Abstract

Introduction: Delayed carpal tunnel syndrome (DCTS) in patients with malunited distal radius fracture (DRF) develops several weeks to months after injury. The main treatment method for these patients is corrective osteotomy and fixation of the radius bone. However, the necessity and methods of median nerve decompression still remain controversial.
Purpose: To evaluate the long-term results of surgical treatment of patients with a malunited distal radius fracture and concurrent delayed carpal tunnel syndrome, depending on the method of median nerve decompression, and to develop a treatment concept.
Methods: The results of treatment were studied in 33 patients (30 women and three men, average age 54.6 years) with malunited DRF complicated by DCTS. All patients underwent corrective osteotomy of the distal radius and osteosynthesis with a volar locking plate. In addition, open carpal tunnel release was performed in the first group of patients through a separate limited surgical approach (OCTR, n=19), while decompression of the median nerve was carried out through an extended flexor carpi radialis approach in the second group (EFCR, n=14). Patients were evaluated clinically (wrist range of motion, hand strength, pain level VAS, DASH score), radiographically, and electromyographically before surgery and one year thereafter. Different degrees of severity of DCTS and deformation of the DRF were compared.
Results: Both groups of patients showed improvements in clinical, radiological, and EMG parameters after surgery (p<0.001). The average time for bone healing was 12 weeks. Patients in the first group (OCTR) achieved more favorable results: significantly increased hand grip strength (p = 0.010), compound muscle action potential (CMAP, p < 0.001), and an improved DASH score (p = 0.038). Depending on the severity of DCTS and the severity of deformity of the DRF, it was found that the most significant favorable changes occurred in moderate and severe degrees of DCTS, as well as with “intermediate” and “predominantly dorsal deformation” of the DRF.
Conclusion: Corrective osteotomy and volar locking plate osteosynthesis with carpal tunnel release are reliable and effective treatments for malunited distal radius fractures with concurrent delayed carpal tunnel syndrome. The best results were obtained after open carpal tunnel release (OCTR) in patients with moderate and severe degrees of DCLS, combined with “intermediate” and “predominantly dorsal deformation” of the DRF. With a mild degree of DCTS as well as a “predominantly palmar deformity” of DRF, decompression of the median nerve can be performed through the main EFCR approach.

Keywords:Distal radius fracture; Malunion; Osteotomy, Delayed carpal tunnel syndrome; Carpal tunnel release; Limited open approach; Extended flexor carpi radialis approach; Median nerve

Introduction

In recent years, the concept of artificial intelligence (AI), shown in 1956 by Professor John McCarthy, has become popular. AI is the scientific field of computer science that focuses on the creation of programs and mechanisms that can display behaviors considered intelligent. It has an increasingly greater impact on all spheres of society. Despite the advances of AI and its connection with the different sciences and in particular with Health Science, in our professional field, there is a lack of knowledge about the impact of its use in the health sector and therefore its perspectives or research potential for future technological projects. Tibial fractures are common injuries and their management is controversial [1-3].

Although the reference standard for treating the majority of tibial fractures is intramedullary nailing, not all fractures (due to their very distal location or due to alterations in the tibial shape or narrowness of its canal) can be treated with said osteosynthesis [4]. Classically they have been treated by open reduction and internal fixation, to achieve primary stabilization and allow faster rehabilitation. However, extensive dissection and deperiostization, coupled with poor local vascularization, led to a high complication rate [5]. Minimally invasive lamina osteosynthesis (MIPO) is the next logical step in the surgical treatment of fractures. It is mainly based on the indirect reduction of the fracture using various techniques. In this way, the fracture environment is better preserved, as well as the blood supply to the bone fragments [6].

The treatment of fractures of the tibia does not currently constitute a traumatological problem that has not been satisfactorily resolved, as is the case with other orthopedic or traumatological conditions, if good results are obtained with bloodless or invasive procedures in the treatment of leg fractures, such as Statistics show it, why is it necessary to review the problem of treatment? Well, there are still figures of disability, invalidity, delayed union and pseudoarthrosis incompatible with the current development of the specialty, this is the reason why, under the protection of the recent improvement of osteosynthesis, various methods of osteosynthesis have been and are being tested. Treatment of diaphyseal tibial fractures [7,8].

The author considered it pertinent to analyze the influence of some of the variables studied using artificial intelligence techniques on the complications of surgical treatment with a blade for tibia fractures.

Method

The research was carried out in the orthopedics and traumatology services of the Milian and Sagua University Hospitals, in the period between 2020 and 2023, the management of plate osteosynthesis for tibia fractures was analyzed, using the conventional RAFI approach method and the modified minimally invasive osteosynthesis method CENDA-234-02-2024 [9]. A mixed, multicenter, multi-stage, and quasi-experimental research was carried out, where scientific research methods were used; empirical and theoretical, in addition, analysis using artificial intelligence. We applied 10-partition cross-validation and applied several machine learning techniques.

Artificial intelligence techniques were applied to analyze the information and search for correlation between variables, specifically complications. To analyze the results of the influence of variables on complications, according to artificial intelligence, the Waikato Environment for Knowledge Analysis System, Version 3.9.6 (c)1999-2022, is used, from the University of Waikato. Hamilton, New Zealand. With cross-validation analysis techniques, also known as cross-validation, this is a technique used in machine learning and statistical analysis. Their goal was to evaluate the results of a statistical analysis and ensure that they are independent of the partition between training and test data. We apply automated construction of decision trees using the J48 pruned tree method, which is a modification of Quilan’s C4.5, and the following tree is reached to infer the complication Figure 1.

Results

Table 1 shows the demographic characterization of the sample studied, the sample size: 129 patients with tibia fracture candidates for surgical treatment, divided into two groups, one where open reduction and internal fixation (ORIF) was applied through a standard with 82 patients and the second group, where the modified MIPO technique was used in 47 patients. The youngest patient was 19 years old at the time of the study; we did not include minors in the study due to the characteristics of the immature skeleton. The oldest was 90 years old. The average age in the sample was 45.3 years, with similar values in both groups and the model was 45 years. There was a predominance of the injury in the male sex, with 72.1% of the cases studied. The data obtained reinforces the statements found in the reviewed bibliography where it is stated that tibia fracture is a pathology that frequently occurs in the working population; it is generally more common in young adults.

CG- control group.
GE- study group.
Source: Database.
The average age in the sample was 45.3 years, with similar values in both groups and the mode was 45 years. There was a predominance of the injury in the male sex, with 72.1% of the cases studied.
The data obtained reinforce the statements found in the reviewed bibliography where it is stated that tibia fracture is a pathology that frequently occurs in the working population; it is generally more common in young adults.

Table 2 shows the distribution of patients according to complications with a total of 29 for 22.4% of the 129 cases studied, with a predominance of these in the group treated conventionally: 21 (16.2%) versus 8 (6.2%) of those treated with MIPO. In the modified MIPO group, no major complications occurred, and those that did occur were associated with sepsis of the wound site [5], one case with exposure of the osteosynthesis material (MOS) and two cases with seroma; a complication that stopped occurring once we took the approach of placing an elastic bandage in the immediate post-surgery period. In the conventional group, 14 major complications occurred, among which the presence of 11 cases with pseudoarthrosis stands out. There are very significant differences according to complications between both groups (study and control) since p<0.01.

Among the most important applications in the application of AI in orthopedics is data analysis, for clinical applications and for research - this is one of the results that the author can show, as far as he knows, it is the first time in which this futuristic option is used in the specialty, this allowed the association of variables and the prognosis of patient behavior. Table 3 It can be seen how the presence of sepsis in the first consultation behaves as the main risk for complications of the variables studied, for surgical treatment with a blade in tibia fractures, both for the study group and for the control group, the same What happens with the AO classification, these results agree with the author’s inference, but what the author and his advisors did not expect is to find that the artificial intelligence methods do not influence the complications of surgical time, nor age, nor the length of hospitalization or the size of the incisions (Table 4).

Discussion

In a retrospective study conducted by the Department of Orthopedic Surgery at Jeju National School of Medicine, Jeju, South Korea evaluating the results of MIPO for fractures of the middle third of the tibia, a total of 37 patients were included (12 female, 25 males) with an average age of 52.7 years (range 28-78 years) [10]. Another investigation carried out in Turkey presents a comparison between two groups of patients with tibia fractures, one treated with intramedullary nailing (IMN) with 30 patients and another with MIPO with 29. In the first group the average age was 47 years of them 19 men and 11 women while, in the second year, he was 52 years old, of them 16 men and 13 women [11]. For Silva Villegas, the male sex is the one with the greatest presence of cases, 74% of the incidence of tibia fractures, Likewise, the age with the highest prevalence is in young adults [12]. The present study agrees on the predominance of these fractures in male adults of working age in which they are exposed to a greater risk of accidents [2,13,14].

X2 =8.1773 p=0.0042 Muy Sig
Source: Database.

Fountain. Artificial intelligence report.

Fountain. Artificial intelligence analysis. Database.

It is of internal relevance to generate own, useful and comparative statistics with other studies, with the purpose of providing detailed information on the current panorama of osteosynthesis in our environment, with respect to the possibilities, frequency of complications of tibia fractures, as well as, the association with multiple factors that lead to developing them and that even turn out to have great prognostic value for the patient’s evolution, inferring which of these variables turn out to have the most impact and whether they are preventable or possibly mitigatable. Due to the growing burden of increasingly complex musculoskeletal conditions, research in orthopedics and traumatology plays an essential role in understanding their pathophysiology, in order to provide the patient with the management with the most evidence available. This is in order to ensure quality care and efficient management of the available infrastructure. Thanks to the use of technology, continuous progress has been achieved in decision making by increasing the precision of diagnostic and therapeutic methods.

In the field of orthopedics, AI plays an increasingly relevant role. It has been used in different scenarios, for example, the diagnosis of fractures, the creation of predictive models to evaluate the probability of certain clinical outcomes such as the risk of fracture and the surgical training of specialists. It is expected that in the future it will allow progress in efficiency and quality in the characterization of conditions in traumatology, while helping to contribute to the reduction of costs associated with the process [15,16]. The author considers that from an anatomical point of view, the distal third of the tibia has limited muscular coverage, so its vascularization is poorer. Noninvasive treatment can result in a number of complications, such as malunion, nonunion, and ankle stiffness, among others. Classically, tibial fractures have been treated by open reduction and internal fixation, to achieve primary stabilization and allow faster rehabilitation.

However, extensive dissection and deperiostization, coupled with poor local vascularization, led to a high rate of complications including infection, poor wound healing, malunion, and nonunion [17,18]. AI in health represents a collection of multiple technologies that allow machines to detect, understand, act and learn, so that they can perform administrative and clinical functions in health. There are few Cuban studies on this topic, although they all agree on aspects such as the advantages since it allows events to be anticipated for resource planning and becomes a useful tool to support decision making and improve the services offered to patients with the creation of predictive models that grow with the supply of constant and real-time information, which help to optimize resources and improve health conditions, in addition, these solutions allow improving clinical management, reducing setbacks, optimize resources and focus attention on patients. In the provincial territory, small steps are being taken in the use of artificial intelligence, it is gradually incorporated into medicine; Its objective is not to replace clinical judgment, but to reaffirm and provide it through its tools and management [19].

With all of these advances, it is clear that it has the potential to revolutionize orthopedics and traumatology, improving patient care and raising the standard of treatment and rehabilitation [20]. As always, it is crucial to stay informed and adapt to these new tools to provide the best possible care for our patients. With constant growth in the volume of patient information being collected, artificial intelligence (AI) is proving to be a promising tool in medical research and in all aspects of patient care journeys and real-time monitoring, both to rehabilitation and surgical training, allowing detailed monitoring and more interactive and effective learning [21].

AI proves to be a powerful tool for analyzing large volumes of orthopedic data, including patient records, clinical trials and research. Employing Natural Language Processing (NLP) and data mining techniques, AI can identify patterns and correlations in information, leading to a better understanding of orthopedic conditions, more effective treatment strategies, and the development of innovative therapies [22]. Through predictive analytics, AI can anticipate patient outcomes and identify potential complications. By analyzing patient data and historical records, AI algorithms can flag risk factors and predict the likelihood of postoperative complications, such as infections or implant failures. This allows for proactive intervention and personalized patient care.

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