montreal Cognitive Assessment, the median score was 27 in the two groups. At 48 hours, the median neuron-specific enolase level was 17 µg per liter in the restrictive-target group and 18 µg per liter in the liberal-target group. The incidence of adverse events was similar in the two groups. CONCLUSIONS: Targeting of a restrictive or liberal oxygenation strategy in comatose patients after resuscitation for cardiac arrest resulted in a similar incidence of death or severe disability or coma. (Funded by the Novo Nordisk Foundation; BOX ClinicalTrials.gov number, NCT03141099.).

Longer retrieval distances to the automated external defibrillator reduces survival after out-of-hospital cardiac arrest.

AIMS: To evaluate and compare survival after out-of-hospital (OHCA), where an automated external defibrillator (AED) was used, in densely, moderately and thinly populated areas. Also, to evaluate the association between AED retrieval distance and survival after OHCA. METHODS: From 2014 to 2018, AEDs used during OHCA in the region of Southern Denmark were systematically collected. OHCAs were included if the OHCA address was known. OHCAs at nursing homes were excluded. To evaluate population density, a map with 1000 × 1000 meter grid cells was used with each cell color-graded according to the number of inhabitants. Densely, moderately and thinly populated areas were defined as ≥200 inhabitants, 20-199 inhabitants and 0-19 inhabitants per km2, respectively. Primary outcome was 30-day survival. RESULTS: A total of 423 cases of OHCA were included, of which 207 (49%) occurred in densely populated areas, while 78 (18%) and 138 (33%) occurred in moderately and thinly populated areas, respectively. AED retrieval distances were: densely populated 105 m (IQR 5-450), moderately populated 220 m (IQR 5-450) and thinly populated 350 m (IQR 5-1500) (P < 0.001). Thirty-day survival was 40%, 31% and 34%, respectively (P = 0.3). In a multivariable regression analysis, mortality increased with 10% per 100 m an AED was placed further away from the site of OHCA. CONCLUSION: Survival after OHCA, where an AED was used, did not seem to differ in thinly, moderately and densely populated areas. The length of the AED retrieval distance, however, was correlated with reduced survival after adjusting for other potentially explanatory variables.

Use and coverage of automated external defibrillators according to location in out-of-hospital cardiac arrest.

AIMS: To evaluate 1) the relative use of automated external defibrillators (AEDs) at different types of AED locations 2) the percentage of AEDs crossing location types during OHCA before use 3) the AED coverage distance at different types of AED locations, and 4) the 30-day-survival in different subgroups. METHODS: From 2014-2018, AEDs used by bystanders during out-of-hospital cardiac arrest (OHCA) in the Region of Southern Denmark were collected. Data regarding registered AEDs was retrieved from the national AED-network. The OHCA site and AED placement was categorized into; 1) Residential; 2) Public; 3) Nursing home, 4) Company/workplace; 5) Institution; 6) Health clinic and 7) Sports facility/recreational. To evaluate 30-day-survival, groups 4-7 were pooled into one Mixed group. RESULTS: In total 509 OHCAs were included. There was high relative usage of AEDs from public places, nursing homes, health clinics and sports facilities, and low relative usage from companies/workplaces, residential areas and institutions. Of AEDs used during residential OHCAs 39% were collected from public places. AEDs placed in residential areas and public places had a coverage of 575 m (IQR 130-1300) and 270 m (IQR5-550), respectively. Thirty-day- survival in public, residential and mixed groups were 49%, 14% and 67%, respectively. CONCLUSION: The relative use of AEDs from public places, nursing homes, sports facilities and health clinics was high, and AEDs used during OHCA in residential areas were most frequently collected from public places. AEDs placed in both residential areas and public places may have a wider coverage area than proposed in current literature.

Global positioning system alerted volunteer first responders arrive before emergency medical services in more than four out of five emergency calls.

AIM: To evaluate response rates for volunteer first responders (VFRs) activated by use of a smartphone GPS-tracking system and to compare response times of VFRs with those of emergency medical services (EMS). Furthermore, to evaluate 30-day-survival after out-of-hospital cardiac arrest (OHCA) on a rural island. METHODS: Since 2012 a GPS-tracking system has been used on a rural island to activate VFRs during all emergency calls requesting an EMS. When activated, three VFRs were recruited and given distinct roles, including collection of the nearest automatic external defibrillator (AED). We retrospectively investigated EMS response data from April 2012 to December 2017. These were matched with VFR response times from the GPS-tracking system. The 30-day survival in OHCA patients was also assessed. RESULTS: In 2266 of 2662 emergency calls (85%) at least one VFR arrived to the site before EMS. Median response times for VFRs (n = 2662) was 4:46 min:sec (IQR 3:16-6:52) compared with 10:13 min:sec (6:14-13:41) for EMS (p < 0.0001). A total of 17 OHCAs took place in public locations and 65 in residential areas. Thirty-day survival in these were 24% and 15%, respectively. CONCLUSION: Use of a smartphone GPS-tracking system to dispatch VFRs ensures that in more than four of five cases, a VFR arrives to the site before EMS. Response times for VFRs were also found to be lower than EMS response times. Finally, the 30-day survival of OHCA patients in a rural area, based on these results, surpass our expectations.

Different Causes of Death in Patients with Myocardial Infarction Type 1, Type 2, and Myocardial Injury.

BACKGROUND: Data outlining the mortality and the causes of death in patients with type 1 myocardial infarction, type 2 myocardial infarction, and those with myocardial injury are limited. METHODS: During a 1-year period from January 2010 to January 2011, all hospitalized patients who had cardiac troponin I measured on clinical indication were prospectively studied. Patients with at least one cardiac troponin I value >30 ng/L underwent case ascertainment and individual evaluation by an experienced adjudication committee. Patients were classified as having type 1 myocardial infarction, type 2 myocardial infarction, or myocardial injury according to the criteria of the universal definition of myocardial infarction. Follow-up was ensured until December 31, 2014. Data on mortality and causes of death were obtained from the Danish Civil Registration System and the Danish Register of Causes of Death. RESULTS: Overall, 3762 consecutive patients were followed for a mean of 3.2 years (interquartile range 1.3-3.6 years). All-cause mortality differed significantly among categories: Type 1 myocardial infarction 31.7%, type 2 myocardial infarction 62.2%, myocardial injury 58.7%, and 22.2% in patients with nonelevated troponin values (log-rank test; P < .0001). In patients with type 1 myocardial infarction, 61.3% died from cardiovascular causes, vs 42.6% in patients with type 2 myocardial infarction (P = .015) and 41.2% in those with myocardial injury (P < .0001). The overall mortality and the causes of death did not differ substantially between patients with type 2 myocardial infarction and those with myocardial injury. CONCLUSIONS: Patients with type 2 myocardial infarction and myocardial injury exhibit a significantly higher long-term mortality compared with patients with type 1 myocardial infarction . However, most patients with type 1 myocardial infarction die from cardiovascular causes in contrast to patients with type 2 myocardial infarction and myocardial injury, in whom noncardiovascular causes of death predominate.

Incidence, Frequency, and Clinical Characteristics of Type 3 Myocardial Infarction in Clinical Practice.

OBJECTIVES: Cardiac death in a patient with symptoms and electrocardiographic changes indicative of myocardial ischemia but without available measurements of cardiac biomarkers is designated a type 3 myocardial infarction. We wanted to investigate the incidence, the frequency, and the characteristics of patients diagnosed as type 3 myocardial infarction. METHODS: The occurrence of deaths in a well-defined geographic region was retrieved from the Danish Civil Registration System during a 1-year period from 2010 to 2011. Complementary data concerning causes of deaths were obtained from the Danish Register of Causes of Death, and ambulance and hospital patient files. Adjudication of the diagnosis was done by 2 local experts and one external senior cardiologist. RESULTS: A total of 2766 of the 246,723 adult residents in the region had died. A type 3 myocardial infarction was diagnosed in 18 individuals, corresponding to an annual incidence of 7.3/100,000 person-years. During the same 1-year period, 488 patients had other types of myocardial infarction implying a 3.6% frequency of type 3 myocardial infarction (18 of 506) among all myocardial infarctions. CONCLUSION: Type 3 myocardial infarction is a rare observation in clinical practice with an annual incidence below 10/100,000 person-years and a frequency of 3%-4% among all types of myocardial infarction. If autopsy data are included, the number of type 3 myocardial infarctions will increase.

Prognostic Impact of Myocardial Injury Related to Various Cardiac and Noncardiac Conditions.

BACKGROUND: Elevated cardiac troponins in clinical conditions other than myocardial infarction are well known. For such occurrences, the term "myocardial injury" has been proposed. The long-term outcome in patients with myocardial injury related to various cardiac and noncardiac clinical disorders is unknown. METHODS: During January 2010 to January 2011, we prospectively studied hospitalized patients who had cardiac troponin I measured on clinical indication. Patients with cardiac troponin I values >30 ng/L and no evidence of myocardial ischemia were diagnosed as having myocardial injury. Patients were classified into 5 categories of plausible related conditions: cardiac ischemic, cardiac nonischemic, noncardiac, multifactorial, or indeterminate. Follow-up was a minimum of 3 years, with all-cause mortality as the single end-point. RESULTS: A total of 3762 patients were considered, of whom 1089 (29%) had myocardial injury. The most common associated conditions were noncardiac (n = 346) or multifactorial (n = 359). Cardiac ischemic (n = 183) and cardiac nonischemic (n = 134) conditions occurred less frequently. After a median of 3.2 years, 645 patients (59%) had died. A multivariate Cox regression analysis showed no difference in mortality between patients with cardiac ischemic and cardiac nonischemic conditions (hazard ratio [HR] 0.75; 95% confidence interval [CI], 0.50-1.13; P = .2). Patients with noncardiac or multifactorial disorders, however, had significantly higher mortality than those with associated cardiac ischemic conditions (HR 1.39; 95% CI, 1.06-1.80; P = .02, and HR 1.94; 95% CI, 1.50-2.51; P <.001), respectively. CONCLUSIONS: In patients with myocardial injury, the most common associated conditions were noncardiac or multifactorial. Of notice, these patients had significantly higher long-term mortality when compared with those with associated cardiac conditions.

Clinical Characteristics and Outcomes of Patients with Myocardial Infarction, Myocardial Injury, and Nonelevated Troponins.

BACKGROUND: Cardiac troponins have emerged as the preferred biomarkers for detecting myocardial necrosis and diagnosing myocardial infarction. However, current cardiac troponin assays do not discriminate between ischemic and nonischemic causes of myocardial cell death. Thus, when an increased troponin value is encountered in the absence of obvious myocardial ischemia, a careful search for other clinical conditions is crucial. METHODS: In 2010 to 2011, we prospectively studied hospitalized patients who had cardiac troponin I measured on clinical indication. An acute myocardial infarction was diagnosed in cases of a cardiac troponin I increase or decrease pattern with at least 1 value >30 ng/L (99th percentile) together with myocardial ischemia. Myocardial injury was defined as cardiac troponin I values >30 ng/L, but without signs or symptoms indicating overt cardiac ischemia. Patients with peak values ≤30 ng/L were classified as nonelevated cardiac troponin I. Follow-up was at least 3 years with all-cause mortality as the sole clinical end point. RESULTS: A total of 3762 patients were included. Of these, 488 (13%) had acute myocardial infarction, 1089 (29%) had myocardial injury, and 2185 (58%) had nonelevated cardiac troponin I values. Patients with myocardial injury frequently presented with dyspnea, were older, and had more comorbidity than patients in the 2 other groups. During a median follow-up of 3.2 years, 1342 patients died. Mortality differed significantly between groups: 39% in those with myocardial infarction, 59% in those with myocardial injury, and 23% in those with nonelevated cardiac troponin I (log-rank test; P < .0001). No significant difference in mortality between patients with type 2 myocardial infarction and patients with myocardial injury was observed (63% and 59%, respectively). CONCLUSIONS: Patients with myocardial injury are older and have more comorbidity than those with acute myocardial infarction. Both groups exhibit a poorer prognosis than patients with nonelevated cardiac troponin I values. Of note, a very high long-term mortality is observed in patients with type 2 myocardial infarction and patients with myocardial injury.

Diagnosis of unstable angina pectoris has declined markedly with the advent of more sensitive troponin assays.

BACKGROUND: Since the arrival of the universal definition of myocardial infarction more sensitive troponin assays have been developed. How these occurrences have influenced the proportions and clinical features of the components of acute coronary syndrome have not been studied prospectively in unselected hospital patients. METHODS: During 2010 we evaluated all patients in whom cardiac troponin I had been measured at a single university hospital. The diagnosis of acute myocardial infarction (ST-elevation myocardial infarction [STEMI] or non-ST-elevation myocardial infarction [NSTEMI]) was established in cases of a rise and/or fall of cardiac troponin I together with cardiac ischemic features. Patients with unstable chest discomfort and cardiac troponin I values below the decision limit of myocardial infarction were diagnosed as having unstable angina pectoris. The definition of acute coronary syndrome included unstable angina pectoris, NSTEMI, and STEMI. Mortality data were obtained from the Danish Civil Personal Registration System. RESULTS: Of 3762 consecutive patients, 516 had acute coronary syndrome. Unstable angina pectoris was present in 7%, NSTEMI in 67%, and STEMI in 26%. The NSTEMI patients were older, more frequently women, and had more comorbidities than patients with unstable angina pectoris and STEMI. At median follow-up of 3.2 years 195 patients had died: 14% of unstable angina pectoris, 45% of NSTEMI, and 25% of STEMI patients. Age-adjusted log-rank statistics revealed differences in mortality: NSTEMI vs unstable angina pectoris (P = .0091) and NSTEMI vs STEMI (P = .0045). CONCLUSIONS: The application of the universal definition together with the use of a contemporary troponin assay seems to have reduced the proportion of patients with unstable angina pectoris to the benefit of patients with NSTEMI. Despite this, NSTEMI patients have a sustained higher mortality than patients with STEMI.