Journal Pre-proof
Surgical factors associated with symptomatic implant removal after
patella fracture
Jayesh Gupta , Elizabeth A. Harkin , Katherine O’Connor ,
Blessing Enobun , Nathan N. O’Hara , Robert V. O’Toole
PII:
DOI:
Reference:
S0020-1383(22)00214-5
https://doi.org/10.1016/j.injury.2022.03.028
JINJ 10068
To appear in:
Injury
Accepted date:
14 March 2022
Please cite this article as:
Jayesh Gupta ,
Elizabeth A. Harkin ,
Katherine O’Connor ,
Blessing Enobun ,
Nathan N. O’Hara ,
Robert V. O’Toole ,
Surgical
factors
associated with symptomatic implant removal after patella fracture, Injury (2022), doi:
https://doi.org/10.1016/j.injury.2022.03.028
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Highlights

Individuals with k-wires were 4.9 times more likely to have symptomatic removal of
implant.

Implant prominence exceeding 5mm might be associated with increased odds of
symptomatic implant removal in patients with patella fractures.

Patients with BMI ≤25 and age ≤45 were more likely to have symptomatic removal
of implant.
1
Surgical factors associated with symptomatic implant removal after patella fracture
Jayesh Gupta, BS, Elizabeth A. Harkin, MD, Katherine O’Connor, BS, Blessing Enobun, MD,
MPH, Nathan N. O’Hara, PhD, and Robert V. O’Toole, MD
From the R Adams Cowley Shock Trauma Center, Department of Orthopaedics, University of
Maryland School of Medicine, Baltimore, Maryland
Conflict of interest and funding:
N. N. O’Hara receives stock or stock options from Arbutus Medical, Inc. unrelated to this study.
R. V. O’Toole is a paid consultant for Lincotek and Smith & Nephew, receives stock options
from Imagen, and receives royalties from Lincotek, all unrelated to this study.
This study did not receive external funding.
Corresponding author
Robert V. O’Toole, MD
R Adams Cowley Shock Trauma Center
Department of Orthopaedics
University of Maryland School of Medicine
22 South Greene Street, T3R62
Baltimore, Maryland 21201
E-mail: rotoole@som.umaryland.edu
Tel: 410-328-6292, Fax: 410-328-2893
2
ABSTRACT
Objectives: To determine whether certain types of fixation and other factors associated with the
fixation could be identified that predict an increased risk of symptomatic implant removal.
Methods: We conducted a retrospective cohort study at our urban academic level 1 trauma
center. Patients aged ≥18 years who underwent operative fixation for patella fracture were
included. The primary outcome was symptomatic implant removal after operative fixation.
Results: Of the 186 study patients (mean age, 44 [SD 17] years, 65% male), 53 patients (28.5%)
underwent symptomatic implant removal. Modifiable risk factors for symptomatic implant
removal included the use of Kirschner (k)-wires (OR: 4.93; 95% CI, 1.89–14.10; p < 0.001), and
a trend towards significance for implant prominence >5 mm (OR: 2.57; 95% CI, 0.93–7.93; p =
0.07). Symptomatic implant removal was also less likely in patients >45 years of age (OR: 0.14;
95% CI, 0.06–0.34; p < 0.01), of a racial minority (OR: 0.40; 95% CI, 0.17–0.88; p = 0.03), and
a body mass index >25 kg/m2 (OR: 0.39; 95% CI, 0.18–0.84; p = 0.02). The final model
demonstrated excellent prognostic performance, with an AUC of 0.83 (0.76–0.90).
Conclusion: We identified both modifiable and non-modifiable factors associated with
symptomatic implant removal in patients with patella fractures. Surgeons should be aware that
the use of k-wires and any implant prominence exceeding 5 mm might be associated with
increased odds of symptomatic implant removal in patients with patella fractures.
Keywords: symptomatic implant removal, patella fracture, k-wires, predictors
3
Introduction
Symptomatic implant requiring removal after operative fixation is the most common
complication of patella open reduction and internal fixation (ORIF) and has been reported with
rates ranging from 17%–70% [1-5]. To our knowledge, no studies to date have identified the
modifiable surgical risk factors associated with symptomatic implant removal. Previous studies
have primarily focused on patella fracture characterization, operative techniques, functional
outcomes after implant removal, and non-modifiable risk factors for implant removal [1-5].
Identification of modifiable surgical risk factors associated with symptomatic implant removal
might allow surgeons to alter operative technique to avoid the risk of future symptomatic implant
removal, and counsel patients with non-modifiable risk factors that place them at a higher risk
for symptomatic implant removal.
The purpose of this retrospective cohort study was to determine the surgical risk factors
associated with symptomatic implant removal after ORIF of patella fractures. Our hypothesis
was that certain types of fixation and other factors associated with the fixation, could be
identified to predict an increased risk of symptomatic implant removal.
Methods
Study participants
This retrospective cohort study was completed after institutional review board approval.
All patients with OTA/AO types 34A-C patella fractures who were treated with ORIF at an
urban, academic level 1 trauma center from 2008 to 2018 (n = 354) were identified from
electronic medical records (Figure 1) [6]. We excluded patients who underwent suture fixation
with no additional use of implant, had complete patellectomy, or had a fracture in the setting of
previous total knee arthroplasty. Patients younger than 18 years of age and those who did not
4
have a minimum follow-up of at least 6 weeks, as patella fractures are thought to typically
require this amount of time to be healed, were also excluded. Patients were included only if they
had removal of implant caused by symptomatic implant, and not for other reasons such as
revision of fixation for implant failure, nonunion or infection.
Outcome and predictors
The primary outcome for this study was removal of symptomatic implant after ORIF of
patella fractures. Patient predictors were selected based on previous literature and clinical
relevance. We included candidate predictors that had minimal correlation to each other and
minimal susceptibility to measurement error. Symptomatic was defined as having localized pain
over the implant for no other medical reason for removal such as implant failure, nonunion or
infection. Elective removal of symptomatic implant was confirmed by reviewing patient
radiographs, clinic notes, and operative reports. Demographics and injury characteristics of
interest were selected based on potential clinical relevance. Demographic characteristics
included age, sex, race, body mass index (BMI), and injury characteristics included OTA/AO
classification. Most patients had OTA/AO type 34C (86%) patella fractures with subtype 34C3
being the most common (45%).
Patella ORIF was categorized as using one or more of the following fixation
constructions: parallel longitudinal Kirschner (k-wires), figure-of-eight tension band,
circumferential cerclage wiring, minifragment screws, cannulated screws, pins, or plates. In our
unadjusted analysis of various constructs, we analyzed each as a separate event regardless of
whether other constructs were also incorporated (Table 1). The amount of implant protrusion was
quantified by one of the authors by viewing immediate postoperative radiographs and using
measurement tool on picture archiving and communication system (PACS) IMPAX 6.5.1.1008
5
(Agfa-Gevaert, Morstel, Begium) or eUnity v6.10.1.2.15 (Client Outlook Inc., Waterloo,
Ontario, Canada) system. The largest protrusion of implant from patella was measured on either
anteroposterior (AP) or lateral views using standard clinical IMPAX or eUnity system. The total
vertical length of the patella was measured on only the lateral radiograph. These two
measurements were used to create a ratio of the amount of protrusion for each patient based on
patella length to account for patella length variance among patients, and to remove magnification
and other calibration issues with fluoroscopic images.
Statistical analysis
Previous studies suggest that a prognostic logistic regression model requires 5 to 10 study
events per prognostic variable for stable results [7,8]. Based on this heuristic, our sample size
was adequate to support a model containing 5 to 10 factors.
We summarized patient demographics, injury characteristics, and implant characteristics
as means with standard deviation (SD) for normally distributed continuous variables and
medians with interquartile ranges (IQR) for skewed data. We described categorical data as
counts with proportions. Patient characteristics were compared based on primary outcome, and P
values were obtained using Student’s t-tests (normally distributed data), Wilcoxon rank-sum test
(skewed, continuous data) or Pearson’s chi-square tests (categorical), as appropriate.
To build a predictive model, all candidate predictors were considered, and we used
stepwise elimination techniques, based on a minimum Akaike Information Criterion (AIC), to
optimize the overall fit of the model. We report the association between prognostic factors and
the outcome as odds ratios with 95% confidence intervals (CIs). The prognostic performance of
the model was assessed based on discrimination and calibration. Discrimination was assessed
with the area under the curve (AUC), in which a value of 1.0 indicates perfect discrimination and
6
a value of 0.5 signifies the model performs no better than chance. Calibration was evaluated by
plotting the probability of symptomatic implant versus the observed outcome with a 95%
confidence interval. A slope of 1.0 would indicate perfect calibration across the predicted range.
To demonstrate the variation in the probability of symptomatic removal of implant based
on our prognostic factors, we plotted the observed combination of modifiable factors (greatest
amount of implant prominence and the use of k-wires) against the probability of symptomatic
implant removal. The plots were stratified by age and BMI, conditioned on race.
Missing predictor data accounted for less than 4% of any given variable and was imputed
using multiple imputations. All statistical analyses were performed using R Version 4.0.0 (R
Foundation for Statistical Computing, Vienna, Austria) and JMP Pro Version 14 (SAS, Cary,
NC).
Results
Of the 186 patients in the study cohort, the majority were male (n = 121, 65%) and White
(n = 109, 59%). The average age of the sample was 44 years (SD 17) and the median BMI was
27 kg/m2 (IQR: 23–31). Significant differences were observed between the patients with and
without symptomatic implant removal based on age and BMI (p < 0.05) (Table 1). The
difference in comminution between the symptomatic implant removal and control group did not
reach the threshold for statistical significance (77.4% vs. 66.2%, p = 0.19).
In the unadjusted analysis, we observed a difference between groups in k-wire usage
(58.5% vs. 22.6%, p < 0.001), use of a figure-of-eight construct (62.3% vs. 36.8%, p = 0.003),
and greatest prominence measurement (11.1 mm vs. 5.1 mm, p < 0.001). No evidence of
statistically significant differences were shown for the other treatment parameters, including
7
screws (77.4% vs. 87.2%, p = 0.15), plates (3.8% vs .7.5%, p = 0.54), cerclage wires (22.6% vs.
14.3%, p = 0.24), and pins (15.1% vs 9.8%, p = 0.44).
Our prognostic adjusted model identified 5 factors associated with symptomatic implant
removal in patella fracture patients (Table 2, Figure 2). With regards to modifiable surgical risk
factors, individuals with k-wires were 4.9 times more likely to have symptomatic removal of
implant (OR: 4.93; 95% CI, 1.89–14.10; p < 0.001). We observed an association near statistical
significance for any implant prominence >5 mm (OR: 2.57; 95% CI, 0.93–7.93; p = 0.07).
Patients >45 years of age were 86% less likely to have symptomatic removal of implant (OR:
0.14; 95% CI, 0.06–0.34; p < 0.001). Black, Asian, and other individuals were 60% less likely to
have symptomatic removal of implant (OR: 0.40; 95% CI, 0.17–0.88; p = 0.03). Patients with
BMI >25 kg/m2 were 61% less likely to have symptomatic removal of implant (OR: 0.39; 95%
CI, 0.18–0.84; p = 0.02).
The prognostic model had a discriminative ability of AUC 0.83 (95% CI, 0.76–0.90),
suggesting that the model had excellent predictive value. The calibration plot further suggests
that our model performed well consistently across the prognostic range (Figure 3).
Discussion
Previous studies have compared patella fracture construct types to determine failure and
symptomatic implant rates [1,3,4]. However, to our knowledge, this is the first study to provide a
model that can predict symptomatic implant removal for patella fractures treated with ORIF
based on both non-modifiable risk factors and modifiable surgical risk factors. Consistent with
previous studies, we observed that symptomatic implant removal was associated with younger
age, BMI <25 kg/m2, and White race. However, we also observed that there appears to be a very
8
strong signal associated with implant removal and the use of k-wires, and possibly associated
with implant prominence exceeding 5 mm.
Research on modifiable surgical predictors of implant removal after patella fracture is
very limited. The current authors’ hypothesis that use of k-wires with greater implant
prominence is associated with an increased risk of symptomatic implant removal was driven by
clinical experience and previous literature on patella fractures [3,4]. Previous studies on
symptomatic implant removal mostly focused on determining incidence of symptomatic implant
removal, comparing implant removal rates between two specific constructs, considering the
complications of specific constructs, or looking at long term functional outcomes [1-5].
The use of k-wires significantly increased odds of implant removal by nearly 5-fold. Some
surgeons might find this result to be expected; however, k-wire fixation remains a very popular
treatment strategy. This result is important to put before clinicians as alternative treatment
options might exist that provide similar fixation results but without the high risk of symptomatic
implant removal.
For example, Busel et al. [9] performed a retrospective review of 50 patella fractures
treated with cannulated screws with FiberWire® (Arthrex, Naples, FL) tension band and
cerclage construction which showed a high risk of union (96%) and low risk of symptomatic
implant removal (8%). Of note, 48/50 patients had OTA/AO 34C fractures; however, none of the
48 patients had a comminuted fracture pattern, specifically OTA/AO 34C3, thus limiting the
generalizability of the cannulated screws with FiberWire® construct for more complex fracture
patterns. In the Hoshino et al. [4] retrospective cohort study of 448 patients, the authors looked
only at the modified tension band technique using either cannulated screws or k-wires, and found
significantly lower symptomatic implant removal (22.6% vs. 36.8%) in the cannulated screws
9
group with no difference in postoperative infection and failure rate. A large proportion of the
patients in Hoshino et al. [4] had OTA/AO 34C3 type fractures. Lebrun et al. [5] evaluated
multiple fixation constructs and found that none of the patients (n = 10) who underwent tension
band wiring with cannulated screws attributed their knee pain to a symptomatic implant.
Additionally, none of the 10 patients required symptomatic implant removal compared with the
overall symptomatic implant removal rate of 52%. We recognize the technical difficulty in using
the cannulated screws and tension band technique in some comminuted fractures. However, our
study and others [4,5,9] support the consideration of alternative fixation techniques when
possible and if supported by the fracture type, to avoid symptomatic implant removal with no
significant changes in infection and failure rates.
Patients with a BMI less than 25 kg/m2 and younger than 45 years of age also appeared
more likely to have symptomatic implant removal. Patients with lower BMI have less
subcutaneous tissue overlying their implant, perhaps resulting in more skin irritation over the
implant site. Surgeons might be less likely to offer surgery as an option for symptomatic implant
to heavier and older patients because of a perceived increased risk for surgery in this population.
It is also possible that younger and thinner patients might be more active on average than older
and heavier patients, and thus more likely to have irritation caused by the implant. Studies
looking at symptomatic implant removal for other fractures, including olecranon, tibial plateau,
and tibial fractures, have found similar findings. Patients with lower BMI or younger age, or a
combination of both are more likely to have symptomatic implant removal [10-12]. Minority
status was also associated with less implant removal. There are several possible explanations for
this finding including unmeasured confounders, but it is also possible that this is another
example of implicit biases affecting disparities in care for minority patients as has been observed
10
in other areas of medicine as well as in fracture care. Dodwell et al. [13] found an association
between implant removal and younger age, White race, and higher socioeconomic status in
pediatric patients with femoral shaft fractures. While we did not track socioeconomic status, this
study found similar trends of higher rates of implant removal in younger and White patients. In
this study and ours, patients should have similar needs for implant removal, yet minorities
underwent fewer implant removal procedures. This and other studies indicate that disparities in
fracture care is complicated and that further studies are required to understand and address the
disparity identified [13-16].
Although significant in the unadjusted analysis, implant prominence only approached
statistical significance in the reduced prognostic model. Interestingly, all k-wire constructs had a
prominence of greater than 5 mm.
This study has many strengths. This is the first study to describe a model that accurately
predicts which type of patients with patella fractures are likely to receive reoperation for
symptomatic implant removal. This is also the first study that identifies modifiable surgical risk
factors that can be used by surgeons to reduce the likelihood of subsequent surgeries after patella
ORIF. The statistical model was developed using robust prognostic methods and the sample size
is adequate to support our research question.
The limitations of this study should also be considered. This is a retrospective study
limited by the quality of chart review from electronic medical records. Our analysis plan
attempted to account for some of the potential sources of bias and other factors typical of
retrospective reviews. Although efforts were made to ensure consistent measurements across
cases and controls, reviewers were not blinded to outcomes, possibly leading to bias. The
retrospective nature of this study does not follow patients after symptomatic implant removal to
11
determine whether symptoms improved, but determining the efficacy of implant removal is well
beyond the scope of the study. Most importantly this is not a prospective clinical trial, so our
findings only show associations and not causation.
Overall, this study provides insight on identifying which patients are likely to have
implant removal. Surgeons should counsel young patients or those with a BMI less than 25
kg/m2 on their increased risk for subsequent reoperation for symptomatic implant removal.
Surgeons should consider that the use of k-wires for patella fracture fixation might be associated
with an increased risk of implant removal. Reducing unnecessary procedures not only benefits
patients but also supports cost effective patient care.
12
References
[1]
Kumar G, Mereddy PK, Hakkalamani S, Donnachie NJ. Implant removal following
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[2]
Greenberg A, Kadar A, Drexler M, Sharfman ZT, Chechik O, Steinberg EL, et al.
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[3]
Hambright DS, Walley KC, Hall A, Appleton PT, Rodriguez EK. Revisiting tension band
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[4]
Hoshino CM, Tran W, Tiberi JV, Black MH, Li BH, Gold SM, et al. Complications
following tension-band fixation of patellar fractures with cannulated screws compared
with kirschner wires. J Bone Jt Surg - Ser A. 2013;95:653-9.
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[5]
Lebrun CT, Langford JR, Sagi HC. Functional outcomes after operatively treated patella
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https://doi.org/10.1097/BOT.0b013e318228c1a1
[6]
Meinberg EG, Agel J, Roberts CS, Karam MD, Kellam JF. Fracture and dislocation
classification compendium-2018. J Orthop Trauma. 2018;32 Suppl 1:S1-S170.
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[7]
Vittinghoff E, McCulloch CE. Relaxing the rule of ten events per variable in logistic and
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[8]
Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the
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[9]
Busel G, Barrick B, Auston D, Achor K, Watson D, Maxson B, et al. Patella fractures
treated with cannulated lag screws and fiberwire® have a high union rate and low rate of
implant removal. Injury. 2020;51:473-7. https://doi.org/10.1016/j.injury.2019.10.002
[10] Mascarenhas D, Connelly D, O’Hara NN, Gage MJ, Coale M, Manson TT, et al.
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fractures with intramedullary nails. Injury. 2018;49:2284-9.
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[11] Bugarinovic G, McFarlane KH, Benavent KA, Janssen SJ, Blazar PE, Earp BE. Risk
factors for hardware-related complications after olecranon fracture fixation. Orthopedics.
2020;43:141-6. https://doi.org/10.3928/01477447-20200314-03
[12] Stewart CC, O’Hara NN, Mascarenhas D, Manson TT, Reahl GB, Connelly D, et al.
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[13] Dodwell E, Wright J, Widmann R, Edobor-Osula F, Pan TJ, Lyman S. Socioeconomic
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[14] Sprague S, Heels-Ansdell D, Bzovsky S, Zdero R, Bhandari M, Swiontkowski M, et al.
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15
Figure Legends
Figure 1: CONSORT diagram. Abbreviations: ORIF, open reduction and internal fixation.
Figure 2. Probability of symptomatic removal of implant conditioned on age, body mass index,
greatest amount of implant prominence, and the use of k-wires.
Figure 3. Calibration plot of predicted probability of symptomatic removal of implant versus
observed probability of symptomatic removal of implant.
Declaration of interest
N. N. O’Hara receives stock or stock options from Arbutus Medical, Inc. unrelated to this study.
R. V. O’Toole is a paid consultant for Lincotek and Smith & Nephew, receives stock options
from Imagen, and receives royalties from Lincotek, all unrelated to this study.
This study did not receive external funding.
Table 1
Patient characteristics
Symptomatic Removal of
Control
p-
(n = 133)
value
37.8 (15.5)
45.9 (17.4)
0.003
23 (43.4)
42 (31.6)
0.18
White
35 (66.0)
74 (55.6)
0.14
Black
10 (18.9)
47 (35.3)
Implant
(n = 53)
Patient and injury parameters
Age, years, mean (SD)
Female, n (%)
Race, n (%)
16
Asian
4 (7.5)
7 (5.3)
Other
4 (7.5)
5 (3.8)
BMI, kg/m2, median [IQR]
27.3 [24.3,
24.3 [23.1, 29.4]
0.02
31.3]
Comminution, n (%)
41 (77.4)
88 (66.2)
0.19
Treatment parameters
K-wires, n (%)
<0.00
31 (58.5)
30 (22.6)
1
Number of k-wires, median [IQR]
<0.00
2.0 [0.0, 2.0]
0.0 [0.0, 0.0]
1
Figure 8, n (%)
Number of Figure 8 knots, median [IQR]
Screws, n (%)
Number of screws, median [IQR]
Plates, n (%)
Number of plates, median [IQR]
Cerclage wires, n (%)
Number of cerclage knots, median [IQR]
Pins, n (%)
Number of pins, median [IQR]
33 (62.3)
49 (36.8)
0.003
2.0 [0.0, 5.0]
0.0 [0.0, 3.0]
0.006
41 (77.4)
116 (87.2)
0.15
2.0 [2.0, 4.0]
2.0 [2.0, 3.0]
0.12
2 (3.8)
10 (7.5)
0.54
0.0 [0.0, 0.0]
0.0 [0.0, 0.0]
0.38
12 (22.6)
19 (14.3)
0.24
0.0 [0.0, 0.0]
0.0 [0.0, 0.0]
0.20
8 (15.1)
13 (9.8)
0.44
0.0 [0.0, 0.0]
0.0 [0.0, 0.0]
0.315
Greatest prominence measurement, mm,
<0.00
11.1 [6.0, 16.4]
5.1 [3.6, 8.5]
median [IQR]
Greatest prominence >5 mm, n (%)
1
44 (83.0)
66 (49.6)
<0.00
17
1
SD, standard deviation; BMI, body mass index; IQR, interquartile range.
Table 2
Factors associated with symptomatic removal of implants
Symptomatic
Removal of
Control,
Implant,
n (%)
Factor
OR (95% CI)
p-value
n (%)
Over 45 years of age
16 (30.2)
78 (58.6)
0.14 (0.06–0.34)
<0.001
Racial minority
18 (34.0)
59 (44.4)
0.40 (0.17–0.88)
0.03
Body mass index >25 kg/m2
23 (43.4)
91 (68.4)
0.39 (0.18–0.84)
0.02
K-wires
31 (58.5)
30 (22.6)
4.93 (1.89– 14.10)
<0.001
Greatest prominence >5 mm
44 (83.0)
66 (49.6)
2.57 (0.93–7.93)
0.07
OR, odds ratio; CI, confidence interval.
18
19
20
21