Literature DB >> 27752560

Factors affecting the accuracy of chest compression depth estimation.

Jung Hee Kang1, Won Chul Cha1, Minjung Kathy Chae1, Hang A Park1, Sung Yeon Hwang1, Sang Chan Jin1, Tae Rim Lee1, Tae Gun Shin1, Min Seob Sim1, Ik Joon Jo1, Keun Jeong Song1, Joong Eui Rhee1, Yeon Kwon Jeong1.   

Abstract

OBJECTIVE: We aimed to estimate the accuracy of visual estimation of chest compression depth and identify potential factors affecting accuracy.
METHODS: This simulation study used a basic life support mannequin, the Ambu man. We recorded chest compression with 7 different depths from 1 to 7 cm. Each video clip was recorded for a cycle of compression. Three different viewpoints were used to record the video. After filming, 25 clips were randomly selected. Health care providers in an emergency department were asked to estimate the depth of compressions while watching the selected video clips. Examiner determinants such as experience and cardiopulmonary resuscitation training and environment determinants such as the location of the camera (examiner) were collected and analyzed. An estimated depth was considered correct if it was consistent with the one recorded. A multivariate analysis predicting the accuracy of compression depth estimation was performed.
RESULTS: Overall, 103 subjects were enrolled in the study; 42 (40.8%) were physicians, 56 (54.4%) nurses, and 5 (4.8%) emergency medical technicians. The mean accuracy was 0.89 (standard deviation, 0.76). Among examiner determinants, only subjects' occupation and clinical experience showed significant association with outcome (P=0.03 and P=0.08, respectively). All environmental determinants showed significant association with the outcome (all P<0.001). Multivariate analysis showed that accuracy rate was significantly associated with occupation, camera position, and compression depth.
CONCLUSIONS: The accuracy rate of chest compression depth estimation was 0.89 and was significantly related with examiner's occupation, camera view position, and compression depth.

Entities:  

Keywords:  Cardiopulmonary resuscitation; Feedback; Manikins; Patient care team; Video recording

Year:  2014        PMID: 27752560      PMCID: PMC5052833          DOI: 10.15441/ceem.14.006

Source DB:  PubMed          Journal:  Clin Exp Emerg Med        ISSN: 2383-4625


INTRODUCTION

High-quality chest compression is an essential element for achieving a good prognosis in cardiac arrest patients. These compressions are composed of an appropriate compression rate (>100/min), appropriate chest compression depth (>5 cm), and sufficient chest recoil [1,2]. Guidelines state the need for mutual feedback among resuscitation providers to maintain these quality indices [3]. Based on the 2010 European Resuscitation Council (ERC) guideline, a team leader should evaluate the quality of the cardiopulmonary resuscitation (CPR) and can change the person providing CPR if necessary [4]. There have been many studies suggesting the effectiveness of feedback devices that measure the rate, depth, and release of chest compression [5-8]. Information on feedback devices was also included in the American Heart Association (AHA; class IIa, level of evidence B) and ERC guidelines since 2010 [1,2]. However, feedback devices are not used frequently in many real-life CPR locations [9]. Frequently, providers choose not to apply the device because of reluctance and ignorance of effectiveness and time and cost to import new systems [9,10]. In many cases, feedback is based on visual estimation by the naked eye. Although objective indicators such as compression rate, respiration rate, and end-tidal carbon dioxide concentration are easy to estimate, compression depth can be difficult. The purpose of our study was to estimate the accuracy of compression depth estimation and to identify potential factors affecting accuracy.

METHODS

Study design and setting

This study was approved by the Institutional Review Board (approval number SMC 2014-03-099-001). This study was a simulation study using mannequins (Ambu man, Ballerup, Denmark). Five basic life support providers volunteered to have video clips recorded while they did chest compressions. They were asked to perform chest compressions of different depths: ≥ 0 & < 1, ≥ 1 & <2, ≥2 & <3, ≥3 & <4, ≥4 & <5, ≥5 &<6, and ≥6 & <7 cm. Compressors did chest compression for a cycle of 30 compressions on their knees. To maintain the same level of depth throughout a cycle, a quality manager monitored compression depths using the Smartman, a PC program provided by the manufacturer (Fig. 1D).
Fig. 1.

The process of how video clips were recorded. (A) Cephalic view, (B) side view, and (C) caudal view. (D) The process showing how compression quality and depth are controlled by the computer system, Ambu Man Compression.

Video clips were recorded by a smartphone camera (Galaxy S3, 1080p Recording System, Samsung, Suwon, Korea). We used 3 recording positions: cephalic (Fig. 1A), side (Fig. 1B), and caudal (Fig. 1C). Camera height was fixed at 155 cm from the floor and 125 cm from the bed on which the mannequin was placed. Of 175 total clips, we randomly sampled 25, 5 clips from each volunteer. An internet-based randomization program was used for the sampling process (http://randomization.com).

Study participants

Study participants were enrolled from a single, tertiary, teaching hospital. All were working or have worked in the emergency department. Shortly after explaining the study, participants filled out survey forms and watched the video clips while estimating the depth of each clip.

Methods and measurements

To measure examiner determinants, we collected information regarding gender, age, occupation, affiliated department, clinical career, resuscitation certification state, and the number of CPR experiences during the past year. To measure the environmental determinants, we included the recording position, chest compressor’s gender, and compression depth.

Outcomes

An estimated depth was considered correct if the recorded depth and the estimated depth were all >5 cm, or all <5 cm (Fig. 2A). For example, if a recorded depth was 1–2 cm and the answer was 4 cm, the answer was considered correct because both depths were consistent with insufficient compression. We used this criterion because the current AHA guideline states that a provider has to compress >5 cm.
Fig. 2.

The shaded areas represent areas where answers were checked as correct (or consistent). (A) Based on the American Heart Association guideline (>5 cm). (B) Based on the European Resuscitation Council guideline 5–6 cm. (C) Exact match. Criteria for (B) and (C) were used for sensitivity analysis.

Sensitivity analysis

For sensitivity analysis, 2 more criteria were applied. The first criterion was according to the 2010 ERC guideline for resuscitation (Fig. 2B). Our second criterion was a strict one: that estimation was considered correct when the recorded and estimated depths were exactly the same (Fig. 2C).

Analysis

All statistical analyses were performed with STATA ver. 13.0 (Stata Co., College Station, TX, USA). Baseline characteristics of this study were expressed as numbers, percentages, and means with standard deviations (SDs). The results are presented as mean with SD and 95% confidence intervals (CIs). Comparisons of continuous data were performed using the t-test and analysis of variance. To identify factors affecting accuracy of compression depth estimation, a multivariate logistic regression was used. P-values <0.05 were considered statistically significant for all statistical testing.

RESULTS

Characteristics of study subjects

A total of 103 health care providers participated in this study. Table 1 shows the demographic characteristics of the participants. The number of males was 28 (27.2%). The mean age was 29.5 years (SD, 5.2). Forty-two (40.8%) were physicians, 56 (54.4%) were nurses, and 5 (4.8%) were emergency medical technicians (EMTs); 81 (78.6%) were currently affiliated with the emergency department; 13 (12.6%) had valid CPR instructor certification issued by the AHA; and 23 (22.3%) had advanced cardiac life support certification. In terms of CPR experience, 45 participants (43.7%) had more than 21 CPR experiences during the past year (Table 1).
Table 1.

Baseline characteristics of examiners (n=103)

CharacteristicValue
Gender
 Male28 (27.2)
 Female75 (72.8)
Age (yr)29.5±5.2
Occupation
 Physician42 (40.8)
 Nurse56 (54.4)
 Emergency medical technician5 (4.9)
Affiliated department
 ED81 (78.6)
 Non-ED22 (21.4)
Clinical career (yr)5.0±5.0
BLS or ACLS instructor
 Yes13 (12.6)
 No90 (87.4)
ACLS provider certification
 Yes23 (22.3)
 No80 (77.7)
No. of CPR experiences (during last year)
 03 (2.9)
 1–527 (26.2)
 6–1011 (10.7)
 11–156 (5.8)
 16–2011 (10.7)
 > 2045 (43.7)

Values are presented as number (%) or mean±SD.

ED, emergency department; ACLS, advanced cardiac life support; CPR, cardiopulmonary resuscitation.

Main results

The mean estimated accuracy was 0.89 (SD 0.76). Table 2 shows the examiner determinants. There was no significant association between accuracy and gender, age, affiliated department, clinical career, instructor certification, or advanced cardiac life support certification. The accuracy rate and number of CPR experiences showed a trend of negative association (P=0.08). The estimated accuracy rate was significantly higher among nurses (P=0.02).
Table 2.

Examiner-determinants and estimation of accuracy

FactorRate of correct answers
P-value
Mean95% CI
Gender0.66
 Male0.890.86–0.92
 Female0.890.88–0.91
Age (yr)0.11
 < 300.900.88–0.92
 ≥ 300.880.85–0.90
Occupation0.02
 Physician0.870.85–0.90
 Nurse0.910.89–0.93
 Emergency medical technician0.850.78–0.91
Affiliated department0.31
 ED0.900.88–0.91
 Non-ED0.880.84–0.91
Clinical career (yr)0.83
 <50.890.87–0.91
 ≥50.890.87–0.92
BLS or ACLS instructor0.57
 Yes0.880.84–0.92
 No0.890.88–0.91
ACLS provider certification0.58
 Yes0.880.85–0.92
 No0.890.88–0.91
No. of CPR experiences (during last year)0.08
 00.920.66–1.18
 1–50.920.90–0.95
 6–100.860.80–0.92
 11–150.850.76–0.95
 16–200.890.86–0.93
 > 200.880.86–0.90

CI, confidence interval; ED, emergency department; ACLS, advanced cardiac life support; CPR, cardiopulmonary resuscitation.

Table 3 shows environmental determinants associated with the estimated accuracy. The percentage of correct answers was significantly higher in video clips that were recorded at the bed side and in the caudal position than in the cephalic position (P<0.001). The estimated accuracy was significantly higher with female compressors (P<0.001). The estimated accuracy was significantly lower in video clips with 4–5 cm or 5–6 cm compressions (P<0.001).
Table 3.

Environmental determinants associated with estimation accuracy

FactorPercentage of correct answers
P-value
Mean95% Confidence interval
Camera position< 0.001
 Cephalic0.770.74–0.79
 Side0.960.94–0.97
 Caudal0.960.95–0.97
Compressor gender< 0.001
 Male0.860.84–0.88
 Female0.910.90–0.93
Compression depth (cm)< 0.001
 ≥ 0 & <11.001.00–1.00
 ≥ 1 & <21.001.00–1.00
 ≥ 2 & <30.990.98–1.00
 ≥ 3 & <40.920.89–0.96
 ≥ 4 & <50.600.53–0.66
 ≥ 5 & <60.700.66–0.74
 ≥ 6 & < 70.940.91–0.97
The 5 factors associated with the estimated accuracy were selected and included for multivariate analysis. The results from logistic regression analysis of these factors are shown in Table 4. The adjusted odds ratio (AOR) of correct estimation was 1.50 (95% CI, 1.09 to 2.09; P=0.01) for nurses compared with physicians. The AOR was 8.19 (95% CI, 5.40 to 12.4; P<0.001) for the caudal position compared with the cephalic position. The AORs were 0.68, 0.03, and 0.06, respectively, for 3–4, 4–5, and 5–6 cm video clips compared with the 0–1 cm video clips.
Table 4.

Logistic regression predicting accurate estimation

FactorNo. of clipsOdds ratio95% CIP-value
Examiner-determinants
 Occupation
  Physician1,050Reference--
  Nurse1,4001.501.09–2.090.01
  Emergency medical technician1250.720.36–1.440.35
No. of CPR experiences (during last year)
  075Reference--
  1–56751.220.43–3.410.71
  6–102750.490.16–1.430.19
  11–151500.480.15–1.520.21
  16–202750.790.27–2.350.67
  >2011250.710.26–1.950.50
Environment-determinants
 Camera position
  Cephalic927Reference--
  Side6180.730.36–1.430.35
  Caudal1,0308.195.40–12.4<0.001
 Compressor gender
  Female1,545Reference--
  Male1,0300.810.54–1.230.32
 Compression depth (cm)
  ≥0 & <1206Reference--
  ≥1 & <25151--
  ≥2 & <36182.590.99–6.770.05
  ≥3 & <42060.680.33–1.400.30
  ≥4 & <52060.030.01–0.07<0.001
  ≥5 & <65150.060.03–0.12<0.001
  ≥6 & <73091--

CI, confidence interval; CPR, cardiopulmonary resuscitation.

We performed sensitivity analysis using different standards for the correct answers. For the ERC guideline–based analysis, the mean accuracy was 0.75 (SD, 0.06). Multivariate analysis revealed statistically significant factors including camera position, compressor gender, and compression depth. For the strict standard, mean accuracy was only 0.40 (SD, 0.11) and the significant factors were the same as the ERC guideline–based standard (Appendix Tables 1–6).

DISCUSSION

In this study, we investigated the accuracy of chest compression depth estimation. The accuracy rate was 0.89 (SD, 0.76), which was similar to previous research [11]. However, when more strict criteria were applied, the estimated accuracy declined to 0.75 (SD, 0.40). Although current guidelines have addressed the importance of mutual feedback, only a few have studied the effect. Lynch et al. [11] found that examiner’s estimation was not sufficient to determine providers’ performance. Although multiple studies reported the importance of a feedback system, there was no research performed with health care providers in the field [12,13]. Accuracy rates did not differ with clinical experience or gender, perhaps because measuring chest compressions is a very simple, low-tech procedure that does not require much experience. No difference in measuring skill was noted in previous studies either [14,15]. In this study, the multivariate analysis showed nurses’ superiority over physicians estimating compression depth, which may result from the tendency of nurses to follow protocols more strictly than physicians. Nurses tend to stand at a distance from chest compression procedures, which may have given them more room to observe chest compression than physicians. However, factors not measured in this study, such as willingness to make an accurate estimation or professional experience, could have caused interactions among variables. Camera position was highly correlated with the accuracy rate, indicating that one should stand at the side or foot of the patient to measure compression quality more accurately. In our study, accuracy rate dropped when the depth was near the target range, which emphasizes that the estimated accuracy in actual practice could be much lower than the result presented here. CPR team leaders should consider these factors while leading a CPR team. Another option could include a real-time feedback system for compression depth. To improve the accuracy of estimation and feedback with precise information, applying new devices and measures is necessary. These measures include physiologic data such as end-tidal carbon dioxide levels, cerebral oximetry, and mechanically produced data such as compression depth by gyroscopes. There are some major limitations to this study. First, study subjects did not fully represent the general population because subjects were enrolled from a single center. Second, watching an actual CPR process could be different from watching a video clip. Each individual used his or her own height and preferred position, which was standardized during the study. Third, the small number of participants could have influenced the negative outcomes. For example, EMT occupation showed an odds ratio of 0.70 without statistical significance. Because the number of enrolled EMTs was only 5, more participants could have led to different results. Last, dividing compression depth into multiple scales would have complicated the determination of depth by examiners, which would have increased the inaccuracy of estimation. In conclusions, the accuracy of chest compression depth estimation was 0.89 (SD, 0.76) in this simulation model. The factors affecting accuracy were occupation, recording position, and compression depth itself.
FactorPercentage of correct answers
P-value
Mean95% CI
Gender0.94
 Male0.750.73–0.78
 Female0.750.74–0.77
Age (yr)0.26
 < 300.760.74–0.77
 ≥ 300.740.72–0.76
Occupation0.81
 Physician0.750.73–0.77
 Nurse0.760.74–0.77
 Emergency medical technician0.740.70–0.79
Affiliated department0.72
 ED0.750.74–0.76
 Non-ED0.760.73–0.78
Clinical career (yr)0.96
 <50.750.74–0.77
 ≥50.750.73–0.77
Instructor certification0.39
 Yes0.740.70–0.77
 No0.750.74–0.77
ACLS certification0.49
 Yes0.740.71–0.78
 No0.750.74–0.77
No. of CPR experience (during last year)0.57
 00.770.54–1.00
 1–50.770.75–0.79
 6–100.730.69–0.77
 11–150.730.66–0.80
 16–200.760.72–0.80
 > 200.750.73–0.77

CI, confidence interval; ED, emergency department; ACLS, advanced cardiac life support; CPR, cardiopulmonary resuscitation.

FactorPercentage of correct answers
P-value
Mean95% CI
Camera position<0.001
 Cephalic0.640.61–0.67
 Side0.800.77–0.83
 Caudal0.830.81–0.85
Compressor gender0.001
 Male0.790.76–0.81
 Female0.730.71–0.75
Compression depth (cm)<0.001
 0–11.001.00–1.00
 1–21.001.00–1.00
 2–31.001.00–1.00
 3–40.990.98–1.00
 4–50.700.64–0.77
 5–60.280.24–0.32
 6–70.340.28–0.39

CI, confidence interval.

FactorNo. of clipOdds ratio95% CIP-value
Occupation
 Physician1,050Reference--
 Nurse1,4001.010.75–1.360.94
 Emergency medical technician1250.950.48–1.850.87
No. of CPR experience (during last year)
 075Reference--
 1–56750.920.40–2.090.84
 6–102750.600.24–1.470.26
 11–151500.620.23–1.650.34
 16–202750.860.35–2.080.74
 >201,1250.750.33–1.700.49
Camera position
 Cephalic927Reference--
 Side6183.642.06–6.45< 0.001
 Caudal1,0300.890.64–1.250.50
Compressor gender
 Female1,545Reference
 Male1,0300.390.26–0.60< 0.001
Compression depth (cm)
 0–1206Reference--
 1–25151.00--
 2–36181.00--
 3–420623555.5–995< 0.001
 4–520623.011.1–47.7< 0.001
 5–65151.721.01–2.900.05
 6–73091.00

CI, confidence interval; CPR, cardiopulmonary resuscitation.

FactorPercentage of correct answers
P-value
Mean95% CI
Gender0.88
 Male0.410.36–0.45
 Female0.400.38–0.43
Age (yr)0.55
 < 300.410.38–0.44
 ≥ 300.400.36–0.43
Occupation0.30
 Physician0.390.36–0.43
 Nurse0.420.39–0.45
 Emergency medical technician0.350.16–0.55
Affiliated department0.66
 ED0.410.38–0.43
 Non-ED0.390.35–0.44
Clinical career (yr)0.53
 <50.400.37–0.43
 ≥50.410.38–0.45
Instructor certification0.33
 Yes0.380.29–0.46
 No0.410.39–0.43
ACLS certification0.65
 Yes0.390.34–0.45
 No0.410.38–0.43
No. of CPR experience (during last year)0.03
 00.450.05–0.85
 1–50.460.42–0.49
 6–100.350.29–0.42
 11–150.330.23–0.44
 16–200.360.29–0.44
 > 200.400.37–0.44

CI, confidence interval; ED, emergency department; ACLS, advanced cardiac life support; CPR, cardiopulmonary resuscitation.

FactorPercentage of correct answers
P-value
Mean95% CI
Camera position< 0.001
 Cephalic0.230.20–0.26
 Side0.530.49–0.57
 Caudal0.490.46–0.52
Compressor gender0.005
 Male0.370.34–0.40
 Female0.430.40–0.45
Compression depth (cm)< 0.001
 0–10.890.84–0.93
 1–20.430.39–0.48
 2–30.410.38–0.45
 3–40.330.26–0.39
 4–50.300.24–0.36
 5–60.280.24–0.32
 6–70.340.28–0.39

CI, confidence interval.

FactorNo. of clipOdds ratio95% CIP-value
Occupation
 Physician1,050Reference--
 Nurse1,4001.040.87–1.250.67
 Emergency medical1250.770.50–1.190.24
Number of CPR experience (during last year)
 075Reference--
 1–56751.020.61–1.720.93
 6–102750.630.36–1.100.11
 11–151500.570.30–1.060.08
 16–202750.660.38–1.160.15
 >201,1250.820.49–1.380.46
Camera position
 Cephalic927Reference--
 Side6182.622.01–3.42< 0.001
 Caudal1,0302.492.00–3.09< 0.001
Compressor gender
 Female1,545Reference--
 Male1,0300.690.56–0.850.001
Compression depth (cm)
 0–1206Reference--
 1–25150.130.08–0.21< 0.001
 2–36180.100.06–0.16< 0.001
 3–42060.070.04–0.13< 0.001
 4–52060.090.06–0.17< 0.001
 5–65150.070.04–0.12< 0.001
 6–73090.080.05–0.13< 0.001

CI, confidence interval; CPR, cardiopulmonary resuscitation.

  14 in total

1.  Video-based CPR training--the importance of quality assurance.

Authors:  Naheed Akhtar; Richard A Field; Robin P Davies; Gavin D Perkins
Journal:  Resuscitation       Date:  2012-03-16       Impact factor: 5.262

2.  Improving cardiopulmonary resuscitation in the emergency department by real-time video recording and regular feedback learning.

Authors:  Cheng Jiang; Yan Zhao; Zhiqiao Chen; Sheng Chen; Xiaobo Yang
Journal:  Resuscitation       Date:  2010-08-19       Impact factor: 5.262

Review 3.  Part 5: adult basic life support: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care.

Authors:  Robert A Berg; Robin Hemphill; Benjamin S Abella; Tom P Aufderheide; Diana M Cave; Mary Fran Hazinski; E Brooke Lerner; Thomas D Rea; Michael R Sayre; Robert A Swor
Journal:  Circulation       Date:  2010-11-02       Impact factor: 29.690

4.  An evaluation of objective feedback in basic life support (BLS) training.

Authors:  Brendan B Spooner; Jon F Fallaha; Laura Kocierz; Christopher M Smith; Sam C L Smith; Gavin D Perkins
Journal:  Resuscitation       Date:  2007-02-01       Impact factor: 5.262

5.  CPR quality improvement during in-hospital cardiac arrest using a real-time audiovisual feedback system.

Authors:  Benjamin S Abella; Dana P Edelson; Salem Kim; Elizabeth Retzer; Helge Myklebust; Anne M Barry; Nicholas O'Hearn; Terry L Vanden Hoek; Lance B Becker
Journal:  Resuscitation       Date:  2007-01-26       Impact factor: 5.262

6.  Assessment of BLS skills: optimizing use of instructor and manikin measures.

Authors:  Bonnie Lynch; Eric L Einspruch; Graham Nichol; Tom P Aufderheide
Journal:  Resuscitation       Date:  2007-09-12       Impact factor: 5.262

7.  Improvement in chest compression quality using a feedback device (CPRmeter): a simulation randomized crossover study.

Authors:  Clément Buléon; Jean-Jacques Parienti; Laurent Halbout; Xavier Arrot; Hélène De Facq Régent; Dan Chelarescu; Jean-Luc Fellahi; Jean-Louis Gérard; Jean-Luc Hanouz
Journal:  Am J Emerg Med       Date:  2013-09-12       Impact factor: 2.469

8.  CPREzy: an evaluation during simulated cardiac arrest on a hospital bed.

Authors:  Gavin D Perkins; Colette Augré; Helen Rogers; Michael Allan; David R Thickett
Journal:  Resuscitation       Date:  2005-01       Impact factor: 5.262

9.  European Resuscitation Council Guidelines for Resuscitation 2010 Section 2. Adult basic life support and use of automated external defibrillators.

Authors:  Rudolph W Koster; Michael A Baubin; Leo L Bossaert; Antonio Caballero; Pascal Cassan; Maaret Castrén; Cristina Granja; Anthony J Handley; Koenraad G Monsieurs; Gavin D Perkins; Violetta Raffay; Claudio Sandroni
Journal:  Resuscitation       Date:  2010-10       Impact factor: 5.262

10.  Real-time audiovisual feedback system in a physician-staffed helicopter emergency medical service in Finland: the quality results and barriers to implementation.

Authors:  Marko Sainio; Antti Kämäräinen; Heini Huhtala; Petri Aaltonen; Jyrki Tenhunen; Klaus T Olkkola; Sanna Hoppu
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2013-07-01       Impact factor: 2.953

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