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Digestive and Liver Disease 42 (2010) 624–628
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Digestive and Liver Disease
journal homepage: www.elsevier.com/locate/dld
Digestive Endoscopy
How to predict a high rate of inappropriateness for upper endoscopy in an
endoscopic centre?
L. Buri a , G. Bersani b , C. Hassan c,∗ , M. Anti d , M.A. Bianco e , L. Cipolletta e , E. Di Giulio f , G. Di Matteo g ,
L. Familiari h , L. Ficano i , P. Loriga j , S. Morini c , V. Pietropaolo k , A. Zambelli l , E. Grossi m ,
M. Intraligi n , F. Tessari o , M. Buscema n , the SIED Appropriateness Working Group1
a
Gastroenterology and Digestive Endoscopy Unit, Cattinara Hospital, Trieste, Italy
Gastrointestinal Endoscopy Service, Malatesta, Cesena, Italy
c
Gastroenterology, Nuovo Regina Margherita, Rome, Italy
d
Gastroenterology Unit, Belcolle Hospital, Viterbo, Italy
e
Division of Gastroenterology and Digestive Endoscopy ASL NA5-Hospital Agostino Maresca, Torre del Greco, Italy
f
Digestive and Liver Disease Unit, Second Medical School, University “La Sapienza”, Sant’Andrea Hospital, Rome, Italy
g
Gastroenterology Unit, “Saverio De Bellis” Hospital, Castellana Grotte, Bari, Italy
h
Gastroenterology, Policlinico G Martino, Messina, Italy
i
Surgery and Oncology Department, “Università di Palermo”, Palermo, Italy
j
Endoscopy Unit, SS Trinità Hospital, Cagliari, Italy
k
Gastroenterology Unit, Policlinico La Sapienza, Rome, Italy
l
Gastroenterology Unit, Maggiore Hospital, Crema, Italy
m
Bracco Imaging S.p.A., Medical Affairs Europe, Milan, Italy
n
Semeion Research Centre for Sciences of Communication, Rome, Italy
o
Idea99, Padova, Italy
b
a r t i c l e
i n f o
Article history:
Received 17 November 2009
Accepted 15 February 2010
Available online 21 March 2010
Keywords:
Appropriateness
Upper endoscopy
a b s t r a c t
Background: Inappropriateness of upper endoscopy (EGD) indication causes decreased diagnostic yield.
Our aim of was to identify predictors of appropriateness rate for EGD among endoscopic centres.
Methods: A post-hoc analysis of two multicentre cross-sectional studies, including 6270 and 8252 patients
consecutively referred to EGD in 44 (group A) and 55 (group B) endoscopic Italian centres in 2003 and
2007, respectively, was performed. A multiple forward stepwise regression was applied to group A, and
independently validated in group B. A <70% threshold was adopted to deﬁne inadequate appropriateness
rate clustered by centre.
Results: discrete variability of clustered appropriateness rates among the 44 group A centres was observed
(median: 77%; range: 41–97%), and a <70% appropriateness rate was detected in 11 (25%). Independent
predictors of centre appropriateness rate were: percentage of patients referred by general practitioners
(GP), rate of urgent examinations, prevalence of relevant diseases, and academic status. For group B,
sensitivity, speciﬁcity and area under receiver operating characteristic curve of the model in detecting
centres with a <70% appropriateness rate were 54%, 93% and 0.72, respectively.
Conclusions: A simple predictive rule, based on rate of patients referred by GPs, rate of urgent examinations, prevalence of relevant diseases and academic status, identiﬁed a small subset of centres
characterised by a high rate of inappropriateness. These centres may be presumed to obtain the largest
beneﬁt from targeted educational programs.
© 2010 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.
1. Introduction
Open-access upper endoscopy (EGD) is the most widespread
access system to endoscopic examinations in the health systems
∗ Corresponding author at: Ospedale Nuovo Regina Margherita, Via Morosini 30,
Rome, Italy. Tel.: +39 06 58446608; fax: +39 06 58446533.
E-mail address: cesareh@hotmail.com (C. Hassan).
1
See Appendix A for the list of members.
of the western world [1]. This type of service allows physicians
to directly schedule elective, common endoscopic procedures for
their patients without prior consultation. Unfortunately, this has
also resulted in a considerable increase in both overall cost and
waiting lists for EGD [2,3].
In order to optimise the use of ﬁnite resources in an open-access
system, ofﬁcial guidelines for the appropriate use of EGD have been
proposed by the American Society for Gastrointestinal Endoscopy
(ASGE) and by the European Panel on the appropriateness of Gastrointestinal Endoscopy (EPAGE) [4,5]. Previous studies based on
1590-8658/$36.00 © 2010 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.dld.2010.02.012
L. Buri et al. / Digestive and Liver Disease 42 (2010) 624–628
these guidelines have generally shown a substantial rate of inappropriate EGD indications, which in turn has been associated with
a markedly decreased diagnostic yield for both relevant ﬁndings
and cancer, and with an unfavourable cost-effectiveness proﬁle as
compared to appropriate procedures [5–13].
The rate of inappropriate indications widely ranged between
10% and 40% in different studies [13], and the few multicentre
studies carried out also showed a moderate degree of variability
among different centres [6,14]. To identify the endoscopic centres
associated with a higher inappropriateness rate of EGD appears
of major importance, since it has been clearly shown that educational programmes directed towards the referring physicians
result into a substantial reduction of the inappropriateness rate
[15,16]. A widespread implementation of such programmes, however, is unlikely, because these initiatives are time-consuming
and costly, also being in competition with similar campaigns for
several other medical procedures [17,18]. Therefore, to identify
simple variables related with the endoscopic setting able to predict the inappropriateness rate of EGDs would allow to target
educational interventions only on a relatively small number of
centres.
The aim of this study, conceived by the Italian Society of Digestive Endoscopy (SIED), was to identify simple factors able to predict
the appropriateness rate for EGD aggregated by centres, in order to
detect those centres with a high inappropriateness rate that may
need interventional programmes.
2. Materials and methods
Two cross-sectional, prospective, multicentre study involving
44 (group A, 6270 patients) and 55 (group B, 8252 patients)
open-access Endoscopy Units uniformly distributed throughout the
country (SIED APPROPRIATENESS PROJECT) were separately performed in 2003 and 2007, respectively [6,19]. In both studies, the
participating centres – which represent 6–8% of all the Italian Endoscopic Units censed by SIED – were also selected to produce a mix of
small and large practices, as well as of academic and not academic
institutions, in order to be representative of the Italian endoscopy
setting. Only a minority of the centres (7 centres) participated in
both studies. However, since no educational initiative was promoted between the two studies, we did not exclude these centres
in both groups. According to the same study protocol of the two
studies, all patients referred to the participating centres for openaccess EGD during 1 month were prospectively enrolled. EGDs were
performed according to predeﬁned weekly schedules, the referring physicians being unaware of the purpose of the study. Before
endoscopy, the following variables were systematically collected:
sex and age of the patient; appropriateness of the EGD indication according to ASGE guidelines; referral physician (primary care
physician (GP) or specialist); setting (inpatient or outpatient); EGD
timing (urgent or elective); ﬁrst EGD or control/follow-up examination. At endoscopy, the presence of relevant ﬁndings (any involving
a modiﬁcation of the treatment and/or management of the patient)
was assigned according to predeﬁned diagnoses listed in Appendix
1.
The clinical association between the appropriateness of the indication according to ASGE guidelines and the detection of relevant
ﬁndings at endoscopy in single patients has been already reported
in previous studies for group A [6] and B [19].
In order to identify eventual predictive variables for the inappropriateness rate of the 44 and 55 individual centres of group A and
B, respectively, we aggregated both the appropriateness rate (i.e.
all appropriate EGD referrals/(appropriate + inappropriate EGD) for
each centre) and the data regarding the following variables for each
centre:
-
625
rate of patients aged ≥45 years
rate of relevant endoscopic diseases detected at endoscopy
rate of hospitalised patients
rate of patients referred by their GP
rate of urgent examinations
rate of follow-up examinations
type of centre (academic/non-academic)
2.1. Statistical analysis
In order to evaluate whether there was a correlation between
the rate of appropriateness in the various centres and each
of the individual variables in the training sample (group A),
the correlation index (Pearson’s r) was calculated. Multiple forward stepwise regression analysis was then used to ﬁnd the
minimum set of independent variables that maximises the correlation with the rate of appropriateness aggregated by centre
(the dependent variable) in group A; this means to ﬁnd the linear regression equation that combines the independent variables
so as to maximise the correlation (measured with R2 , the coefﬁcient of determination) with the dependent variable; the forward
selection begins with no predictor in the regression equation,
so the independent variable with the highest correlation with
the dependent variable is the ﬁrst to be included in the equation; at each subsequent step the variable which most increases
the value of R2 is added, while maintaining signiﬁcant F values
at 0.05% [20]; the addition of variables stops when it does not
produce a signiﬁcant increase of R2 . The coefﬁcient of determination R2 represents the percentage of variance in the data that
is explained by the linear model and therefore the closer it is
to 1.0, the greater the representativeness of the linear model
adopted.
By using the regression model, we computed the predicted
value of appropriateness for each of the 44 centres of group
A. By comparing the predicted values with the observed values
of aggregated appropriateness rates – that served as the reference standard – we measured the accuracy of the model for
detecting those centres associated with an inadequate appropriateness rate (i.e. too low). In detail, we adopted 70% as a
threshold to deﬁne inadequate the appropriateness rate of a centre, because the mean appropriateness rates in the previous studies
was higher than 70% in 6 out of 8 series with an overall median
of 74%, suggesting that 70% may be a reliable cut-off to identify
a small subset of centres that may need a further intervention
[13]. The 55 centres of group B were used for validation of the
predictive model, adopting the same 70% threshold. Sensitivity,
speciﬁcity, positive and negative predictive value, and area under
the receiver operating characteristic curve (AUC), and the 95% conﬁdence intervals, were calculated for both groups [21]. The receiver
operating curve represents the relationship between sensitivity
and speciﬁcity for the prediction of each of the considered outcomes.
For comparison between the two groups, the 2 -test and
Mann–Whitney U test were used to compare categorical and continuous variables, respectively. All data analyses were carried out
with Excel (Microsoft Corp., Redmond Wash.) and SPSS statistical
software. Differences were considered signiﬁcant at a 5% probability level.
3. Results
The median rate of the aggregated appropriateness of EGD
among the 44 and 55 centres of groups A and B was 77% and 78%,
with a considerable variability among the different centres (range:
41–97%, group A; 44–94%, group B). The aggregated appropriate-
626
L. Buri et al. / Digestive and Liver Disease 42 (2010) 624–628
Table 2
Correlation between the aggregated appropriateness rate and the operative variables cumulatively clustered by centre in the group A (training group).
Variable
Correlation (Pearson’s r)
p
Rate of patients aged ≥45 years
Rate of relevant ﬁndings at EGD
Rate of inpatients
Rate of referrals by GP
Rate of urgent examinations
Rate of follow-up EGD
Academic status
0.15
0.40
0.41
−0.41
0.35
−0.21
0.15
0.42
0.002
0.0007
0.01
0.02
0.17
0.09
Table 3
Results of the forward multiple regression analysis applied to the training group A
(a) and validation group (b). The list of the variables included in the model by the
forward stepwise linear multiple regression is shown.
Fig. 1. Distribution of the aggregated values of appropriateness rate observed in
the 44 centres of the Study A and in the 55 centres of the Study B. The threshold
line corresponds to a 70% appropriateness rate. Each circle represents an endoscopic centre, with black circles representing those centres predicted to have a <70%
appropriateness rate by the model.
Table 1
Operative characteristics of the endoscopy centres participating in the study. Data
are reported aggregated by centres, so that the median corresponds to the central
value among the 44 and 55 values computed in the individual centres of groups A
and B, respectively.
Variable
Group A
Median (range)
Group B
Median (range)
Rate of patients aged ≥45 years
Rate of relevant ﬁndings at EGD
Rate of referrals by GP
Rate of inpatients
Rate of urgent examinations
Rate of follow-up EGD
73% (60–85%)
44% (24–89%)
62% (29–88%)
28% (0–58%)
8% (0–28%)
35% (2–66%)
73% (56–88%)a
46% (26–81%)a
56% (11–84%)a
25% (7–55%)a
7% (1–16%)a
35% (10–63%)a
a
No statistically signiﬁcant difference between group A and B, respectively.
Coefﬁcient
Std. err.
(a)
Costant
% referred by GP in centre Ci
% urgent examinations in centre Ci
% relevant disease in centre Ci
Ci academic centre or not
0.68
−0.24
0.70
0.34
0.07
0.067
0.126
0.264
0.143
0.04
(b)
Costant
% referred by GP in centre Ci
% urgent examinations in centre Ci
% relevant disease in centre Ci
0.88
−0.3
0.43
0.19
0.07
0.21
0.28
0.11
t
p
7.023
2.454
2.303
2.299
2.01
13.34
2.02
2.05
2.28
0.0001
0.019
0.027
0.027
0.04
0.0001
0.04
0.03
0.028
Forward stepwise multiple regression selected as independently associated with the aggregated appropriateness rate of the
individual centres in group A the following 4 variables (Table 3):
aggregated percentage of patients referred by their GP, aggregated
rate of urgent examinations, aggregated prevalence of relevant diseases and the academic status of a centre. These variables were
combined in a predictive model, producing the following regression
equation:
Appropriateness rate of centre Ci
= 0.68 − 0.24 (% referred by GP in centre Ci )
ness rate was lower than the 70% adopted threshold in 11 (25%)
centres in group A, and in 11 (20%) in group B (Fig. 1).
Regarding the operative characteristics of the different centres
in both groups, median values and ranges aggregated by centres
are reported in Table 1. Overall, 8 (18%) centres were academic in
group A, and 11 (20%) in the group B.
The correlation between the appropriateness rate of the individual centres and each variable aggregated by centre, expressed
as Pearson’s r, is shown in Table 2 (group A). The correlation with
the aggregated appropriateness rate appeared to be higher for the
percentage of patients referred by GP in the individual centres, the
rate of hospitalised patients, the prevalence of relevant endoscopic
diseases, and the percentage of urgent examinations, whilst it was
lower for the rate of follow-up examinations, the percentage of
patients aged ≥45 years, and the academic proﬁle, all aggregated
by centre.
+ 0.70 (% urgent examinations in centre Ci )
+ 0.34 (% relevant disease in centre Ci )
+ 0.07(Ci academic centre or not)
This model appeared to explain 41% of the variability of the
aggregated appropriateness rates among the different centres (R2 :
0.405, F4:36:6.468, p < 0.001), and the corresponding AUC was 0.76.
The regression model predicted 9 (16%) centres in group B to
have an appropriateness rate lower than the 70% adopted threshold
(Fig. 1). In detail, sensitivity, speciﬁcity, and AUC were 54%, 93%
and 0.72 (Table 4). There was no statistically signiﬁcant difference
between the AUCs (Fig. 2) calculated in the training (group A) and
validating samples (group B). The corresponding predicted values
of appropriateness rate computed for each of the 55 centres have
Table 4
Accuracy values of the predictive model for correctly identifying those centres with an aggregated appropriateness rate lower than the adopted threshold (70%) in the
validating group B. The false negatives represent the centres with an observed (aggregated) appropriateness rate below the threshold, but with a predicted value higher than
the same threshold. PPV: positive predictive value; NPV: negative predictive value; FP: false positives; TP: true positives.
Rate of centres below the
threshold
All positives (FP + TP)
False negatives
Sensitivity (95%CI)
Speciﬁcity (95%CI)
PPV (95%CI)
NPV (95%CI)
AUC–ROC (95%CI)
20%a
16%b
9%c
54% (25–84%)
93% (85–100%)
67% (36–97%)
89% (80–98%)
0.72 (0.58–0.82)
a
b
c
Corresponding to 11 centres.
Corresponding to 9 centres.
Corresponding to 5 centres.
L. Buri et al. / Digestive and Liver Disease 42 (2010) 624–628
Fig. 2. Receiver operating curve (ROC) representing the accuracy of the regression model in identifying those endoscopic centres associated with an aggregated
appropriateness rate below the adopted threshold of 70% for the training (group
A, squares) and the validation (group B, circles) samples. The ROC represents the
relationship between sensitivity and speciﬁcity for the prediction of each of the considered outcomes. No statistically signiﬁcant difference emerged when comparing
the area under the ROC of groups A (0.76) and group B (0.72).
been compared with the original values – that served as reference
criteria to assess the overall accuracy – in Fig. 1.
4. Discussion
Our study identiﬁed several variables – rates of patients referred
by GP and urgent examinations, prevalence of relevant diseases and
academic status – able to predict the aggregated appropriateness
rate of individual endoscopic centres. Of note, most of the selected
variables – i.e. rate of prescriptions by GP or urgent EGDs – are
simple to be assessed and promptly available in most GI units. The
only exception may be represented by the prevalence of relevant
disease. However, the relatively high prevalence of relevant ﬁndings – nearly 50% – allows an accurate estimate with a relatively
small number of patients (i.e. 100–200), also facilitated by a widely
accepted deﬁnition of the relevant endoscopic ﬁndings [5–13].
The inverse association between the aggregated appropriateness rate of a single centre and the overall rate of prescription
by GPs conﬁrms, at a different level, the same association
shown in clinical studies dealing with individual patients [5–13].
Analogously, the direct association between the aggregated appropriateness rate and the rate of urgent examination is well in line
with the proposal of prioritisation of urgent examinations with a
dedicated triage [18]. Regarding the association with the prevalence of relevant ﬁndings, it may be speculated that physicians
practicing in a setting with more prevalent disease are more used
to appropriately select patients for EGD, and a similar assumption
could be put forward for the academic centres.
The importance of this predictive rule is strictly related with
the very high variability of the aggregated appropriateness rates
among the different centres, widely ranging between 41% and 97%
and between 44% and 94% in the two included series, so that it
may be useful to discriminate those centres characterised by a very
poor performance. In our series, for instance, we showed a clearly
inadequate aggregated appropriateness rate – lower than 70% – in
20–25% of the centres.
The importance of predicting a poor appropriateness rate in
individual centres is also strengthened by the possibility to effec-
627
tively improve it with dedicated interventions. A 1-day training
course to all GPs referring to an Italian GI Unit reduced the
pre-interventional inappropriateness rate from 23% to 7%, also
decreasing the waiting lists by 15% [15]. Similarly, when referring
GPs received training with respect to indications during the ﬁrst
2 years of the program, the rate of inappropriate referrals for EGD
was only 3% [16].
When taking into consideration the very low prevalence of
relevant ﬁndings and cancer in inappropriate procedures, and
the unfavourable cost-effectiveness proﬁle of inappropriate EGDs
[5–13], the possibility to target educational interventions only to
those centres that may gain a substantial beneﬁt appears relevant.
Our analysis showed that, assuming as acceptable an aggregated
appropriateness rate ≥70%, only 16–20% of all the endoscopic centres would be predicted to deserve a dedicated program. This would
be enough to substantially reduce the poor-performing centres
from 20–25% to 9%. To focus health interventions only on a relatively small number of centres would appear as a more realistic
and practical approach than a widespread implementation of the
educational programs. Not only the number of endoscopic centres
in any western country is countless, but also each endoscopic centre
has several referring physicians who would need to be addressed by
the educational initiative. It is extremely unlikely that, in a period
of resource and budget constraint, a widespread implementation of
educational programs only to improve the appropriateness rate of
EGD will take place. On the other hand, to limit these programmes
to 16–20% of the centres sounds as a more rational and reasonable
health strategy. According to our analysis, the impact of any educational program would be superior, when addressing GPs in a setting
of low prevalence of relevant ﬁndings.
There are limitations to the present analysis. Although we aggregated all the available variables to predict the appropriateness rate
of individual centres, we failed to explain a substantial part of the
study variability. This may be related with the existence of other
variables that are difﬁcult to be identiﬁed, or with the complex
social and psychological dynamics involving the patient and the
prescribing doctor, that may not be explained by means of a linear
model. For instance, we cannot exclude that other characteristics of
the centres, such as the length of the waiting lists, diverse availability of radiology or breath test for H. pylori infection, and different
costs among the competing strategies, may have some inﬂuence
on appropriateness, suggesting the need for further research in this
ﬁeld. However, such uncertainty appeared to affect more the sensitivity than the speciﬁcity at the adopted thresholds, marginalising
the risk of a waste of resources, when implementing educational
programmes. Secondly, the degree of correlation among the operative variables and the aggregated appropriateness was rather poor.
This mirrors the results from clinical studies in which no single
variable appeared to be strongly related with the appropriateness
of the request. For instance, endoscopic relevant ﬁndings were
detected in a substantial rate of inappropriate or follow-up EGD
[5–12]. Similarly, although the rate of inappropriateness among
GPs’ was signiﬁcantly higher than that among specialists, more
than half of the GP’s prescriptions were still appropriate [5–12].
Thirdly, It could also be argued that some of the factors identiﬁed by the present analysis – such as GP prescription or follow-up
examination – were already shown to be clinical predictors of inappropriateness for single patients [5–12]. However, this is the ﬁrst
study, as far as we know, that showed that some of these variables
are also effective in discriminating among individual centres, when
aggregated. This means that ASGE guidelines, although originally
intended only to be a help in the clinical decision regarding an individual patient, should not be restricted to a clinical use, whilst they
may also be applied as a health policy indicator. Fourthly, despite
no ofﬁcial initiative by SIED was concealed after the publication of
the ﬁrst study, we cannot exclude that the dissemination of such
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L. Buri et al. / Digestive and Liver Disease 42 (2010) 624–628
information may have changed physician attitude to prescribe EGD.
However, the similar level of inappropriateness observed between
the two studies seems to marginalise this possibility [6,19]. Finally,
the suboptimal sensitivity of the predictive rule is likely to misclassify some centres with a high rate of inappropriateness as centres
that do not need further educational initiatives. However, this risk
would appear to be compensated by a substantial reduction of the
implementation cost to only a 16–20% of the centres.
In conclusion, we showed that simple aggregated variables,
related with the different settings in which GI-units operate, may
be able to predict the appropriateness rate of individual endoscopic
centres, and, especially, to identify a small subset of centres with
a high rate of inappropriateness that require further intervention.
This should reduce wasting of health and economic resources when
implementing dedicated educational programmes.
Conﬂict of interest
Enzo Grossi is an employee for BRACCO SPA.
Appendix A. SIED Appropriateness Working Group
Costa G (Ospedale di Tortona – ASL 20, Piemonte); Grassini
M, Niola P (Ospedale “Cardinal Massaia”, Asti); Del Piano M, Carmagnola S (Ospedale Maggiore della Carità, Novara); Allegretti
A, Vallarino E (E.O. Ospedali Galliera, Genova); Leoci C, Popovic
A (Ospedale di Manerbio – A.O. Desenzano G., Brescia); Snider
L, Bellini O (Azienda Ospedaliera “S. Anna”, Como); Manes G
(Azienda Ospedaliera “L. Sacco”, Milano); Lancini GP, Cestari R
(Spedali Civili di Brescia, Brescia); Centenaro R, Boni F (Ospedale
Civile di Melegnano, Milano); Gebbia C, Iollo P (Ospedale “Città di
Sesto S. Giovanni”, Milano); Bertozzo A, Piazzi L (Ospedale Civile,
Bolzano); Bottona E, Pantalena M (Ospedale “Cazzavillan”, Arzignano, Vicenza); Battaglia L, Marino S (Ospedale Piove di Sacco ULSS
14 – Chioggia, Padova); Ederle A, Ntakirutimana E (Ospedale “G.
Fracastoro” – S. Bonifacio – ULSS 20, Verona); Marcon V (Ospedale
Civile Agordo, Belluno); Marin R, Cervellin E (Ospedale Di Dolo,
Venezia); Okolicsanyi L, Monica F (Ospedale Regionale – ULSS 9,
Treviso); Cappiello R, Sablich R (Ospedale S. Maria degli Angeli, Pordenone); Simeth C (Ospedale Cattinara, Trieste); Zilli M (Ospedale
Santa Maria della Misericordia, Udine); Trande P, De Martinis E
(Nuovo Ospedale Civile S. Agostino Estense, Modena); Merighi
A, Boarino V (Azienda Ospedaliera Universitaria Policlinico, Modena); Cortini C, Maltoni S (Ospedale G.B. Morgagni, Forli’); Rossi
A (Casa di Cura “Malatesta – Novello”, Cesena); Frosini G, Longobardi L (Azienda Ospedaliera Universitaria Senese “S. Maria delle
Scotte”, Siena); Macri’ G, Dabizzi E (Azienda Ospedaliera Universitaria “Careggi”, Firenze); Pincione F, Widmayer C (ASL 1 – Ospedale
Civico, Massa); Tatali M (AUSL Marche – Zona Territoriale 2 Urbino,
Pesaro); Ferrini G (Ospedale “F. Renzetti”, Chieti); Neri M, Laterza
F (Ospedale Clinicizzato SS. Annunziata, Chieti); Spadaccini A, Silla
M (Ospedale “San Pio da Pietrelcina”, Vasto, Chieti); Pastorelli A
(Ospedale “Belcolle”, Viterbo); Spada C, Costamagna G. Petruzziello
L (Università Cattolica del Sacro Cuore “Policlinico A. Gemelli”,
Roma); Gabbrielli A, Di Matteo F (Università Campus “Bio Medico”,
Roma); Zullo A (Ospedale “Nuovo Regina Margherita”, Roma); Onorato M (Policlinico Umberto I, Roma); Stroppa I, Andrei F (Policlinico
Tor Vergata, Roma); Grimaldi E, De Filippo FR (Ospedale Civile – A.O.
Caserta, Caserta); Di Giorgio P, Giannattasio F (Ospedale “S.Maria di
Loreto – Mare”, Napoli); Piscopo R (Ospedale Evangelico “Villa Betania”, Napoli); Ingrosso M, Spera G (Università Cattolica del Sacro
Cuore, Campobasso); Fregola G, Quatraro F (Ente Ecclesiastico Osp.
Reg. “F.Miulli”, Bari); De Maio G, Corazza L (Ospedale “Madonna
delle Grazie”, Matera); Giglio A, Rodino’ S (Ospedale “Pugliese –
Ciaccio”, Catanzaro); Iaquinta L. (Ospedale di San Giovanni in Fiore,
Cosenza); Ciliberto E, Cavaliere C (Ospedale S. Giovanni di Dio, Crotone); Fatta MF, Stiriti A., Naim G (Ospedale Civile, Scilla, Reggio
Calabria); Assenza G (Ospedale “E. Muscatello”, Siracusa); Brancato
FP (Ospedale di Alcamo, Trapani); Tortora A, Giacobbe G (Policlinico
Universitario “G. Martino”, Messina); Italy; Cannizzaro R (Centro
di riferimento Oncologico, Aviano, Pordenone); Di Napoli A, Recchia S (Ospedale “San Giovanni Bosco”, Torino); Marino M (Osp.
Civ. “G.Bernabeo”, Ortona, Chieti).
Appendix B. Supplementary data
Supplementary data associated with this article can be found, in
the online version, at doi:10.1016/j.dld.2010.02.012.
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