Classification Of Deformities Research Articles

Early to short-term radiographic follow-up of metal-augmented baseplates in reverse shoulder arthroplasty for treatment of glenoid deformity in glenohumeral arthritis and rotator cuff arthropathy

Hypothesis and backgroundAs reverse total shoulder arthroplasty (rTSA) has evolved, the use of augmented glenoid baseplates has increased. While there are benefits of metal augmentation, literature concerning the mid- to long-term follow-up of these implants is emerging. The purpose of this study is to report early to short-term radiographic follow-up of patients with glenoid deformity treated with a metal-augmented glenoid baseplate. Our hypothesis is that we will see a low incidence of osteolysis, loosening, complications, and revision of these implants regardless of diagnosis, augment type, or patient demographics. MethodsWe performed a single-center retrospective review of all patients undergoing primary reverse shoulder arthroplasty with an augmented metallic baseplate for rotator cuff arthropathy and glenohumeral arthritis. Patients undergoing revision procedures or reverse arthroplasty for fractures were excluded. All patients had a minimum of 1-year radiographic follow-up. Preoperative imaging was reviewed to confirm the diagnosis and glenoid deformity classification. Postoperative radiographs were reviewed for evidence of complications, revisions, osteolysis, baseplate loosening, and failure. Clinical data were reviewed for complications. ResultsPrimary rTSA with a metal-augmented baseplate (38 full wedge and 22 half wedge augments) was performed on 60 patients who met inclusion criteria (mean age 74 ± 7). The average radiographic follow-up of all patients was 17 months. In our cohort, there was one patient with aseptic loosening of a full wedge implant that was not revised. There were no other complications, revision surgeries, baseplate failures, or acromial stress fractures. Six patients developed scapular notching, and five patients were found to have asymptomatic glenoid osteolysis. Two patients with full wedge implants developed aseptic humeral loosening. Pearson chi-square post hoc analysis found no correlation between augment type, gender, or glenoid deformity classification and radiographic changes such as glenoid or humeral osteolysis, loosening, or scapular notching. We did find a statistically significant correlation (P = .018) between patients with body mass index > 35 and glenoid osteolysis. Discussion and conclusionPrimary rTSA for patients with rotator cuff arthropathy or glenohumeral arthritis with glenoid deformity corrected with metal-augmented glenoid baseplates results in a low complication rate and an acceptable outcome at a minimum 1-year follow-up. Compared to other similar cohorts, our patients did not experience any acromial stress fractures, and only one patient had loosening of the glenoid component that was not ultimately revised. Further studies with longer follow-up will be needed, but early outcomes are promising and support the increase in the use of these implants.

Roussouly classification of adult spinal deformity

With an estimated prevalence of 68% among healthy adults without a previous diagnosis of scoliosis, adult spinal deformities are a growing concern as the population ages. Our understanding of this growing concern has been historically guided by previous studies performed on the pediatric population. Over time, different classifications have been developed with their own respective limitations. The Roussouly classification was the first classification to describe the shapes of an asymptomatic spine. It considers lumbar lordosis, pelvic incidence, and the inflection point from lumbar lordosis to thoracic kyphosis to attempt to stratify the shapes of an asymptomatic spine. This classification aims to guide treatment, provide information regarding prognosis, allow stratification for research, and be highly reproducible. Overall, the Roussouly classification is a novel way to think about sagittal malalignment, considering the patient’s individual anatomy, while allowing for communication between surgeons. Additionally, it has proven to be a reliable system that provides prognostic value for clinicians and may minimize complications when a patient’s sagittal alignment is optimized using this classification system.

MACHINE LEARNING AND ARTIFICIAL NEURAL NETWORK TECHNOLOGIES IN THE CLASSIFICATION OF POSTKERATOTOMIC CORNEAL DEFORMITY

Backgraund: A thorough analysis of both the optical and anatomical properties of the cornea in patients after anterior radial keratotomy is of particular importance in choosing the optical strength of an intraocular lens in the surgical treatment of cataracts and other types of optical correction. The variability of the clinical picture of postkeratotomic deformity (PCRD) determines the need to develop its classification and is an important task of modern ophthalmology.
 Aims: to develop an automated system of classification of corneal PCRD using machine learning and an artificial neural network based on the analysis of topographic maps of the cornea.
 Materials and methods: depersonalized results of the analysis of medical records of 250 patients aged 59.63±5.95 (from 46 to 76) years were used as the material. The analysis of 500 maps of the relief-topography of the anterior and posterior surfaces of the cornea and 3 stages of machine learning of the PCRD classification were carried out.
 Results: Stage 1- analysis of the relief topography of the anterior and posterior surfaces of the cornea allowed us to fix the numerical values of the elevation of the anterior and posterior surfaces of the cornea in three ring-shaped zones. At stage 2, in the course of deep machine learning, a direct distribution neural network was selected and created. 8 auxiliary parameters describing the shape of the anterior and posterior surfaces of the cornea were established. Stage 3 was accompanied by obtaining algorithms for the classification of PCRD depending on the ratio of test and training samples, which ranged from 75 to 91%..
 Conclusion: The use of artificial neural network algorithms can become a useful tool for automatic classification of postkeratotomic corneal deformity in patients who have previously undergone radial keratotomy.

A publicly available newborn ear shape dataset for medical diagnosis of auricular deformities

Early and accurate diagnosis of ear deformities in newborns is crucial for an effective non-surgical correction treatment, since this commonly seen ear anomalies would affect aesthetics and cause mental problems if untreated. It is not easy even for experienced physicians to diagnose the auricular deformities of newborns and the classification of the sub-types, because of the rich bio-metric features embedded in the ear shape. Machine learning has already been introduced to analyze the auricular shape. However, there is little publicly available datasets of ear images from newborns. We released a dataset that contains quality-controlled photos of 3,852 ears from 1,926 newborns. The dataset also contains medical diagnosis of the ear shape, and the health data of each newborn and its mother. Our aim is to provide a freely accessible dataset, which would facilitate researches related with ear anatomies, such as the AI-aided detection and classification of auricular deformities and medical risk analysis.

Classification of postburn deformities of the breast

Classification of postburn deformities of the breast

Two-stage video-based convolutional neural networks for adult spinal deformity classification.

Assessment of human gait posture can be clinically effective in diagnosing human gait deformities early in life. Currently, two methods-static and dynamic-are used to diagnose adult spinal deformity (ASD) and other spinal disorders. Full-spine lateral standing radiographs are used in the standard static method. However, this is a static assessment of joints in the standing position and does not include information on joint changes when the patient walks. Careful observation of long-distance walking can provide a dynamic assessment that reveals an uncompensated posture; however, this increases the workload of medical practitioners. A three-dimensional (3D) motion system is proposed for the dynamic method. Although the motion system successfully detected dynamic posture changes, access to the facilities was limited. Therefore, a diagnostic approach that is facility-independent, has low practice flow, and does not involve patient contact is required. We focused on a video-based method to classify patients with spinal disorders either as ASD, or other forms of ASD. To achieve this goal, we present a video-based two-stage machine-learning method. In the first stage, deep learning methods are used to locate the patient and extract the area where the patient is located. In the second stage, a 3D CNN (convolutional neural network) device is used to capture spatial and temporal information (dynamic motion) from the extracted frames. Disease classification is performed by discerning posture and gait from the extracted frames. Model performance was assessed using the mean accuracy, F1 score, and area under the receiver operating characteristic curve (AUROC), with five-fold cross-validation. We also compared the final results with professional observations. Our experiments were conducted using a gait video dataset comprising 81 patients. The experimental results indicated that our method is effective for classifying ASD and other spinal disorders. The proposed method achieved a mean accuracy of 0.7553, an F1 score of 0.7063, and an AUROC score of 0.7864. Additionally, ablation experiments indicated the importance of the first stage (detection stage) and transfer learning of our proposed method. The observations from the two doctors were compared using the proposed method. The mean accuracies observed by the two doctors were 0.4815 and 0.5247, with AUROC scores of 0.5185 and 0.5463, respectively. We proved that the proposed method can achieve accurate and reliable medical testing results compared with doctors' observations using videos of 1 s duration. All our code, models, and results are available at https://github.com/ChenKaiXuSan/Walk_Video_PyTorch. The proposed framework provides a potential video-based method for improving the clinical diagnosis for ASD and non-ASD. This framework might, in turn, benefit both patients and clinicians to treat the disease quickly and directly and further reduce facility dependency and data-driven systems.

Applied surgical methods and outcomes in crooked nose rhinoplasty.

In this retrospective and multicentric study, we investigated applied surgical methods in rhinoplasty for crooked nose deformity. The retrospective data for 300 crooked nose deformity cases (191 males and 109 females) were used in our study. Classification of the initial deformities was performed as (1) I-shaped crooked nose deformity, (2) C-shaped crooked nose deformity, (3) Reverse C-shaped crooked nose deformity, and (4) S-shaped crooked nose deformity. As an operation technique, L-strut septoplasty was performed. The applied surgical methods in rhinoplasty to correct the crooked nose are evaluated and classified. Our results showed that initial deformities in crooked nose patients were I-shaped crooked nose deformity (34%), C-shaped crooked nose deformity (28%), Reverse C-shaped crooked nose deformity (21.3%), and S-shaped crooked nose deformity (16.7%). L-strut septoplasty was performed, and the results of the applied methods to correct the crooked nose were evaluated and classified. It was noticed that more than one procedure was applied to each case: (1) double-side lateral osteotomy (86.6%), (2) wedge bone resection on one side of the osteotomy (7.3%), (3) single-side lateral osteotomy (6%), (4) symmetric spreader grafts (56%), (5) asymmetric spreader grafts (10.6%), (6) shaving of the transverse wing of dorsal septum (8%), (7) correction of deviated dorsal septum (16.3%), (8) displaced anterior nasal spine (12.6%), (9) clocking suture (dorsal septal rotation suture) (9%), (10) dorsal septal scoring and splinting graft (8.3%), and equalizing lateral cruses (12.6%). I-shaped and C-shaped crooked nose deformities were mainly detected in crooked nose deformity patients. Correcting the crooked nose, double-side lateral osteotomy, and symmetric spreader grafts were the most applied techniques to correct the crooked nose. Other rhinoplasty techniques were also applied to these patients; more than one technique was needed.

Value of multi-channel somatosensory evoked potentials recording in patients undergoing scoliosis correction surgery.

We aimed to investigate the value of intraoperative multi-channel recording of somatosensory evoked potentials (SSEPs) in patients undergoing posterior instrumentation surgery with fusion. This study included 176 patients with scoliosis who underwent posterior correction surgery from January 2019 to June 2020. Among them, 88 patients underwent routine SSEPs monitoring via single-channel (Cz'-Fpz) cortical recording (control group), while the remaining 88 patients underwent multi-channel (Cz'-Fpz and C3'-C4') SSEPs monitoring in the cortex. Chi-square and Fisher's exact tests were used to analyze the influence of age, spinal deformity classification, and Cobb angle on waveform differentiation and the success rate of SSEPs monitoring. Univariate analysis revealed that age, type of scoliosis, and Cobb angle exerted significant effects on the success rate of intraoperative SSEPs monitoring, and the SSEPs waveform differentiation rate was poorest among patients with congenital scoliosis. Intraoperative monitoring results indicated that the success rate of single-channel SSEPs monitoring was 90.9%, while that of multi-channel monitoring was 98.9% (P < 0.05). Among the intraoperative alarm cases, the incidence of adverse events after single-channel SSEPs monitoring was 66.7%, while the incidence of adverse events after multi-channel SSEPs monitoring was only 28.6%. Multi-channel cortical SSEPs monitoring can effectively and accurately evaluate the function of the posterior column of the spinal cord. Use of multi-channel SSEP monitoring may help to improve the success rate of monitoring and reduce the incidence of postoperative adverse events in patients with congenital scoliosis.

The impact of baseline cervical malalignment on the development of proximal junctional kyphosis following surgical correction of thoracolumbar adult spinal deformity.

The objective of this study was to identify the effect of baseline cervical deformity (CD) on proximal junctional kyphosis (PJK) and proximal junctional failure (PJF) in patients with adult spinal deformity (ASD). This study was a retrospective analysis of a prospectively collected, multicenter database comprising ASD patients enrolled at 13 participating centers from 2009 to 2018. Included were ASD patients aged > 18 years with concurrent CD (C2-7 kyphosis < -15°, T1S minus cervical lordosis > 35°, C2-7 sagittal vertical axis > 4 cm, chin-brow vertical angle > 25°, McGregor's slope > 20°, or C2-T1 kyphosis > 15° across any three vertebrae) who underwent surgery. Patients were grouped according to four deformity classification schemes: Ames and Passias CD modifiers, sagittal morphotypes as described by Kim et al., and the head versus trunk balance system proposed by Mizutani et al. Mean comparison tests and multivariable binary logistic regression analyses were performed to assess the impact of these deformity classifications on PJK and PJF rates up to 3 years following surgery. A total of 712 patients with concurrent ASD and CD met the inclusion criteria (mean age 61.7 years, 71% female, mean BMI 28.2 kg/m2, and mean Charlson Comorbidity Index 1.90) and underwent surgery (mean number of levels fused 10.1, mean estimated blood loss 1542 mL, and mean operative time 365 minutes; 70% underwent osteotomy). By approach, 59% of the patients underwent a posterior-only approach and 41% underwent a combined approach. Overall, 277 patients (39.1%) had PJK by 1 year postoperatively, and an additional 189 patients (26.7%) developed PJK by 3 years postoperatively. Overall, 65 patients (9.2%) had PJF by 3 years postoperatively. Patients classified as having a cervicothoracic deformity morphotype had higher rates of early PJK than flat neck deformity and cervicothoracic deformity patients (p = 0.020). Compared with the head-balanced patients, trunk-balanced patients had higher rates of PJK and PJF (both p < 0.05). Examining Ames modifier severity showed that patients with moderate and severe deformity by the horizontal gaze modifier had higher rates of PJK (p < 0.001). In patients with concurrent cervical and thoracolumbar deformities undergoing isolated thoracolumbar correction, the use of CD classifications allows for preoperative assessment of the potential for PJK and PJF that may aid in determining the correction of extending fusion levels.

A Proposal for the Classification of Temporomandibular Joint Disc Deformity in Hemifacial Microsomia.

Hemifacial microsomia (HFM) is the second most common congenital craniofacial disease and has a wide spectrum of symptoms. The classic diagnostic criterion for hemifacial microsomia is the OMENS system, which was later refined to the OMENS+ system to include more anomalies. We analyzed the data of 103 HFM patients with magnetic resonance imaging (MRI) for temporomandibular joint (TMJ) discs. The TMJ disc classification was defined into four types: D0 for normal disc size and shape; D1 for disc malformation with adequate length to cover the (reconstructed) condyle; D2 for disc malformation with inadequate length to cover the (reconstructed) condyle; and D3 for no obvious presence of a disc. Additionally, this disc classification was positively correlated with the mandible classification (correlation coefficient: 0.614, p < 0.01), ear classification (correlation coefficient: 0.242, p < 0.05), soft tissue classification (correlation coefficient: 0.291, p < 0.01), and facial cleft classification (correlation coefficient: 0.320, p < 0.01). In this study, an OMENS+D diagnostic criterion is proposed, confirming the conjecture that the development of the mandibular ramus, ear, soft tissue, and TMJ disc, as homologous and adjacent tissues, is affected to a similar degree in HFM patients.

Labeling of Baropodometric Analysis Data Using Computer Vision Techniques in Classification of Foot Deformities.

Background and Objectives: Foot deformities are the basis of numerous disorders of the locomotor system. An optimized method of classification of foot deformities would enable an objective identification of the type of deformity since the current assessment methods do not show an optimal level of objectivity and reliability. The acquired results would enable an individual approach to the treatment of patients with foot deformities. Thus, the goal of this research study was the development of a new, objective model for recognizing and classifying foot deformities with the application of machine learning, by labeling baropodometric analysis data using computer vision methods. Materials and Methods: In this work, data from 91 students of the Faculty of Medicine and the Faculty of Sports and Physical Education, University of Novi Sad were used. Measurements were determined by using a baropodometric platform, and the labelling process was carried out in the Python programming language, using functions from the OpenCV library. Segmentation techniques, geometric transformations, contour detection and morphological image processing were performed on the images, in order to calculate the arch index, a parameter that gives information about the type of the foot deformity. Discussion: The foot over which the entire labeling method was applied had an arch index value of 0.27, which indicates the accuracy of the method and is in accordance with the literature. On the other hand, the method presented in our study needs further improvement and optimization, since the results of the segmentation techniques can vary when the images are not consistent. Conclusions: The labeling method presented in this work provides the basis for further optimization and development of a foot deformity classification system.

Commentary on "Classification(s) of Cervical Deformity".

Commentary on "Classification(s) of Cervical Deformity".

Reply to Commentary on "Classification(s) of Cervical Deformity".

Reply to Commentary on "Classification(s) of Cervical Deformity".

THE ASSESSMENT OF THE SAGITTAL SPINOPELVIC ALIGNMENT THROUGH THE L1-PELVIS ANGLE

The spinopelvic alignment is often assessed via the Pelvic Incidence-Lumbar Lordosis (PI-LL) mismatch. Here we describe and validate a simplified method to evaluating the spinopelvic alignment through the L1-Pelvis angle (L1P). This method is set to reduce the operator error and make the on-film measurement more practicable.126 standing lateral radiographs of patients presenting for Total Hip Arthroplasty were examined. Three operators were recruited to label 6 landmarks. One operator repeated the landmark selection for intra-operator analysis. We compare PI-LL mismatch obtained via the conventional method, and our simplified method where we estimate this mismatch using PI-LL = L1P - 90°. We also assess the method's reliability and repeatability.We found no significant difference (p &gt; 0.05) between the PI-LL mismatch from the conventional method (mean 0.22° ± 13.6) compared to L1P method (mean 0.0° ± 13.1). The overall average normalised root mean square error (NRMSE) for PI-LL mismatch across all operators is 7.53% (mean −3.3° ± 6.0) and 6.5% (mean −2.9° ± 4.9) for the conventional and L1P method, respectively. In relation to intra-operator repeatability, the correlation coefficients are 0.87 for PI, 0.94 for LL, and 0.96 for L1P. NRMSE between the two measurement sets are PI: 9.96%, LL: 5.97%, and L1P: 4.41%. A similar trend is observed in the absolute error between the two sets of measurements.Results indicate an equivalence in PI-LL measurement between the methods. Reproducibility of the measurements and reliability between operators were improved. Using the L1P angle, the classification of the sagittal spinal deformity found in the literature translates to: normal L1P&lt;100°, mild 100°&lt;L1P&lt;110°, and severe L1P&gt;110°. Surgeons adopting our method should expect a small improvement in reliability and repeatability of their measurements, and a significant improvement of the assessment of the mismatch through the visualisation of the angle L1P.

Influence of Weightbearing Computed Tomography in the Progressive Collapsing Foot Deformity Classification System.

The objective of this study was to compare progressive collapsing foot deformity (PCFD) classifications performed using clinical and conventional radiographs (CR) with classifications established using clinical and weightbearing computed tomography (WBCT). This retrospective comparative study evaluated 89 consecutive PCFD feet (84 patients). Three readers performed chart reviews and CR evaluations, determining PCFD classifications that were previously published. After a washout period, the sequence was randomized, and a new classification was executed using clinical and WBCT assessment. One of the readers repeated the WBCT evaluation for intrarater reliability. Interrater reliability for the WBCT was found moderate (0.55) and intrarater excellent (0.98). Evaluation using WBCT produced 29.6% of 1ABC (CR: 25.4%, P = .270), 11.6% of 1ABCD (CR: 6.9%, P = .081), and 6.4% of BC (CR: 3.3%, P = .090) as most prevalent. Class A was presented in 83.9% (CR: 89.5%, P = .55), class B in 89.9% (CR: 76.4%, P < .001), class C in 93.6% (CR: 86.2%, P = .004), class D in 46.4% (CR: 34.8%, P = .006), and class E in 27.7% (CR: 22.5%, P = .158) of the classifications performed by WBCT. WBCT showed a different rate of deformity recognition, which increased the incidence of all classes, especially B, C, and D. An excellent intrarater agreement was found, which infers assessment reliability combining clinical and WBCT evaluation. The obtained information could enhance disease understanding and supply patients with more precise care. Level III, retrospective comparative study.

Classification and management of the midfoot Charcot diabetic foot

Charcot neuroarthropathy adversely affects the quality of life of diabetic patients with peripheral neuropathy and therefore early diagnosis is essential. The midfoot is the commonest site for Charcot deformity and can lead to ulceration, deep infection and amputation. The goal of treatment in Charcot arthropathy is to achieve a stable, plantigrade foot without infection and ulceration to allow for ambulation in the long term. The aim of this article is to review the classification of Charcot midfoot deformity and assess the role of non-operative and surgical measures in the management of these patients. We specifically reviewed the indications and literature around surgical exostectomy.

A Novel Classification for Diabetic Foot Ulcers of the First Ray.

Diabetic foot ulcers of the first ray result from several distinct biomechanical mechanisms related to anatomical deformities, which must be addressed if surgical offloading is contemplated. The objective of this study was to create a classification of the anatomical deformities of first-ray ulcers that could lead to better standardization of treatment and reporting. The authors performed a file review of patients with diabetic neuropathy diagnosed with first-ray ulcers over a period of 3 years in an outpatient setting. Anatomical deformities were diagnosed clinically and reported with ulcer location. The primary classification was the metatarsophalangeal joint, the interphalangeal joint, and the distal phalanx. Records for 59 patients (mean age, 62 years) with University of Texas A1 and A2 ulcers were reviewed. Mean ulcer duration was 2 months. The more common deformities were hallux valgus (41%), hallux valgus interphalangeus (14%), and hallux malleus (20%), and these were primarily associated with metatarsophalangeal, interphalangeal joint, and tip-of-toe ulcers, respectively (P < .0001). By classifying ulcer locations, the relevant corrective surgery may be chosen. Although some prophylactic procedures may be safe and effective, prophylactic hallux valgus correction in the diabetic foot requires further study.

Surgical treatment of combined injuries of the neck and shoulder joints

To develop the algorithm for effective surgical restoration of shoulder joint and neck functions and acceleration of social and labor rehabilitation. There were 116 patients with combined consequences of burns of the neck and shoulder joints between 2012 and 2021. These ones amounted to 29.4% of all patients with lesions of the neck or shoulder joints. Simultaneous surgeries with correction of post-burn cicatricial deformities and contractures were performed in 66 patients (56.9%). Age of patients ranged from 18 to 72 years, and 96% of them were employable. There were 89 (76.7%) women and 27 (23.3%) men. We assessed spread and localization of cicatricial process, as well as restriction of mobility of the neck and shoulder joint to select optimal surgical approach. Classification of neck deformities and contractures of shoulder joints considering severity of cicatricial lesion and functional impairment made it possible to systematize the approach to reconstructive procedures. Reconstructive surgery included repair with local tissues including skin-fatty flap, non-perforated split or full-thickness skin autograft, rotated flaps including those based on perforator vessels, as well as preliminary skin stretching. In general, 116 patients with combined lesions of the neck and shoulder joints underwent 314 surgeries. To accelerate rehabilitation, we performed simultaneous surgeries with correction of deformities and contractures in 66 patients (56.9%). Staged reconstructive surgeries were carried out in 50 patients. Acute dermotension and skin-fatty neck flap grafting were the most common for deformities and contractures of the neck. Skin-fatty axillary flap was used in most patients with contractures of shoulder joints. Simultaneous surgeries can accelerate rehabilitation. Correct algorithm of staged surgical treatment reduces rehabilitation period and eliminates functional disorders.

Classification(s) of Cervical Deformity.

Cervical spine deformities (CSD) are complex surgical issues with currently heterogenous management strategies. The classification of CSD is still an evolving field. Rudimentary classification schemas were initially proposed in the late 20th century but were largely informal and based on the underlying etiology (i.e. , postsurgical, traumatic, or inflammatory). The first formal classification schema was proposed by Ames et al. in 2015 who established a standard nomenclature for describing these deformities. This classification system established 5 deformity descriptors based on curve apex location (cervical, cervicothoracic, thoracic, craniovertebral junctional, and coronal deformities) and 5 deformity modifiers which helped surgeons utilize a standard language when discussing CSD patients. Koller et al. in 2019 subsequently established a classification system for patients with rigid cervical kyphosis based on regional and global sagittal alignment. Most recently, Kim et al. in 2020 proposed an updated classification system utilizing dynamic cervical spine imaging to guide surgical treatment of CSD patients. It identified 4 major groups of deformities - (1) those with "flat-neck" deformities caused by cervical lordosis T1 slope mismatch; (2) those with focal kyphotic deformities between 2 cervical vertebrae; (3) those with cervicothoracic deformities caused by large T1 slope; and (4) those with coronal deformities. Group 2 deformities most often required combined anterior-posterior approaches with short constructs, and group 3 deformities most often required posterior-only approaches with 3-column osteotomies.

Minimally invasive surgery for lesser toe deformity: a clinical audit of a proposed treatment algorithm

Objective: There is increasing interest in the performance of minimally invasive foot surgery (MIS); however, limited evidence and treatment algorithms are available to support its use and guide surgical decision-making. The aim of this prospective clinical audit was to report the efficacy of a treatment algorithm used to treat patients presenting with lesser toe deformities using MIS techniques. Methods: A prospective clinical audit of 38 patients who underwent 55 MIS procedures for complex and simple lesser toe deformities was conducted between April 2018 and June 2022. All patients were followed up for a minimum of 12 months post operatively. The audit was conducted following the National Research Ethics Service (NRES) guidelines on clinical audit. Results: Mean pre-operative Visual Analogue Pain (VAS) score was 3.95 with a median of 5.00. The mean post-operative VAS scores improved to 0.23 after six weeks and 0.43 after 12 weeks. A Mann-Whitney U test concluded that this improvement was statistically significant (p&lt;0.05). Conclusion: This algorithm appears effective in treating lesser toe deformities independent of deformity classification, concomitant surgery, gender or whether the surgery was performed in a hospital or private clinical setting. Level of Evidence V; Therapeutic Study; Expert Opinion.