Patellar Morphology in Recurrent Lateral Patellofemoral Instability: Associations With Risk Factors and Postoperative Outcomes

Abstract

Background:

Patellar morphology, most commonly described by the Wiberg classification, is a potential risk factor for recurrent lateral patellofemoral instability. However, the Wiberg classification has not been widely used in this population, and therefore its clinical utility remains unclear.

Purpose:

(1) To determine the incidence of Wiberg types and to explore relationships between the Wiberg classification and risk factors in a population of patients with recurrent lateral patellofemoral instability. (2) To evaluate the relationship between the Wiberg classification and disease-specific quality of life outcomes after primary medial patellofemoral ligament (MPFL) reconstruction.

Study Design:

Cohort study; Level of evidence, 3.

Methods:

A population of 447 patients who underwent MPFL reconstruction for recurrent instability was enrolled. Preoperative demographic and pathoanatomic data were collected prospectively. Intrarater reliability of the Wiberg classification was assessed using a weighted kappa (κw). Pearson and Spearman correlation coefficients, as well as ordinal logistic regression, were used to explore relationships between the Wiberg classification and risk factors for patellofemoral instability. A 1-way analysis of variance assessed preoperative and 24-month postoperative Banff Patellofemoral Instability Instrument (BPII) scores in relation to the Wiberg classification.

Results:

The study enrolled 447 patients, including 539 knees (21.5% male knees; 78.5% female knees), with a mean age at first dislocation of 14.9 years (SD, 6.1). The distribution of patellae by the Wiberg classification was 30.6% type 1 (n = 165), 47.1% type 2 (n = 254), and 22.3% type 3 (n = 120). κw intrarater agreement for the Wiberg classification was substantial (κw = 0.75). An ordinal logistic regression demonstrated a statistically significant −2 log likelihood model (P < .001) that included high-grade trochlear dysplasia, age at first dislocation, and WARPS/STAID (WARPS [weak, atraumatic, risky anatomy, pain, subluxation] / STAID [strong, traumatic, anatomy normal, instability, dislocation]) score as predictive of Wiberg type. No significant differences existed between Wiberg types for pre- (F = 4.167; P = .02) or postoperative BPII scores (F = 0.121; P = .89).

Conclusion:

In this large cohort of patients with recurrent patellofemoral instability, a statistically significant ordinal logistic regression model, including the combination of trochlear dysplasia, WARPS/STAID score, and age at time of first dislocation, predicted Wiberg classification. No relationship was determined between the Wiberg classification and pre- or postoperative BPII 2.0 quality of life scores.

Keywords

patellofemoral instability patellar stabilization Wiberg classification trochlear dysplasia patellar morphology

Lateral patellofemoral instability (LPI), a debilitating knee condition that primarily affects young, active individuals, is characterized by patellar dislocation and is associated with pain, limited function, recurrent instability episodes, and possible long-term osteoarthritis.^31,51,53 Recurrent instability after a first-time dislocation is one of the most common complications. Numerous risk factors for recurrence have been recognized, including age, biological sex, open physes, and physical activity.^3,29,41 Furthermore, a history of contralateral patellofemoral dislocation has been associated with an increased risk of ipsilateral dislocation, indicating the importance of underlying pathoanatomic risk factors.^10,30 Trochlear dysplasia, patella alta, patellar tilt, and increased tibial tubercle–trochlear groove (TT-TG) distance have been identified as the most significant pathoanatomic risk factors for recurrent dislocations.^2,11,16 Despite the increased awareness of these factors, determining their contribution to recurrent LPI, both individually and in combination, has been challenging because of the multifactorial presentation of the condition. Understanding these interactions is vital in predicting those at the highest risk for recurrence, determining appropriate treatment strategies, and improving patient outcomes.

Patellar morphology, most commonly assessed using the Wiberg classification, has not been thoroughly explored as a pathoanatomic risk factor for LPI.⁵² First introduced in 1941, the Wiberg classification describes patellar morphology as types 1, 2, and 3 based on the relative medial and lateral patellar facet sizes on a skyline radiograph.⁵² The medial facet of type 1 is concave and similar in size to the lateral facet. The medial facet of type 2 is similarly concave but is smaller than the lateral facet. The medial facet of type 3 is convex, smaller than the lateral facet, and nearly vertical. While initially developed to describe normal anatomic variations of the patella, the Wiberg classification has since been used to classify dysplastic patellar features, with the severity of the dysplasia increasing with the classification grades.^38,45,52 The Wiberg classification has not been widely used in studies of recurrent LPI, and its clinical utility in the population remains unclear.

Gathering robust demographic and diagnostic imaging data from patients with recurrent LPI is crucial in understanding the utility of the Wiberg classification. Specifically, baseline prevalence of Wiberg types should be established in this population to enable investigation of patellar morphology and its relationship to other risk factors. Associations between the Wiberg classification and recurrent LPI have been described; however, the classification's relationship with many demographic and pathoanatomic risk factors in LPI remains unclear or unknown.^{38,39,42,43,46} Due to the complex interactions between risk factors in LPI, examining bivariate relationships with the Wiberg classification in isolation may be misleading. A sufficiently powered regression analysis is required to evaluate if demographic and pathoanatomic factors predict Wiberg classification types.

Optimizing clinical decision-making requires a thorough understanding of pathoanatomic risk factors and their influence on clinical outcomes. An important clinical evaluation is patient-reported outcome measures (PROMs), which provide a holistic evaluation of symptoms and function. The Banff Patellofemoral Instability Instrument (BPII) was the first disease-specific PROM used to evaluate quality of life after patellar stabilization.²⁶ This measure has demonstrated validity, reliability, and responsiveness in adolescents and adults with recurrent patellofemoral instability before and after surgical stabilization.^26,33

The primary purpose of this study was to determine the incidence of Wiberg types and explore relationships between the Wiberg classification and risk factors in patients with recurrent LPI. The secondary purpose was to evaluate relationships between the Wiberg classification and patient-reported disease-specific quality of life outcomes after primary medial patellofemoral ligament (MPFL) reconstruction.

Methods

A cohort study was conducted using prospectively collected data from a single orthopaedic surgeon (L.A.H.). Between 2008 and 2022, 447 patients (539 knees) with recurrent LPI underwent primary MPFL reconstruction, with or without concurrent procedures performed “à la carte.”¹⁴ The diagnosis of recurrent LPI was confirmed by clinical history, physical examination, and diagnostic imaging. All patients failed nonoperative treatment, including bracing, strengthening, or physical therapy. Patients who underwent concomitant ligament surgeries, including anterior cruciate ligament or medial collateral ligament reconstruction, revision patellofemoral stabilization, or were aged <12 years, were excluded. The MPFL reconstruction was performed using a consistent double-bundle technique with suture anchor patellar fixation and interference screw femoral fixation.²⁷ In the context of clinical and imaging findings, concomitant trochleoplasty was considered for Dejour type B or D trochlear dysplasia, tibial tubercle osteotomy (TTO) was considered if the TT-TG distance and/or Caton-Deschamps ratio was elevated, and femoral or tibial osteotomy was considered for moderate to severe valgus alignment or torsion.^13,14,18,49 Any previous or concurrent surgical procedures were documented. All patients followed a standardized phase-based postoperative rehabilitation protocol with variation for any concomitant procedures.²³ Functional exercises and quadriceps activation using electrical muscle stimulation were emphasized to promote a return to daily activities and sports.

Preoperatively, demographic data were collected, including biological sex at birth, age at first dislocation, age at time of surgery, operative limb side, body mass index (BMI), and number of dislocations. A complete history and physical examination included an assessment of alignment, Beighton score, and genu recurvatum. The WARPS/STAID classification was also assessed. The WARPS/STAID classification stratifies patients with patellofemoral instability into 2 subtypes, with WARPS describing atraumatic onset with risky anatomy and STAID describing traumatic onset with normal anatomy.²⁵ Because WARPS/STAID is based on a scoring system, it can be characterized as both a classification system and a scoring instrument.²⁵ Lower scores were indicative of WARPS characteristics and higher scores were indicative of STAID characteristics. A percentage score was calculated based on the summary of 5 different metrics associated with the scale, enabling data to be treated as continuous in the analysis.²⁵

Preoperative diagnostic imaging was used to measure and classify pathoanatomic risk factors. All patients received radiographs (anteroposterior, lateral, and skyline), and axial imaging, computed tomography (CT), or magnetic resonance imaging (MRI), based on imaging availability. True lateral radiographs were considered adequate and utilized when there was <3 mm overlap of the femoral condyles.²⁴ For statistical analysis, thresholds were set a priori to define risk factors as normal or pathological. Patellar morphology was assessed on skyline radiographs according to the Wiberg classification.⁵² Supratrochlear bump was measured on lateral radiographs.^4,15 Trochlear dysplasia was categorized in a binary grouping: absent and low grade (Dejour type A) or high grade (Dejour types B-D).³⁶ TT-TG distance, measured as the medial-to-lateral distance from the deepest aspect of the trochlear groove to the center of the tibial tubercle, was considered increased at ≥18 mm or ≥15 mm on CT and MRI, respectively.⁵⁰ Patellar tilt was measured as the angle between the posterior femoral condylar line and the line between the medial and lateral edges of the patella and was considered elevated >20° on either CT or MRI.²² Patella alta, measured by the Caton-Deschamps ratio on lateral radiographs, was considered elevated at ≥1.2.⁵¹ A Beighton score of ≥4 was considered positive.⁵ Genu recurvatum was measured by a goniometer, with an angle of ≥10° considered positive.¹⁸ Postoperatively, any redislocations were noted and confirmed by history and physical examination. Data were collected by the primary investigator (L.A.H.). Patients completed the BPII score preoperatively and 24 months postoperatively.

Statistical Analysis

Descriptive statistics, including frequencies and percentages, were calculated for the patient cohort. The incidence of the Wiberg types was calculated, and the intrarater reliability of the classification was evaluated through a blind test-retest conducted 2 weeks apart by the primary investigator. A weighted kappa (κw) assessed the intrarater agreement in a subset of 60 knees with a range of Wiberg types. Linear weighting was applied to account for the ordinal nature of the data.

Descriptive analyses, including means, standard deviations, and percentages for factors with dichotomous pathoanatomic threshold values, were produced for continuous variables (age at first dislocation, age at time of surgery, BMI, WARPS/STAID score, supratrochlear bump size, TT-TG distance, patellar tilt, patella alta, and Beighton score). WARPS/STAID data were treated as continuous based on the percentage score summarizing the 5 metrics of the scale. The frequencies and corresponding percentages of the categorical variables (limb side, number of dislocations, trochlear dysplasia grade, and genu recurvatum) were calculated and grouped by Wiberg classification types. Pathoanatomic risk factors were measured for the descriptive, correlation, and regression statistical analyses.

To explore initial bivariate relationships with the Wiberg classification, Pearson and Spearman rank correlation coefficients were calculated for the continuous and categorical variables, respectively (Appendix Tables A1 and A2). An ordinal logistic regression model was created to predict Wiberg classification types, including risk factors from the statistically significant correlation coefficients, existing literature, and clinical experience. The selection of an ordinal logistic regression model for this analysis was designed to preserve the patellar morphology severity types and detect differences between the types with higher sensitivity. A chi-square goodness of fit was employed to measure the model fit, including the ability of the model to accurately predict the Wiberg classification types. The recommended minimum sample size for logistic regression, based on theoretical testing and projections, was 500.⁶ Therefore, the sample of 539 knees exceeded an adequate sample size and ensured statistical soundness. The final model fit of the ordinal regression model was assessed using maximum likelihood estimation (–2 log likelihood method).

The relationship of Wiberg types to PROMs was explored through a 1-way analysis of variance (ANOVA) of the preoperative and 24-month postoperative BPII scores. All data were analyzed using SPSS IBM Version 29. This study received ethics approval from the University of Calgary Conjoint Health Research Ethics Board.

Results

Demographic and Pathoanatomic Descriptive Analysis

The study enrolled 447 patients, including 539 knees (21.5% male knees, 78.5% female knees; 54% left, 46% right) who underwent an MPFL reconstruction during the study period. In total, 137 (25.4%) knees had concurrent procedures performed (TTO, 81 [15.0%]; trochleoplasty, 50 [9.3%]; distal femoral osteotomy, 6 [1.1%]). An additional 17 knees had surgical procedures before the index MPFL reconstruction (TTO, 16 [3.0%]; Roux-Goldthwait, 1 [0.2%]). Surgical failure, defined as redislocation of the patella, was confirmed in 13 (2.4%) cases at 24 months postoperative.

In the 539 knees, there were 30.6% Wiberg type 1 (n = 165), 47.1% Wiberg type 2 (n = 254), and 22.3% Wiberg type 3 (n = 120) patellae. For the test-retest reliability for the Wiberg classification, the κw was 0.75 (95% CI, 0.62-0.89), indicating substantial agreement.³⁷ Pathoanatomic and demographic risk factor descriptive data are listed by Wiberg type in Table 1 for the continuous data and Table 2 for the categorical variables. Factors consistent with a dysplastic femur or tibia and greater pathoanatomy (lower age at first dislocation, WARPS subtype, trochlear dysplasia, increased TT-TG, and patellar tilt) were more frequent in the Wiberg type 3 patellae. As Wiberg type increased from type 1 to type 3, there was an increased percentage of male patients compared with female patients and an increased percentage of ≥21 dislocations. No relationship was seen between indices of ligamentous laxity or BMI and Wiberg type. Variables surpassing the predefined pathological threshold value included 282 knees (52.3%) with an elevated patellar tilt, 267 (49.5%) with a positive Beighton score, 217 knees (40.3%) with high-grade trochlear dysplasia, 178 knees (33.0%) with an increased TT-TG distance, and 156 (28.9%) with an increased Caton-Deschamps ratio.

Table 1

Continuous Demographic and Pathoanatomic Risk Factors of Recurrent LPI Across Wiberg Types ^a

Predictor Variable	Mean (SD), Overall (N=539)	Wiberg Type 1 (n=165)	Wiberg Type 2 (n=254)	Wiberg Type 3 (n=120)
Age at first dislocation, y	14.9 (6)	15.7 (7.1)	15.0 (5.5)	13.5 (5.4)
Age at time of surgery, y	23.5 (2.8)	23.7 (9.6)	24.2 (7.7)	22.0 (6.9)
BMI	24 (4.7)	23.6 (4.4)	24.0 (4.6)	24.5 (5.4)
WARPS/STAID score	5.3 (2.8)	6.1 (2.6)	5.2 (2.8)	4.4 (2.9)
Supratrochlear bump size, mm	4.9 (1.5)	4.6 (1.1)	4.9 (1.5)	5.0 (1.7)
TT-TG distance, mm	15.7 (5.1)	14.8 (5.0)	15.5 (5.1)	16.8 (4.8)
Patellar tilt, deg	22.7 (10.8)	20.2 (9.5)	22.7 (10.4)	26.1 (12.5)
Caton-Deschamps ratio	1.1 (0.2)	1.1 (0.0)	1.1 (0.2)	1.1 (0.2)
Beighton score	3.6 (2.9)	3.5 (2.8)	3.7 (2.9)	3.3 (3.0)
BPII score
Preoperative	31.7 (16.8)	29.5 (15.6)	31.6 (17.4)	35.3 (16.3)
Postoperative	70.2 (22.2)	69.2 (22.7)	70.7 (21.9)	70.1 (21.5)

Data are presented as mean (SD). BMI, body mass index; BPII, Banff Patellofemoral Instability Instrument; LPI, lateral patellofemoral instability; TT-TG, tibial tubercle–trochlear groove; WARPS/STAID, weak, atraumatic, risky anatomy, pain, subluxation / strong, traumatic, anatomy normal, instability, dislocation. All valures are reported per knee.

Table 2

Categorical Demographic and Pathoanatomic Risk Factors of Recurrent LPI Across Wiberg Types ^a

	Grouping	Total Knees(n = 539)	Wiberg Type1 (n = 165)	Wiberg Type 2 (n = 254)	Wiberg Type 3 (n = 120)
Biological sex	Male	116 (21.5)	26 (15.8)	50 (19.7)	40 (33.3)
Biological sex	Female	423 (78.5)	139 (84.2)	204 (80.3)	80 (66.7)
Number of dislocations	1	89 (16.5)	23 (13.9)	45 (17.7)	21 (17.5)
	2-5	195 (36.2)	68 (41.2)	89 (35.0)	38 (31.7)
	6-10	66 (12.2)	21 (12.7)	28 (11.0)	17 (14.2)
	11-20	37 (6.9)	15 (9.1)	17 (6.7)	5 (4.2)
	21+	152 (28.2)	38 (23.0)	75 (29.5)	39 (32.5)
Trochlear dysplasia	No + low grade	322 (59.7)	119 (72.1)	151 (59.4)	52 (43.3)
Trochlear dysplasia	High grade	217 (40.3)	46 (27.9)	103 (40.6)	68 (56.7)
Genu Recurvatum	No	330 (61.2)	98 (59.4)	158 (62.2)	74 (61.7)
Genu Recurvatum	Yes	207 (38.4)	66 (40.0)	96 (37.8)	45 (37.5)

Data are presented as n (%). LPI, lateral patellofemoral instability. All values are reported per knee.

Correlation Analysis

To explore initial bivariate relationships with the Wiberg classification, Pearson and Spearman rank correlation coefficients were calculated for the 13 continuous and categorical variables (Appendix Table A1). Correlation results revealed that WARPS/STAID (r = −0.216; P < .001), TT-TG distance (r = 0.140; P < .002), patellar tilt (r = 0.197; P < .001), high-grade trochlear dysplasia (r = .26; P < .001), and age at first dislocation (r = −0.129; P = .003) demonstrated statistically significant correlations with the Wiberg classification.

Ordinal Logistic Regression Analysis

Ordinal logistic regression analysis was conducted using the variables that were statistically significant in the Pearson and Spearman correlation (WARPS/STAID, TT-TG distance, patellar tilt, high-grade trochlear dysplasia, and age at first dislocation) with the addition of patella alta based on previous literature and clinical experience. Based on model fitting, the final model demonstrated a statistically significant −2 log likelihood model between the Wiberg classification and 3 predictor variables in combination (P < .001). Output results demonstrated that high-grade trochlear dysplasia contributed the greatest (P = .003) to the model, followed by the WARPS/STAID score (P = .01), with age at first dislocation contributing the least (P = .06) (Table 3). Model fitting is reflected in Table 4. The additional chi-square goodness-of-fit test indicated a Pearson significance value of .058 and a deviance value of .008, indicating that some variables contributed less to the model than others.

Table 3

Ordinal Logistic Regression Estimates for Wiberg Classification Predictors ^a

Predictors	Estimate	SE	Wald	df	P	95% CI
Predictors	Estimate	SE	Wald	df	P	Lower Bound	Upper Bound
Trochlear dysplasia	0.62	0.21	9.08	1	.003	0.21	1.03
WARPS/STAID score	–0.09	0.04	6.53	1	.01	–0.16	–0.02
Age at first dislocation	–0.03	0.01	3.53	1	.06	–0.05	0.001

WARPS/STAID, weak, atraumatic, risky anatomy, pain, subluxation / strong, traumatic, anatomy normal, instability, dislocation.

Table 4

Model Fit Statistics for Ordinal Logistic Regression

Model	–2 Log Likelihood	Chi-square	df	P
Intercept only	759.4
Final	717.4	42.0	5	<.001

Wiberg Classification Relationship to Patient-Reported Outcomes

The secondary purpose, investigating the relationship between the Wiberg classification and postoperative quality of life, was explored using a 1-way ANOVA. Descriptive data of BPII scores across Wiberg classification types is listed in Table 5. No statistically significant differences existed between Wiberg classification types for preoperative (F = 4.167; P = .02) or postoperative BPII scores (F = 0.121; P = .89).

Table 5

Mean BPII Outcome Scores Across Wiberg Classification Types ^a

BPII Score	Wiberg Classification Type	Mean	SD	95% CI for Mean
BPII Score	Wiberg Classification Type	Mean	SD	Lower Bound	Upper Bound
Preoperative	1	29.5	15.6	27.1	31.9
	2	31.5	17.5	29.3	33.7
	3	35.3	16.4	32.3	38.2
	Total	31.7	16.8	30.3	33.2
Postoperative, 24 mo	1	69.6	22.9	66.1	73.1
	2	70.7	22.0	68.0	73.4
	3	70.1	21.6	66.2	74.0
	Total	70.2	22.2	68.3	72.1

BPII, Banff Patellofemoral Instability Instrument.

Discussion

In this large cohort of patients with recurrent LPI, ordinal regression analysis identified that the combination of high-grade trochlear dysplasia, a lower WARPS/STAID score, and younger age at the time of first dislocation were predictive of a more dysplastic patella. The role of the dysplastic patella as a risk factor for LPI is not widely discussed. In addition, the relationship between a dysplastic trochlea and a dysplastic patella is poorly understood. This study utilized known pathoanatomic and demographic risk factors for LPI to investigate relationships with dysplastic patellae as categorized by the Wiberg classification. These findings provide preliminary evidence that patellar morphology should be considered among the pathoanatomic factors that are associated with LPI. Although the Wiberg classification was not associated with postoperative quality of life outcomes, the ordinal regression results suggest that the classification may have clinical value in identifying patterns of risk factors in LPI. Correlation analyses included TT-TG distance and patellar tilt as factors that correlate with Wiberg type, but these did not reach significance in the ordinal regression. Patella alta demonstrated no correlation or relationship with patellar shape.

The large number of risk factors described for LPI and the wide variety of combinations of presentation has made it difficult to tease out which factors contribute the most to the recurrence of patellar instability and failure after patellar stabilization. Using large data sets and complex, well-powered statistics allows a more robust assessment of the risk factors and their contribution to patient presentation with LPI. This becomes important in treatment algorithms where each patient is unique and treatment decisions are required. This study reports that the combination of trochlear dysplasia, a lower WARPS/STAID score, and younger age at first dislocation, in combination, are related to the degree of patellar dysplasia. The inclusion of these factors is not surprising because all are integral to the concept of distal femoral dysplasia and a higher risk of recurrent LPI.

Trochlear dysplasia is highly prevalent in LPI and has been reported in 85% of patients compared with only 6% of the general population.^16,17 In the present study, high-grade trochlear dysplasia was a strong predictor of increasing Wiberg types. These results align with literature reporting significant positive correlations between trochlear and patellar dysplasia.^19,34 One research group investigated multiple factors associated with LPI in relation to patellar morphology and reported correlations between patellar shape and patellar tilt and trochlear dysplasia.⁴³ A second group similarly demonstrated a significant binary relationship between Wiberg type 3 and Dejour type D.³⁸ A 2023 study performed a match cohort analysis of 212 patients with LPI.⁷ Using a binary logistic regression model, these authors reported that 5 risk factors in combination contributed to the model, TT-TG distance, patellar height, congruence angle, sulcus depth, and Wiberg index. These papers align with the present study's findings; however, the representation of factors in the cohort study may not meet the statistical thresholds for sufficiently powered regression analysis, thus limiting the conclusions. The significant relationship between patellar and trochlear dysplasia demonstrated in the present study is also unsurprising, considering how the articulating surfaces of the patellofemoral joint work together biomechanically.

Several hypotheses exist regarding the interaction between trochlear dysplasia and patellar dysplasia. One hypothesis is that increased lateral forces produce a more developed lateral facet and a hypoplastic medial facet, creating a Wiberg type 3 patella.^34,43 Alternatively, another hypothesis is that decreased medial tension on the patella leads to a hypoplastic medial facet.¹⁹ Both of these theories may fit the developmental data that have been published for patients with LPI; however, the question of cause or effect remains unanswered. Does a dysplastic trochlear “create” a dysplastic patella or does the trochlea not form properly because there is no normal patella to mold it? Studies in rabbits have demonstrated that creating lateral instability in a growing rabbit leads to changes in patellar morphology and that subsequent surgical stabilization of the patella can improve those measurements.³⁵ Importantly, similar findings have been described after patellar stabilization in growing children.⁴⁰

The other risk factors that contributed to the ordinal regression, WARPS/STAID score, and age at first dislocation are both inherent to a higher proportion of risky pathoanatomic and demographic features in patients with LPI. The WARPS/STAID classification stratifies patients with patellofemoral instability into 2 subtypes, based on percentage scores.²⁵ Lower scores describe atraumatic onset with risky anatomy, whereas higher scores describe traumatic onset with normal anatomy.²⁵ Similar to the Patellar Instability Severity Score, the classification is based primarily on pathoanatomic factors.³ Therefore, given this focus on anatomic risk, it is unsurprising that higher Wiberg classification types, describing increased dysplasia, are related to lower WARPS/STAID scores. Age has been demonstrated as a risk factor for both primary and recurrent instability.^1,9,43 The younger that patients are when they are evaluated for LPI, the more likely they are to have significant pathoanatomic risk factors. If risk factors such as trochlear dysplasia are associated with growth plate development, it stands to reason that multiple growth centers may be affected, not only the distal femur.³² In addition, form follows function; for example, if a trochlea is dysplastic at a young age, the patella may follow suit.

Interestingly, pathoanatomic risk factors often associated with LPI did not significantly contribute to the ordinal model fit for patellar morphology. Although patellar tilt and TT-TG distance were significantly correlated with patellar morphology in the initial assessments, they were not significant in the ordinal regression model. Patella alta, considered one of the core risk factors for LPI, did not demonstrate a significant correlation or a significant fit in the ordinal regression model for patellar morphology. These results are representative of the multifactorial nature of LPI. Although a dysplastic patellar may be associated with some risk factors, such as grade of trochlear dysplasia, other risk factor associations may be independent. These data question the role of lateral directed forces and patellar location in a well-formed groove as etiological factors in dysplasia of the patella.

The relationship between patellar dysplasia and quality of life after patellar stabilization is less clear. In the present study, Wiberg classification type did not influence patient-reported quality of life 24 months after MPFL reconstruction. Considering the relationships between Wiberg classification and the WARPS/STAID score, and previous research demonstrating that pathoanatomic risk factors and age at the time of surgery were predictive of BPII scores, it may have been expected that Wiberg types would be associated with postoperative PROM scores.²⁸ However, the influence on PROMs is multifactorial and not only based on pathoanatomy, but also biopsychosocial factors including work-related concerns, recreational activities, sport participation/competition, lifestyle, and social and emotional considerations.^26,28 Therefore, one pathoanatomic risk factor in isolation may not directly influence postoperative outcome scores. The simplicity or coarseness of the Wiberg classification may also contribute to the lack of significant association with BPII scores.

Limitations

The present study has some limitations. The recruited cohort is a convenience sample of patients with recurrent LPI treated at a single tertiary clinic, with data collected by a single observer. Therefore, this sample may not represent the full spectrum of LPI patients, limiting the generalizability of the study results to the LPI population requiring surgical intervention. The coarseness of the Wiberg classification is a concern, as recognizing only 3 patellar types may not adequately capture the variation in patellar morphology and could obscure important anatomic differences. The assessment of the intrarater reliability of the classification without interrater reliability may limit the strength of conclusions, however the intrarater reliability of this study has indicated substantial agreement and is a prerequisite for substantial interrater reliability. Future research should thoroughly explore the intra- and interrater reliability of the Wiberg classification in LPI, including whether additional morphology types might increase the veracity and validity of the classification. This study used plain radiograph axial imaging to classify the patellar shape as described by Wiberg; therefore, comparison with other studies may be limited due to the use of MRI or CT to define Wiberg types. Capturing trochlear pathoanatomy in a single low- versus high-grade dichotomy may oversimplify this complex pathoanatomy in patients with LPI. Measurement error is a consideration for all included pathoanatomic risk factors, as well as the reliability of classifications used to categorize the data. Thresholds for risk factors remain a moving target, and more research is required to validate these in large LPI populations.

Debate continues over the most appropriate techniques, including the type of image (radiograph, CT, or MRI) to classify patellar morphology. Future research should standardize a comprehensive battery of reliable measures and the defined pathoanatomic values for patients with LPI.^12,21,47 Important directions include validating novel dynamic and 3-dimensional imaging and related measurements describing the complex bony morphology and congruence of the PF joint for individual patients.^8,20,44,48 Machine learning algorithms, harnessing the power of large multicenter data sets, will also be important in creating predictive models for treatment based on comprehensive dynamic 3-dimensional imaging, standardized measurements, and classification systems.

Conclusion

In this large cohort of patients undergoing MPFL reconstruction for recurrent LPI, a robustly powered ordinal logistic regression demonstrated that the combination of high-grade trochlear dysplasia, lower WARPS/STAID scores, and younger age at the time of first dislocation were predictive of patellar dysplasia, as classified by Wiberg. Patellar shape in isolation, was not associated with pre- and postoperative quality of life scores. This study suggests that patellar morphology is associated with the pathoanatomic risk of LPI and that the Wiberg classification may be a useful clinical tool for identifying morphologic patterns associated with an increased risk of recurrent LPI.

Footnotes

Appendix 1

Table A2

Spearman Rank Bivariate Correlation of the Wiberg Classification and Categorical Risk Factor Variables

		Wiberg Classification	Limb Side	Number of Dislocations	Type of Dysplasia	Genu Recruvatum
Wiberg Classification	Spearman Rank Correlation	1	–0.082	0.033	0.256 ^a	0.02
	Significance (2-tailed)		.056	.44	<.001	.65
	n	539	539	539	539	537

Correlation is significant at the 0.1 level (2-tailed).

Final revision submitted October 1, 2025; accepted October 31, 2025.

One or more of the authors has declared the following potential conflict of interest or source of funding: L.A.H. has received research funding from Smith & Nephew, Pendopharm, and ConMed; consulting fees from Smith & Nephew, ConMed, Pendopharm, and Sanofi; and speaking fees from Smith & Nephew, ConMed, Pendopharm, and Sanofi and holds stock options in PrecisionOS. AOSSM checks author disclosures against the Open Payments Database (OPD). AOSSM has not conducted an independent investigation on the OPD and disclaims any liability or responsibility relating thereto.

Ethical approval for this study was obtained from University of Calgary Conjoint Health Research Ethics Board (Ethics ID: REB15-0616).

ORCID iD

Sarah Kerslake

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