Resuscitation Science

What Is the Optimal Chest Compression Depth During Out- of-Hospital Cardiac Arrest Resuscitation of Adult Patients?

Ian G. Stiell, MD; Siobhan P. Brown, PhD; Graham Nichol, MD; Sheldon Cheskes, MD; Christian Vaillancourt, MD; Clifton W. Callaway, MD; Laurie J. Morrison, MD; James Christenson, MD; Tom P. Aufderheide, MD; Daniel P. Davis, MD; Cliff Free, EMT-P; Dave Hostler, PhD; John A. Stouffer, EMT-P; Ahamed H. Idris, MD; and the Resuscitation Outcomes Consortium Investigators

Background—The 2010 American Heart Association guidelines suggested an increase in cardiopulmonary resuscitation compression depth with a target >50 mm and no upper limit. This target is based on limited evidence, and we sought to determine the optimal compression depth range. Methods and Results—We studied emergency medical services–treated out-of-hospital cardiac arrest patients from the Resuscitation Outcomes Consortium Prehospital Resuscitation Impedance Valve and Early Versus Delayed Analysis clinical trial and the Epistry-Cardiac Arrest database. We calculated adjusted odds ratios for survival to hospital discharge, 1-day survival, and any return of circulation. We included 9136 adult patients from 9 US and Canadian cities with a mean age of 67.5 years, mean compression depth of 41.9 mm, and a return of circulation of 31.3%, 1-day survival of 22.8%, and survival to hospital discharge of 7.3%. For survival to discharge, the adjusted odds ratios were 1.04 (95% CI, 1.00–1.08) for each 5-mm increment in compression depth, 1.45 (95% CI, 1.20–1.76) for cases within 2005 depth range (>38 mm), and 1.05 (95% CI, 1.03–1.08) for percentage of minutes in depth range (10% change). Covariate-adjusted spline curves revealed that the maximum survival is at a depth of 45.6 mm (15-mm interval with highest survival between 40.3 and 55.3 mm) with no differences between men and women. Conclusions—This large study of out-of-hospital cardiac arrest patients demonstrated that increased cardiopulmonary resuscitation compression depth is strongly associated with better survival. Our adjusted analyses, however, found that maximum survival was in the depth interval of 40.3 to 55.3 mm (peak, 45.6 mm), suggesting that the 2010 American Heart Association cardiopulmonary resuscitation guideline target may be too high. Clinical Trial Registration—URL: http://www.clinicaltrials.gov. Unique identifier: NCT00394706. (Circulation. 2014;130:1962-1970.) Key Words: cardiopulmonary resuscitation ◼ emergency medical services ◼ heart arrest

ut-of-hospital cardiac arrest (OHCA) leads to an esti- support, and effective postresuscitation care.2–6 Considerable Omated 330 000 deaths each year in the United States and efforts by communities and hospitals to strengthen these links Canada.1 Although overall survival for treated OHCA is low, have led to only modestly better survival rates in recent years.1 hospital discharge rates vary from 3.0% to 16.3%.1 This varia- Clinical Perspective on p 1970 tion in survival can be partly attributed to local differences in the 5 key links in the chain of survival: rapid emergency In recent years, those involved in cardiac resuscitation have medical services (EMS) access, early cardiopulmonary resus- recognized that the quality, quantity, and timeliness of CPR citation (CPR), early defibrillation, early advanced cardiac life are key determinants for survival from cardiac arrest and that

Received January 15, 2014; accepted September 11, 2014. From the Department of Emergency Medicine and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada (I.G.S., C.V.); Clinical Trials Center, Department of Biostatistics (S.P.B., G.N.) and Department of Medicine (G.N.), University of Washington, Seattle, WA; University of Washington-Harborview Center for Prehospital Emergency Care, Seattle, WA (G.N.); Division of Emergency Medicine, Department of Family and Community Medicine (S.C.), and Division of Emergency Medicine, Department of Medicine (L.J.M.), University of Toronto, Toronto, Ontario, Canada; Rescu, Li Ka Shing Knowledge Institute, St Michael’s Hospital, Toronto, Ontario, Canada (S.C., L.J.M.); Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA (C.W.C., D.H.); Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia, Canada (J.C.); Department of Emergency Medicine, Medical College of Wisconsin, Milwaukee, WI (T.P.A.); Department of Emergency Medicine, University of California, San Diego, CA (D.P.D.); Camas Fire Department, Camas, WA (C.F.); Central Washington University, Ellensburg, WA (J.A.S.); Departments of Emergency Medicine and Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX (A.H.I.). The online-only Data Supplement is available with this article at http://circ.ahajournals.org/lookup/suppl/doi:10.1161/CIRCULATIONAHA. 114.008671/-/DC1. Correspondence to Ian G. Stiell, MD, Ottawa Hospital Research Institute, Clinical Epidemiology Unit, Office F657, The Ottawa Hospital, Civic Campus, 1053 Carling Ave, Ottawa, Ontario, K1Y 4E9, Canada. E-mail [email protected] © 2014 American Heart Association, Inc. Circulation is available at http://circ.ahajournals.org DOI: 10.1161/CIRCULATIONAHA.114.008671 Downloaded from http://circ.ahajournals.org/1962 at University of Arizona on February 17, 2016 Stiell et al CPR Compression Depth 1963 delivery of chest compressions is often poor.7,8 Recent tech- cardiopulmonary arrest outside of the hospital within the catch- nological advances now allow for the detailed measurement ment area of a participating ROC EMS agency and were treated with and review of key compression parameters.9–11 Using this defibrillation or delivery of chest compressions by EMS providers. We included patients with any initial cardiac rhythm. We excluded 12 13 technology, Christenson et al and Vaillancourt et al dem- patients who did not have attempts at resuscitation by EMS, with an onstrated an association between outcomes of OHCA patients obvious cause of arrest, whose arrests were EMS witnessed, who and the proportion of each resuscitation minute during which received a shock from a bystander-applied automated external defi- compressions were delivered (chest compression fraction). brillator, and anyone who had >5 minutes of EMS CPR before the 14 pads were applied. We also excluded patients for who ≥1 minute of Cheskes et al found that longer perishock and preshock electronic CPR compression depth data were not available. These pauses were independently associated with a decrease in sur- data may have been unavailable because some EMS agencies do not vival to hospital discharge in patients presenting in a shock- use defibrillators with accelerometers capable of measuring compres- able rhythm. Idris et al15 described an association between sion depth or because of inadvertent failure to capture and transmit chest compression rate and return of spontaneous circulation. the data. The ROC PRIMED trial and the ROC Epistry were reviewed and Chest compression depth is another aspect of CPR for which approved by the appropriate local institutional review boards (United data are limited. Current CPR guidelines for compression rate States) or research ethics boards (Canada) without the need for and depth have been, for the most part, derived with relatively informed consent from subjects. Strict confidentiality was maintained little robust human data to support them.3,16 The 2005 guide- at all times, and no personal identifiers were retained in the database. lines recommended a depth range of 38 to 50 mm, whereas the new 2010 guidelines recommend a depth of ≥50 mm (2 in) Data Collection with no upper limit specified. For compression depth, clini- The characteristics of chest compressions were measured via an cal studies to date have been small, with insufficient power to accelerometer interface between the rescuer and the patient’s chest evaluate clinically important outcomes.7,17–22 Our group stud- using commercially available defibrillators. Tracings were acquired and downloaded from Phillips (N=1869; Andover, MA) and ZOLL ied 1029 OHCA cases and found lower-than-recommended (N=7246; Chelmsford, MA) defibrillators.10,27 CPR process mea- compression depth in half of patients by 2005 guideline stan- sures, including compression rate, chest compression fraction, and dards and almost all by 2010 standards, as well as an inverse compression depth, were calculated by proprietary automated exter- association between compression depth and rate.23 We found nal defibrillator analytic software. Chest compression fraction was a strong association between survival outcomes and increased defined as the proportion of resuscitation time without spontaneous circulation during which chest compressions were administered. compression depth but no clear evidence to support or refute Compression depth was defined as the posterior depression of the the 2010 recommendations of >50 mm. Our objective for the anterior chest wall in millimeters. The mean compression values for current study was to determine the optimal compression depth all minute intervals were averaged for each patient using all available for adults in a large sample of OHCA patients. minutes in the first 10 minutes after pads were placed. For compres- sion depth, we defined depth within the recommended range as per the 2005 international guidelines, with an average depth of ≥38 mm. Methods We described the case as being within the recommended depth if the mean depth was ≥38 mm for >60% of the minutes recorded. Design and Setting Patient and clinical data were abstracted from EMS and hospital The Resuscitation Outcomes Consortium (ROC) is composed of 10 records using standardized definitions for patient characteristics, EMS US and Canadian universities and their regional EMS systems and has process, and outcome at hospital discharge. Data were abstracted a mandate to conduct large controlled trials of prehospital interven- locally, coded without personal health information, and transmitted to tions for cardiac arrest and trauma. This study represents an analysis the data coordinating center electronically. Site-specific quality assur- of consecutive OHCA cases prospectively gathered in the recent ROC ance included initial EMS provider training in data collection and Prehospital Resuscitation Impedance Valve and Early Versus Delayed continuing education of EMS providers. The data coordinating center Analysis (PRIMED) trial or in the ROC Epistry-Cardiac Arrest.24 The assured the quality of the data by a variety of techniques.1 ROC PRIMED trial used a partial factorial design, whereby most patients were randomly assigned to 2 concurrent protocols. The first protocol compared early rhythm analysis versus later rhythm analy- Outcome Measures sis, and the second protocol compared use of an impedance threshold The primary outcome was survival to hospital discharge, defined as device versus use of a sham impedance threshold device. The ROC discharged alive from hospital after the index OHCA. Patients who Epistry is a prospective multicenter observational registry of OHCA were transferred to another acute care facility (eg, to undergo implant- in EMS agencies and receiving institutions and includes patient out- able cardioverter defibrillator placement) were considered to still be comes and electronic data on the CPR process.25 hospitalized. Patients were considered discharged if transferred to a The ROC EMS network consists of 36 000 EMS professionals nonacute ward or facility. The secondary outcomes were survival to within 260 EMS agencies; provides coverage to an estimated 24 the next calendar day and return of spontaneous circulation (ROSC). million people from urban, suburban, and rural communities; and Survival for 1 day meant that the patient was still alive 1 day past the transports patients to 287 different hospitals.26 This analysis included date of the event. ROSC refers to the presence of a palpable pulse OHCA patients treated by EMS and for whom electronic compres- for any duration of time before arrival at the hospital. Data were sion depth data were available. Sites that did not have the techni- abstracted from collated EMS and hospital source documents. cal capacity to measure compression depth were not included, and, hence, this study included data from 95 participating EMS agencies affiliated with 9 US and Canadian ROC sites. At the time of data Statistical Analysis collection, OHCA patients were being treated according to the 2005 All of the statistical analyses were performed with commercially guideline standards for compression depth (38–50 mm). available statistical packages (SAS version 9.1.3; SAS Institute, Cary, NC; R version 2.14.1; R Foundation for Statistical Computing, Vienna, Austria). Summary results are presented as mean (±SD) or Population median (interquartile range). To test differences in baseline charac- We included all individuals from the ROC PRIMED trial or the teristics between subjects who did and did not survive to discharge, ROC Epistry, ≥18 years of age, who experienced nontraumatic likelihood ratio χ2 tests or t tests were used as appropriate. ANOVA Downloaded from http://circ.ahajournals.org/ at University of Arizona on February 17, 2016 1964 Circulation November 25, 2014 was used to compare mean compression depths across study sites. in terms of clinical significance for characteristics and out- The association between depth and rate categories was tested with a comes to those excluded, except that none were from British 2 likelihood ratio χ test. The association between compression depth Columbia, more were from Toronto, and they had a lower sur- (evaluated separately with 4 approaches) and outcomes of interest was quantified using multivariate logistic regression with the Huber- vival rate (Table I in the online-only Data Supplement). White sandwich SE.28 The key covariates/potential confounders The patients in the study were typical of OHCA cases, with assessed were age, sex, public location, bystander witnessed arrest, only 13% from a public location, 44% bystander witnessed, bystander CPR, EMS response time, CPR fraction, compression rate, 42% receiving bystander CPR, and 99% having an advanced site, and device manufacturer. We did not include cardiac rhythm, life-support EMS crew in attendance (Table 1). The mean val- because this is potentially a path variable. Smoothing splines were used to explore the relationship between average compression depth ues for CPR process measures were compression rate of 108 and outcome, with a goal of finding the optimal 15-mm interval for (SD, 16) per minute and chest compression fraction of 0.68 depth.29 Smoothing splines were creating by including the b-spline (SD, 0.15). Of all patients, 31.3% had ROSC, 22.8% survived basis for a natural cubic spline of depth in a logistic regression model 1 day, and 7.3% survived to hospital discharge. in place of the other depth measures. Four degrees of freedom were Table 2 displays compression depth data, which was avail- used in the unadjusted models and 5 in the adjusted. able per case for a median of 7 minutes (interquartile range, 5–10). The overall median chest compression depth was 41 Results mm (interquartile range, 35–48 mm), and 36% of cases had a During the study period from June 2007 to December 2010, mean value <38 mm. In addition, we calculated that 40% of EMS agencies in the 10 participating ROC sites treated 27 986 cases were not within the 2005 recommended range for depth. cases of cardiac arrest. Of these patients, all but 9266 were We also found (Table II in the online-only Data Supplement) excluded for the reasons indicated in Figure 1; another 130 that compression rate and depth were inversely related cases had missing data, leaving a final study group of 9136 (P<0.001), such that 53% of cases with a compression rate patients. The most common reason for exclusion was missing >120 also had depth <38 mm. time from 911 telephone call to EMS arrival (65 cases); miss- Figure 2 shows the distribution of survival to hospital ing subject age was the next most common (n=35). The other discharge by compression depth categories with unadjusted 30 subjects were missing various covariates used in the regres- smoothed spline plots and shows much poorer outcomes for sion models. The patients in the final study cohort were similar patients with the lowest mean compression depth values. There is a gradual increase in the probability of survival as average depth increases, but this appears to fall off again at the greater depth levels, with a similar pattern for both men and women. See also Figure I in the online-only Data Supplement. We compared the univariate characteristics of the 666 patients who survived to discharge with those who did not (Table 3) and found many correlates with better outcome, including whether the compression depth was greater and within the recommended range (P<0.001). We conducted 4 multivariate analyses (Table 4) to evaluate the association of compression depth and other covariates on the 3 survival measures. Not unexpectedly, the factors most strongly associ- ated with good outcomes were arrest in a public location and bystander witnessed cases (odds ratios not shown). All 4 of the depth measures (mean values, categories, and within rec- ommended range) were independently associated with better outcomes for all 3 of the survival measures. For survival to discharge, the adjusted odds ratios were 1.04 (95% CI, 1.00– 1.08) for each 5-mm increment in compression depth, 1.45 (95% CI, 1.20–1.76) for cases within depth range, and 1.05 (95% CI, 1.03–1.08) for percentage of minutes in depth range (10% change). Sensitivity analyses adjusted for initial rhythm and duration of CPR and found similar results except for lit- tle association between compression depth and survival for patients with a nonshockable rhythm (Table III in the online- only Data Supplement). Finally, we created a covariate-adjusted smoothed spline plot with 95% CIs of the probability of survival versus com- pression depth. Inspection of Figure 3A reveals that survival peaks at 45.6 mm (15-mm interval with highest survival between 40.3 and 55.3 mm). The survival curves are very Figure 1. Patient enrollment. similar for men and women (Figure 3B). Downloaded from http://circ.ahajournals.org/ at University of Arizona on February 17, 2016 Stiell et al CPR Compression Depth 1965

Table 1. Patient Characteristics Table 2. Compression Depth Measures

Characteristics Total (n=9136) Total (n=9136) Age, mean (SD), y 67.5 (16.4) Chest compression depth*, median (Q1, Q3), mm 41 (35, 48) Men, n (%) 5857 (64) Mean (SD) 41.9 (11.7) Public location, n (%) 1161 (13) Compression depth category, % (n)* Bystander witnessed, n (%) 4065 (44) <38 mm 36 (3334) Bystander CPR, n (%) 3633 (42) 38–51 mm 45 (4134) Site, n (%) >51 mm 18 (1668) Alabama 22 (0) Within depth range, % (n)† 60 (5461) Percentage of minutes in recommended range, mean (SD) 61 (39) Dallas/Fort Worth 272 (3) Milwaukee 936 (10) *Data show the average depth in millimeters for 10 minutes. †Data show the average depth ≥38 mm for ≥60% of minutes with Ottawa 1389 (15) cardiopulmonary resuscitation process measures available. Pittsburgh 596 (7) Portland 168 (2) San Diego 842 (9) Discussion Seattle/King County 837 (9) Interpretation of Findings Toronto 4074 (45) This large ROC data set allowed us to accurately evaluate the role of CPR compression depth in the outcomes of OHCA EMS response patients. We found that adequate compression depth was often Time from 911 call to scene, mean (SD), min 5.9 (2.5) not provided according to the 2005 guidelines and usually not Time from 911 call to first EMS shock 10.5 (3.5) provided according to the 2010 guidelines. We also found a assessment, mean (SD), min significantly deleterious effect on compression depth when ALS first on scene, n (%) 3274 (36) the mean compression rate was faster than recommended. We ALS on scene, n (%) 9049 (99) demonstrated that increased depth, using a variety of measures, No. of responding EMS units, mean (SD)* 2.6 (0.8) is strongly associated with short-term outcomes, as well as bet- ter survival to hospital discharge. A covariate-adjusted spline EMS interventions analysis further shows that the maximum survival in this sam- Intubation attempted, n (%) 6747 (74) ple was observed in the mean depth interval of 40.3 to 55.3 mm Shocks delivered, n (%) 3647 (40) (peak, 45.6 mm). Finally, despite a large presumed difference Epinephrine use noted, n (%) 7923 (87) in weight between men and women, their optimal compression CPR process measures depth appears to be the same. These findings do not support recent guideline changes that recommend compression depth CPR before first analysis, n (%) 8409 (92) exceed 50 mm (2 in) with no upper limit specified. CPR fraction, mean (SD) 0.68 (0.15) Chest compression rate, mean (SD) 108.3 (16.0) Previous Studies Initial cardiac rhythm, n (%) The 2010 CPR guidelines significantly increased the recom- VF/VF 2181 (24) mended minimum compression depth from 38 to 50 mm but PEA 1845 (20) acknowledged insufficient evidence to indicate a specific upper limit.3,16 Although there have been some animal30–32 Asystole 4513 (49) and human data suggesting better outcomes with increased AED no shock, no strip 583 (6) compression depth, the evidence for depth >50 mm is very Cannot determine/missing 14 (0) sparse. Most clinical studies have tended to evaluate overall Device, n (%) CPR performance or feedback, usually in patients with shock- Philips 1869 (20) able rhythms, and have not focused on the independent impact of compression depth.7,17–21 These studies have been relatively Zoll 7246 (79) small, with insufficient power to evaluate clinically important Other 21 (0) outcomes or to compare different levels of depth. Edelson et Outcomes al18 found an association between greater compression depth Any prehospital ROSC, n (%) 2861 (31.3) and shock success in 60 cases but had only 5 patients with 22 Survived ≥1 day, n (%) 2081 (22.8) depth >50 mm. A subsequent larger study of in-hospital Survived to hospital discharge, n (%) 666 (7.3) cardiac arrest debriefing demonstrated better ROSC with better overall CPR performance but did not isolate specific Note that percentages are of cases with nonmissing data. AED indicates compression depth levels as a factor.21 Kramer-Johansen et automated external defibrillator; ALS, advanced life support; CPR, cardiopulmonary 19 resuscitation; EMS, emergency medical services; PEA, pulseless electrical al evaluated 284 patients and found better hospital admis- activity; ROSC, return of spontaneous circulation; and VF, ventricular fibrillation. sion rates with increased compression depth, but very few *Information was only available about the first 4 EMS units at the scene. cases had depth >50 mm. Babbs et al22 examined a library of Downloaded from http://circ.ahajournals.org/ at University of Arizona on February 17, 2016 1966 Circulation November 25, 2014

All l (%) va Survi 0.00 0.02 0.04 0.06 0.08 <25 25−29 30−34 35−3940−44 45−49 50−54 55−59 60−64 65+ n=180 n=646 n=1177 n=1784 n=1825 n=1347 n=883 n=474 n=251 n=270 Depth (mm)

Males ) al (% iv Su rv 0.00 0.02 0.04 0.06 0.08 0.10 <25 25−29 30−34 35−3940−44 45−49 50−54 55−59 60−64 65+ n=114 n=376 n=727 n=1112 n=1199 n=898 n=580 n=334 n=174 n=175 Depth (mm)

Females ) al (% iv Su rv 0.00 0.02 0.04 0.06 0.08 0.10 0.12 <25 25−29 30−34 35−3940−44 45−49 50−54 55−59 60−64 65+ n=66 n=270 n=450 n=672n=626 n=449 n=303 n=140 n=77 n=95 Depth (mm) Figure 2. Smoothing spline of survival on depth. prehospital CPR process data and found, in 101 patients with depth Subsequent to the 2010 CPR guidelines, our group pub- >51 mm, a higher rate of electric conversion but no difference lished a specific compression depth analysis of 1029 OHCA in ROSC or other clinical outcomes. cases from the ROC Epistry.23 We found a strong association

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Table 3. Univariate Comparison of Clinical Characteristics of Patients Who Did and Did Not Survive to Hospital Discharge

Outcome Deaths (n=8470) Survivors (n=666) P Value From χ2 or t Test Age, mean (SD), y 68.2 (16.3) 58.8 (15.3) <0.001 Men, n (%) 5387 (63.6) 470 (70.6) <0.001 Public location, n (%) 932 (11.0) 229 (34.4) <0.001 Bystander witnessed, n (%) 3546 (41.9) 519 (77.9) <0.001 Bystander CPR, n (%) 3269 (40.9) 364 (56.9) <0.001 EMS response Time from 911 call to scene, mean (SD) 5.9 (2.5) 5.2 (2.0) <0.001 Time from 911 call to first EMS shock assessment, mean (SD) 10.6 (3.5) 9.2 (2.9) <0.001 ALS first on scene, n (%) 3017 (35.8) 257 (38.9) 0.258 ALS on scene, n (%) 8385 (99.0) 664 (99.7) 0.037 Number of responding EMS units, mean (SD)* 2.6 (0.8) 2.7 (0.8) <0.001 EMS interventions Intubation attempted, n (%) 6274 (74.1) 473 (71.0) 0.088 Shocks delivered, n (%) 3099 (36.6) 548 (82.3) <0.001 Epinephrine use noted, n (%) 7547 (89.2) 376 (56.5) <0.001 CPR process measures CPR before first analysis, n (%) 7796 (92.0) 613 (92.0) 1.000 CPR fraction, mean (SD) 0.69 (0.14) 0.64 (0.17) <0.001 Chest compression rate, mean (SD) 108.4 (16.0) 107.1 (16.1) 0.038 Chest compression depth, mean (SD), mm 41.8 (11.8) 43.5 (10.7) <0.001 Compression depth category, % (n) <38 mm 3150 (37.2) 184 (27.6) 38–51 mm 3790 (44.7) 344 (51.7) >51 mm 1530 (18.1) 138 (20.7) <0.001 Within recommended depth range, % (n)† 5006 (59.1) 455 (68.3) <0.001 Percentage of minutes in depth range, mean (SD) 61% (39) 69% (37) <0.001 Initial cardiac rhythm, n (%) VF/VF 1670 (19.7) 511 (76.7) PEA 1754 (20.7) 91 (13.7) Asystole 4462 (52.7) 51 (7.7) AED no shock, no strip 571 (6.7) 12 (1.8) Cannot determine/missing 13 (0.2) 1 (0.2) <0.001 Note that percentages are of cases with nonmissing data. AED indicates automated external defibrillator; ALS, advanced life support; CPR, cardiopulmonary resuscitation; EMS, emergency medical services; PEA, pulseless electrical activity; ROSC, return of spontaneous circulation; and VF, ventricular fibrillation. *Information was only available for the first 4 EMS units at the scene. †Average depth was ≥38 mm for ≥60% of minutes with CPR process measures available. between survival outcomes and increased compression depth mean, 29 seconds), and we did not examine data beyond 10 but had insufficient power to identify the optimal compression minutes of CPR. We did not have data for body size, firm- depth for adult men or women. ness of the surface under the patient, leaning, or duty cycle, all possible confounders to the interpretation of compression Limitations and Strengths depth data.33 We did, however, adjust for sex, which may be The study population represents a consecutive sample of cases considered a crude proxy for weight, and found no difference from sites where compression depth could be measured and between men and women. We had no measurements for chil- during a period when the 2005 guideline standards were in dren under age 18 years. We did not reliably capture data on use. Regardless, we could detect no selection bias in our cases whether device feedback was provided to providers. compared with those not included. Our records could not cap- The major strengths of the study include a large sample of ture CPR data before the placement of accelerometer pads, a patients with all initial rhythms, from 9 geographically dis- time period estimated to be <30 seconds (median, 16 seconds; parate locations in the US and Canada, and receiving use of

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Table 4. Adjusted Odds Ratios for Association of 4 Separate Depth Measures With 3 Survival Outcomes

Prehospital ROSC Survival to Day After Arrest Survival to Discharge Compression Depth Measure Adjusted OR (CI)* P Value Adjusted OR (CI)* P Value Adjusted OR (CI)* P Value Compression depth (5-mm increments) 1.06 (1.04–1.08) <0.001 1.05 (1.03–1.08) <0.001 1.04 (1.00–1.08) 0.045 Compression depth category, mm <38 0.70 (0.60–0.80) 0.71 (0.61–0.83) 0.69 (0.53–0.90) 38–51 0.86 (0.75–0.97) 0.88 (0.76–1.01) 1.03 (0.82–1.31) >51 Reference <0.001† Reference <0.001† Reference <0.001† Within depth range‡ 1.27 (1.15–1.40) <0.001 1.25 (1.11–1.39) <0.001 1.45 (1.20–1.76) <0.001 Percentage of minutes in depth range 1.04 (1.02–1.05) <0.001 1.04 (1.02–1.05) <0.001 1.05 (1.03–1.08) <0.001 (10% change) The ORs for each of the depth measures were estimated from a separate multivariable logistic regression model. The estimates and CIs for the other covariates come from the model that includes depth as a linear variable. CI indicates confidence interval; CPR, cardiopulmonary resuscitation; OR, odds ratio; and ROSC, return of spontaneous circulation. *Data were adjusted for age, sex, public location, bystander witnessed, bystander CPR, CPR fraction, chest compression rate, time from 911 call to emergency medical services at scene, device manufacturer, and study site. †Data show the type III test of the association between depth and outcome. ‡Average depth was ≥38 mm for ≥60% of minutes with CPR process measures available. devices from 2 different manufacturers. The overall survival- providers must be mindful of achieving adequate compression to-discharge proportion of 7.3% is quite reasonable, consider- depth but without going too deep. In the absence of other large ing that we excluded cases witnessed by EMS or that received studies, we anticipate that future recommendations for optimal bystander AED shocks. With 1668 patients who received an compression depth for adults may be in the range of 40 to 55 average compression depth >50 mm, we were able to conduct mm. Providers must be cognizant of achieving proper compres- robust analyses on clinically important outcomes and evaluate sion depth along with other CPR process measures, such as rate, depth in a variety of ways. fraction, and perishock pauses. Of note is that depth and rate are inversely related, such that exceeding the target for one will Clinical Implications likely lead to underperformance for the other. How best to assist This study has a number of important implications for those per- EMS responders in providing excellent CPR is unknown, but forming CPR. Our data clearly indicate that ROSC, short-term presumably this includes a combination of good training, CPR survival, and survival to discharge are better when compression process debriefing, and possibly real-time feedback.34,35 depth is greater. Compared with the 2010 guideline recommen- dation depth of >50 mm, however, we found a peak effect at 45.6 Research Implications mm within an interval of 40.3 to 55.3 mm, with similar results for Clinical studies of the CPR process are difficult to conduct but both men and women. Hence, we believe that professional CPR are essential if we are to know the optimal targets and interplay

ABSurvival to Hospital Discharge Survival to Hospital Discharge 0.15 0.15 Male Female 0.10 0.10 Probability of Survival Probability of Survival 0.05 0.05 0.00 0.00 40.3 45.6 55.3 20 30 40 50 60 20 30 40 50 60 Depth (mm) Depth (mm) Figure 3. A, Covariate-adjusted survival to discharge by compression depth with 95% confidence intervals (CIs).B , Covariate-adjusted survival to discharge by compression depth for men and women separately. Downloaded from http://circ.ahajournals.org/ at University of Arizona on February 17, 2016 Stiell et al CPR Compression Depth 1969 among compression depth, compression rate, ventilations, 7. Wik L, Kramer-Johansen J, Myklebust H, Sørebø H, Svensson L, Fellows compression fraction, duty cycle, and recoil. In addition, more B, Steen PA. Quality of cardiopulmonary resuscitation during out-of-­ hospital cardiac arrest. JAMA. 2005;293:299–304. data for children are required to understand the best CPR pro- 8. Abella BS, Sandbo N, Vassilatos P, Alvarado JP, O’Hearn N, Wigder HN, cess parameters to optimize survival. Ultimately we need ran- Hoffman P, Tynus K, Vanden Hoek TL, Becker LB. Chest compression domized intervention trials that evaluate the impact of different rates during cardiopulmonary resuscitation are suboptimal: a prospective study during in-hospital cardiac arrest. Circulation. 2005;111:428–434. combinations of CPR process targets on patient survival. 9. Kramer-Johansen J, Edelson DP, Losert H, Köhler K, Abella BS. Uniform reporting of measured quality of cardiopulmonary resuscitation (CPR). Conclusions Resuscitation. 2007;74:406–417. This large study of OHCA patients from a variety of set- 10. Aase SO, Myklebust H. Compression depth estimation for CPR quality assessment using DSP on accelerometer signals. IEEE Trans Biomed Eng. tings demonstrated that increased CPR compression depth is 2002;49:263–268. strongly associated with better survival to hospital discharge. 11. Ornato JP, Peberdy MA. Measuring progress in resuscitation: it’s time for An adjusted analysis, however, found that maximum survival a better tool. Circulation. 2006;114:2754–2756. 12. Christenson J, Andrusiek D, Everson-Stewart S, Kudenchuk P, Hostler D, was in the mean depth interval of 40.3 to 55.3 mm (peak, 45.6 Powell J, Callaway CW, Bishop D, Vaillancourt C, Davis D, Aufderheide mm), suggesting that the 2010 American Heart Association TP, Idris A, Stouffer JA, Stiell I, Berg R; Resuscitation Outcomes CPR guideline target may be too high. We encourage the use Consortium Investigators. Chest compression fraction determines sur- of all validated strategies for prehospital and in-hospital car- vival in patients with out-of-hospital ventricular fibrillation. Circulation. 2009;120:1241–1247. diac arrest resuscitations to assist rescuers to stay within range 13. Vaillancourt C, Everson-Stewart S, Christenson J, Andrusiek D, Powell for key CPR parameters. J, Nichol G, Cheskes S, Aufderheide TP, Berg R, Stiell IG. The impact of increased chest compression fraction on return of spontaneous circulation for out-of-hospital cardiac arrest patients not in ventricular fibrillation. Acknowledgments Resuscitation. 2011;82:1501–1507. We gratefully acknowledge the tremendous effort and contribu- 14. Cheskes S, Schmicker RH, Christenson J, Salcido DD, Rea T, Powell J, tion of thousands of EMS providers and first responders who made Edelson DP, Sell R, May S, Menegazzi JJ, Van Ottingham L, Olsufka M, this logistically challenging trial possible. We also thank Catherine Pennington S, Simonini J, Berg RA, Stiell I, Idris A, Bigham B, Morrison Clement and Angela Marcantonio for their assistance with the article, L; Resuscitation Outcomes Consortium (ROC) Investigators. Perishock as well as Tom Rea for insightful comments. pause: an independent predictor of survival from out-of-hospital shock- able cardiac arrest. Circulation. 2011;124:58–66. 15. Idris AH, Guffey D, Aufderheide TP, Brown S, Morrison LJ, Nichols Sources of Funding P, Powell J, Daya M, Bigham BL, Atkins DL, Berg R, Davis D, Stiell The ROC is supported by a series of cooperative agreements to I, Sopko G, Nichol G; Resuscitation Outcomes Consortium (ROC) 10 regional clinical centers and 1 data coordinating center (5U01 Investigators. Relationship between chest compression rates and outcomes HL077863, HL077881, HL077871 HL077872, HL077866, from cardiac arrest. Circulation. 2012;125:3004–3012. HL077908, HL077867, HL077885, HL077887, HL077873, and 16. Sayre MR, Koster RW, Botha M, Cave DM, Cudnik MT, Handley AJ, Hatanaka T, Hazinski MF, Jacobs I, Monsieurs K, Morley PT, Nolan JP, HL077865) from the National Heart, Lung, and Blood Institute in Travers AH; Adult Basic Life Support Chapter Collaborators. Part 5: adult partnership with the National Institute of Neurological Disorders basic life support–2010 International Consensus on Cardiopulmonary and Stroke, US Army Medical Research and Materiel Command, Resuscitation and Emergency Cardiovascular Care Science With Treatment the Canadian Institutes of Health Research–Institute of Circulatory Recommendations. Circulation. 2010;122(16 suppl 2):S298–S324. and Respiratory Health, Defense Research and Development Canada, 17. Abella BS, Alvarado JP, Myklebust H, Edelson DP, Barry A, O’Hearn N, the Heart and Stroke Foundation of Canada, and the American Heart Vanden Hoek TL, Becker LB. Quality of cardiopulmonary resuscitation Association. during in-hospital cardiac arrest. JAMA. 2005;293:305–310. 18. Edelson DP, Abella BS, Kramer-Johansen J, Wik L, Myklebust H, Barry AM, Merchant RM, Hoek TL, Steen PA, Becker LB. Effects of compres- Disclosures sion depth and pre-shock pauses predict defibrillation failure during car- None. diac arrest. Resuscitation. 2006;71:137–145. 19. Kramer-Johansen J, Myklebust H, Wik L, Fellows B, Svensson L, Sørebø H, Steen PA. Quality of out-of-hospital cardiopulmonary resuscitation References with real time automated feedback: a prospective interventional study. 1. Nichol G, Thomas E, Callaway CW, Hedges J, Powell JL, Aufderheide TP, Resuscitation. 2006;71:283–292. Rea T, Lowe R, Brown T, Dreyer J, Davis D, Idris A, Stiell I; Resuscitation 20. Olasveengen TM, Tomlinson AE, Wik L, Sunde K, Steen PA, Myklebust Outcomes Consortium Investigators. Regional variation in out-of-hospital H, Kramer-Johansen J. A failed attempt to improve quality of out-of- cardiac arrest incidence and outcome. JAMA. 2008;300:1423–1431. hospital CPR through performance evaluation. Prehosp Emerg Care. 2. Cummins RO, Ornato JP, Thies WH, Pepe PE. Improving survival from 2007;11:427–433. sudden cardiac arrest: the “chain of survival” concept. Circulation. 21. Edelson DP, Litzinger B, Arora V, Walsh D, Kim S, Lauderdale DS, 1991;83:1832–1847. Vanden Hoek TL, Becker LB, Abella BS. Improving in-hospital cardiac 3. 2005 American Heart Association Guidelines for Cardiopulmonary arrest process and outcomes with performance debriefing. Arch Intern Resuscitation and Emergency Cardiovascular Care. Circulation. Med. 2008;168:1063–1069. 2005;112:IV1–203. 22. Babbs CF, Kemeny AE, Quan W, Freeman G. A new paradigm for 4. Stiell IG, Wells GA, Field B, Spaite DW, Nesbitt LP, De Maio VJ, Nichol human resuscitation research using intelligent devices. Resuscitation. G, Cousineau D, Blackburn J, Munkley D, Luinstra-Toohey L, Campeau 2008;77:306–315. T, Dagnone E, Lyver M; Ontario Prehospital Advanced Life Support Study 23. Stiell IG, Brown SP, Christenson J, Cheskes S, Nichol G, Powell J, Bigham Group. Advanced cardiac life support in out-of-hospital cardiac arrest. N B, Morrison LJ, Larsen J, Hess E, Vaillancourt C, Davis DP, Callaway Engl J Med. 2004;351:647–656. CW; Resuscitation Outcomes Consortium (ROC) Investigators. What is 5. Rea TD, Cook AJ, Stiell IG, Powell J, Bigham B, Callaway CW, Chugh S, the role of chest compression depth during out-of-hospital cardiac arrest Aufderheide TP, Morrison L, Terndrup TE, Beaudoin T, Wittwer L, Davis resuscitation? Crit Care Med. 2012;40:1192–1198. D, Idris A, Nichol G; Resuscitation Outcomes Consortium Investigators. 24. Stiell IG, Nichol G, Leroux BG, Rea TD, Ornato JP, Powell J, Christenson Predicting survival after out-of-hospital cardiac arrest: role of the Utstein J, Callaway CW, Kudenchuk PJ, Aufderheide TP, Idris AH, Daya MR, data elements. Ann Emerg Med. 2010;55:249–257. Wang HE, Morrison LJ, Davis D, Andrusiek D, Stephens S, Cheskes S, 6. Peberdy MA, Ornato JP. Post-resuscitation care: is it the missing link in Schmicker RH, Fowler R, Vaillancourt C, Hostler D, Zive D, Pirrallo RG, the Chain of Survival? Resuscitation. 2005;64:135–137. Vilke GM, Sopko G, Weisfeldt M; ROC Investigators. Early versus later Downloaded from http://circ.ahajournals.org/ at University of Arizona on February 17, 2016 1970 Circulation November 25, 2014

rhythm analysis in patients with out-of-hospital cardiac arrest. N Engl J 31. Ristagno G, Tang W, Chang YT, Jorgenson DB, Russell JK, Huang L, Med. 2011;365:787–797. Wang T, Sun S, Weil MH. The quality of chest compressions during car- 25. Morrison LJ, Nichol G, Rea TD, Christenson J, Callaway CW, diopulmonary resuscitation overrides importance of timing of defibrilla- Stephens S, Pirrallo RG, Atkins DL, Davis DP, Idris AH, Newgard tion. Chest. 2007;132:70–75. C; ROC Investigators. Rationale, development and implementation 32. Wu JY, Li CS, Liu ZX, Wu CJ, Zhang GC. A comparison of 2 types of of the Resuscitation Outcomes Consortium Epistry-Cardiac Arrest. chest compressions in a porcine model of cardiac arrest. Am J Emerg Med. Resuscitation. 2008;78:161–169. 2009;27:823–829. 26. Davis DP, Garberson LA, Andrusiek DL, Hostler D, Daya M, Pirrallo 33. Perkins G, Kocierz L, Smith S, McCulloch R, Davies R. Compression R, Craig A, Stephens S, Larsen J, Drum AF, Fowler R. A descriptive feedback devices over estimate chest compression depth when performed analysis of Emergency Medical Service Systems participating in the on a bed. Resuscitation. 2009;80:79–82. Resuscitation Outcomes Consortium (ROC) network. Prehosp Emerg 34. Hostler D, Everson-Stewart S, Rea TD, Stiell IG, Callaway CW, Care. 2007;11:369–382. Kudenchuk PJ, Sears GK, Emerson SS, Nichol G; Resuscitation Outcomes 27. ZOLL Medical Corporation. E Series Operators Guide. Chelmsford, MA: Consortium Investigators. Effect of real-time feedback during cardiopul- ZOLL Medical Corporation; 2010. monary resuscitation outside hospital: prospective, cluster-randomised 28. Huber P. Robust Statistics. New York, NY: Wiley; 1981. trial. BMJ. 2011;342:d512. 29. Hastie TJ. Generalized additive models. In: S. Chambers JM, Hastie TJ, eds. 35. Bobrow BJ, Vadeboncoeur TF, Stolz U, Silver AE, Tobin JM, Crawford Statistical Models. Pacific Grove, CA: Wadsworth & Brooks/Cole. 1992. SA, Mason TK, Schirmer J, Smith GA, Spaite DW. The influence of sce- 30. Li Y, Ristagno G, Bisera J, Tang W, Deng Q, Weil MH. Electrocardiogram nario-based training and real-time audiovisual feedback on out-of-hospital waveforms for monitoring effectiveness of chest compression during car- cardiopulmonary resuscitation quality and survival from out-of-hospital diopulmonary resuscitation. Crit Care Med. 2008;36:211–215. cardiac arrest. Ann Emerg Med. 2013;62:47–56.e1.

Clinical Perspective The 2010 American Heart Association cardiopulmonary resuscitation (CPR) guidelines recommended a CPR compres- sion depth for adults of ≥50 mm (2 in), with no upper limit specified, although this was based on limited human data. This study of 9136 adult out-of-hospital cardiac arrest patients from 9 US and Canadian cities in the Resuscitation Outcomes Consortium found that adequate compression was often not provided, particularly when the compression rate was faster than recommended. The study clearly demonstrated that increased CPR compression depth is strongly associated with better survival to hospital discharge. In addition, however, analyses showed that the maximum survival was observed in the mean depth interval of 40.3 to 55.3 mm (peak, 45.6 mm). Finally, despite a large presumed difference in weight between men and women, their optimal compression depth appeared to be the same. The authors conclude that the 2010 American Heart Association CPR guideline target for compression depth may be too high. They encourage the use of all validated strategies for prehospital and in-hospital cardiac arrest resuscitations to assist rescuers to stay within range for key CPR parameters, including compression depth and rate.

Downloaded from http://circ.ahajournals.org/ at University of Arizona on February 17, 2016 What Is the Optimal Chest Compression Depth During Out-of-Hospital Cardiac Arrest Resuscitation of Adult Patients? Ian G. Stiell, Siobhan P. Brown, Graham Nichol, Sheldon Cheskes, Christian Vaillancourt, Clifton W. Callaway, Laurie J. Morrison, James Christenson, Tom P. Aufderheide, Daniel P. Davis, Cliff Free, Dave Hostler, John A. Stouffer and Ahamed H. Idris and the Resuscitation Outcomes Consortium Investigators

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Downloaded from http://circ.ahajournals.org/ at University of Arizona on February 17, 2016 SUPPLEMENTAL MATERIAL APPENDICES

Supplemental Methods

Summary results are presented as mean (±SD) or median (IQR). To test differences in baseline characteristics between subjects who were included in the analysis and those excluded due to missing data, likelihood ratio chi-squared tests or t-tests were used as appropriate. The association between compression depth (evaluated separately with four approaches) and outcomes of interest was quantified using multivariate logistic regression with the Huber-White sandwich standard error.1 The key covariates/potential confounders assessed were age, sex, public location, bystander witnessed arrest, bystander CPR, EMS response time, CPR fraction, compression rate, site, and device manufacturer. Additional sensitivity analyses adjusted for initial cardiac rhythm and duration of CPR. Smoothing splines were used to explore the relationship between average compression depth and outcome.2 Unadjusted smoothing splines were creating by including the b-spline basis with four degrees of freedom for a natural cubic spline of depth in a logistic regression model in place of the other depth measures.

Supplemental References

1. Huber P. Robust Statistics. 1981. Wiley, New York.

2. Hastie TJ. Generalized additive models. In: Statistical Models in S. Chambers JM, Hastie TJ, eds. 1992. Wadsworth & Brooks/Cole, Pacific Grove, California.

Appendix Table 1. Comparison of Analysis Cohort with Patients Excluded Due to Missing Compression Depth or Covariates

p-value

Analyzed Excluded from Chi-

Cohort Patients squared or

t-test

N=9,136 N=13,727

Age - mean (SD) 67.5 (16.4) 66.3 (16.8) <0.001

Male - n (%) 5857 (64%) 8744 (64%) <0.001

Public location – n (%) 1161 (13%) 2026 (15%) <0.001

Bystander witnessed – n (%) 4065 (44%) 5854 (43%) <0.001

Bystander CPR – n (%) 3633 (42%) 5916 (45%) <0.001

Site - n (%)

ARC 22 (0%) 512 (4%)

BC 0 (0%) 2601 (19%)

DFW 272 (3%) 1403 (10%)

MLW 936 (10%) 515 (4%)

OTT 1389 (15%) 2068 (15%)

PGH 596 (7%) 295 (2%)

PTL 168 (2%) 1499 (11%)

SDG 842 (9%) 643 (5%)

SKC 837 (9%) 1901 (14%)

TOR 4074 (45%) 2290 (17%) <0.001

EMS Response

Time from 911 call to scene – mean (SD) 5.9 (2.5) 6.1 (3.9) <0.001

Time from 911 call to first EMS shock assessment – mean (SD) 10.5 (3.5) 10.4 (4.8) 0.028

ALS first on scene – n (%) 3274 (36%) 5492 (41%) <0.001

ALS on scene – n (%) 9049 (99%) 13105 (95%) 0.028 Number of responding EMS units1—mean (SD) 2.6 (0.8) 2.5 (0.7) <0.001

EMS Interventions

Intubation attempted - n (%) 6747 (74%) 9450 (69%) 0.133

Shocks delivered - n (%) 3647 (40%) 5002 (37%) <0.001

Epinephrine use noted - n (%) 7956 (87%) 10715 (79%) <0.001

CPR process measures

CPR prior to first analysis – n (%) 8409 (92%) 13018 (95%) 0.552

CPR fraction – mean (SD) 0.68 (0.15) 0.76 (0.16) <0.001

Chest compression rate – mean (SD) 108.3 (16.0) 118.7 (18.1) <0.001

Initial cardiac rhythm – n (%)

VF/VF 2181 (24%) 3255 (24%)

PEA 1845 (20%) 2378 (17%)

Asystole 4513 (49%) 6109 (45%)

AED no shock, no strip 583 (6%) 1703 (12%)

Cannot Determine/Missing 14 (0%) 282 (2%) <0.001

Device - n (%)

Philips 1869 (20%) 739 (6%)

Zoll 7246 (79%) 3760 (29%)

Medtronic/Other 21 (0%) 8627 (66%) <0.001

Outcomes

Any pre-hospital ROSC – n (%) 2861 (31.3%) 4583 (33.4%) <0.001

Survived at least one day – n (%) 2081 (22.8%) 3450 (25.2%) <0.001

Survived to hospital discharge – n (%) 666 (7.3%) 1210 (8.9%) <0.001

Appendix Table 2. Compression Rate versus Compression Depth

Average Compression Rate / Minute

0 to 80 81 to 120 121+ Total

Average <38 mm 45% (109) 32% (2256) 53% (969) 36% (3334)

Compression 38-51 30% (73) 48% (3405) 36% (656) 45% (4134)

Depth mm

>51 mm 24% (58) 20% (1418) 11% (192) 18% (1668)

Total 100% 100% 100% 100%

(240) (7079) (1817) (9136)

Chi-square test for association: p < 0.001

Appendix Table 3: Sensitivity Analyses - Survival to Discharge

First Rhythm Adjusted for Duration of Adjusted for First Rhythm VT/VF Non-shockable CPR

Adjusted OR Adjusted OR Adjusted OR p- Adjusted OR p- p-value p-value (CI)1 (CI)1 (CI)3 value (CI)4 value

Compression Depth (5mm 1.04 (0.98, 1.09) 0.178 1.01 (0.96, 1.06) 0.770 1.02 (0.99, 1.05) 0.264 1.03 (0.99, 1.07) 0.092 increments)

Compression Depth Category

<38 mm 0.73 (0.53, 1.02) 0.88 (0.53, 1.45) 0.81 (0.62, 1.07) 0.77 (0.56, 1.04)

38-51 mm 1.08 (0.81, 1.44) 0.91 (0.56, 1.48) 1.06 (0.83, 1.36) 1.17 (0.89, 1.54)

>51 mm reference 0.019 reference 0.878 reference 0.054 Reference 0.005

Within Depth Range2 1.35 (1.05, 1.73) 0.019 1.15 (0.81, 1.64) 0.443 1.27 (1.04, 1.56) 0.021 1.48 (1.18, 1.85) <0.001

Percent of minutes in depth range 1.04 (1.00, 1.07) 0.029 1.02 (0.98, 1.07) 0.320 1.03 (1.00, 1.06) 0.020 1.05 (1.02, 1.08) <0.001

(10% change)

1Adjusted for age, sex, public location, bystander witnessed, bystander CPR, CPR fraction, chest compression rate, time from 911 call to EMS at scene, device manufacturer, and study site.

2Average depth at least 38 mm for at least 60% of minutes with CPR process measures available.

3Adjusted for age, sex, public location, bystander witnessed, bystander CPR, CPR fraction, chest compression rate, time from 911 call to EMS at scene, device manufacturer, study site, and first recorded rhythm. 4Adjusted for age, sex, public location, bystander witnessed, bystander CPR, CPR fraction, chest compression rate, time from 911 call to EMS at scene, device manufacturer, study site, and duration of CPR. Excludes 97 subjects who are missing duration of CPR.

The odds ratios for each of the depth measures was estimated from a separate multivariable logistic regression model. Appendix Figure 1. Unadjusted Smoothing Spline of Different Survival Outcomes by Depth

ROC PRIMED-Appendix—12/22/2011 (for more information please go to the ROC website at www.uwctc.org and click on ROC)

Alabama Resuscitation Center, University of Alabama at Birmingham, Birmingham, AL: Jeffrey D. Kerby, MD, PhD, Principal Investigator

Core Investigators: Henry E. Wang, MD, Todd B. Brown, MD, MSPH

Coordinators: Shannon W. Stephens, EMT-P, Carolyn R. Williams, BSN, BSME, Sandra Caldwell, MA, Katherine R. Lai, BS, Randal Gray, NREMT-P, MA Ed

EMS Investigators/Collaborators: Joe E. Acker, EMT-P, MPH, Michael L. Minor, EMT-P, John Reed, BSN, EMT-P

Hospital Investigators/Collaborators: Jason Begue, MD, Willie Gilford, MD

Participating EMS Agencies: Bessemer Fire Dept, Birmingham Fire and Rescue, Center Point Fire District, Pelham Fire Dept, Regional Paramedical Services, Rocky Ridge Fire District, Vestavia Hills Fire Dept, Hoover Fire Dept

Dallas Center for Resuscitation Research, University of Texas Southwestern Medical Center, Dallas, TX: Ahamed H. Idris, MD, Principal Investigator

Core Investigators: Raymond Fowler, MD, Ronna Miller, MD, Joseph Minei, MD, Paul Pepe, MD, Michael Ramsay, MD, Robert Simonson, MD, Jane Wigginton, MD

Coordinators: Sarah Beadle, MD, Dixie Climer, RN, Melinda Moffat, RN, Pamela Owens, David Gallegos, Sandra O’Neill, MS, MA, LP, Ron Smith, MBA

EMS Investigators/Collaborators: Fernando Benitez, MD, Billy Craft, EMTP, Lucy Detamble, RN, Steven Deutsch, EMT-P, Tod Gillam, EMT-P Tony Harvey, EMTP, Suzanne Hewitt, RN, Marshal Isaacs, MD, Tami Kayea, EMTP, Richard LaChance, EMTP, Thomas Lehman, Dorothy Lemecha, MD, Chris Malvik, EMT-P, Paul Mayer, MD, Jeffrey Metzger, MD, Danny Miller, EMTP, Bobby Muse, EMT-P, Karen Pickard, RN, Bobby Ross, EMT-P, Chris Vinson, EMTP

Hospital Investigators/Collaborators: Steven Arze, MD, Sean Black, MD, Matthew Bush, MD, Ralph Kelly, DO, Edward Thornton, MD, William Elder. MD, John Marcucci, MD, Lawrence Hum, MD, Mark Gamber, MD

Participating EMS Agencies: Carrollton Fire Dept, Dallas Fire Rescue, Irving Fire Dept, Mesquite Fire Dept

Milwaukee Resuscitation Research Center, Medical College of Wisconsin, Milwaukee, WI: Tom P. Aufderheide, MD, Principal Investigator

ROC PRIMED-ITD-ALvAE Appendix – 8/10/2010

Core Investigators: Ronald G. Pirrallo, MD, MHSA, Karen J. Brasel, MD, MPH, Andrea L. Winthrop, MD, John P. Klein, PhD

Coordinators: Joseph Brandt, BS, NREMT-P, Walter Bialkowski, MS, Jennifer Noldin, BS, Christopher Sandoval, BS, Kevin Morrow, MFA, David J. Kitscha, BS, MS, Barbara J. Burja, BA, EMT, Chris von Briesen, BA, CCRC, Christopher W. Sparks, Pamela Walsh, EMT

EMS Investigators/Collaborators: John Chianelli, MS, Rosemarie Forster, MSOLQ, RHIA, EMT- P, Michael Milbrath, EMT-P, Lauryl Pukansky, BS, RHIA, Kenneth Sternig, MS-EHS, BSN, EMT- P, Eugene Chin, RN, EMT-P, Nancy Frieberg, RN, EMT-P, Kim Krueger, RN, EMT-P, Del Szewczuga, RN, EMT-P, Thomas Duerr, Rebecca Funk, BS, RHIA, EMT-B, Gail Jacobsen, BS, Janis Spitzer, Richard Demien, James Martins, John Cohn, Russell R. Spahn, M.A., EMT-P, Mike Jankowski, B.A., EMT-P, Timothy James, William E. Wentlandt Jr., MBA, EFO, David Berousek, Brian M. Satula, B.A., NREMT, Jay B. Behling, B.S., EMT-B, Dean K. Redman, B.A., EFO, Steven Hook, BS, CFOD, Andrew Neargarder, Jim Singer, RN

Hospital Investigators/Collaborators: Thomas Reminga, MD, Dennis Shepherd, MD, Peter Holzhauer, MD, Jonathan Rubin, MD, Craig Skold, MD, Orlando Alvarez, MD, Heidi Harkins, MD, Edward Barthell, MD, William Haselow, MD, Albert Yee, MD, John Whitcomb, MD, Eduardo E. Castro, MD, Steven Motarjeme, MD, Paul Coogan, MD, Keith Rader, MD, Jeff Glaspy, MD, Gary Gerschke, MD, Howie Croft, MD, Mike Brin, MD, Cory Wilson, MD, Anne Johnson, MD, William Kumprey, MD

Participating EMS Agencies: Cudahy Fire Dept, Franklin Fire Dept, Greendale Fire Dept, Greenfield Fire Dept, Hales Corners Fire Dept, Milwaukee County Airport Fire Dept, Milwaukee Fire Dept, North Shore Fire Dept, Oak Creek Fire Dept, South Milwaukee Fire Dept, Wauwatosa Fire Dept, West Allis Fire Dept

Ottawa/OPALS/British Columbia RCC, Ottawa Health Research Institute, University of Ottawa, Ottawa, Ontario and St. Paul’s Hospital, University of British Columbia, British Columbia, Canada: Ian Stiell, MD, Principal Investigator

Core Investigators: Jim Christenson, MD, Christian Vaillancourt, MD

Coordinators: Cathy Clement, RN, Tammy Beaudoin, CCHRA, Marc-Andre Da Ponti, A-EMCA, ACP, Julie Cummins, A-EMCA, RN, MSc, Sarah Pennington, RN, Helen Connolly, RN, Stanley Morrow, A-EMCA, ACP, Christine Tym, CHIM, Ghislaine Lepage, CHIM, Jane Banek, CHIM

EMS Investigators/Collaborators: Jonathan Dreyer, MD, Douglas Munkley, MD, Jason Prpic, MD, Justin Maloney, MD, Paul Colella, MD, Andrew Affleck, MD, David Waldbillig, MD, Paul Bradford, MD, Kenneth Boyle, EMCA, RRT, CMA, Lorie Luinstra-Toohey, BScN, MHA, John Trickett, BScN, Nicole Sykes, BScN, RN, Elaine Graham, ACP, Kieran Ballah, EMCA, Cathie Hedges, A-EMCA, ACP, Renee MacPhee, PhD, Bob DeRaad, RN, Dug Andrusiek, PCP, Dan Bishop, ACP, Ron Straight, ACP, Brian Twaites, ACP, Stuart Donn, PhD, Laura McCleary, ACP

Participating EMS Agencies: Ottawa-OPALS-London Fire Dept, Ottawa Fire Rescue, Windsor Fire Rescue, Cambridge Fire Dept, Niagara Falls Fire Rescue, St Catharine's Fire Rescue,

ROC PRIMED-ITD-ALvAE Appendix – 8/10/2010 Page 2 of 6

Sudbury Fire Rescue, Thorold Fire Dept, Thunder Bay Fire Rescue, Waterloo Fire Rescue, Welland Fire Rescue, Niagara EMS, Prescott-Russell EMS, Sudbury EMS, Superior North EMS, Waterloo Regional EMS, AA and M Volunteer Ambulance, Essex-Windsor EMS, Harrow Ambulance Service, Ottawa Paramedic Service, Sun Parlour EMS, Thames EMS, Port Colborne Fire

Vancouver BC-Abbotsford Fire Dept, Aggassiz Valley Fire Dept, Burnaby Fire Dept, City of North Vancouver Fire Dept, BC Ambulance, Coquitlam Fire Dept, Delta Fire Dept, Langley City Fire Dept, Langley Township Fire Dept, Maple Ridge Fire Dept, Mission Fire Dept, New Westminster Fire Dept, North Vancouver District Fire Dept, Pitt Meadows Fire Dept, Port Coquitlam Fire Rescue, Port Moody Fire Dept, Richmond Fire Dept, Squamish Fire Dept, Surrey Fire Dept, Vancouver Fire Dept, West Vancouver Fire Dept, Whistler Fire Dept, White Rock Fire Dept, Central Saanich Fire Dept, Esquimalt Fire Dept, Langford Fire Dept, Oak Bay Fire Dept, Qualicum Beach Fire Dept, Sooke V Fire Dept, Victoria Fire Dept BC Heath Authorities: Fraser Health Authority, Vancouver Island Health Authority, Vancouver Coastal Health Authority and Providence Health Care

Pittsburgh Resuscitation Network, the University of Pittsburgh, Pittsburgh, PA: Clifton Callaway, MD, PhD, Principal Investigator

Core Investigators: Samuel Tisherman, MD, Jon Rittenberger, MD, David Hostler,PhD

Coordinators: Joseph Condle, Mitch Kampmeyer, Timothy Markham, Maureen Morgan

EMS Investigators/Collaborators: Paul Sabol, Gina Sicchitano, Anthony Shrader, Greg Stull, William Groft, Robert McCaughan, Rodney Rohrer, David Fuchs, MD, Francis Guyette, MD, MS, William Jenkins, MD, Ronald Roth, MD, Heather Walker, MD

Hospital Investigators: Thomas Campbell, MD, Ankur Doshi, MD, Bruce MacLeod, MD

Participating EMS Agencies: Ambulance and Chair, City of Pittsburgh EMS, City of Pittsburgh Fire, Mutual Aid Ambulance

Portland Resuscitation Outcomes Consortium, Oregon Health and Science University, Portland, OR: Mohamud R. Daya MD, MS, Principal Investigator

Core Investigators: Terri A. Schmidt MD, MS, Craig D. Newgard, MD, MPH, Jerris R. Hedges, MD, MS

Coordinators: Denise E. Griffiths, BS, CCRP, Dana M. Zive, MPH, Aaron W. Monnig, EMT-P, Abdolaziz Yekrang, MPA, MA, Brett Tomlin, BS, Michael Kampp, BS, Jenny Cook, BS, Joan Burns, RN, Maria Nelson, MD, Yoko Nakamura, MD

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EMS Investigators/Collaborators: Jonathan Jui, MD, MPH, Ritu Sahni, MD, MPH, Craig R. Warden, MD, MPH, Skip Freedman, MD, Mike Shertz, MD, Marc D. Muhr, EMT-P2, John A. Stouffer, EMT-P, Jay Cross, EMT-P, Joe Costigan, EMT-P, Kyle Gorman, MBA, EMT-P, Pontine Rosteck, EMT-P, Mike Verkest, EMT-P, Cyndi Newton, EMT-P, Tina Beeler, EMT-P, Karl Koenig, EMT-P, Jan Lee, EMT-P, Roxy Barnes, BSN, Doug Boyce, EMT-P, Brad Allen, EMT-P, TJ Bishop, EMT-P, Mike Hollingsworth, EMT-P, Eric Schult EMT-P, Scott Sullivan, EMT-P, Rick Williams, EMT-P, Steve Dehart, EMT-P, Mark Stevens, EMT-P, Rene Pizzo, EMT-P, Rob Hawks, EMT-P, Adam Glaser, EMT-P, Jonathan Chin, MS, EMT-P, Jason Blount, EMT-P, Gert Zoutendijk, Chris Koppenhafer, Corie Depuy, Kristen Hinds, Trish Noble

Hospital Investigators/Coordinators: Lynn Wittwer, MD, Michael Albrich, MD, Tony Carnevale MD, Piroska Schlesinger, BS, Kristen Schmiedeskamp, BS, Amy Reiter, RN, Kathy Arnold, RN, Phyllis Ramey, RN, Roger McDonald, RN, Helen Walsh, RN

Participating EMS Agencies: American Medical Response - Clackamas, Clark, and Multnomah Counties, Camas Fire Department, Clackamas County Fire District #1, Clark County Fire District #6, Gresham Fire and Emergency Services, Hillsboro Fire Department, Lake Oswego Fire Department, Metro West Ambulance, North Country Ambulance, Portland Fire and Rescue, Portland International Airport Fire Department, Tualatin Valley Fire and Rescue, Vancouver Fire Department

UCSD-San Diego Resuscitation Research Center, University of California at San Diego, San Diego, CA: Daniel Davis, MD, Principal Investigator

Core Investigators: Gary Vilke, MD, James Dunford, MD

Coordinators: Donna Kelly Aker, RN, Thea Barsalou, RN

EMS Investigators/Collaborators: Bruce Haynes, MD, Brad Schwartz, MD

Hospital Investigators: Don Mebust MD, Robert Bei MD, Graydon Skeoch MD, Michele Grad MD, Ian Grover MD, Jerrold Glassman MD, Steven R. Andree MD, Lisa Morikado MD, Mark Kramer MD, Thomas Calkins MD, Mark Tamsen MD, William Linnik MD, Judd Glasser MD

Participating EMS Agencies: El Cajon Fire Dept ALS, Julian-Cuyamaca Fire Dept ALS, North County Fire Dept ALS, Poway Fire Dept ALS, San Marcos Fire Dept ALS, Santee Fire Dept ALS, Viejas Fire Dept, City of San Diego Fire Rescue Department, Vista Fire Dept ALS

Seattle-King County Center for Resuscitation Research at the University of Washington, University of Washington, Seattle, WA: Peter J. Kudenchuk, MD, Principal Investigator

Core Investigators: Tom D. Rea, MD; Michael Copass, MD; Mickey S. Eisenberg, MD

Coordinator: Michele Olsufka, RN; Debi Solberg, RN, MN; Sally Ragsdale, ARNP

EMS Investigators/Collaborators: Jonathan Larsen, Mike Helbock

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Participating EMS Agencies: Bellevue Fire Dept, Bothell Fire Dept, Burien Fire KCFD 2, Kirkland Fire KCFD 41, Renton Fire and Emergency Services, Snoqualmie Fire, Duvall Fire KCFPD 45, Eastside Fire & Rescue, Enumclaw Fire KCFPD 28, Fall City Fire KCFPD 27, Kent Fire Dept, Maple Valley Fire and Life Safety KCFPD #43, Mercer Island Fire Dept, KCFD #44 Mountainview, North Highline Fire KCFD 11, Northshore/ Kenmore Fire KCFD 16, Port of Seattle Fire Dept, KCFPD #47 Ravensdale/Palmer, Redmond Fire Dept, SeaTac Fire Dept, Seattle Fire Dept, Shoreline Fire KCFD 4, Skykomish Fire KCFD 50, KCFD #20 Skyway, Snoqualmie Pass Fire 51, South King County Medic 1, South King Fire & Rescue, Tukwila Fire Dept, Valley Regional Fire Authority, Vashon Island Fire KCFD 13, Woodinville Fire KCFD 36

Toronto Regional Resuscitation Research Out of Hospital Network (Toronto Regional RescuNET), University of Toronto, Toronto, Ontario, Canada: Arthur Slutsky, MD, MASc, Principal Investigator

Core Investigators: Laurie J Morrison, MD, MSc, FRCPC; Paul Dorian, MD, MSc; Alan Craig, MScPl; Andrew Baker MD, FRCPC; , Jamie Hutchison, MD, FRCPC; Ori Rotstein, MD, MSc; P. Richard Verbeek, MD, FRCPC; Russell MacDonald, MD, MPH, FCFP, FRCPC; Sandra Black, MD, FRCP(C); Sandro Rizoli, MD, PhD, FRCSC, FACS; Sheldon Cheskes, MD, CCFP (EM), FCFP; Steven Brooks, MD, MHSc

Coordinators: Adam Byers, Ahmed Taher, Anuar Turgulov, Blair Bigham, Bruce Cameron, Caitlin Wenkstern, Cathy Zhan, Christopher Foerster, Craig Beers, Jaime Beecroft, Jamie Frank, Malcolm Mercer, Markus Kernen, Michael Grife, Mohammad Qovaizi, Patrick Van Rooyen, Peter DeMaio, Rishab Chadha, Suzanne Chung, Tyrone Perreira, Welson Ryan

EMS Investigators/Collaborators: Andy Benson, Dana Bradshaw, Dave Mokedanz, Doug Silver, Greg Sage, Jacob Stevens, Jason Whiteley, Jennifer Shield, John Locke, Judy Moore, Kenneth Webb, Kevin King, Marty Epp, Michael Feldman, Michael Nemeth, Philip Moran, Richard Renaud, Rob Burgess, Roy Suthons, Russ Olynyk, Steve McNenly, Steve Tyukodi, Terri Burton, Tim Waite, Verena Jones, Warren Beckett

Hospital Investigators/Coordinators: Amy Back, Carolyn Vardy, Dina Braga, Don Redelmeier, Donna Chen, Evelina Kadic, Grace Burgess, Hannelore Mueller, Jacob Simonini, Jennifer Walker, Jessica Tyrwhitt, Judith Renton, Julie Spence, Katherine Allan, Kerri Bath, Laura Steeves, Lauren Lewarne, Lesley Ann Molyneaux, Margaret McGrath-Chong, Mariecar Pagulayan, Mark McLennan, Mediha Kadic, Melanie Piette, Nida Shahid, Raj Gobin, Roman Nowickyj, Selamawit Tessema, Shawn Hogan, Steve Driscoll

Participating EMS Agencies: Ajax Fire and Emergency Services, Brampton Fire and Emergency Services, Clarington Fire Services, Central East Prehospital Care Program, District of Muskoka, Durham Region Emergency Medical Services, Halton Region Emergency Medical Services, Medavie Emergency Medical Services, Mississauga Fire and Emergency Services, Muskoka Ambulance Communication Center, Muskoka Ambulance Service, Muskoka Emergency Medical Services, Peel Regional Paramedic Services, Pickering Fire Services, Sunnybrook Osler Centre for Prehospital Care, Toronto Emergency Medical Services, Toronto Fire Services, Uxbridge Fire Services, Whitby Fire and Emergency Services

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Steering Committee: Chair: Myron Weisfeldt, MD, Johns Hopkins University School of Medicine, Baltimore, MD Co-Chair–Cardiac: Joseph P. Ornato, MD, Virginia Commonwealth University Health System, Richmond, VA

National Heart, Lung, and Blood Institute, Bethesda, MD: George Sopko, MD, MPH, Debra Egan, MPH, David Lathrop, PhD, Alice Mascette, MD, Patrice Desvigne Nickens, MD, Colin Wu, PhD, Phyllis Mitchell, PhD, Tracey Hoke, MD

Clinical Trial Center, University of Washington, Department of Biostatistics, Seattle, WA: Gerald van Belle, PhD, Scott Emerson, MD, PhD, Graham Nichol, MD, MPH, Brian Leroux, PhD, Judy Powell, BSN, Lois Van Ottingham, BSN, Gena Sears, BSN, Siobhan Everson-Stewart, PhD, Robert Schmicker, MS, Andrea Cook, PhD, Kyle Rudser, PhD, Robert B. Ledingham, MS, Ben Bergsten-Buret, Richard Moore, BS, Amy Gest, MPA, Colleen Sitlani, MS, Kent Koprowicz, MS, Liz Thomas, MS, Erin Gabriel, MS, Ken Wu, MS, Danielle Schroeder, BS, Chi Shen, MS, Winnie Kirdpoo, BS, Jackie Berhorst, Anna Leonen, MS, Yang Wang, PhD, Al Hallstrom, PhD

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