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JDR Clinical Research Supplement
vol. XX • issue X • suppl no. X
DOI: 10.1177/0022034514563077. 1Department of Periodontology, Institute of Odontology, The Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden;
*corresponding author, jan.derks@odontologi.gu.se
A supplemental appendix to this article is published electronically only at http://jdr.sagepub.com/supplemental.
© International & American Associations for Dental Research
J. Derks1*, J. Håkansson1, J.L. Wennström1, C. Tomasi1, M. Larsson1, and T. Berglundh1
Effectiveness of Implant Therapy
Analyzed in a Swedish Population:
Early and Late Implant Loss
CLINICAL INVESTIGATIONS
Abstract:
Treatment outcomes in
implant dentistry have been mainly
assessed as implant survival rates in
small, selected patient groups of spe-
cialist or university clinical settings.
This study reports on loss of dental
implants assessed in a large and ran-
domly selected patient sample. The
results were aimed at representing
evaluation of effectiveness of implant
dentistry. Using the national data reg-
ister of the Swedish Social Insurance
Agency, 4,716 patients were randomly
selected. All had been provided with
implant-supported restorative therapy
in 2003. Patient files of 2,765 patients
(11,311 implants) were collected from
more than 800 clinicians. Information
on patients, treatment procedures,
and outcomes related to the implant-
supported restorative therapy was
extracted from the files. In total, 596 of
the 2,765 subjects, provided with 2,367
implants, attended a clinical exami-
nation 9 y after therapy. Implant loss
that occurred prior to connection of the
supraconstruction was scored as an
early implant loss, while later occur-
ring loss was considered late implant
loss. Early implant loss occurred in
4.4% of patients (1.4% of implants),
while 4.2% of the patients who were
examined 9 y after therapy pre-
sented with late implant loss (2.0% of
implants). Overall, 7.6% of the patients
had lost at least 1 implant. Multilevel
analysis revealed higher odds ratios for
early implant loss among smokers and
patients with an initial diagnosis of
periodontitis. Implants shorter than
10 mm and representing certain
brands also showed higher odds
ratios for early implant loss. Implant
brand also influenced late implant
loss. Implant loss is not an uncom-
mon event, and patient and implant
characteristics influence outcomes
(ClinicalTrials.gov NCT01825772).
KEY WORDS
: endosseous dental
implantation, implant-supported den-
tal prosthesis, adverse effects, multivar-
iate analysis, survival rate, treatment
outcome.
Introduction
Restorative therapy using dental
implants is considered a safe and
predictable treatment procedure in
edentulous and partially dentate patients
(Jung et al. 2012; Pjetursson et al. 2012).
The main outcome variable reported
in longitudinal studies is the rate of
implant survival, and data are based on
the proportion and number of implants,
while information on proportions of
affected patients is rare (Berglundh
et al. 2002). The documentation is also
predominantly based on assessments
made in small, selected patient groups
(i.e., so-called convenience samples)
(Tomasi and Derks 2012), and treatment
was in most cases performed by
clinicians in specialist or university
clinical settings. Thus, treatment
outcomes were mainly assessed
in efficacy evaluations rather than
appraisals of effectiveness (Berglundh
and Giannobile 2013). It is important
to adapt to recommendations on
improvement of reporting on treatment
outcomes (Tonetti and Palmer 2012)
and to address the need for randomly
selected and appropriately sized patient
groups treated by different categories of
clinicians.
The adult population in Sweden
is provided with federal financial
support for dental care, including
implant-supported restorative therapy,
which is administered by the Swedish
Social Insurance Agency (SSIA,
Försäkringskassan). In 2003, the federal
subsidies increased for patients ≥65 y of
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age, resulting in a dominance of implant-
supported restorative therapy among
treatment procedures in this group of
patients.
In this study, we report on loss of
dental implants assessed in a large
and randomly selected patient sample.
The national data register of the SSIA
provided unique access to a group of
patients who had received implant-
supported restorative therapy. The results
were aimed at representing evaluation of
the effectiveness of implant dentistry.
Materials and Methods
The study protocol was approved
by the regional Ethical Committee,
Gothenburg, Sweden (Dnr 290-10)
and registered at ClinicalTrials.gov
(NCT01825772). Strengthening the
Reporting of Observational Studies in
Epidemiology (STROBE) guidelines
were followed. The study consisted of
an analysis of patient files and a clinical
evaluation about 9 y after completion of
implant-supported restorative therapy.
Study Sample
The patient material used in the present
study has been previously described
(Derks et al. 2014). Briefly, 4,716 subjects
in 2 age groups (45–54 y and 65–74 y in
2003) provided with implant-supported
restorative therapy in 2003 were randomly
selected from the national data register of
the SSIA. All subjects were contacted by
letter and asked for consent to access their
patient files. Name and social security
number, unique to each individual, were
used to identify all subjects.
Analysis of Patient Files
Documentation related to the implant-
supported restorative therapy was
requested from the respective dental
clinicians of all consenting patients.
All patient files were copied and
subsequently returned. Reported
information regarding patients, treatment
procedures, and treatment outcomes
was extracted from the patient files and
entered into a database by 2 examiners
(J.D. and M.L.). Patient data included
information on history of diabetes,
cardiovascular diseases, and periodontitis
at the time of implant therapy. Patients
were categorized as smokers if reported
to be smoking at the time of implant
therapy. All other patients, including
former smokers, were categorized as
nonsmokers. In addition, the frequency
of recall visits following the completion
of the implant-supported restorative
therapy was assessed and categorized as
“regular” if the patient had attended on
an annual basis.
Clinicians involved in the treatment
were categorized with regard to private
or public dental clinical setting and
general practitioner or registered
specialist by the Swedish National
Board of Health and Welfare at the time
of treatment. For surgical treatment,
specialists in oral/maxillofacial surgery
and periodontics were considered, while
prosthetic treatment involved specialists
in prosthodontics, stomatognathic
physiology, and periodontics.
Implants were categorized according
to brand, as defined by implant system
and provider. Implants were also grouped
regarding length (<10 mm and ≥10 mm),
diameter (<4 mm and ≥4 mm), and
installation protocols (1-stage and 2-stage).
Bone augmentation procedures, including
ridge and sinus augmentation, and the use
of prophylactic antibiotics were recorded.
Implants were categorized according
to jaw and anterior/posterior position.
Anterior was defined as the region
corresponding to tooth position canine
to canine. Further categorization included
type of prosthetic retention, design
of suprastructure, type of connection,
and prosthetic loading protocols.
Loading was categorized as “early” if the
supraconstruction was connected <4 wk
after implant placement.
Clinical Evaluation
In total, 900 subjects, stratified for age,
were randomly selected from the patient-
file database and subsequently invited to a
free-of-cost examination at a conveniently
located dental clinic in Sweden about
9 y after therapy. The examinations were
carried out by specialists in periodontics,
predominantly by 2 investigators (J.D.
and J.H.), and included clinical and
radiographic assessments of the relevant
implant regions.
Assessment of Implant Loss
If implant loss had occurred prior to
connection of the supraconstruction, it
was scored as an early implant loss. If
the loss had occurred afterward, it was
considered a late implant loss. Early
implant loss was assessed in patient files
by 2 examiners. Double assessments
revealed an inter- and intraexaminer
agreement of 1.0 (Cohen’s unweighted
k). Late implant loss was recorded at the
clinical examination.
Consequences of implant loss
were noted as reported in patient
files. Changes in treatment planning,
placement of new implants, and
noncontinuation of treatment were
recorded for early implant loss. For late
implant loss, placement of new implants,
prosthodontic therapy, and partial or total
loss of reconstructions were scored.
Data Analysis
Recorded data were expressed in
mean values and frequency distributions.
Frequencies of early and late implant
loss were assessed on the implant and
patient level (SPSS 21.0; SPSS, Inc.,
Chicago, IL, USA). To identify factors
affecting the probability of implant loss,
we used multiple logistic multilevel
models (MLwiN 2.28; Center of Multilevel
Modelling, University of Bristol, Bristol,
UK). The hierarchical analyses included
the patient at the higher level and
the implant at the lower level. The
logit function was applied to link the
linear model with the probability of
the binary event. Two models, one for
“early loss” and one for “late loss,” were
built. The independent factors entered
into the models were retrieved from
the patient-file database. For the factor
“implant brand,” 4 groups were formed:
1) Straumann group implants (Basel,
Switzerland), 2) Nobel Biocare group
implants (Zurich, Switzerland), 3) Astra
Tech group implants (Mölndal, Sweden),
and 4) other. Brands representing less
than 5% of all implants were collapsed
into one group to facilitate the statistical
analysis.
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Models were built with the intercept
as a random term. All variables were
tested by the Wald test in a bivariate
analysis. Significant factors were entered
into a multiple model (fixed effect).
Nonsignificant factors were removed
backward until a final model was created
containing only significant factors (P <
0.05). The intercept for each parameter
was transformed into an odds ratio (OR),
including a 95% confidence interval.
Parameters were estimated using the
Markov chain Monte Carlo method with
50,000 simulations.
Results
Patient Sample
In total, 3,107 subjects gave their
consent for access to patient files, of
which the files of 2,765 patients were
retrieved from more than 800 clinicians.
The patient files covered a mean ± SD
function time of 5.4 ± 2.2 y following
implant therapy. Of 900 invited subjects,
596 attended the clinical examination
(Fig.). Reasons for nonattendance were
lack of interest (187 subjects), general
health (68), unable to contact (30), and
deceased (19). For the patients attending
the clinical examination, a mean ± SD
of 8.9 ± 0.8 y had passed since implant
placement. Attending and nonattending
subjects did not differ significantly in
terms of age, sex, systemic disease, and
therapy-related parameters (e.g., average
number of implants per patient).
Table 1 describes patient-related data in
terms of sex, general and dental health
status, and implant-supported restorative
therapy. Table 2 describes implant-related
data. Three brands (termed Astra Tech,
Nobel Biocare, and Straumann group of
implants) represented 90% of all implants.
Among Astra Tech group implants,
99.2% had a TiOblast surface; 98.7%
of all Nobel Biocare group implants
had a TiUnite surface; and 99.9% of all
Straumann group implants had an SLA
surface. Within the remaining 10% of
“other” implants, the predominant brands
were Biomet 3i (3.3% of all implants;
Palm Beach Gardens, FL, USA), CrescoTi
(1.7%; Kristianstad, Sweden), XiVE (1.3%;
Mannheim, Germany), Frialit (1.3%;
Mannheim, Germany), and Lifecore
(1.2%; Burlington, MA, USA).
Implant Loss
The analysis of patient files (n =
2,765) revealed that 121 subjects (4.4%)
experienced early implant loss with a
total of 154 implants (1.4%) lost (Table 3).
Within this group, 102 patients lost 1, 10
lost 2, 4 lost 3, and 5 lost 4 implants. Of
the 121 subjects affected by early implant
loss, 76 (63%) underwent new implant
placement procedures. Treatment planning
had to be adjusted for 21 (17%). For 2
patients (2%), therapy was not continued
after the early loss had occurred, and for 33
patients (27%), treatment was completed
without renewed implant placement or
changes in treatment planning.
Among the 596 patients examined
clinically, 45 (7.6%) experienced implant
loss, irrespective if it had occurred early
or late. A total of 72 implants (3.0%) were
lost. Twenty-five (4.3%) of the 596 patients
experienced late implant loss, representing
46 implants (2.0%). Within this group,
13 patients lost 1, 8 patients lost 2, and 1
patient lost 3 implants. One patient lost 4
and 2 patients lost 5 implants each. Of the
25 patients affected by late implant loss, 6
(24%) underwent new implant placement
procedures. For 8 patients (32%), new
supraconstructions were produced. For 4
patients (16%), supraconstructions were
modified, while for 5 subjects (20%), the
whole supraconstruction was lost and not
replaced. For 8 cases (32%), late implant
loss had no impact on the prosthetic
rehabilitation.
Early and late implant loss according
to implant brands are described in the
Appendix Table.
Table 4 shows the results of the
multilevel analysis for the event
“early loss.” Of the significant factors
identified in the bivariate analyses, 4
factors showed significantly higher
odds ratios (ORs) for early loss in the
final model: subjects with an initial
diagnosis of periodontitis (OR, 3.3),
smokers (OR, 2.3), implants <10 mm
(OR, 3.8), and implant brand. Compared
with Straumann group implants, Nobel
Biocare group implants (OR, 1.9), Astra
Tech group implants (OR, 2.1), and the
category of “other” implants (OR, 7.8)
presented with significantly higher odds
ratios for early loss.
Data register (SSIA) of patients (age 65-74)
treated with implants in 2003
(n>23000)
Questionnaire sent
(n=3000)
Random selection
Data register (SSIA) of patients (age 45-54)
treated with implants in 2003
(n=1716)
Questionnaire sent
(n=1716)
Questionnaire returned
(n=3827)
Consent: Access to patient files
(n=3107)
Patient files collected
(n=2765)
Invited to clinical examination
(n=900)
Random selection
Attended clinical examination
(n=596)
Assessment:
Early implant loss
Assessment:
Late implant loss
Figure.
Patient enrollment (n = number of patients)
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Results of the multilevel analysis for “late
loss” are also described in Table 4. The
final model showed associations between
late loss and implant brand. Straumann
group implants were used as reference
(OR, 1.0). Odds ratios for Nobel Biocare
group implants and Astra Tech group
implants were 6.1 and 5.2, respectively. For
“other” implants (OR, 58.2), a significantly
higher odds ratio was observed.
Discussion
In the present study, early and late
occurring loss of dental implants were
evaluated in a large and randomly selected
patient sample. It was demonstrated that
early implant loss occurred in 4.4% of
patients, while 4.2% of the patients who
were examined around 9 y after therapy
presented with late implant loss. Taken
together, 7.6% of the patients had lost
at least 1 implant. In addition, multilevel
analysis revealed higher odds ratios
for early implant loss among smokers
and patients with an initial diagnosis of
periodontitis. Implants shorter than 10
mm and representing certain brands also
showed higher odds ratios for early implant
loss. Implant brand also influenced late
implant loss. It is suggested that implant
loss is not an uncommon event and that
patient and implant characteristics influence
outcomes.
The present study reports on a patient
material, which in several aspects is
different from that presented in most clinical
studies on dental implant therapy. The
national data register of the SSIA covers
almost all individuals >20 y of age receiving
dental care in public or private setting
in Sweden. As the register also included
patients exposed to restorative therapy
using dental implants, the patient groups
of the present study represent a random
sample of the selected age categories of
the population. In addition, the implant-
supported restorative therapy in the present
study was carried out by a large number
of clinicians representing different clinical
settings and training in the field. Thus,
in contrast to previous publications on
so-called convenience patient samples,
the present study sample constitutes a
true cohort. The evaluation also applies
to everyday clinical practice and provides
data on effectiveness rather than efficacy
(Berglundh and Giannobile 2013).
Patients from 2 age groups were
randomly selected for the present
study. As stated above, in 2003, the
federal subsidies for implant-supported
restorative therapy increased for patients
≥65 y of age. A reference group of
younger individuals (45–54 y) was also
included in the study (Derks et al. 2014).
Table 1.
Patient-Related Information Retrieved from Patient Files
Patient File
Sample (n = 2,765)
Clinical Examination
Sample (n = 596)
Female sex 54 55
Smoker 30 29
Diabetes 8 5
Myocardial infarction 2 2
Stroke 2 2
Periodontitis diagnosis 24 22
Prophylactic antibiotics at implant placement 86 84
Implants per patient, mean ± SD 4.1 ± 2.9 4.0 ± 2.8
Surgery
General practitioner 22 21
Specialist 78 79
Prosthetics
General practitioner 76 73
Specialist 24 27
Maintenance
General practitioner 82 80
Specialist 14 17
None 4 3
Frequency of recall visits
Regular (annual) 81 82
Irregular 19 18
All data are given in percentages unless otherwise noted.
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Table 2.
Implant-Related Information Retrieved from Patient Files
Patient File
Sample (n = 11,311
Implants)
Clinical Examination
Sample (n = 2,367
Implants)
Implant brand
Astra Tech group implants (Astra Tech Implant System) 19 19
Nobel Biocare group implants (Brånemark System, Replace Select) 41 40
Straumann group implants (Straumann Dental Implant System) 30 32
Other 10 9
Implant length
<10 mm 9 9
≥10 mm 91 91
Implant diameter
<4 mm 59 56
≥4 mm 41 44
Jaw
Maxilla 58 60
Mandible 42 40
Position
Anterior (canine-canine) 45 44
Posterior 55 56
Implant placement
Immediate (same session as tooth extraction) 4 4
Healed ridge 96 96
Installation procedure
1-stage 49 49
2-stage 51 51
Bone augmentation procedure 7 8
Loading
Early/direct (<4 wk from implant placement) 7 5
Late (≥4 wk) 93 95
Retention of supraconstruction
Screw retained 83 81
Cemented 16 19
Removable 1 0
Design of supraconstruction
Single 10 12
Multiunit without cantilever 30 30
Multiunit with cantilever 60 58
Connection
Single 10 12
Implant-implant 89 87
Implant-tooth 1 1
All data are given in percentages.
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The findings on early implant loss
presented in the current study disclosed
that the proportion of affected patients
was larger than that of early lost implants
(4.2% vs. 1.4%). While similar results
were presented in a multicenter study on
implant loss performed in private clinics
(Esposito et al. 2010), results from a study
conducted in a university clinic revealed
that early loss occurred in 0.7% of
implants and 0.8% of patients (Bornstein
et al. 2008).
The approach of a retrospective
evaluation of early implant loss carried
out in the present study was also applied
by Alsaadi et al. (2007). They examined
2,004 patient files from a university clinic
and reported that 258 implants (3.6%)
in 178 patients (8.9%) were lost prior to
or at abutment connection. Most cases
(91%) had lost 1 or 2 implants. While the
Table 3.
Implant Loss
Early Loss (2,765 Patients,
11,311 Implants)
Late Loss (596 Patients, 2,367
Implants, Mean Function
Time: 8.9 y)
Total Loss (596 Patients,
2,367 Implants, Mean
Function Time: 8.9 y)
Patients affected 121 (4.4%)
10 patients unaccounted for
25 (4.2%) 45 (7.6%)a
Implants lost 154 (1.4%)
50 implants unaccounted for
46 (2.0%)b
2 implants unaccounted for
72 (3.0%)
2 implants unaccounted for
aEarly and/or late loss.
bEarly lost implants not considered for calculation of percentage.
Table 4.
Factors Associated with Early and Late Implant Loss: Multiple Multilevel Analysis
Early Loss (11,311 Implants,
2,765 Subjects)
Early Loss (% of
Implants) Odds Ratio
95% Confidence
Interval P Value
Periodontitis diagnosis
No 1.0 1
Yes 2.3 3.29 1.69–6.42 0.001
Smoking
Nonsmoker 0.9 1
Smoker 2.2 2.32 1.03–5.24 0.042
Implant length
≥ 10 mm 1.2 1
<10 mm 3.0 3.78 2.15–6.64 <0.001
Implant brand
A 0.7 1
B 1.3 1.94 1.02–3.69 0.043
C 1.5 2.10 1.03–4.30 0.042
D 3.5 7.79 3.69–16.47 <0.001
Late Loss after 8.9 y (2,367
Implants, 596 Subjects)
Late Loss (% of
Implants) Odds Ratio
95% Confidence
Interval P Value
Implant brand
A 0.5 1
B 2.4 6.13 0.47–80.51 0.139
C 2.5 5.23 0.28–99.38 0.244
D 3.8 58.15 2.35–1435.92 0.012
Implant brands: A, Straumann implant group; B, Nobel Biocare implant group; C, Astra Tech implant group; D, other.
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data presented by Alsaadi et al. (2007)
indicated larger proportions of early lost
implants and affected patients than in
the present study, a similar percentage
of patients presenting with 1 or 2 lost
implants was found in the 2 studies.
The findings on higher odds ratios for
smokers and implants with length
<10 mm for early implant loss reported
by Alsaadi et al. (2007) are consistent
with results in the present study.
The multilevel analysis of implant-
related factors on early implant loss
in the present study showed that, in
addition to implant length, implant
brand influenced the outcome. Thus,
Straumann group implants presented
with a lower odds ratio for early implant
loss than other implant brands. As
the Straumann group implants in the
present material had a 1-piece design
that included both the intraosseous and
transmucosal portions, the installation
procedure for this implant type called
for a nonsubmerged or so-called 1-stage
technique. Other categories of implants,
however, comprised 2 parts and were,
hence, installed using either a 1- or a
2-stage (initially submerged) technique.
The analysis of early implant loss in
the present study failed to demonstrate
significant differences between the 2
installation procedures. Reasons for
the observed differences between
implant brands with regard to early
implant loss are not detectable from
the current material. Factors related to
implant design in combination with
site preparation may be considered, as
early implant loss indicates a failure in
integration of the implant in bone tissue
following implant installation.
The results from the analysis of patient-
related factors in the present study
revealed that an initial diagnosis of
periodontitis had a higher odds ratio for
early implant loss. While periodontitis
is one of the most common diseases in
humans and one of the main reasons
for tooth loss, the susceptibility to the
disease itself may not explain the higher
odds ratio. The consequences of the
progression of the disease, however,
with advanced attachment and bone
loss and, eventually, tooth loss result
in an edentulous ridge with reduced
dimensions. Reduced ridge dimensions
may also reflect the use of implants with
length <10 mm. In this context, it should
be realized that differences in bone
quality of the alveolar process between
patients with and without periodontitis
may not exist as studies on human bone
samples failed to demonstrate differences
between patient groups (Cecchinato
et al. 2012; Lindhe et al. 2012).
The second part of the present
investigation was based on findings
made in a clinical examination
performed on 596 of 900 invited
patients at 9 y after therapy. The rate
of attendance may be considered
high, taking into account the age
of the 2 patient groups (54–63 and
74–83 y, respectively, at the time of
clinical examination) and the varying
accessibility for patients to dental
clinics in this nationwide project. The
examination revealed that 2.0% of
implants in 4.2% of the patients were
lost during the 9 y after prosthesis
connection. These findings indicate
better outcomes in comparison with data
reported in long-term studies in implant
dentistry. Results from a systematic
review revealed a mean total implant
loss rate of 5.1% after 5 y and 6.9% after
10 y (Pjetursson et al. 2012). Most of
the 32 studies included in the review
represented 5-y outcomes, with early
and late implant loss occurring in 2.4%
and 2.7%, respectively. In addition, the
patients in the review by Pjetursson
et al. (2012) represented in most cases
specialist or university clinical settings.
The evaluations made in the present
study on late implant loss did not
disclose any differences in outcomes
between clinical settings (i.e., public vs.
private practice or general practitioner
vs. registered specialist). Furthermore, no
associations between late implant loss
and patients with an initial diagnosis of
periodontitis or presenting with irregular
recall visits were found. This observation
is not in agreement with data reported in
a 10-y study on implant loss in different
categories of patients (Roccuzzo
et al. 2010). In addition, the finding that
smoking was not associated with late
implant loss is not in agreement with
data presented in systematic reviews
(Heitz-Mayfield and Huynh-Ba 2007;
Strietzel et al. 2007).
The multilevel analysis in the present
study disclosed that implant brand also
influenced late implant loss. As was the
case for differences between implant
brands regarding early implant loss, the
data from the present material did not
provide explanations for the differences
in late implant loss. In addition, there
may be several reasons for late implant
loss, such as progressive marginal bone
loss, damages on the interface between
the implant and the bone tissue, or
harm to the implant, including implant
fracture.
The present study also examined the
consequences of early and late occurring
implant loss. The findings indicate that
for the individual patient, implant loss
has a significant effect on the overall
treatment outcome of implant-supported
restorative therapy.
In summary, the present study reported
on outcomes in implant dentistry
assessed in a large and randomly
selected patient sample representing
effectiveness of the treatment
procedures. Almost 8% of patients had
lost ≥1 implants, and several patient- and
implant-related factors influencing early
and late occurring loss were detected.
Author Contributions
J. Derks, contributed to data analysis,
drafted the manuscript; J. Håkansson,
contributed to conception and design,
critically revised the manuscript;
J.L. Wennström and T. Berglundh,
contributed to conception, design, and
data analysis, drafted the manuscript;
C. Tomasi and M. Larsson, contributed
to data analysis, critically revised the
manuscript. All authors gave final
approval and agree to be accountable for
all aspects of the work.
Acknowledgments
The authors greatly appreciate Dr. Max
Petzold for assistance in the statistical
analysis. The study was supported
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by grants from the Swedish Social
Insurance Agency (Försäkringskassan);
the Swedish Research Council (VR:
K2013-52X-22197-01-3); TUA research
Gothenburg, Sweden; and the Swedish
Dental Society. Dr. Berglundh reports
grants and personal fees from Dentsply
Implants IH, outside the submitted
work. Dr. Derks, Dr. Tomasi, and Dr.
Wennström report personal fees from
Dentsply Implants IH, outside the
submitted work. The authors declare no
potential conflicts of interest with respect
to the authorship and/or publication of
this article.
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