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55 Emergency (2016); 4 (2): 55-64

REVIEW ARTICLE

Comparison of Ultrasonography and Radiography in Detection of Thoracic

Bone Fractures; a Systematic Review and Meta-Analysis

Mahmoud Yousefifard1, Masoud Baikpour2, Parisa Ghelichkhani3, Hadi Asady4, Abolfazl Darafarin5,

Mohammad Reza Amini Esfahani5, Mostafa Hosseini6, 7*, Mehdi Yaseri6, Saeed Safari5

1. Department of Physiology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. 2. Department of Medicine, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

3. Department of Intensive Care Nursing, School of Nursing and Midwifery, Tehran University of Medical Sciences, Tehran, Iran. 4. Department of Occupational Health Engineering, Faculty of Public Health, Tehran University of Medical Sciences, Tehran, Iran. 5. Department of Emergency Medicine, Shohadaye Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

6. Sina Trauma and Surgery Research Center, Tehran University Medical Sciences, Tehran, Iran. 7. Department of Epidemiology and Biostatistics, school of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

*Corresponding Author: Mostafa Hosseini, Department of Epidemiology and Biostatistics School of Public Health, Tehran University of Medical Sciences,

Poursina Ave, Tehran, Iran; Email: [email protected]; Tel: +982188989125; Fax: +982188989127. Received: June 2015; Accepted: August 2015

Abstract

Introduction: The potential benefit of ultrasonography for detection of thoracic bone fractures has been proven

in various surveys but no comprehensive conclusion has been drawn yet; therefore, the present study aimed to

conduct a thorough meta-analytic systematic review on this subject. Methods: Two reviewers independently car-

ried out a comprehensive systematic search in Medline, EMBASE, ISI Web of Knowledge, Scopus, Cochrane Library,

and ProQuest databases. Data were summarized as true positive, false positive, true negative and false negative

and were analyzed via STATA 11.0 software using a mixed-effects binary regression model. Sources of heterogene-

ity were further assessed through subgroup analysis. Results: Data on 1667 patients (807 subjects with and 860

cases without thoracic fractures), whose age ranged from 0 to 92 years, were extracted from 17 surveys. Pooled

sensitivity and specificity of ultrasonography in detection of thoracic bone fractures were 0.97 (95% CI: 0.90-0.99;

I2= 88.88, p<0.001) and 0.94 (95% CI: 0.86-0.97; I2= 71.97, p<0.001), respectively. The same measures for chest

radiography were found to be 0.77 (95% CI: 0.56-0.90; I2= 97.76, p<0.001) and 1.0 (95% CI: 0.91-1.00; I2= 97.24,

p<0.001), respectively. The sensitivity of ultrasonography was higher in detection of rib fractures, compared to

fractures of sternum or clavicle (97% vs. 91%). Moreover, the sensitivity was found to be higher when the proce-

dure was carried out by a radiologist in comparison to an emergency medicine specialist (96% vs. 90%). Conclu-

sion: Base on the findings of the present meta-analysis, screening performance characteristic of ultrasonography

in detection of thoracic bone fractures was found to be higher than radiography. However, these characteristics

were more prominent in detection of rib fractures and in cases where was performed by a radiologist.

Key words: Thoracic fractures; ultrasonography; radiography; diagnostic tests, routine

Cite this article as: Yousefifard M, Baikpour M, Ghelichkhani P, et al. Comparison of ultrasonography and radiography in detec-tion of thoracic bone fractures; a systematic review and meta-analysis. Emergency. 2016; 4(2):55-64.

Introduction: arly diagnosis of rib fractures can rapidly indicate

the source of thoracic pain and be helpful in pain

management of trauma patients. Other than pain,

rib fractures have been reported to be associated with

morbidity and mortality in elderly patients (3-5). In

most emergency departments, ultrasonography is con-

sidered as one of the most useful screening tools for

rapid evaluation of trauma patients (6). Application of

ultrasonography for assessment of chest wall injuries

has been reported from 1980s (7). Since then the tech-

nology of ultrasound devices has significantly improved

so that images with higher resolutions are obtained. In

light of these improvements, the diagnostic value of this

modality has been considerably enhanced (9). In this re-

gard, studies have illustrated a considerably high diag-

nostic value of ultrasonography in detection of thoracic

fractures, even higher than that of chest radiography (8,

10-12). For instance in his narrative review, Chan re-

ferred to ultrasonography as a reliable diagnostic tool

E


Yousefifard et al 56

for detection of thoracic bone fractures (13). Neverthe-

less, still no comprehensive review has been carried out

comparing the diagnostic values of chest ultrasonogra-

phy and radiography in detection of thoracic fractures.

One solution is to perform a meta-analysis on the availa-

ble evidence (15, 16). Accordingly, the present system-

atic review and meta-analysis aimed to determine the di-

agnostic values of chest ultrasonography and radiog-

raphy in detection of thoracic bone fractures.

Methods: Search strategy and selection criteria The study protocol was established based on the guide-lines of Meta-analysis of Observational Studies in Epide-miology statement (MOOSE) (19). After selection of key-words from Medical Subject Heading (MeSH) terms and EMTREE, two reviewers (M.Y, P.G) independently car-ried out an extended systematic search in databases of Medline (via PubMed), EMBASE (via OvidSP), ISI Web of Knowledge, Scopus, Cochrane Library, and ProQuest

without any time or language limitations. The keywords included “Ultrasonography” OR “Sonography” OR “Ultra-sound” OR “Radiography” OR “Chest Film” OR “Chest Ra-diograph” combined with “Rib Fractures” OR “Chest Wall Fracture” OR “Sternum Fracture” OR “Sternal Fracture” OR “Clavicle Fracture” OR “Scapula Fracture”. Addition-ally, the bibliographies of original and review articles as well as Google Scholar were also searched. All the studies evaluating the diagnostic accuracy of ultrasonography or chest radiography in detection of chest wall fractures were assessed. Review and editorial articles, case re-ports and studies with sample populations of less than 10 patients were excluded. Data extraction Two reviewers (M.Y, P.G) independently worked on summarizing the data regarding assessing quality of studies, baseline characteristics of patients (age, gender, the number of patients with and without hemothorax, the etiology of hemothorax), the characteristics of ultra-sonography device (transducer, frequency), physicians in charge of imaging interpretation, blinding status, sam-pling method (consecutive, convenience), study design

Figure 1: Flowchart of the study.


57 Emergency (2016); 4 (2): 55-64

Ta

ble

1: C

har

ecte

rist

ics

of

incl

ud

ed s

tud

ies

Stu

dy

N

o. o

f p

ati

en

t (+

/ -

) A

ge

1 (

ye

ars

) M

ale

(%

) R

efe

ren

ce /

In

de

x

Tra

nsd

uce

r /

Op

era

tor

Sa

mp

lin

g /

F

ract

ure

W

ea

kn

ess

es

He

nd

rich

1

99

5 (

1)

15

/ 3

0

45

(2

9-6

1)

57

.8

CX

R /

US

7.5

MH

z /

R

adio

logi

st

Co

nv

enie

nce

/

ster

nu

m

Lo

w s

amp

le s

ize

Po

ssib

ilit

y o

f se

lect

ion

bia

s

En

gin

20

00

(2

) 1

8 /

5

35

.4 (

18

-75

) 8

2.6

C

XR

/ U

S 7

.5 M

Hz

/

Rad

iolo

gist

C

on

ven

ien

ce /

St

ern

um

Ret

rosp

ecti

ve

des

ign

L

ow

sam

ple

siz

e P

oss

ibil

ity

of

sele

ctio

n b

ias

Hu

rle

y 2

00

4

(8)

15

/ 5

3

1 (

16

-55

) 7

8.6

C

T /

US,

CX

R

12

.5 M

Hz

/

Rad

iolo

gist

C

on

secu

tiv

e /

Rib

L

ow

sam

ple

siz

e

Ra

ine

r 2

00

4

(11

) 7

6 /

12

51

± 1

9

59

C

T /

US,

CX

R

5-t

o 1

0-M

Hz

/ R

adio

logi

st

Co

nv

enie

nce

/

Ster

nu

m

Jin

20

06

(1

0)

23

/ 1

6

45

.2 (

15

-82

) 5

2

CT

/ U

S, C

XR

5

-to

9-M

Hz

/ R

a-d

iolo

gist

C

on

ven

ien

ce /

M

ult

iple

L

ow

sam

ple

siz

e P

oss

ibil

ity

of

sele

ctio

n b

ias

Tra

ub

20

07

(1

4)

68

/ 7

3

47

.2 (

18

-89

) 7

5

CT

/ C

XR

N

A /

R

adio

logi

st

Co

nv

enie

nce

/

Rib

R

etro

spec

tiv

e d

esig

n

Po

ssib

ilit

y o

f se

lect

ion

bia

s W

oo

tto

n-

Go

rge

s 2

00

8 (

17

) 1

31

/ 9

4

0.2

(0

.1-0

.5)

4

1.7

C

T /

CX

R

NA

/

Rad

iolo

gist

C

on

secu

tiv

e /

Rib

Ret

rosp

ecti

ve

des

ign

P

oss

ibil

ity

of

sele

ctio

n b

ias

Lo

w s

amp

le s

ize

Cro

ss 2

01

0

(18

) 4

3 /

57

10

.7 (

1-1

7)

87

.3

CX

R /

US

10

- to

15

-MH

z/

EP

C

on

ven

ien

ce /

C

lav

icle

P

oss

ibil

ity

of

sele

ctio

n b

ias

We

inb

erg

2

01

0 (

20

) 2

5 /

18

7

13

(3

-23

) N

R

CT

/ U

S 7

.5-

to 1

0-M

Hz/

E

P

Co

nv

enie

nce

/

Cla

vic

le a

nd

rib

P

oss

ibil

ity

of

sele

ctio

n b

ias

Yo

u 2

01

0

(21

) 2

4 /

12

4

3 (

8-7

3)

52

.8

CT

/ U

S 7

-to

12

-MH

z /

Rad

iolo

gist

C

on

secu

tiv

e /

Rib

L

ow

sam

ple

siz

e

Szu

cs-F

ar-

ka

s 2

01

1

(22

) 3

9 /

24

64

.4 ±

14

.7

73

C

T /

CX

R

NA

/

Rad

iolo

gist

C

on

ven

ien

ce /

R

ib

Ret

rosp

ecti

ve

des

ign

L

ow

sam

ple

siz

e P

oss

ibil

ity

of

sele

ctio

n b

ias

Ya

zka

n

20

12

(2

3)

83

/ 8

3

40

.8 (

16

-92

) 7

3.5

C

T /

CX

R

NA

/

Surg

eon

C

on

secu

tiv

e /

Rib

R

etro

spec

tiv

e d

esig

n

Bła

siń

ska

2

01

3 (

24

) 3

4 /

26

N

R

NR

C

T /

CX

R

NA

/

Rad

iolo

gist

C

on

secu

tiv

e /

Mu

ltip

le

Lo

w s

amp

le s

ize

Ch

ard

oli

2

01

3 (

25

) 5

1 /

14

9

37

.9 (

16

- 9

0)

84

C

T /

CX

R

NA

/ E

P

Co

nv

enie

nce

/

Rib

Th

e in

terp

reta

tio

n o

f th

e C

XR

an

d C

T w

ere

no

t in

bli

nd

fas

hio

n

Po

ssib

le s

elec

tio

n b

ias

U

zun

20

13

(1

2)

92

/ 8

2

8 (

15

- 4

0)

73

C

T /

US,

CX

R

NR

/

Rad

iolo

gist

C

on

secu

tiv

e /

Rib

P

oss

ibil

ity

of

rep

ort

ing

bia

s

Ho

ffst

ett

er

20

14

(2

6)

15

/ 2

4

61

(2

4-8

7)

60

.7

CT

/ C

XR

N

A /

R

adio

logi

st

Co

nse

cuti

ve

/ M

ult

iple

R

etro

spec

tiv

e d

esig

n

Lo

w s

amp

le s

ize

Pa

rk 2

01

5

(27

) 5

5 /

55

5

6.2

(1

6.9

) 5

7.4

C

T /

CX

R

NA

/

Rad

iolo

gist

C

on

secu

tiv

e /

Rib

L

ow

sam

ple

siz

e

1, (

+ /

-):

nu

mb

er o

f p

atie

nt

wit

h f

ract

ure

/ n

um

ber

of

pa

tien

t w

ith

ou

t fr

actu

re; 2

, Nu

mb

er a

re p

rese

nte

d a

s m

ean

± s

tan

dar

d d

evia

tio

n o

r (r

ange

).

CT

: Co

mp

ute

d t

om

og

rap

hy

; CX

R: C

hes

t ra

dio

gra

ph

y; E

P:

Em

erge

ncy

ph

ysi

cian

; NA

: No

t ap

pli

cab

le;

NR

: No

t R

epo

rted

; US:

Ult

raso

no

gra

ph

y.



(retrospective, prospective). Finally the number of true positive (TP), true negative (TN), false positive (FP), and false negative (FN) cases were extracteded. Disagree-ments were discussed with the third reviewer (M.H) and a solution was proposed. In cases of data inaccessibility, the corresponding authors of the articles were con-tacted. Data presented as charts were extracted via the method proposed by Sistrom and Mergo (28). In cases where only the sensitivity and specificity were pre-sented, reliable web-based programs were used to calcu-late the number of TP, TN, FP, and FN cases. Quality assessment Quality of the studies were assessed based on the guide-lines of 14-Item Quality Assessment of Diagnostic Accu-racy Studies (QUADAS2) tool (29). The quality assess-ment were performed based on following items: ac-ceptable reference tests, accounting for indeterminate results, avoiding differential verification bias, disease progression bias, incorporation bias and verification bias, blind index test interpretation, blind interpretation of reference test, explained withdrawal, relevant clinical data available, and representative spectrum. A total grading of poor, fair, and good was attributed to each survey and only the fair and good studies were included in the meta-analysis. Statistical analysis Analysis was performed using STATA 11.0 statistical software via MIDAS module. To evaluate the screening performance characteristics of ultrasonography and ra-diography in detection of chest wall fractures, summary receiver operative curves (SROCs) were drawn and pooled sensitivity, specificity, positive likelihood ratio and negative likelihood ratio with 95% confidence inter-val (95% CI) were calculated. Due the high heterogeneity between the included studies, mixed-effects binary re-gression model was used. Heterogeneity was evaluated through calculations of I2 and χ2 tests and a P value of less than 0.1 together with an I2 greater than 50% were considered as positive heterogeneity (30). Subgroup analysis was performed to identify the source of hetero-geneity. Deek’s asymmetry funnel plot was used to search for publication bias. In all the analyses, p value of less than 0.05 was considered as statistically significant. Results: Study characteristics 17 out of 3894 studies found in the comprehensive search were included in the systematic review and meta-analysis (1, 2, 8, 10-12, 14, 17, 18, 20-27). 5 studies had assessed the diagnostic accuracy of ultrasonography in detection of thoracic bone fractures (1, 2, 18, 20, 21), 8 diagnostic value of chest radiography (14, 17, 22-27), and 4 diagnostic values of ultrasonography and radiog-raphy simultaneously (8, 10-12). 1667 cases (807 with and 860 without fractures) were extracted from the 17

mentioned articles, whose age ranged from 0 to 92 years old. Figure 1 shows the inclusion process of articles and table 1 summarizes the characteristics of included stud-ies. No publication bias was observed (Figure 2). Meta-analysis The results of the analyses are presented as SROCs and Funnel plots in Figures 3 to 5. The area under the curve of SROC for ultrasonography and radiography in detec-tion of chest wall fractures were found to be 0.99 (95% CI: 0.97-0.99) and 0.97 (95% CI: 0.96-0.99), respectively (Figure 3). Pooled sensitivity and specificity of ultraso-nography in detection of thoracic bone fractures were 0.97 (95% CI: 0.90-0.99; I2= 88.88, p<0.001) and 0.94 (95% CI: 0.86-0.97; I2= 71.97, p<0.001), respectively (Figure 4-A). These characteristics for radiography were found to be 0.77 (95% CI: 0.56-0.90; I2= 97.76, p<0.001) and 1.0 (95% CI: 0.91-1.00; I2= 97.24, p<0.001), respec-tively (Figure 5-A). In addition, pooled positive and neg-ative likelihood ratios of ultrasonography were 16.26 (95% CI: 6.26-38.87; I2= 59.14, p<0.001) and 0.03 (95% CI: 0.01-0.11; I2= 86.76, p<0.001), respectively (Figure 4-B), while these measures for radiography were re-ported to be 774.63 (95% CI: 7.0-8573.0; I2= 96.62, p<0.001) and 0.23 (95% CI: 0.11-0.48; I2= 96.94, p<0.001), respectively (Figure 5-B). Subgroup Analysis There were significant heterogeneity between the arti-cles (Figure 4 and 5). Subgroup analysis was performed to remove its effects and find its probable sources. Table 2 presents the results of this analysis. Specificity of ultra-sonography in detection of thoracic bone fractures was directly correlated with frequency of transducer (90% vs. 95%). The sensitivity of this modality was found to be higher in detection of rib fractures rather than fractures of clavicle or sternum (97% vs. 91%). Moreover it was found that the sensitivity would be higher if the proce-dure is performed by a radiologist (96%) compared to an emergency medicine specialist (90%). Sample size was another source of heterogeneity. Studies with sam-ple sizes of greater than 100 patients reported higher di-agnostic accuracies for ultrasonography in detection of thoracic bone fractures (97% vs. 91%). As can be seen in Table 2, the most important factor af-fecting sensitivity of chest radiography is the interpret-ing physician. The sensitivity was found to be 66% when the radiogram was interpreted by an emergency medi-cine specialist while it was 80% when interpreted by a radiologist. Furthermore, consecutive sampling method compared with convenience (80% vs. 73%) and sample size of more than 100 patients (82% vs. 73%) were also found to be sources of heterogeneity. Discussion: Base on the results of the present meta-analysis sensitiv-ity of chest ultrasonography in detection of thoracic


59 Emergency (2016); 4 (2): 55-64

Ta

ble

2:

Sub

gro

up

an

aly

sis

of

dia

gn

ost

ic a

ccu

racy

fo

r ch

est

rad

iogr

aph

y a

nd

ult

raso

no

grap

hy

in d

etec

tio

n o

f th

ora

cic

bo

ne

frac

ture

s

N

o. o

f st

ud

ies

Biv

ari

ate

ra

nd

om

-eff

ect

mo

de

l

Se

nsi

tiv

ity

(9

5%

CI)

P

S

pe

cifi

city

(9

5%

CI)

p

h

ete

rog

en

eit

y, I

2

P*

Ult

raso

no

gra

ph

y

Pa

tie

nt

en

roll

me

nt

Co

nse

cuti

ve

3

0.9

8 (

0.9

5-1

.00

) 0

.01

0

.90

(0

.77

-1.0

0)

0.5

5

43

.0 %

0

.18

Co

nv

enie

nce

6

0

.95

(0

.90

-0.9

9)

0

.91

(0

.86

-0.9

6)

Op

era

tor

Em

erge

ncy

ph

ysi

cian

3

0

.90

(0

.81

-0.9

8)

<0

.00

1

0.9

0 (

0.8

3-0

.97

) 0

.09

2

1.0

%

0.2

8

Oth

er p

hy

sici

an

6

0

.96

(0

.93

-0.9

9)

0

.91

(0

.84

-0.9

8)

Sa

mp

le s

ize

< 1

00

6

0

.91

(0

.84

-0.9

7)

0.0

1

0.9

0 (

0.8

3-0

.97

) 0

.04

1

2.0

%

0.3

2

≥ 1

00

3

0

.97

(0

.94

-1.0

0)

0

.93

(0

.87

-0.9

8)

Fre

qu

en

cy o

f tr

an

sdu

cer

5-1

0 M

Hz

6

0.9

4 (

0.8

9-0

.99

) 0

.62

0

.90

(0

.85

-0.9

5)

0.0

3

0.0

%

0.5

1

10

-15

MH

z 3

0

.95

(0

.88

-1.0

0)

0

.95

(0

.89

-1.0

0)

Ty

pe

of

fra

ctu

re

Rib

4

0

.97

(0

.93

-1.0

0)

0.0

1

0.8

9 (

0.8

3-0

.96

) 0

.01

4

5.0

%

0.1

6

Ster

nu

m /

Cla

vic

le

5

0.9

1 (

0.8

4-0

.97

)

0.9

3 (

0.9

4-0

.98

)

Ra

dio

gra

ph

y

Pa

tie

nt

en

roll

me

nt

Co

nse

cuti

ve

7

0.8

0 (

0.5

9 -

1.0

0)

0.7

0

1.0

0 (

1.0

0 -

1.0

0)

0.9

9

0.0

%

0.7

0

Co

nv

enie

nce

5

0

.73

(0

.45

- 1

.00

)

1.0

0 (

0.9

8 -

1.0

0)

Op

era

tor

Em

erge

ncy

ph

ysi

cian

3

0

.66

(0

.27

- 1

.00

) 0

.53

1

.00

(1

.00

- 1

.00

) 0

.99

0

.0 %

0

.78

Oth

er p

hy

sici

an

9

0

.80

(0

.63

- 0

.98

)

1.0

0 (

1.0

0 -

1.0

0)

Sa

mp

le s

ize

< 1

00

7

0

.73

(0

.49

- 0

.97

) 0

.44

1

.00

(1

.00

- 1

.00

) 0

.99

0

.0 %

0

.57

≥ 1

00

5

0

.82

(0

.61

- 1

.00

)

1.0

0 (

1.0

0 -

1.0

0)

Ty

pe

of

fra

ctu

re

Rib

8

0

.77

(0

.57

- 0

.97

) 0

.56

1

.00

(1

.00

- 1

.00

) 0

.99

0

.0 %

0

.98

Ster

nu

m /

Cla

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bone fractures following trauma was prominently higher than radiography (97% vs. 77%). Yet, the specificity of radiography was found to be significantly higher than ul-trasonography in this regard (100% vs. 94%). On this ba-sis and according to calculated likelihood ratios, a nega-tive result of ultrasonography in detection of thoracic fracture is more reliable than radiography (negative likelihood ratio=0.03), while a positive result of chest ra-diography is more reliable than ultrasonography (posi-tive likelihood ratio=774.63). Ultrasonography had a higher sensitivity in diagnosis of rib fractures rather than other chest wall bones, while the type of fracture had no effect on diagnostic value of radiography. This finding can be ascribed to the higher attention that physicians pay to rib fractures rather than other chest wall bones such as scapula and sternum. Fractures are diagnosed via ultrasonography based on observation of cortical bone disruption. In cases of small fractures, detection of this sign in sonogram and distin-guishing it from other findings is highly dependent on the skills of the operator. The role of operator’s skills in detection of injuries via ultrasonography was verified in the present study as well (31-34). Ultrasonography by a radiologist has a higher sensitivity compared to emer-gency medicine specialist. The present study found that the specificity of this modality increased with frequen-cies of higher than 10MHz which might be due to the higher resolution obtained with higher frequencies (35), making it easier to detect the signs of fracture. Some narrative review articles and qualitative system-atic reviews are indicative of the potential benefit of ul-trasonography in detection of chest wall fractures. In this regard, Chan, in his systematic review conducted on studies indexed in Medline, declares that ultrasonogra-phy has a higher sensitivity in detection of thoracic bone fractures compared to radiography (13). Finding the di-agnostic accuracy of ultrasonography to be two times the ability of radiography in fracture diagnosis, Dietrich et al. also referred to ultrasonography as a useful diagnostic tool for detection of rib fractures (36). The results of the present meta-analysis were congruent with these find-ings. Presence of considerable heterogeneity between the in-cluded articles and simultaneous inclusion of retrospec-tive and prospective studies in the meta-analysis were major limitations of this study. Subgroup analysis was performed to overcome the heterogeneity problem. Conclusion: Base on the findings of the present meta-analysis, screening performance characteristic of ultrasonogra-phy in detection of thoracic bone fractures was found to be higher than radiography. However, these characteris-tics were more prominent in detection of rib fractures and in cases where was performed by a radiologist.

Acknowledgments: None Conflict of interest: None Funding support: This research has been supported by Tehran University of Medical Sciences & health Services grant number: 93-02-38-25618. Authors’ contributions: All authors passed four criteria for authorship contribu-

tion based on recommendations of the International

Committee of Medical Journal Editors.

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animals: A systematic review with meta-analysis. Biol Blood Marrow Transplant. 2015: [In press]. 17. Wootton-Gorges SL, Stein-Wexler R, Walton JW, Rosas AJ, Coulter KP, Rogers KK. Comparison of computed tomography and chest radiography in the detection of rib fractures in abused infants. Child Abuse Negl. 2008;32(6):659-63. 18. Cross KP, Warkentine FH, Kim IK, Gracely E, Paul RI. Bedside ultrasound diagnosis of clavicle fractures in the pediatric emergency department. Acad Emerg Med. 2010;17(7):687-93. 19. Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283(15):2008-12. 20. Weinberg ER, Tunik MG, Tsung JW. Accuracy of clinician-performed point-of-care ultrasound for the diagnosis of fractures in children and young adults. Injury. 2010;41(8):862-8. 21. You JS, Chung YE, Kim D, Park S, Chung SP. Role of sonography in the emergency room to diagnose sternal fractures. J Clin Ultrasound. 2010;38(3):135-7. 22. Szucs-Farkas Z, Lautenschlager K, Flach PM, et al. Bone images from dual-energy subtraction chest radiography in the detection of rib fractures. Eur J Radiol. 2011;79(2):e28-32. 23. Yazkan R, Ergene G, Tulay CM, Güneş S, Han S. Comparison of Chest Computed Tomography and Chest X-Ray in the Diagnosis of Rib Fractures in Patients with Blunt Chest Trauma. JAEM. 2012;11:171-5. 24. Błasińska-Przerwa K, Pacho R, Bestry I. Pneumonol Alergol Pol. Pneumonologia Alergologia Polska. 2013;81(6):518-26. 25. Chardoli M, Hasan-Ghaliaee T, Akbari H, Rahimi-Movaghar V. Accuracy of chest radiography versus chest computed tomography in hemodynamically stable patients with blunt chest trauma. Chin J Traumatol. 2013;16(6):351-4. 26. Hoffstetter P, Dornia C, Schafer S, et al. Diagnostic significance of rib series in minor thorax trauma compared to

plain chest film and computed tomography. J Trauma Manag Outcomes. 2014;8:10. 27. Park JB, Cho YS, Choi HJ. Diagnostic accuracy of the inverted grayscale rib series for detection of rib fracture in minor chest trauma. Am J Emerg Med. 2015;33(4):548-52. 28. Sistrom CL, Mergo PJ. A simple method for obtaining original data from published graphs and plots. Am J Roentgenol. 2000;174(5):1241-4. 29. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529-36. 30. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557. 31. Abbasi S, Farsi D, Hafezimoghadam P, Fathi M, Zare MA. Accuracy of emergency physician-performed ultrasound in detecting traumatic pneumothorax after a 2-h training course. Eur J Emerg Med. 2013;20(3):173-7. 32. Bui-Mansfield LT, Chen DC, O'Brien SD. Accuracy of ultrasound of musculoskeletal soft-tissue tumors. Am J Roentgenol. 2015;204(2):W218. 33. Fine D, Perring S, Herbetko J, Hacking C, Fleming J, Dewbury K. Three-dimensional (3D) ultrasound imaging of the gallbladder and dilated biliary tree: reconstruction from real-time B-scans. Br J Radiol. 1991;64(767):1056-7. 34. Lee JH, Jeong YK, Park KB, Park JK, Jeong AK, Hwang JC. Operator-dependent techniques for graded compression sonography to detect the appendix and diagnose acute appendicitis. Am J Roentgenol. 2005;184(1):91-7. 35. Majumdar S, Kumar PS, Pandit A. Effect of liquid-phase properties on ultrasound intensity and cavitational activity. Ultrason Sonochem. 1998;5(3):113-8. 36. Dietrich CF, Mathis G, Cui XW, Ignee A, Hocke M, Hirche TO. Ultrasound of the pleurae and lungs. Ultrasound Med Biol. 2015;41(2):351-65.



A B

Figure 2: Deeks’ funnel plot asymmetry test for assessment of publication bias. P values < 0.05 was considered as significant. Ultrasonography (A); Radiography (B). ESS: Effective sample sizes.

A B

Figure 3: Summary receiver operative curves (SROC) for ultrasound (A) and chest radiography (B) in detection of thoracic bone fractures. AUC: Area under the curve; SENS: Sensitivity; SPEC: Specificity.

1

2

3

4

56

7

8

9

.1

.15

.2

.25

1/r

oo

t(E

SS)

1 10 100 1000

Diagnostic Odds Ratio

Study

RegressionLine

Deeks' Funnel Plot Asymmetry Testpvalue = 0.68

1

2

3

4

5

6

7

8

9

1011

12

.05

.1

.15

.2

.25

1/r

oo

t(E

SS)

1 10 100 1000

Diagnostic Odds Ratio

Study

RegressionLine

Deeks' Funnel Plot Asymmetry Testpvalue = 0.39

12

3

4

5

6

7

8

9

0.0

0.5

1.0

Sen

siti

vit

y

0.00.51.0Specificity

Observed Data

Summary Operating PointSENS = 0.97 [0.90 - 0.99]SPEC = 0.94 [0.86 - 0.97]

SROC CurveAUC = 0.99 [0.97 - 0.99]

95% Confidence Contour

95% Prediction Contour

SROC with Prediction & Confidence Contours

1

2

3

45

6

7

8

9

10

11

12

0.0

0.5

1.0

Sen

siti

vit

y

0.00.51.0Specificity

Observed Data

Summary Operating PointSENS = 0.77 [0.56 - 0.90]SPEC = 1.00 [0.91 - 1.00]

SROC CurveAUC = 0.97 [0.96 - 0.99]

95% Confidence Contour

95% Prediction Contour

SROC with Prediction & Confidence Contours


63 Emergency (2016); 4 (2): 55-64

A

B

Figure 4: Forest plot of screening performance characteristics of chest ultrasonography in detection of thoracic bone fractures. Sensitivity and specificity (A); Diagnostic likelihood ratio (DLR) (B). CI: Confidence interval.

SENSITIVITY (95% CI)

Q = 71.95, df = 8.00, p = 0.00

I2 = 88.88 [82.99 - 94.77]

0.97[0.90 - 0.99]

1.00 [0.96 - 1.00]

1.00 [0.86 - 1.00]

0.93 [0.76 - 0.99]

0.95 [0.84 - 0.99]

1.00 [0.85 - 1.00]

0.80 [0.70 - 0.89]

0.93 [0.68 - 1.00]

0.89 [0.65 - 0.99]

1.00 [0.78 - 1.00]1.00 [0.78 - 1.00]

Author / year

COMBINED

Uzun 2013

You 2010

Weinberg 2010

Cross 2010

Jin 2006

Rainer 2004

Hurley 2004

Engin 2000

Hendrich 1995

0.7 1.0

SPECIFICITY (95% CI)

Q = 28.54, df = 8.00, p = 0.00

I2 = 71.97 [52.99 - 90.95]

0.94[0.86 - 0.97]

0.89 [0.52 - 1.00]

1.00 [0.74 - 1.00]

0.88 [0.80 - 0.94]

0.96 [0.88 - 1.00]

1.00 [0.79 - 1.00]

0.83 [0.52 - 0.98]

1.00 [0.48 - 1.00]

0.60 [0.15 - 0.95]

0.97 [0.83 - 1.00]0.97 [0.83 - 1.00]

Author / year

COMBINED

Uzun 2013

You 2010

Weinberg 2010

Cross 2010

Jin 2006

Rainer 2004

Hurley 2004

Engin 2000

Hendrich 1995

0.1 1.0

DLR POSITIVE (95% CI)

Q = 32.43, df = 8.00, p = 0.00

I2 = 59.14 [59.14 - 91.52]

16.26[6.80 - 38.87]

6.63 [1.52 - 29.00]

25.48 [1.68 - 386.24]

7.89 [4.59 - 13.56]

27.17 [6.95 - 106.19]

33.29 [2.17 - 511.15]

4.82 [1.35 - 17.15]

10.88 [0.76 - 155.24]

2.22 [0.75 - 6.58]

20.02 [4.19 - 95.62]20.02 [4.19 - 95.62]

Author / year

COMBINED

Uzun 2013

You 2010

Weinberg 2010

Cross 2010

Jin 2006

Rainer 2004

Hurley 2004

Engin 2000

Hendrich 1995

0.8 511.2

DLR NEGATIVE (95% CI)

Q = 60.44, df = 8.00, p = 0.00

I2 = 86.76 [79.40 - 94.13]

0.03[0.01 - 0.11]

0.01 [0.01 - 0.10]

0.02 [0.01 - 0.32]

0.08 [0.02 - 0.31]

0.05 [0.01 - 0.19]

0.02 [0.01 - 0.33]

0.24 [0.14 - 0.40]

0.10 [0.02 - 0.48]

0.19 [0.04 - 0.82]

0.03 [0.01 - 0.50]0.03 [0.01 - 0.50]

Author / year

COMBINED

Uzun 2013

You 2010

Weinberg 2010

Cross 2010

Jin 2006

Rainer 2004

Hurley 2004

Engin 2000

Hendrich 1995

0 1



A

B

Figure 5: Forest plot of screening performance characteristics of chest radiography in detection of thoracic bone fractures. Sensi-tivity and specificity (A); Diagnostic likelihood ratio (DLR) (B). CI: Confidence interval.

SENSITIVITY (95% CI)

Q =438.10, df = 11.00, p = 0.00

I2 = 97.49 [96.76 - 98.21]

0.77[0.56 - 0.90]

0.65 [0.61 - 0.68]

0.47 [0.21 - 0.73]

1.00 [0.96 - 1.00]

0.49 [0.35 - 0.63]

0.47 [0.30 - 0.65]

0.81 [0.71 - 0.89]

0.34 [0.28 - 0.41]

0.60 [0.51 - 0.69]

0.69 [0.57 - 0.80]

1.00 [0.85 - 1.00]

0.80 [0.70 - 0.89]

0.93 [0.68 - 1.00]0.93 [0.68 - 1.00]

Author / year

COMBINED

Park 2015

Hoffstetter 2014

Uzun 2013

Chardoli 2013

Blasinska 2013

Yazkan 2012

Szucs-Farkas 2011

Wootton 2008

Traub 2007

Jin 2006

Rainer 2004

Hurley 2004

0.2 1.0

SPECIFICITY (95% CI)

Q =399.03, df = 11.00, p = 0.00

I2 = 97.24 [96.42 - 98.06]

1.00[0.91 - 1.00]

0.94 [0.90 - 0.96]

1.00 [0.86 - 1.00]

1.00 [0.63 - 1.00]

1.00 [0.98 - 1.00]

1.00 [0.87 - 1.00]

1.00 [0.96 - 1.00]

0.55 [0.38 - 0.71]

1.00 [0.96 - 1.00]

1.00 [0.96 - 1.00]

1.00 [0.79 - 1.00]

0.83 [0.52 - 0.98]

1.00 [0.48 - 1.00]1.00 [0.48 - 1.00]

Author / year

COMBINED

Park 2015

Hoffstetter 2014

Uzun 2013

Chardoli 2013

Blasinska 2013

Yazkan 2012

Szucs-Farkas 2011

Wootton 2008

Traub 2007

Jin 2006

Rainer 2004

Hurley 2004

0.4 1.0

DLR POSITIVE (95% CI)

Q =420.69, df = 11.00, p = 0.00

I2 = 96.62 [96.62 - 98.15]

774.63[7.00 - 85753.00]

10.50 [6.60 - 16.69]

23.44 [1.44 - 382.77]

17.90 [1.21 - 264.74]

147.12 [9.12 - 1000]

25.46 [1.60 - 405.59]

135.00 [8.50 - 1000]

0.76 [0.52 - 1.13]

114.43 [7.19 - 1000]

136.30 [8.55 - 1000]

33.29 [2.17 - 511.15]

4.82 [1.35 - 17.15]

10.88 [0.76 - 155.24]10.88 [0.76 - 155.24]

Author / year

COMBINED

Park 2015

Hoffstetter 2014

Uzun 2013

Chardoli 2013

Blasinska 2013

Yazkan 2012

Szucs-Farkas 2011

Wootton 2008

Traub 2007

Jin 2006

Rainer 2004

Hurley 2004

0.5 85753.0

DLR NEGATIVE (95% CI)

Q =359.29, df = 11.00, p = 0.00

I2 = 96.94 [96.00 - 97.88]

0.23[0.11 - 0.48]

0.37 [0.34 - 0.42]

0.54 [0.34 - 0.86]

0.01 [0.01 - 0.09]

0.51 [0.39 - 0.67]

0.54 [0.39 - 0.74]

0.20 [0.13 - 0.30]

1.19 [0.89 - 1.00]

0.40 [0.32 - 0.49]

0.31 [0.22 - 0.44]

0.02 [0.01 - 0.33]

0.24 [0.14 - 0.40]

0.10 [0.02 - 0.48]0.10 [0.02 - 0.48]

Author / year

COMBINED

Park 2015

Hoffstetter 2014

Uzun 2013

Chardoli 2013

Blasinska 2013

Yazkan 2012

Szucs-Farkas 2011

Wootton 2008

Traub 2007

Jin 2006

Rainer 2004

Hurley 2004

0 1

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