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Selection of treatment according to the differentiation of syndromes is the kernel theory of traditional Chinese medicine. Different symptoms play different roles in the differentiation of syndromes. It is important to know the contribution rate of each symptom quantitatively. How to find the most informative symptoms combination served as the differential diagnosis standard of a syndrome is also a significant problem in traditional Chinese medicine too. Mutual information can measure arbitrary statistical dependence between variables. Features selection based on mutual information has been widely applied. In this paper, a new definition of contribution rate based on mutual information is proposed. In the definition, joint mutual information needs some form of calculation. An efficient calculation method of joint mutual information and a novel features selection method are developed. Here combinatorial contribution rate is defined as a stopping rule instead of prescribing the number of selected symptoms. The selected symptoms are input to a supervised BP neural network for diagnosing syndrome. Finally, the feasibility of the method is illustrated through a TCM example.

The syndrome is the basic pathological unit and the key concept in traditional Chinese medicine (TCM), and the herbal remedy is prescribed according to the syndrome a patient catches. Nevertheless, few studies are dedicated to investigate the number of syndromes in chronic renal failure (CRF) patients and what these syndromes are. In this paper, we carry out a clinical epidemiology survey and obtain 601 CRF cases, including 72 symptoms in each report. Based on association delineated by mutual information, we propose a novel pattern discovery algorithm to discover syndromes, which probably have overlapped symptoms in TCM. A revised version of mutual information is presented here to discriminate positive and negative association. The algorithm self-organizedly discovers 16 effective patterns, each of which is verified manually by TCM physicians to recognize the syndrome it belongs to. The super-additivity of cluster by mutual information is proved and n-class association concept is introduced in our model to reduce computational complexity. Validation of the algorithm is performed by using the syndrome data and consolidated clinically to have 16 patterns. The results indicate that the algorithm achieves a high sensitivity with 96.48% and each classified pattern is of clinical significance. Therefore, we conclude that the algorithm provides an excellent solution to chronic renal failure problem in the context of traditional Chinese medicine.

We describe a case of Hajdu-Cheney syndrome affecting the scaphotrapeziotrapezoid joint presently being treated non-operatively. This syndrome poses the problem of non-union when surgical intervention is required.

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Leveraging on External Expertise.

Cubital tunnel syndrome is the second most common nerve compression syndrome seen in the upper limb. Paresthesia and weakness are the two most common presentations in the hand. If left untreated, compression can lead to irreversible nerve damage, resulting in a loss of function of the forearm and hand. Therefore, recognizing the various clinical presentations of cubital tunnel syndrome can lead to early detection and prevention of nerve damage. Conservative management is usually tried first and involves supporting the elbow using a splint. If this fails and symptoms do not improve, surgical management is indicated. There are 3 main surgical techniques used to relieve compression of the nerve. These are simple decompression, anterior transposition and medial epicondylectomy. Studies comparing the techniques have demonstrated particular advantages to using one or another. However, the overall technique of choice is based on both the clinical scenario and the surgeon’s digression. Following primary cubital tunnel surgery, recurrent symptoms can often occur due to a variety of pathological and non-pathological causes and revision surgery is usually warranted. This article provides a complete review of cubital tunnel syndrome.

Lack of specific guidelines in the literature renders management of radial longitudinal deficiency (RLD) exceedingly diverse. This diversity in treatment approaches can lead to variability in outcomes and pose a challenge in determining the most effective interventions for each individual case of RLD. Surgeons must carefully consider the unique characteristics and needs of each patient when developing a treatment plan for this complex condition. Around 40% of cases are linked to syndromes like Holt–Oram syndrome, thrombocytopenia absent radius (TAR) syndrome, Fanconi anaemia and VACTERL. Hand surgeons must be knowledgeable about these conditions, as they may be the first to identify these syndromes in children. Associated elbow stiffness can also be a crucial factor in treatment decision-making. Although this condition has been studied for more than 10 decades, the surgical treatment that is currently available is not completely successful in restoring ‘normal’ wrist function and appearance. Centralisation and radialisation procedures continue to be the cornerstones of surgical treatment. Many innovative approaches include altering the biomechanics of this condition with bony or soft tissue procedures and microvascular techniques. Understanding the proximal limb changes is crucial in the holistic management of this challenging malformation. This article presents a treatment algorithm based on literature evidence and our clinical experience.

Level of Evidence: Level V (Therapeutic)

Objective: To investigate the distribution and characteristics of traditional Chinese medicine (TCM) syndromes and its elements on chronic bronchitis (CB) based on real-world data (RWD) so as to optimize the treatment strategies.

Methods: A real-world study based on 2207 medical records collected from five hospitals in China, to explore the relationship between TCM syndrome and CB using the big data methods. Factor analyses were used to reduce the dimensions of TCM syndrome elements and found common factors. Additionally, cluster analyses were performed to value combinations of TCM syndrome element. Finally, association rule analyses were employed to assess the structures of TCM syndromes elements and estimate the patterns of TCM syndrome.

Results: A total of 21 TCM syndromes were extracted from RWD in this work. There were four TCM syndromes consisting of Tan_Zhuo_Zu_Fei, Tan_Re_Yong_Fei, Feng_Han_Xi_Fei, and Feng_Re_Fan_Fei with $>5.0$% frequency based on the distribution frequency. The two top Xu TCM syndromes of Fei_Yin_Xu and Fei_Shen_Qi_Xu were identified. The top six pathogenesis TCM syndrome elements were Tan, Huo, Feng, Han, Qi_Xu, and Yin_Xu. Factor analyses, cluster analyses, and association rule analyses demonstrated that Tan, Huo, Feng, Han, Qi-Xu, Yin-Xu, Fei, and Shen were the core TCM syndrome elements.

Conclusion: The four common Shi TCM syndromes of Tan_Zhuo_Zu_Fei, Tan_Re_Yong_Fei, Feng_Han_Xi_Fei, and Feng_Re_Fan_Fei for CB were detected in the real world study, and the two Xu TCM syndromes of Fei_Yin_Xu and Fei_Shen_Qi_Xu were identified. The Mix TCM syndrome of Fei_Pi_Qi_Xu_Tan_Shi_Yun_Fei was the main syndrome. The core TCM syndrome elements of Tan, Huo, Feng, Han, Qi_Xu, and Yin_Xu, Fei, and Shen were determined in the entire sample.

In [5] a method is described to reformulate Sudan's algorithm for list decoding (see [7]) into solving a linear system of equations involving (generalized) syndromes. The advantage of this description is that one has to deal with a smaller system, as well as that one can apply faster algorithms (e.g. Sakata's algorithm [6]). In this paper we investigate how to do the same for the more general Guruswami-Sudan algorithm for list decoding. We concentrate our investigation on RS-codes and one-point Hermitian codes.