Essay Writing Service

1 Star2 Stars3 Stars4 Stars5 Stars (No Ratings Yet)
Loading...

Utilization of Mechanical Circulatory Support in Patients Hospitalized After Out-of-Hospital Cardiac Arrest

do not necessarily reflect the views of UKDiss.com.

Trends in Utilization of Mechanical Circulatory Support in Patients Hospitalized After Out-of-Hospital Cardiac Arrest

Abstract:

Objective: This study sought to examine the trends and predictors of mechanical circulatory support (MCS) use in patients hospitalized after out-of-hospital cardiac arrest (OHCA).

Background: There is a paucity of data regarding MCS use in patients hospitalized after OHCA.

Methods: We conducted an observational analysis of MCS use in 985,861 patients hospitalized after OHCA between January 2008 and December 2014 in the Nationwide Inpatient Sample database. On multivariable analysis, we also assessed factors associated with MCS use and survival to discharge.

Results: Among the 985,861 patients, 52,842 (5.4%) had MCS utilized. Intra-aortic balloon pump (IABP) was the most commonly used MCS after OHCA with frequency of 48,307 (4.9%), followed by extracorporeal membrane oxygenation (ECMO) 3,746 (0.4%), and percutaneous ventricular assist devices (PVAD) 3,352 (0.3%). From 2008 to 2014, there was a relative increase in the utilization of MCS by 13.6% from 5% in 2008 to 5.7% in 2014 (P trend < 0.001). The use of IABP demonstrated a decline by 4.3% from 2008 to 2014 (4.9% to 4.7%, P trend <0.001), whereas PVAD use increased by 1700% (0.04% to 0.7%, P trend <0.001), and ECMO use increased by 392% (0.1% to 0.7%, P trend <0.001). Younger, male patients with myocardial infarction, higher co-morbid conditions, VT/VF as initial rhythm, and presentation to a large urban hospital were more likely to receive percutaneous MCS implantation. Survival to discharge was significantly higher in patients who were selected to receive MCS (56.9% vs. 43.1%, OR: 1.16, 95% CI: (1.11-1.21), p-value <0.001).

ConclusionsThere is a steady increase in the use of MCS in OHCA, especially PVAD and ECMO, despite lack of randomized clinical trial data supporting their outcomes. Our study shows a possible suggestion of better outcomes in this highly selected group of patients.  More definitive randomized studies are needed to assess accurately the optimal role of MCS in this patient population.

Key Words: Out of hospital cardiac arrest, mechanical circulatory support, intra-aortic balloon pump, extra corporeal bypass with membrane oxygenator, percutaneous ventricular assist device

 

 

 

 

 

 

 

 

 

Abbreviations:

OHCA: Out of hospital cardiac Arrest

MCS: Mechanical circulatory support

PVAD: Percutaneous ventricular assist device

ECMO: Extra corporeal bypass with membrane oxygenator

PVAD: Percutaneous ventricular assist device

CS: Cardiogenic shock

VT: Ventricular tachycardia

Vfib: Ventricular fibrillation

PEA: Pulseless electric activity

 

Introduction:

In the Unites States, each year approximately 360,000 people experience emergency medical service (EMS) assessed out of hospital cardiac arrest (OHCA) 1.There are several factors that play a role in determining survival after the OHCA i.e., age, initial rhythm, resuscitation delay, delays in intubation and defibrillation etc2-4. Mortality within 24 hours of return of spontaneous circulation (ROSC) typically is attributed to refractory shock leading to recurrent cardiac arrest or multi-organ system failure5,6 (5-8). Cardiogenic shock (CS) requiring vasopressor support is seen in up to 50% of the survivors of OHCA7 (9). Higher mean arterial pressures after OHCA are associated with better survival8 (10). Historically, mechanical circulatory support (MCS) was limited to intra-aortic balloon pumps (IABP)  and ECMO9-11 (11-13). Since IABP were not associated with improvement in mortality, their use compared with newer devices has been challenged (14, 15). Other MCS devices, such as Impella (Abiomed Inc., Danvers, Massachusetts), Tandem Heart (Cardiac Assist, Inc., Pittsburgh, Pennsylvania), and ECMO, which possess an ability to provide greater hemodynamic support than IABP, have a potential to improve clinical outcomes13-15 (16-18). As defined by the 2015 Society for Cardiovascular Angiography and Interventions/American College of Cardiology/Heart Failure Society of America/Society of Thoracic Surgeons Clinical Expert Consensus on the use of percutaneous MCS in cardiovascular care, the primary objective of MCS is to reduce myocardial oxygen demand and left ventricular stroke work while providing adequate coronary perfusion16(19). There is a paucity of data with regards to the trends of MCS use after OHCA in the United States. We studied the national inpatient sample (NIS) database to examine the current trends of MCS in patients with OHCA.

Methods:

Data Source:

Data were obtained from 2008-2014 NIS databases. NIS database is a part of the Healthcare Cost and Utilization Project (HCUP), sponsored by the Agency for Healthcare Research and Quality. Details regarding NIS have been previously described17(20). In brief, NIS is the largest publicly available inpatient health care database in the United States and contains the data of 20% stratified sample of US community hospitals. Discharge weights are provided for each patient discharge record and can be used to obtain national estimates. Data in NIS are drawn from all the states participating in HCUP, which make up to 97% of the US population. NIS has the data from approximately 8 million hospitalizations. Each hospitalization is de-identified and maintained in the NIS as a unique entry with 1 primary discharge diagnosis and less than 24 secondary diagnoses during that hospitalization. Each entry also carries information on patient’s demographics, insurance status, comorbidities, primary and secondary procedures, hospital charges and in-hospital outcomes.

Study Population:

Patients with OHCA were identified by the International classification of Diseases, Ninth edition, Clinical Modification (ICD-9 CM) code 427.5 if present in any diagnostic fields. This code has shown a positive predictive value upto 82 %18%( 21-23). We included all patients 18 years or older and excluded all observations with ICD-9-CM code 99.60 (cardiopulmonary resuscitation) or 99.63 (closed chest cardiac massage) to avoid inclusion of in-hospital cardiac arrest (IHCA). Some prior studies on NIS database have utilized a similar approach to identify IHCA19,20 and OHCA21,22(28-30).  We further excluded patients with do not resuscitate (DNR) orders (N = 149, 024), or records with missing data on age, sex, survival and/or discharge disposition, or type of admission as pregnancy or trauma related (N = 12, 294). Our final study sample included 985, 861 patients with OHCA (Figure 1). Patients with ventricular tachycardia (VT) or ventricular fibrillation (VF) were identified by ICD-9-CM code 427.1 or 427.41 (n=249, 422, 25.3%). Patient records without either of these codes were considered to have pulseless electric activity (PEA) or asystole as the cardiac arrest rhythm (n=736, 439, 74.7%). The ICD-9-CM codes 37.61, 37.68, and 37.65 were used to identify patients who underwent IABP, PVAD (included both Impella and Tandem Heart), and ECMO placement, respectively.

Outcomes of Interest:

The primary measure of interest was the use of MCS in patients with OHCA. We studied temporal trends in MCS use from 2008 to 2014 and the factors associated with their use. We also compared trends of survival to hospital discharge in patients with and without MCS use. These outcomes were assessed in subgroups of the patients with VT/VF and PEA/asystole as a cause of OHCA.

Definition of Variables

We used NIS variables to identify patient age, sex, and race. We divided race into white, black, Hispanic, and others (Asian or Pacific Islander, Native American, and others). We defined the severity of comorbid conditions by using the Deyo modification of the Charlson Comorbidity Index. This index contains 17 comorbid conditions with differential weights. The score ranges from 0 to 33, with higher scores corresponding to greater burden of comorbid diseases. Facilities were considered to be teaching hospitals if they had an American Medical Association–approved residency program, were a member of the Council of Teaching Hospitals, or had a full-time equivalent interns and resident to patient ratio of 0.25 or higher. Hospital location (rural/urban) and bed size were also recorded. The bed size cutoff points divided into small, medium, and large have been done so that approximately one-third of the hospitals in a given region, location, and teaching status combination would fall within each bed size category. A list of ICD-9-CM and Clinical Classifications Software codes provided by the Agency for Healthcare Research and Quality used to identify comorbidities is provided in Supplementary Table 1.

Statistical Analysis:

We calculated the weighted estimates by applying stratum weights to the discharges according to the stratum from which the discharge was drawn. Pearson χ2 test was utilized for examining the baseline characteristics for categorical variables (expressed in percentages); the unpaired, 2- tailed t test for normally distributed continuous variables reported as mean [ SD or SE]; and the Wilcoxon signed rank test if continuous variables were not normally distributed in the study population. We used the Cochrane- Armitage test to evaluate the trend of MCS (IABP, PVAD, and ECMO) and survival to discharge during the study period. A P-value of less than 0.05 was considered significant. We generated a multivariable logistic regression model to calculate the odds ratio (OR) of MCS according to year. Multivariate model was adjusted for age, sex, race, myocardial infarction, initial cardiac arrest rhythm (VT/VF Vs. PEA/asystole), Deyo modification of Charlson comorbidity index, primary expected payer, median household income, and hospital level variables including hospital bed size, location, teaching status, and region.  We created similar models to identify independent predictors of survival to hospital discharge.

Data were complete for all covariates except race (10.1% missing), median household income (2.5% missing), hospital bed size (0.6% missing), hospital location (0.7% missing), and primary expected payer (0.2% % missing). We performed multiple imputations for missing values using the fully conditional specification method (an iterative Markov Chain Monte Carlo algorithm) in STATA statistical software, version 11.0 (Stata Corp). Results with and without multiple imputations were not significantly different; therefore, only the former are presented.

This study was deemed exempt from approval by the University of Miami Miller school of Medicine Institutional Review board as HCUP is a publicly variable database that contains de-identified patient data and no patient consent was required.

 

 

Results:

Baseline characteristics and use of MCS:

Of the 985,861 patients with OHCA, 52,842 (5.4%) underwent utilization of MCS.  Mean age (SD) of the study population was 66.1 (16) years, 44.1 % were females, and 67.9% were white. Differences in the baseline characteristics of the patient population with and without MCS are summarized in the Table 1.

Younger, white males, with history of coronary artery disease, heart failure, higher scores on Deyo modification of the Charlson co-morbidity index as well as VT/VF as a cause of OHCA were more likely to receive MCS as shown in Table-2. On the other hand, patients with history of chronic obstructive pulmonary disease and chronic kidney disease were less likely to receive MCS. Finally, we found higher utilization of MCS in patients with higher socio-economic class admitted to large, urban teaching hospital located in the Midwest and Northeast region of the United States.

Temporal Trends of the Mechanical Circulatory Support Utilization:

From 2008 to 2014 the utilization of MCS has relatively increased by 13.6% from 5% in 2008 to 5.7% in 2014 (P trend < 0.001). IABP was the most commonly used MCS after OHCA with a frequency of 48,307 (4.9%), followed by ECMO 3,746 (0.4%), and PVAD 3,352 (0.3%). Trend of IABP use decreased by 4.3% from 2008 to 2014 (4.9% to 4.7%, P trend <0.001), whereas PVAD utilization increased by 1700% (0.04% to 0.7%, P trend <0.001), and ECMO by 392% (0.1% to 0.7%, P trend <0.001). Trends in the use of IABP decreased in both VT/VF (11.5% to 10.0%, P trend <0.001) and PEA/asystole (2.8% to 2.7%, P trend <0.001), whereas the trends for utilization of PVAD and ECMO increased in both VT/VF (PVAD = 0.1% to 1.5%, P trend <0.001; ECMO = 0.2% to 1.2%, P trend <0.001), and PEA/asystole (PVAD = 0.02% to 0.42%, P trend <0.001; ECMO = 0.11% to 0.5%, P trend <0.001) ( Figure 2, Supplementary Table-2).

After adjustment, OR for overall MCS use was statistically significant in 2014 compared with 2008 (OR: 1.11, 95% CI: 1.02 to 1.21, p=0.01). Adjusted odds of IABP use was not significantly different in 2014 compared with 2008 (OR: 0.94, 95% CI: 0.86 to 1.03, p=0.16).  However, adjusted OR of PVAD (OR: 13.39, 95% CI: 7.07 to 25.34, p<0.001) and ECMO (OR: 3.68, 95% CI: 2.52 to 5.39, p<0.001) were significantly higher in 2014 compared with 2008. Based on initial rhythm, adjusted OR for MCS use in VT/VF was not significantly different (OR: 1.01, 95% CI: 0.90 to 1.13, p 0.878), whereas OR for MCS use in PEA/asystole was higher in 2014 compared with 2008 (OR 1.26, 95% CI: 1.11 to 1.42, p< 0.001).

Independent Patient and Hospital Factors Associated with Mechanical Circulatory support use

After adjustment, on multivariable analysis, patients were more likely to get MCS if they were younger, male sex, White, other race ((Asian or Pacific Islander, Native American, and others), higher Deyo modification of the Charlson Comorbidity Index, VT/VF being the cause of OHCA, and had acute myocardial infarction. Patients who were selected to receive MCS were more likely to have private insurance, higher socio-economic status and were more likely to present to a large teaching hospital of the Midwest region in the United States. (Table 2)

Trends of survival to hospital discharge in patients with Mechanical Circulatory Support:

Survival to discharge in our study population was 43.9%. Overall survival to discharge was significantly higher in patients who were selected to receive MCS (56.9% vs. 43.1%, p-value<0.001). Survival to discharge increased significantly in patients who were not selected to receive MCS (39.6% to 46.7%, P trend<0.001) over the study period. Trend for survival to discharge decreased in patients who were selected to receive MCS (59.3% to 55.7%, p-value<0.001) during the study period. This was predominantly driven by decreased survival in patients on IABP. Survival to discharge had significantly increased in patients who were selected to receive PVAD (33.3% to 44.5%, p<0.001) or ECMO (31.6% to 44.8%, p<0.001). (Figure-3, Supplementary table 3)

Independent Patient and Hospital Factors associated with Survival to discharge:

After adjustment, on multivariate analysis, patients more likely to survive were younger, white, had myocardial infarction, VT/VF OHCA, and had lower Deyo modification of the Charlson Comorbidity Index. Survivors were more likely to be from a higher socio-economic class, more likely to have a private insurance, including health maintenance organization, and presented to large teaching hospital (Table 3). After adjustment, survival to hospital discharge also increased significantly over the study period from 2008 to 2014. Survival to discharge was also higher in patients who were selected to receive MCS use.

Discussion

In this nationwide cohort study, we examined temporal trends as well as patient and hospital characteristics of percutaneous MCS utilization following OHCA. Our analysis yielded several findings that merit further consideration. First, the use of MCS has increased significantly in patients with OHCA in the United States during the study period (2008-2014). IABP was the most commonly utilized MCS. However, use of IABP decreased significantly during the study period and utilization of PVAD and ECMO increased exponentially. Second, younger, male patients with myocardial infarction, higher co-morbid conditions, VT/VF as initial rhythm, and presentation to large urban hospitals were more likely to receive percutaneous MCS implantation. Third, survival to hospital discharge was higher in patients who were selected to receive MCS.  However, the survival to discharge with MCS use might be influenced by selection bias.

OHCA remains a major public health concern. Considerable progress has been made in the care of OHCA patients; however survival still remains very low. This has promoted a drive towards exploring mechanical circulatory support possibly to improve hemodynamic derangements and promote myocardial protection.  In the 2016 statement from interventional council of American College of Cardiology, an algorithm for the use of MCS among patients with cardiac arrest has been proposed23 (31). Stretch et al and Khera et al studied overall trends of short-term MCS use in all patients > 18 years from the NIS database24,25 (32,33). In another study, Khera and colleagues examined temporal trends of percutaneous MCS use in the setting of percutaneous coronary intervention using the same database until 201226 (34). Because of the inclusion of a heterogeneous patient population, these studies do not provide direct insight into MCS use in the patients with OHCA. Furthermore, in these studies patients who received ECMO were either not included25,26(33, 34) or excluded24 (32) from the analysis. In our study, we have examined temporal trends, patient and hospital characteristics, and in-hospital outcomes of 8620 percutaneous MCS devices in the setting of OHCA, and we have also included trend of ECMO utilization from 2008 to 2014 in this selected group of patient population compared with the prior studies done through NIS24-26 (32-34).

Early MCS can provide hemodynamic support as well as myocardial protection, which can in turn aid in resolution of shock and can also limit further secondary cerebral injury from hypoperfusion. Out of the various MCS devices, ECMO has been traditionally utilized for post cardiac arrest cardiopulmonary and hemodynamic support27,28 (35,36). The 2015 American Heart Association Guidelines for cardiac arrest have utilized the term extracorporeal cardiopulmonary resuscitation (ECPR) to describe the initiation of veno-arterial ECMO emergently in patients with cardiac arrest with a goal of providing a quick support until the restoration of spontaneous circulation for a reversible cause of cardiac arrest29 . Utilization of ECMO for IHCA has been promising30  but for OHCA data has been scarce and conflicting2-4,31.32 (2-4,).  In the CHEER (mechanical CPR, Hypothermia, ECMO and Early Reperfusion) trial, patients with both IHCA and OHCA had better outcomes with ECMO support33 (44). In a  study done by Maekawa et al  on 162 patients with witnessed cardiac arrest, survival at 3 months was better with ECPR  (29.2% vs. 8.3%, p=0.018) compared with conventional CPR32 (43). Furthermore, Sakamoto et al34 (45) also demonstrated improved neurologic outcomes at 1 and 6 months follow up in patients who received a treatment bundle including ECPR in OHCA patients with VT/VF compared with non-ECPR. In our analysis, we found that utilization of ECMO increased significantly from 194 (0.14%) in 2008 to 1043 (0.69%) in 2014.  Survival was also increased from 31.6% in 2008 to 44.8% in 2014.

In our study, we found an overall 4.9% decrease in IABP use from 2008 to 2014 in all patients with OHCA. We also found almost 19-fold increase in overall use of PVAD for all OHCA and 22-fold increase in OHCA with PEA/asystole as initial rhythm. Efficacy Study of LV Assist Device to Treat Patients With Cardiogenic Shock [ISAR-SHOCK] trial randomized 26 patients with cardiogenic shock between Impella 2.5 and IABP (46). In this trial, 85% of patients in Impella arm and 69% of IABP arm had cardiac arrest prior to randomizations. Overall 30-day survival in this trial was 46%.  In the “IMPella versus IABP Reduces mortality in STEMI patients treated with primary PCI in Severe cardiogenic SHOCK” (IMPRESS in Severe Shock) trial which was a randomized, prospective, open-label, multi-center trial, 48 patients with cardiogenic shock were assigned to Impella CP (n=24) or IABP (n=24). In this trial, 92% of the overall population had cardiac arrest and overall 30-day mortality was 50% in IABP arm and 46% in Impella CP arm35 (47). Manzo-Silberman et al studied 78 post cardiac arrest patients from a single center registry and concluded that Impella LP 2.5 is feasible in this patient population36 (48). Overall 28 days mortality in this study was 77% in Impella LP 2.5 group and 70.5% in the IABP group. There are several factors that could explain difference in mortality between different studies, including but not limited to different inclusion criteria, heterogeneous clinical variables in different studies, and most important ; timing of the device placement.  There are some external factors like delays in CPR, quality of CPR, bystander CPR and time of arrival of emergency medical personnel could impact on survival2-4 (2-4).  Our data represents outcomes from real-world clinical practice in the United States. In our study, overall survival to discharge was 58.5% in OHCA patients who were selected to receive IABP, and 44.2% in patients who were selected for other PVAD. The data on the use of Tandem Heart in cardiac arrest is scarce. Currently, experience of utilizing Tandem Heart in cardiac arrest is limited mostly to cardiogenic shock or PCI14,25,38 (17, 33, 49).

Our study indicates the overall upward trend in the utilization of MCS in OHCA from 2008 to 2014 despite lack of randomized clinical trial data supporting their outcomes. IABP use initially increased from 4.9% in 2008 to 5.4% in 2011, followed by significant decrease, which was compensated by rise in PVAD and ECMO utilizations. Sandhu et alhad studied the temporal trends of MCS in cardiogenic shock patients undergoing  PCI  through the Cath-PCI registry and  found that use of the IABP decreased during their study from 2009 to 201339 (50). Similarly, Agarwal et alstudied temporal trends of MCS in cardiogenic shock in STEMI patients from the NIS and found that there was a steady increase in the use of IABP from 2003 to 2009, followed by decline during the period 2010 to 201240 (51).  The decline in the use of IABP compared with newer percutaneous MCS can be explained in part due to better perceived hemodynamic support from newer devices compared with IABP13-15,

Our results should be interpreted in the lights of following limitations.  We relied on the ICD-9 codes for our data collection and case identification. This method has been utilized in prior studies with a very good positive predictive value, but the coding practices vary with each hospital. We were able to collect the data only from the patients who were successfully transported to the hospitals after the OHCA. The data about patients who died in the field, during transport, or in the ER could not be captured. We tried to exclude all patients with IHCA in our analysis, but it is possible that some IHCA were included due to coding errors. In addition, some of the OHCA patients could have received CPR in the hospital as continuation of the resuscitative efforts and might have been erroneously excluded from the study cohort. The NIS database has some limitations, as it does not collect clinical data such as labs, angiographic data, or other clinical variables.  Data on presentations such as witnessed vs. unwitnessed arrest, or the duration of CPR, and time to insertion of MCS after arrival are not available. As Impella and tandem heart shares same ICD 9 code, it is not possible to distinguish among these two devices. The higher survival is likely from selection bias since sicker patients with more comorbidities were not selected for MCS support. Younger, male patients with myocardial infarction, VT/VF as initial rhythm, and presentation to large urban hospital are more likely to receive percutaneous MCS implantation. All of these characteristics have been shown to be associated with better survival. Being an observational study, a causal relation between MCS use and survival cannot be implied. NIS sampling design and the above limitations are unlikely to affect the primary purpose of the study which is to report trends of MCS use in OHCA patients. The main strength of this study is the representation of real-world clinical practice of MCS use in OHCA in the United States with a large sample size.

Conclusion:

Among patients with OHCA, the use MCS has been steadily increasing in the study period of 2008-2014 despite lack of randomized clinical trial data supporting their outcomes. Use of ECMO and PVAD has shown an exponential increase, whereas the use of IABP has been steadily declining over the study period. Younger, male patients with myocardial infarction, higher co-morbid conditions, VT/VF as initial rhythm, and presentation to large urban hospitals are more likely to receive percutaneous MCS implantation. The survival to discharge was higher among the patients with MCS use, though we cannot determine if that is due to selection bias and residual confounding or whether there may be a true benefit. Adequately powered randomized studies are needed to assess the impact of MCS use among patients with OHCA.

 

Disclosures:

Patel NJ: None

Patel N: None

Bhardwaj B: None

Golwala H: None

Kumar Varun:

Arora S: None

Patel S: None

Patel N: None

Hernandez GA: None

Badheka Apurva: None

Alfonso CE: None

Cohen MG: None

Bhatt DL –

Dr. Deepak L. Bhatt discloses the following relationships – Advisory Board: Cardax, Elsevier Practice Update Cardiology, Medscape Cardiology, Regado Biosciences; Board of Directors: Boston VA Research Institute, Society of Cardiovascular Patient Care; Chair: American Heart Association Quality Oversight Committee; Data Monitoring Committees: Cleveland Clinic, Duke Clinical Research Institute, Harvard Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine, Population Health Research Institute; Honoraria: American College of Cardiology (Senior Associate Editor, Clinical Trials and News, ACC.org), Belvoir Publications (Editor in Chief, Harvard Heart Letter), Duke Clinical Research Institute (clinical trial steering committees), Harvard Clinical Research Institute (clinical trial steering committee), HMP Communications (Editor in Chief, Journal of Invasive Cardiology), Journal of the American College of Cardiology (Guest Editor; Associate Editor), Population Health Research Institute (clinical trial steering committee), Slack Publications (Chief Medical Editor, Cardiology Today’s Intervention), Society of Cardiovascular Patient Care (Secretary/Treasurer), WebMD (CME steering committees); Other: Clinical Cardiology (Deputy Editor), NCDR-ACTION Registry Steering Committee (Chair), VA CART Research and Publications Committee (Chair); Research Funding: Amarin, Amgen, AstraZeneca, Bristol-Myers Squibb, Chiesi, Eisai, Ethicon, Forest Laboratories, Ironwood, Ischemix, Lilly, Medtronic, Pfizer, Roche, Sanofi Aventis, The Medicines Company; Royalties: Elsevier (Editor, Cardiovascular Intervention: A Companion to Braunwald’s Heart Disease); Site Co-Investigator: Biotronik, Boston Scientific, St. Jude Medical (now Abbott); Trustee: American College of Cardiology; Unfunded Research: FlowCo, Merck, PLx Pharma, Takeda.

Kapur NK:

 

 

 

 

References:

1. Mozaffarian D, Benjamin EJ, Go AS, et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics-2015 update: a report from the American Heart Association. Circulation. 2015;131(4):e29-e322.

2. Daya MR, Schmicker RH, Zive DM, et al, Wang H; Resuscitation Outcomes Consortium Investigators. Out-of-hospital cardiac arrest survival improving over time: results from the Resuscitation Outcomes Consortium (ROC). Resuscitation. 2015;91:108–115.

3. Centers for Disease Control and Prevention. 2014 Cardiac Arrest Registry to Enhance Survival (CARES) National Summary Report. https:// mycares.net/sitepages/uploads/2015/2014%20Non-Traumatic%20National%20Summary%20Report.pdf. Accessed May 13, 2015.

4.  Kern KB , Hilwig RW , Rhee RH, et al, “Myocardial dysfunction after resuscitation from cardiac arrest: an example of global myocardial stunning,” Journal of the American College of Cardiology, vol. 28, no. 1, pp. 232–240, 1996.

5. Marwick TH, Case CC, Siskind V, et al. Prediction of survival from resuscitation: a prognostic index derived from multivariate logistic model analysis. Resuscitation 1991; 22:129.

6.  Kaji AH,  Hanif AM, Thomas JL,et al, “Out-of-hospital cardiac arrest: early in-hospital hypotension versus out-of-hospital factors in predicting in-hospital mortality among those surviving to hospital admission,” Resuscitation, vol. 82, no. 10, pp. 1314–1317, 2011.

7.  Ostenfeld S, Lindholm MG, Kjaergaard J, et al implication of out-of-hospital cardiac arrest in patients with cardiogenic shock and acute myocardial infarction. Resuscitation. 2015 Feb;87:57-62. doi: 10.1016/j.resuscitation.2014.11.010. Epub 2014 Dec 2.

8. J. H. Kilgannon, B. W. Roberts, A. E. Jones et al., “Arterial blood pressure and neurologic outcome after resuscitation from cardiac arrest,” Critical Care Medicine, vol. 42, no. 9, pp. 2083–2091, 2014.

9. Naidu SS. Novel percutaneous cardiac assist devices: The science of and indications for hemodynamic support. Circulation. 2011;123:533–43.

10. Kantrowitz A, Tjønneland S, Freed PS, et al. Initial clinical experience with intraaortic balloon pumping in cardiogenic shock JAMA. 1968; 203:113–8.

11. Rastan AJ, Dege A, Mohr M,et al. Early and late outcomes of 517 consecutive adult patients treated with extracorporeal membrane oxygenation for refractory postcardiotomy cardiogenic shock. J Thorac Cardiovasc Surg. 2010;139: 302–11, 311 e1.

13. Burkhoff D, O’Neill W, Brunckhorst C,et al. Feasibility study of the use of the TandemHeart percutaneous ventricular assist device for treatment of cardiogenic shock. Catheter Cardiovasc Interv 2006; 68:211–7.

14. Kar B, Gregoric ID, Basra SS,et al. The percutaneous ventricular assist device in severe refractory cardiogenic shock. .  J Am Coll Cardiol. 2011 Feb 8;57(6):688-96. doi: 10.1016/j.jacc.2010.08.613. Epub 2010 Oct 14.

15. O’Neill WW, Kleiman NS, Moses J,et al . A prospective, randomized clinical trial of hemodynamic support with Impella 2.5 versus intra-aortic balloon pump in patients undergoing high-risk percutaneous coronary intervention: the PROTECT II study. Circulation. 2012 Oct 2;126(14):1717-27. doi: 10.1161/CIRCULATIONAHA.112.098194. Epub 2012 Aug 30.

16. Rihal CS, Naidu SS, Givertz MM, et al. 2015 SCAI/ ACC/HFSA/STS Clinical Expert Consensus Statement on the Use of Percutaneous Mechanical Circulatory SupportDevices in Cardiovascular Care: Endorsed by the American Heart Assocation, the Cardiological Society of India, and Sociedad Latino Americana de Cardiologia Intervencion;Affirmation of Value by the Canadian Association of Interventional Cardiology- Association Canadienne de Cardiologie d’intervention. J Am Coll Cardiol 2015;65:e7–26.

17. HCUP National Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). 2012. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/nisoverview.jsp

18. De Bruin ML, van Hemel NM, Leufkens HG,et al. Hospital discharge diagnoses of ventricular arrhythmias and cardiac arrest were useful for epidemiologic research.  J Clini Epidemiol.2005;58(12):1325-1329.

19. Kolte D, Khera S, Aronow WS, et al. Regional variation in the incidence and outcomes of in-hospital cardiac arrest in the United States. Circulation. 2015;131(16):1415-1425.

20.  Kumar G, Nanchal R. Trends in survival after in-hospital cardiac arrest. N Engl J Med. 2013;368(7):680.

21. Patel  N, Patel  NJ, Macon  CJ,  et al.  Trends and outcomes of coronary angiography and percutaneous coronary intervention after out-of-hospital cardiac arrest associated with ventricular fibrillation or pulseless ventricular tachycardia.  JAMA Cardiol. 2016;1(8):890-899.

22. Johnson NJ, Salhi RA, Abella BS et al. Emergency department factors associated with survival after sudden cardiac arrest. Resuscitation. 2013 Mar;84(3):292-7. doi: 10.1016/j.resuscitation.2012.10.013. Epub 2012 Oct 24.

23. Atkinson TM, Ohman EM, O’Neill WW et al. Interventional Scientific Council of the American College of Cardiology.A Practical Approach to Mechanical Circulatory Support in Patients Undergoing Percutaneous Coronary Intervention: An Interventional Perspective. JACC Cardiovasc Interv. 2016 May 9;9(9):871-83. doi: 10.1016/j.jcin.2016.02.046.

24.  Stretch R, Sauer CM, Yuh DD,et al . J Am Coll Cardiol. 2014 Oct 7;64(14):1407-15. doi: 10.1016/j.jacc.2014.07.958.National trends in the utilization of short-term mechanical circulatory support: incidence, outcomes, and cost analysis.

25. Khera R, Cram P, Lu X, Vyas A et al. Trends in the use of percutaneous ventricular assist devices: analysis of national inpatient sample data, 2007 through 2012. JAMA Intern Med. 2015 Jun;175(6):941-50. doi: 10.1001/jamainternmed.2014.7856.

26.  Khera R, Cram P, Vaughan-Sarrazin M, et al. Use of Mechanical Circulatory Support in Percutaneous Coronary Intervention in the United States. Am J Cardiol. 2016 Jan 1;117(1):10-6. doi: 10.1016/j.amjcard.2015.10.005. Epub 2015 Oct 23.

27. Thiagarajan RR, Brogan TV, Scheurer MA et al Extracorporeal membrane oxygenation to support cardiopulmonary resuscitation in adults. Ann Thorac Surg 2009; 87:778–85.

28. Napp LC, Kuhn C, Hoeper MM, et al. Cannulation strategies for percutaneous extracorporeal membrane oxygenation in adults. Clin Res Cardiol 2016; 105:283–96.

29. Callaway CW, Donnino MW, Fink EL et al.Part 8: Post-Cardiac Arrest Care: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. . Circulation. 2015 Nov 3;132(18 Suppl 2): S465-82. doi: 10.1161/CIR.0000000000000262

30. Lin JW, Wang MJ, Yu HY, et al. Comparing the survival between extracorporeal rescue and conventional resuscitation in adult in-hospital cardiac arrests: propensity analysis of three-year data. Resuscitation 2010; 81(7): 796–803.

31. Nagao K, Hayashi N, Kanmatsuse K, et al. Cardiopulmonary cerebral resuscitation using emergency cardiopulmonary bypass, coronary reperfusion therapy and mild hypothermia in patients with cardiac arrest outside the hospital. J Am Coll Cardiol 2000; 36: 776–783.

32. Maekawa K, Tanno K, Hase M,et al. Extracorporeal cardiopulmonary resuscitation for patients with out-of-hospital cardiac arrest of cardiac origin: a propensity-matched study and predictor analysis. Crit Care Med 2013; 41:1186–96.

33. Stub D, Bernard S, Pellegrino V et al. Refractory cardiac arrest treated with mechanical CPR, hypothermia, ECMO and early reperfusion (the CHEER trial). Resuscitation. 2015 Jan; 86:88-94. doi: 10.1016/j.resuscitation.2014.09.010. Epub 2014 Oct 2.

34. Sakamoto T, Morimura N, Nagao K, et al. Extracorporeal cardiopulmonary resuscitation versus conventional cardiopulmonary resuscitation in adults with out-of-hospital cardiac arrest: a prospective observational study. Resuscitation 2014; 85:762–8.

35. Seyfarth M, Sibbing D, Bauer I et al.A randomized clinical trial to evaluate the safety and efficacy of a percutaneous left ventricular assist device versus intra-aortic balloon pumping for treatment of cardiogenic shock caused by myocardial infarction. J Am Coll Cardiol. 2008 Nov 4;52(19):1584-8. doi: 10.1016/j.jacc.2008.05.065.

36. Ouweneel DM, Eriksen E, Sjauw KD et al. Percutaneous Mechanical Circulatory Support Versus Intra-Aortic Balloon Pump in Cardiogenic Shock After Acute Myocardial Infarction.J Am Coll Cardiol. 2017 Jan 24;69(3):278-287. doi: 10.1016/j.jacc.2016.10.022.

37. Manzo-Silberman S, Fichet J, Mathonnet A et al. Percutaneous left ventricular assistance in post cardiac arrest shock: comparison of intra-aortic blood pump and IMPELLA Recover LP2.5. Resuscitation. 2013 May;84(5):609-15. doi: 10.1016/j.resuscitation.2012.10.001. Epub 2012 Oct 13.

38. Thiele H, Sick P, Boudriot E et al. Randomized comparison of intra-aortic balloon support with a percutaneous left ventricular assist device in patients with revascularized acute myocardial infarction complicated by cardiogenic shock. Eur Heart J. 2005; 26:1276 –1283.

39. Sandhu A, McCoy LA, Negi SI SM, et al. Use of mechanical circulatory support in patients undergoing percutaneous coronary intervention: insights from the National Cardiovascular Data Registry. Circulation. 2015 Sep 29;132(13):1243-51. doi: 10.1161/CIRCULATIONAHA.114.014451. Epub 2015 Aug 18. 31.

40. Agarwal S, Sud K, Martin JM,et al. Trends in the Use of Mechanical Circulatory Support Devices in Patients Presenting With ST-Segment Elevation Myocardial Infarction. JACC Cardiovasc Interv. 2015 Nov;8(13):1772-4. doi: 10.1016/j.jcin.2015.07.015.

Table 1:  Baseline characteristics among patients with OHCA with and without mechanical circulatory support.

Variable Without MCS With MCS Overall P value
94.6 5.4
933,019 52,842 985,861
Age, mean ± SD * , y 66.2 +/- 16.1 63.4 +/- 13.6 66.10 +/- 16.00 <0.001
Female, % 44.8 32.0 44.1 <0.001
Race, % <0.001
White 67.6 74.2 67.9
Black 17.7 9.4 17.2
Hispanic 8.3 8.2 8.3
Others 6.5 8.2 6.6
Missing
Myocardial Infarction, % 21.2 71.8 24.0 <0.001
VT  /VF ‡ 23.5 56.2 25.3 <0.001
Coronary angiogram or PCI x, % 15.7 82.6 19.3 <0.001
Deyo modification of Charlson Comorbidity Index <0.001
0 17.1 5.9 16.6
1 22.6 29.4 22.9
>=2 60.3 64.7 60.5
Primary expected payer, %       <0.001
Medicare 62 49.3 61.3
Medicaid 10.4 8.9 10.4
Private Insurance 19.5 32 20.2
Uninsured 8.1 9.8 8.2
Median household income category for patient’s zip code, % <0.001
     0-25th percentile 32.2 26.3 31.8
     26-50th percentile 26.8 26.3 26.7
     51-75th percentile 22.9 25.3 23.0
     76-100th percentile 18.2 22.1 18.4
Hospital Characteristics, %
   Hospital bed size, % <0.001
     Small 11.5 6.7 11.2
     Medium 24.7 20.8 24.5
     Large 63.9 72.5 64.3
   Urban location, % 90.2 95.4 90.5
   Teaching hospital, % 50.5 61.1 51.1
   Hospital Region, % <0.001
     Northeast 16.4 17.8 16.5
     Midwest 22.3 26.3 22.5
     South 41.5 36.4 41.2
     West 19.8 19.5 19.8
   Weekends admission, % 24.5 23.5 24.4
Comorbidities, %
Obesity 12.4 13.4 12.4 0.002
Hypertension 57.3 54.4 57.2 <0.001
Diabetes Mellitus 32.7 32.5 32.7 0.809
Smoking 12.1 17.8 12.4 <0.001
CAD § 33.7 72.8 35.8 <0.001
Family history of CAD§ 1.6 4.4 1.8 <0.001
Previous myocardial infarction 6.8 8.3 6.9 <0.001
Previous PCI 5.1 8.5 5.3 <0.001
Previous CABG ll 6.5 3.9 6.3 <0.001
Previous cardiac arrest 0.5 0.6 0.5 0.394
Atrial Fibrillation 24.3 21.7 24.2 <0.001
Congestive heart failure 33.7 46.9 34.4 <0.001
Chronic pulmonary disease 25.0 17.7 24.6 <0.001
Pulmonary circulation disorders 6.3 2.6 6.1 <0.001
Peripheral vascular disease 11.2 11.8 11.2 0.06
Chronic renal failure 25.8 17.9 25.4 <0.001
Fluid and electrolyte disorder 53.2 52.8 53.2 0.44
Neurological disorder 13.6 0.7 13.2 <0.001
Anemia 24.3 18.3 24.o <0.001
Coagulopathy 14.2 22.4 14.6 <0.001
Hematological or oncological malignancy 7.4 2.0 7.1 <0.001

Abbreviations: * SD: Standard deviation; VT: ventricular tachycardia; ‡VF: ventricular fibrillation; x PCI: percutaneous coronary intervention; §CAD: coronary artery disease; ll CABG: coronary arteries bypass grafting

Table 2. Multivariable predictors of MCS/IABP/PVAD/ECMO use

Assist device( MCS) P-value IABP P-value PVAD P-value ECMO P-value
Odds ratio (95% CI) Odds ratio (95% CI) Odds ratio (95% CI) Odds ratio (95% CI)
Year
2008 Referent Referent Referent Referent
2009 1.05 (0.96-1.15) 0.246 1.05 (0.96-1.15) 0.313 2.89 (1.39-5.82) 0.004 1.10 (0.68-1.77) 0.701
2010 0.99 (0.91-1.09) 0.932 0.98 (0.89-1.07) 0.612 3.79 (1.89-7.57) <0.001 1.62 (1.04-2.52) 0.033
2011 1.23 (1.12-1.34) <0.001 1.17 (1.07-1.28) 0.001 6.27 (3.23-12.15) <0.001 2.42 (1.61-3.64) <0.001
2012 1.21 (1.11-1.32) <0.001 1.11 (1.01-1.21) 0.026 8.92 (4.66-17.07) <0.001 3.35 (2.26-4.96) <0.001
2013 1.10 (1.00-1.20) 0.040 0.98 (0.89-1.07) 0.640 10.04 (5.27-19.15) <0.001 3.17 (2.15-4.69) <0.001
2014 1.11 (1.02-1.21) 0.013 0.94 (0.86-1.03) 0.156 13.39 (7.07-25.34) <0.001 3.68 (2.52-5.39) <0.001
Age (10 year increment) 0.91 (0.89-0.92) <0.001 0.95 (0.93-0.97) <0.001 0.85 (0.80-0.92) <0.001 0.63 (0.59-0.66) <0.001
Female 0.79 (0.75-0.83) <0.001 0.79 (0.75-0.83) <0.001 0.67 (0.56-0.81) <0.001 0.88 (0.75-1.04) 0.130
Race
     White Referent Referent Referent Referent
     Black 0.60 (0.55-0.65) <0.001 0.58 (0.54-0.63) <0.001 0.68 (0.52-0.89) 0.005 0.70 (0.56-0.89) 0.003
     Hispanic 1.04 (0.95-1.13) 0.396 1.06 (0.97-1.16) 0.182 0.97 (0.71-1.33) 0.866 0.90 (0.67-1.22) 0.507
     Others 1.21 (1.11-1.31) <0.001 1.18 (1.08-1.29) <0.001 1.22 (0.91-1.64) 0.190 1.22 (0.93-1.60) 0.512
Myocardial Infarction 7.20 (6.83-7.58) <0.001 7.94 (7.51-8.40) <0.001 5.15 (4.24-6.25) <0.001 1.51 (1.26-1.82) <0.001
VT*/VFIB 2.35 (2.25-2.46) <0.001 2.40 (2.29-2.52) <0.001 2.21 (1.85-2.63) <0.001 1.58 (1.33-1.86) <0.001
Deyo modification of Charlson Comorbidity Index
0 Referent Referent Referent Referent
1 1.44 (1.30-1.60) <0.001 1.51 (1.35-1.69) <0.001 1.79 (1.13-2.86) 0.014 1.57 (1.22-2.00) <.001
>=2 1.27 (1.15-1.40) <0.001 1.33 (1.19-1.48) <0.001 2.38 (1.52-3.73) 0.001 1.37 (1.08-1.75) 0.010
Primary expected payer, %
Medicare Referent Referent Referent Referent
Medicaid 0.97 (0.88-1.06) 0.452 1.00 (0.91-1.10) 0.968 0.91 (0.66-1.26) 0.582 0.96 (0.73-1.27) 0.788
Private Insurance 1.36 (1.28-1.45) <0.001 1.35 (1.27-1.44) <0.001 1.43 (1.15-1.77) 0.001 1.80 (1.46-2.22) <0.001
Uninsured 1.09 (1.00-1.19) 0.057 1.17 (1.07-1.29) <0.001 0.95 (0.69-1.32) 0.773 0.73 (0.52-1.02) 0.061
Median household income category for patient’s zip code, %
     0-25th percentile Referent Referent Referent Referent
     26-50th percentile 1.06 (1.00-1.13) 0.056 1.06 (0.99-1.13) 0.076 0.81(0.65-1.02); 0.077 1.17 (0.93-1.47) 0.182
     51-75th percentile 1.08 (1.01-1.15) 0.019 1.07 (1.00-1.15) 0.043 0.86 (0.68-1.09) 0.211 1.35 (1.07-1.69) 0.010
     76-100th percentile 1.17 (1.10-1.26) <0.001 1.16 (1.08-1.24) <0.001 1.02 (0.80-1.30) 0.858 1.42 (1.12-1.80) 0.004
   Hospital bed size, %
     Small Referent Referent Referent Referent
     Medium 1.35 (1.23-1.48 <0.001 1.29 (1.17-1.42) <0.001 1.90 (1.27-2.84) 0.002 3.89 (1.94-7.79) <0.001
     Large 1.95 (1.79-2.12) <0.001 1.76 (1.61-1.92 <0.001 2.99 (2.05-4.34) 13.41 (6.93-25.97) <0.001
   Urban location, % 1.54 (1.38-1.72) <0.001 1.51 (1.35-1.70) <0.001 1.71 (1.02-2.85) 0.040 1.31 (0.51-3.36) 0.576
   Teaching hospital, % 1.49 (1.42-1.57) <0.001 1.37 (1.30-1.44) <0.001 2.00 (1.64-2.43) <0.001 11.38 (8.02-16.15) <0.001
   Hospital Region, %
     Northeast Referent Referent Referent Referent
     Midwest 1.11 (1.04-1.20) 0.003 1.19 (1.10-1.28) <0.001 1.19 (0.91-1.54) 0.201 0.40 (0.31-0.52) <0.001
     South 0.94 (0.88-1.01) 0.081 0.98 (0.91-1.05) 0.539 1.00 (0.79-1.28) 0.997 0.61 (0.51-0.74) <0.001
     West 0.93 (0.86-1.00) 0.045 0.97 (0.90-1.05) 0.442 1.09 (0.83-1.43) 0.523 0.46 (0.36-0.59) <0.001

Abbreviations: VF†: ventricular fibrillation VT*: ventricular tachycardia,

Table 3. Multivariate predictors of survival to discharge

Overall P-value VT/VF P-value PEA/Asystole P-value
Odds ratio (95% CI) Odds ratio (95% CI) Odds ratio (95% CI)
Assist device 1.16 ( 1.11-1.21) <0.001 0.96 (0.90-1.03) 0.248 1.34 (1.26-1.44) <0.001
Year
2008 Referent Referent Referent
2009 0.93 (0.90-0.97) <0.001 0.89 (0.83-0.97) 0.004 0.95 (0.91-0.99) 0.025
2010 1.02 (0.98-1.06) 0.322 1.00 (0.93-1.08) 0.910 1.02 (0.98-1.07) 0.288
2011 1.23 (1.18-1.27) <0.001 1.21 (1.12-1.31) <0.001 1.23 (1.18-1.29) <0.001
2012 1.26 (1.21-1.31) <0.001 1.22 (1.13-1.32) <0.001 1.27 (1.21-1.33) <0.001
2013 1.32 (1.27-1.37) <0.001 1.25 (1.16-1.34) <0.001 1.34 (1.29-1.40) <0.001
2014 1.31 (1.26-1.36) <0.001 1.30 (1.21-1.40) <0.001 1.31 (1.26-1.37) <0.001
Age (10 year increment) 0.87 (0.86-0.88) <0.001 0.87 (0.86-0.89) <0.001 0.87 (0.86-0.88) <0.001
Female 1.01 (0.99-1.03) 0.223 0.93 (0.89-0.97) <0.001 1.04 (1.02-1.07) <0.001
Race
     White Referent Referent Referent
     Black 0.89 (0.86-0.91) <0.001 0.78 (0.74-0.83) <0.001 0.93 (0.90-0.96) <0.001
     Hispanic 0.89 (0.86-0.92) <0.001 0.76 (0.70-0.82) <0.001 0.93 (0.90-0.97) 0.001
     Others 0.85 (0.82-0.89) <0.001 0.74 (0.68-0.80) <0.001 0.90 (0.86-0.94) <0.001
Myocardial Infarction 1.37 (1.34-1.40) <0.001 1.63 (1.56-1.70) <0.001 1.22 (1.19-1.26) <0.001
VT*/VF 1.92 (1.88-1.97) <0.001
Deyo modification of Charlson Comorbidity Index
0 Referent Referent Referent
1 1.01 (0.98-1.05) 0.460 1.13 (1.05-1.21) 0.001 0.96 (0.93-1.00) 0.046
>=2 0.86 (0.83-0.88) <0.001 0.87 (0.82-0.93) <0.001 0.86 (0.83-0.88) <0.001
Primary expected payer, %
Medicare Referent Referent Referent
Medicaid 0.88 (0.84-0.91 <0.001 1.05 (0.97-1.13) 0.236 0.82 (0.79-0.86) <0.001
Private Insurance 1.14 (1.11-1.17) <0.001 1.44 ( 1.36-1.52) <0.001 1.03 (1.00-1.07) 0.047
Uninsured 0.69 (0.66-0.72) <0.001 0.92 (0.85-0.99) 0.034 0.61 (0.58-0.64 <0.001
Median household income category for patient’s zip code, %
     0-25th percentile Referent Referent Referent
     26-50th percentile 1.06 (1.03-1.09) <0.001 1.06 (1.00-1.12) 0.039 1.06 (1.02-1.09) <0.001
     51-75th percentile 1.08 (1.05-1.11) <0.001 1.09 (1.03-1.15) 0.003 1.08 (1.04-1.11) <0.001
     76-100th percentile 1.14 (1.11-1.28) <0.001 1.19 (1.11-1.26) <0.001 1.12 (1.09-1.17) <0.001
   Hospital bed size, %
     Small Referent Referent Referent
     Medium 1.03 (0.99-1.06) 0.124 0.99 (0.92-1.07) 0.876 1.04 (0.99-1.08) 0.087
     Large 1.08 (1.05-1.12) <0.001 1.00 (0.93-1.07) 0.992 1.11 (1.07-1.15) <0.001
   Urban location, % 1.19 (1.15-1.24) <0.001 0.95 (0.87-1.03) 0.228 1.26 (1.21-1.32) <0.001
   Teaching hospital, % 1.03 (1.01-1.05) 0.010 1.01 (0.97-1.05) 0.661 1.04 (1.01-1.06) 0.005
   Hospital Region, %
     Northeast Referent Referent
     Midwest 1.03 (1.00-1.07) 0.062 0.99 (0.93-1.06) 0.873 1.05 (1.01-1.09) 0.021
     South 0.99 (0.96-1.02) 0.472 0.97 (0.91-1.02) 0.251 1.00 (0.97-1.03) 0.885
     West 0.97 (0.94-1.01) 0.111 1.00 (0.94-1.07) 0.977 0.96 (0.93-1.00) 0.054

Abbreviations:  VF†: ventricular fibrillation VT*: ventricular tachycardia;

Figure 1:  Study design and patient selection

All patients ≥18 years of age with OHCA

N=1147179

 

Patients who had DNR orders

(149, 024)

 

N= 998, 155

 

All observations with missing information on age, sex and mortality or type of admission is pregnancy, newborn or trauma related or disposition is missing were excluded (n=12, 294)

 

 

N= 985, 861

 

 

 

Abbreviations: OHCA: out of hospital cardiac arrest; DNR: do not resuscitate

 

 

Figure 2: Temporal trends of the use of MCS. Legend:2a. Trends of the use of MCS over the study duration; 2b. Trends of the use of MCS in patients with VT/Vfib as initial rhythm 2c. Trends of the use of MCS in patients with PEA/Asystole as initial rhythm.

Abbreviations: MCS: Mechanical circulatory support; VT: Ventricular tachycardia; Vfib: Ventricular fibrillation; PEA: Pulseless electric activity

2a

2b

2c

Figure 3:  Survival trends with MCS use. Legend: 3a: Trends of survival in all patients with MCS use; 3b: Trends of survival in patients with VT/Vfib as initial rhythm; 3c: Trends of survival among patients with PEA/Asystole as initial rhythm

Abbreviations: MCS: Mechanical circulatory support; VT: Ventricular tachycardia; Vfib: Ventricular fibrillation

3a

3b

3c

Supplementary Table 1. ICD 9 codes

  ICD 9 diagnosis and procedure codes
Out of hospital cardiac arrest 427.5
Ventricular tachycardia 427.1
Ventricular fibrillation 427.41, 427.42
Coronary angiogram 88.54, 88.55, 88.56, 88.57, 00.24, 00.59,37.22, 37.23
PCI 36.06, 36.07,00.40, 00.41, 00.42, 00.43, 00.44, 00.45, 00.46, 00.47, 00.48,00.66
Acute myocardial infarction 410.1x – 410.9x
Coronary artery disease 414.00 – 414.07
Family history of coronary artery disease  V17.3
Prior myocardial infarction 412
Prior percutaneous coronary intervention V45.82
Prior coronary artery bypass grafting V45.81
Prior cardiac arrest V12.53
Family history of sudden cardiac death V17.41
Carotid artery disease 433.10
Atrial fibrillation 427.31

Supplementary Table 2. Trends for MCS* use in OHCA patients from 2008 to 2014

  Overall 2008 2009 2010 2011 2012 2013 2014 Relative change
Overall 985,861 138,908 143,147 142,753 141,077 129,936 138,908 151,231
MCS (N) 52941 6973 7229 6609 8239 7809 7487 8620
Percentage (%) 5.37 5.02 5.05 4.63 5.84 6.01 5.39 5.7 13.55
IABP(N) 48307 6806 6943 6310 7632 6965 6556 7093
Percentage (%) 4.9 4.9 4.85 4.42 5.41 5.36 4.72 4.69 -4.29
PVAD ll (N) 3352 56 200 243 451 611 708 1089
Percentage (%) 0.34 0.04 0.14 0.17 0.32 0.47 0.51 0.72 1700.00
ECMO # (N) 3746 194 286 300 508 715 722 1043
Percentage (%) 0.38 0.14 0.2 0.21 0.36 0.55 0.52 0.69 392.86
VT/VF, % 249226 33782 33897 34075 36835 34329 35588 40802
MCS (N) 29683 3932 3973 3745 4575 4370 4263 4843
Percentage (%) 11.91 11.64 11.72 10.99 12.42 12.73 11.98 11.87 1.98
IABP (N) 27515 3868 3837 3609 4313 3992 3836 4064
Percentage (%) 11.04 11.45 11.32 10.59 11.71 11.63 10.78 9.96 -13.01
PVAD (N) 3038 443 434 382 505 464 414 405
Percentage (%) 0.8 0.1 0.41 0.38 0.74 1.1 1.19 1.52 1420.00
ECMO (N) 1595 74 142 150 184 254 292 506
Percentage (%) 0.64 0.22 0.42 0.44 0.5 0.74 0.82 1.24 463.64
PEA ** /Asystole, % 736635 105125 109250 108678 104242 95607 103320 110429
MCS (N) 23204 3049 3245 2869 3638 3432 3213 3777
Percentage (%) 3.2 2.9 3.0 2.6 3.5 3.6 3.1 3.4 17.93
IABP (N) 20773 2944 3103 2706 3304 2973 2717 3026
Percentage (%) 2.8 2.8 2.8 2.5 3.2 3.1 2.6 2.7 -2.14
PVAD (N) 1326 21 66 109 177 229 289 464
Percentage (%) 0.18 0.02 0.06 0.1 0.17 0.24 0.28 0.42 2000.00
ECMO (N) 2136 116 142 141 323 459 434 541
Percentage (%) 0.29 0.11 0.13 0.13 0.31 0.48 0.42 0.49 345.45

Abbreviations: *MCS: mechanical circulatory support; OHCA: Out of Hospital Cardiac Arrest; ‡IABP: intra-aortic balloon pump;  ll PVAD: percutaneous ventricular assist device; # ECMO: extra corporeal membrane oxygenation; ** PEA: pulseless electric activity

Supplementary Table 3: Trends of Survival to discharge in OHCA patients from 2008 to 2014

Survival (%) 2008 2009 2010 2011 2012 2013 2014 Overall
Overall, % 40.5 39.7 40.8 45.5 46.2 47.1 47.2 43.9
Without MCS 39.6 38.9 40.1 44.7 45.5 46.6 46.7 43.1
With MCS 59.3 54.8 55.2 58.8 56.9 57.3 55.7 56.9
IABP 60.0 54.9 56.3 60.8 59.5 59.4 58.1 58.5
PVAD 33.3 56.1 51.0 51.1 36.6 41.3 44.5 44.2
ECMO 31.6 46.6 30.5 32.4 36.4 44.5 44.8 39.8
VT/VF, % 56.3 54 56.1 60 60.1 60.5 61.2 58.4
Without MCS 55 53.1 55.2 59 59.8 60.1 61.1 57.7
With MCS 65.7 60.7 63.1 64.9 61.9 64 62.1 63.2
IABP 66.3 60.5 64.3 66.5 63.6 65.1 64.8 64.5
PVAD 57.1 60.7 57.7 52.7 43.4 56.5 46.4 50.8
ECMO 26.7 51.7 33.3 40.5 49 47.5 49 45.5
PEA/Asystole, % 35.5 35.3 36 40.4 41.2 42.5 42.1 38.9
Without MCS 35.1 34.8 35.8 40 40.8 42.3 41.9 38.6
With MCS 51 47.7 44.8 51.1 50.6 48.5 47.5 48.8
IABP 51.8 47.9 45.6 53.3 54.2 51.4 49 50.5
PVAD 0 46.2 43.5 48.6 25.5 19 41.9 34.7
ECMO 34.8 41.4 27.6 27.7 29.4 42.5 40.7 35.6

Abbreviations: MCS: mechanical circulatory support; IABP: intraaortic balloon pump;  PVAD: percutaneous ventricular assist device;  ECMO: extra corporeal membrane oxygenation; VT: ventricular tachycardia; VF: ventricular fibrillation; PEA: pulseless electric activity



Recommendation
EssayHub’s Community of Professional Tutors & Editors
Tutoring Service, EssayHub
Professional Essay Writers for Hire
Essay Writing Service, EssayPro
Professional Custom
Professional Custom Essay Writing Services
In need of qualified essay help online or professional assistance with your research paper?
Browsing the web for a reliable custom writing service to give you a hand with college assignment?
Out of time and require quick and moreover effective support with your term paper or dissertation?
Did you find someone who can help?

Fast, Quality and Secure Essay Writing Help 24/7!