Correlation of Kennedy Osteitis Score with the Tissue and Peripheral Eosinophil Counts in Patients of Eosinophilic Chronic Rhinosinusitis.

Background: The presence of osteoid bone in chronic rhinosinusitis especially the eosinophilic subtype is commonly associated with recalcitrant illness. In practice, the radiological features of osteitis sinus alterations are frequently described, but the clinical and histopathologic implications are not well understood. Objective: This study was done to correlate the radiological and the clinico-histopathological aspects in patients of eosinophilic chronic rhinosinusitis. Methods: A cross-sectional study was done on sixty patients of chronic rhinosinusitis with nasal polyposis (CRSwNP) patients especially the eosinophilic subtype undergoing sinus surgery. Radiologically, osteitis was graded using standards that had already been published in the literature. Analysis was done on the relationships between CT documented osteitis, histopathological, and peripheral eosinophilic counts in patients of eosinophilic chronic rhinosinusitis. Results: The patients with higher tissue eosinophilia and higher peripheral eosinophils had higher osteitis score. Pearson's correlation coefficient between Tissue Eosinophils and KOS was highly significant with p-value <0.001 (0.891). R2 value for KOS versus Tissue Eosinophils was 79.44%,implying that 79.44% variations were explained by Tissue Eosinophils in KOS. And R2 value for KOS versus Peripheral Eosinophils was 74.26%, implying that 74.26% variations were explained by Peripheral Eosinophils in KOS. Thereby, showing a positive relationship between the variables that were studied. Conclusion: Kennedy Osteitis Score, histopathological and peripheral eosinophilia can be used as a marker to predict the disease severity in eosinophilic chronic rhinosinusitis.

The survival and clinical performance of anterior composite resin restorations and posterior indirect and cast restorations used to treat generalised tooth wear.

Objective To evaluate the survival and clinical performance of restorative materials used in the rehabilitation of generalised severe tooth wear within a UK NHS postgraduate teaching hospital.Methods The clinical performance of 527 restorations on 20 patients with generalised severe tooth wear was reviewed after a mean period of five years. Anterior teeth were restored with direct composite resin and posterior teeth with indirect restorations. The study used the modified United States Public Health Service criteria for restoration assessment. Survival of the restorations was analysed using Kaplan-Meier survival curves, the log-rank test and the Cox proportional hazards regression analysis.Results The sample included 20 participants: 13 men and 7 women, with a median age of 51.8 years (range: 33-73 years). The median survival time for all restorations was 11.3 years when major failures were considered and 5.9 years for restorations when all types of failure were considered. A median survival time of 5.9 years for composite resin restorations and over seven years for cast restorations was found when considering all failures. Composite resin restorations commonly failed as a result of fracture, wear and marginal discolouration. Factors significantly influencing restoration survival were the material used, aetiology, incisal relationship and tooth location. The biological complications associated with this treatment regime were rare. Patient satisfaction remained generally high, with greatest dissatisfaction related to treatment time.Conclusions The use of anterior composite resin with posterior indirect restorations to treat generalised severe tooth wear is a viable treatment modality with very few major complications.

Frequency of fungal isolation and antifungal susceptibility pattern of the fungal isolates from nasal polyps of chronic rhinosinusitis patients at a tertiary care centre in north India.

Sinonasal polyposis is considered to be the end-result of a chronic inflammatory process in the sinonasal mucosa. Its underlying mechanisms are still unclear, but the involvement of fungi has been suggested for many years. In the present study, we retrospectively evaluated the clinical and mycological profile of 161 patients with chronic rhinosinusitis (CRS) and nasal polyps who were undergoing surgery at our tertiary care facility during 2002 to 2010. CT scan findings and per-operative presence of allergic mucin were provisionally suggestive of fungal rhinosinusitis (FRS) in all the patients. Total serum IgE and peripheral eosinophilia were noted. Histological examination of polyp tissue showed eosinophilic mucin in 100% of the cases and the incidence of allergic fungal rhinosinusitis (AFRS) was 83.9% in the patient population. KOH and/or culture were positive for fungal hyphae or yeast in 93% (150/161) of the patients. Aspergillus spp. were the most commonly recovered isolates (70%). MICs of all A. flavus and A. fumigatus isolates were within the susceptible zone for itraconazole, voriconazole, and amphoterecin B. In conclusion, allergic fungal rhinosinusitis (FRS) is a common disorder in patients with sinonasal polyposis and due to its recurrent and intractable nature, a high degree of clinical suspicion for the presence of FRS in nasal polyposis should be considered.

Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks.

Although numerous R-peak detectors have been proposed in the literature, their robustness and performance levels may significantly deteriorate in low-quality and noisy signals acquired from mobile electrocardiogram (ECG) sensors, such as Holter monitors. Recently, this issue has been addressed by deep 1-D convolutional neural networks (CNNs) that have achieved state-of-the-art performance levels in Holter monitors; however, they pose a high complexity level that requires special parallelized hardware setup for real-time processing. On the other hand, their performance deteriorates when a compact network configuration is used instead. This is an expected outcome as recent studies have demonstrated that the learning performance of CNNs is limited due to their strictly homogenous configuration with the sole linear neuron model. This has been addressed by operational neural networks (ONNs) with their heterogenous network configuration encapsulating neurons with various nonlinear operators. In this study, to further boost the peak detection performance along with an elegant computational efficiency, we propose 1-D Self-Organized ONNs (Self-ONNs) with generative neurons. The most crucial advantage of 1-D Self-ONNs over the ONNs is their self-organization capability that voids the need to search for the best operator set per neuron since each generative neuron has the ability to create the optimal operator during training. The experimental results over the China Physiological Signal Challenge-2020 (CPSC) dataset with more than one million ECG beats show that the proposed 1-D Self-ONNs can significantly surpass the state-of-the-art deep CNN with less computational complexity. Results demonstrate that the proposed solution achieves a 99.10% F1-score, 99.79% sensitivity, and 98.42% positive predictivity in the CPSC dataset, which is the best R-peak detection performance ever achieved.

Real-Time Patient-Specific ECG Classification by 1D Self-Operational Neural Networks.

OBJECTIVE: Despitethe proliferation of numerous deep learning methods proposed for generic ECG classification and arrhythmia detection, compact systems with the real-time ability and high accuracy for classifying patient-specific ECG are still few. Particularly, the scarcity of patient-specific data poses an ultimate challenge to any classifier. Recently, compact 1D Convolutional Neural Networks (CNNs) have achieved the state-of-the-art performance level for the accurate classification of ventricular and supraventricular ectopic beats. However, several studies have demonstrated the fact that the learning performance of the conventional CNNs is limited because they are homogenous networks with a basic (linear) neuron model. In order to address this deficiency and further boost the patient-specific ECG classification performance, in this study, we propose 1D Self-organized Operational Neural Networks (1D Self-ONNs). METHODS: Due to its self-organization capability, Self-ONNs have the utmost advantage and superiority over conventional ONNs where the prior operator search within the operator set library to find the best possible set of operators is entirely avoided. RESULTS: Under AAMI recommendations and with minimal common training data used, over the entire MIT-BIH dataset 1D Self-ONNs have achieved 98% and 99.04% average accuracies, 76.6% and 93.7% average F1 scores on supra-ventricular and ventricular ectopic beat (VEB) classifications, respectively, which is the highest performance level ever reported. CONCLUSION: As the first study where 1D Self-ONNs are ever proposed for a classification task, our results over the MIT-BIH arrhythmia benchmark database demonstrate that 1D Self-ONNs can surpass 1D CNNs with a significant margin while having a similar computational complexity.

Unusual presentations of primary head and neck tuberculosis and review of literature.

BACKGROUND/PURPOSE: The diagnosis of TB in the head & neck region is challenging due to diverse presentations and due to changing clinical pictures. The aim of this article is to report three unusual primary cases of head and neck tuberculosis in immunocompetent patients presenting to our hospital with description of their clinical presentation, appropriate diagnostic methods used and treatment response of these patients. METHODS: Three clinical cases were of primary tuberculosis of the lacrimal system, the thyroid gland and of the temporal space were clinically worked up. The aspirate from the swellings were sent for Cytology and Gene Xpert tests. RESULTS: The Gene Xpert tests were positive in these unusual cases and aided the Cytology in promptly confirming the diagnosis which otherwise would be missed if staining for AFB is negative. ATT was started and responded well to the treatment. CONCLUSION: These cases demonstrate the importance of having a high index of suspicion for tuberculosis as a cause of head and neck swellings, especially in developing countries. It also illustrates the value of needle aspiration in such swellings and sending it for cytology and Gene Xpert for early diagnosis of tuberculosis.

Management of Fungal Rhinosinusitis: Experience From a Tertiary Care Centre in North India.

Introduction Fungal rhinosinusitis (FRS) has increased over the past few decades due to the rampant use of antibiotics, steroids, immunosuppressive drugs, increased incidence of HIV and uncontrolled diabetes. The current study reviews the types, clinical presentation, microbiology, histopathology and outcomes related to FRS in a tertiary care center in North India. Methods We retrospectively reviewed the clinical and follow-up records of patients diagnosed with FRS over three years. The data reviewed included clinical workup, ophthalmological profile, comorbidities, immunological status, radiological investigations, intraoperative and histopathological findings, treatment and follow-up records. In addition, we performed a descriptive analysis of the reviewed data. Results The study consisted of 30 FRS patients (16 male, 14 female). In that, 77% of cases were of allergic FRS, while fungal ball, chronic invasive, chronic granulomatous and acute invasive FRS represented 3%, 10%, 3% and 7% cases, respectively. The most common presentation in non-invasive forms was nasal obstruction, nasal discharge, hyposmia and polyposis, while it was facial pain and headache in the invasive varieties. After appropriate medical and surgical management through endoscopic sinus surgery, the recurrence rate in non-invasive and invasive fungal sinusitis was 16.6% and 20.8%, respectively. There was nil mortality at a minimum of one year of follow-up. Conclusion The non-invasive forms of FRS are common and have a relatively mild course. Early medical and surgical intervention and management of the underlying comorbidities are the key factors in managing invasive FRS. Close follow-up after surgery is also necessary for the timely detection and management of recurrences.

Analysis of the efficacy of the pectoralis major myocutaneous flap in reconstructive head and neck surgery.

INTRODUCTION: Although free flaps have been used predominantly in past decades for the soft tissue reconstruction of head and neck malignancies, Pectoralis major myocutaneous flap (PMMF) is still a reliable workhorse for patients with co-existing co-morbidities or low economic status where free flaps are not feasible. PATIENTS AND METHODS: It was a retrospective study done on 36 patients of head and neck malignancies over the period of 5 years in which PMMF was used as a method of reconstruction in our hospital. Patients were followed up for a period of one year and outcome of PMMF was evaluated. RESULTS: Out of 36 patients 31 were of oral cancer and 5 were of carcinoma hypopharynx. Incidence of total flap necrosis was nil and partial flap necrosis was 16.6%. Orocutaneous fistula was found in 16.6%, wound dehiscence was in 19.4% and infection was found in 13.5% of patients. Non-flap related complications were found in 13.8% of patients. 35 out of 36 patients (97.2%) eventually achieved satisfactory surgical outcome of PMMF reconstruction. CONCLUSION: PMMF is a reliable method of reconstruction for head and neck malignancies especially in basic healthcare settings. With minimal expertise and groundwork, it is still a cost-effective workhorse flap for head and neck reconstruction.

Blind ECG Restoration by Operational Cycle-GANs.

OBJECTIVE: ECG recordings often suffer from a set of artifacts with varying types, severities, and durations, and this makes an accurate diagnosis by machines or medical doctors difficult and unreliable. Numerous studies have proposed ECG denoising; however, they naturally fail to restore the actual ECG signal corrupted with such artifacts due to their simple and naive noise model. In this pilot study, we propose a novel approach for blind ECG restoration using cycle-consistent generative adversarial networks (Cycle-GANs) where the quality of the signal can be improved to a clinical level ECG regardless of the type and severity of the artifacts corrupting the signal. METHODS: To further boost the restoration performance, we propose 1D operational Cycle-GANs with the generative neuron model. RESULTS: The proposed approach has been evaluated extensively using one of the largest benchmark ECG datasets from the China Physiological Signal Challenge (CPSC-2020) with more than one million beats. Besides the quantitative and qualitative evaluations, a group of cardiologists performed medical evaluations to validate the quality and usability of the restored ECG, especially for an accurate arrhythmia diagnosis. SIGNIFICANCE: As a pioneer study in ECG restoration, the corrupted ECG signals can be restored to clinical level quality. CONCLUSION: By means of the proposed ECG restoration, the ECG diagnosis accuracy and performance can significantly improve.

Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs.

Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has become a potential field of research in recent years. Although several studies have been conducted, still there are some vital challenges present in the deployment of EEG-based biometrics, which is stable and capable of handling the real-world scenario. One of the key challenges is the large signal variability of EEG when recorded on different days or sessions which impedes the performance of biometric systems significantly. To address this issue, a session invariant multimodal Self-organized Operational Neural Network (Self-ONN) based ensemble model combining EEG and keystroke dynamics is proposed in this paper. Our model is tested successfully on a large number of sessions (10 recording days) with many challenging noisy and variable environments for the identification and authentication tasks. In most of the previous studies, training and testing were performed either over a single recording session (same day) only or without ensuring appropriate splitting of the data on multiple recording days. Unlike those studies, in our work, we have rigorously split the data so that train and test sets do not share the data of the same recording day. The proposed multimodal Self-ONN based ensemble model has achieved identification accuracy of 98% in rigorous validation cases and outperformed the equivalent ensemble of deep CNN models. A novel Self-ONN Siamese network has also been proposed to measure the similarity of templates during the authentication task instead of the commonly used simple distance measure techniques. The multimodal Siamese network reduces the Equal Error Rate (EER) to 1.56% in rigorous authentication. The obtained results indicate that the proposed multimodal Self-ONN model can automatically extract session invariant unique non-linear features to identify and authenticate users with high accuracy.

Self-organized operational neural networks for severe image restoration problems.

Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs. It has become the go-to methodology for tackling image restoration and has outperformed the traditional non-local class of methods. However, the top-performing networks are generally composed of many convolutional layers and hundreds of neurons, with trainable parameters in excess of several million. We claim that this is due to the inherently linear nature of convolution-based transformation, which is inadequate for handling severe restoration problems. Recently, a non-linear generalization of CNNs, called the operational neural networks (ONN), has been shown to outperform CNN on AWGN denoising. However, its formulation is burdened by a fixed collection of well-known non-linear operators and an exhaustive search to find the best possible configuration for a given architecture, whose efficacy is further limited by a fixed output layer operator assignment. In this study, we leverage the Taylor series-based function approximation to propose a self-organizing variant of ONNs, Self-ONNs, for image restoration, which synthesizes novel nodal transformations on-the-fly as part of the learning process, thus eliminating the need for redundant training runs for operator search. In addition, it enables a finer level of operator heterogeneity by diversifying individual connections of the receptive fields and weights. We perform a series of extensive ablation experiments across three severe image restoration tasks. Even when a strict equivalence of learnable parameters is imposed, Self-ONNs surpass CNNs by a considerable margin across all problems, improving the generalization performance by up to 3 dB in terms of PSNR.

Self-organized Operational Neural Networks with Generative Neurons.

Operational Neural Networks (ONNs) have recently been proposed to address the well-known limitations and drawbacks of conventional Convolutional Neural Networks (CNNs) such as network homogeneity with the sole linear neuron model. ONNs are heterogeneous networks with a generalized neuron model. However the operator search method in ONNs is not only computationally demanding, but the network heterogeneity is also limited since the same set of operators will then be used for all neurons in each layer. Moreover, the performance of ONNs directly depends on the operator set library used, which introduces a certain risk of performance degradation especially when the optimal operator set required for a particular task is missing from the library. In order to address these issues and achieve an ultimate heterogeneity level to boost the network diversity along with computational efficiency, in this study we propose Self-organized ONNs (Self-ONNs) with generative neurons that can adapt (optimize) the nodal operator of each connection during the training process. Moreover, this ability voids the need of having a fixed operator set library and the prior operator search within the library in order to find the best possible set of operators. We further formulate the training method to back-propagate the error through the operational layers of Self-ONNs. Experimental results over four challenging problems demonstrate the superior learning capability and computational efficiency of Self-ONNs over conventional ONNs and CNNs.

Analysis of the efficacy of the pectoralis major myocutaneous flap in reconstructive head and neck surgery.

INTRODUCTION: Although free flaps have been used predominantly in past decades for the soft tissue reconstruction of head and neck malignancies, Pectoralis major myocutaneous flap (PMMF) is still a reliable workhorse for patients with co-existing co-morbidities or low economic status where free flaps are not feasible. PATIENTS AND METHODS: It was a retrospective study done on 36 patients of head and neck malignancies over the period of 5 years in which PMMF was used as a method of reconstruction in our hospital. Patients were followed up for a period of one year and outcome of PMMF was evaluated. RESULTS: Out of 36 patients 31 were of oral cancer and 5 were of carcinoma hypopharynx. Incidence of total flap necrosis was nil and partial flap necrosis was 16.6%. Orocutaneous fistula was found in 16.6%, wound dehiscence was in 19.4% and infection was found in 13.5% of patients. Non-flap related complications were found in 13.8% of patients. 35 out of 36 patients (97.2%) eventually achieved satisfactory surgical outcome of PMMF reconstruction. CONCLUSION: PMMF is a reliable method of reconstruction for head and neck malignancies especially in basic healthcare settings. With minimal expertise and groundwork, it is still a cost-effective workhorse flap for head and neck reconstruction.

Human-in-the-Loop Predictive Analytics Using Statistical Learning.

The human-in-the-loop cyber-physical system provides numerous solutions for the challenges faced by the doctors or medical practitioners. There is a linear trend of advancement and automation in the medical field for the early diagnosis of several diseases. One of the critical and challenging diseases in the medical field is coma. In the medical research field, currently, the prediction of these diseases is performed only using the data gathered from the devices only; however, the human's input is much essential to accurately understand their health condition to take appropriate decision on time. Therefore, we have proposed a healthcare framework involving the concept of artificial intelligence in the human-in- the-loop cyber-physical system. This model works via a response loop in which the human's intention is concluded by gathering biological signals and context data, and then, the decision is interpreted to a system action that is recognizable to the human in the physical environment, thereby completing the loop. In this paper, we have designed a model for early prognosis of coma using the electroencephalogram dataset. In the proposed approach, we have achieved the best results using a statistical learning algorithm called autoregressive integrated moving average in comparison to artificial neural networks and long short-term memory models. In order to measure the efficiency of our model, we have used the root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE) value to evaluate the linear models as it gives the difference between the measured value and true or correct value. We have achieved the least possible error value for our dataset. To conduct this experiment, we used the dataset available in the phsyionet opensource community.

A robust approach for industrial small-object detection using an improved faster regional convolutional neural network.

With the increasing pace in the industrial sector, the need for a smart environment is also increasing and the production of industrial products in terms of quality always matters. There is a strong burden on the industrial environment to continue to reduce impulsive downtime, concert deprivation, and safety risks, which needs an efficient solution to detect and improve potential obligations as soon as possible. The systems working in industrial environments for generating industrial products are very fast and generate products rapidly, sometimes leading to faulty products. Therefore, this problem needs to be solved efficiently. Considering this problem in terms of faulty small-object detection, this study proposed an improved faster regional convolutional neural network-based model to detect the faults in the product images. We introduced a novel data-augmentation method along with a bi-cubic interpolation-based feature amplification method. A center loss is also introduced in the loss function to decrease the inter-class similarity issue. The experimental results show that the proposed improved model achieved better classification accuracy for detecting our small faulty objects. The proposed model performs better than the state-of-the-art methods.

Deranged Pulmonary Function Tests in Allergic Rhinitis in North Indian Patients.

INTRODUCTION: Significant associations between allergic rhinitis and bronchial asthma have been established and as a result of bronchial hyper-responsiveness, patients can have deranged pulmonary function tests. We aim to compare previous such studies with the result of our study done in India wherein we identify among allergic rhinitis patients who despite not having overt asthmatic symptoms, have pulmonary function derangements, quite possibly at a subclinical disease level. MATERIALS AND METHODS: We studied 74 patients of allergic rhinitis and after meticulous clinical work up, they underwent blood tests including hemogram, absolute eosinophil count, and total serum IgE followed by pulmonary function tests. RESULTS: Out of 74 patients 60 (81%) had intermittent allergic rhinitis whereas only 14 (19%) had persistent allergic rhinitis. Pulmonary function tests showed reversible obstruction, ie, >10% improvement in FEV1 with inhaled bronchodilators (as seen in asthma) in 18 (24.3%), mild obstruction in 14, and moderate obstruction in 4 cases. CONCLUSION: The study emphasizes the importance of pulmonary symptoms and the performance of pulmonary function tests in cases of allergic rhinitis patients to rule out latent asthma.

Variables affecting the change in systemic blood pressure in response to nasal CPAP in obstructive sleep apnea patients.

We hypothesized that an improvement in systemic blood pressure (BP) during continuous positive airway pressure (CPAP) treatment of obstructive sleep apnea (OSA) would be related to severity of hypertension (HTN), morphometric parameters such as body mass index, and level of CPAP adherence. We tested this hypothesis with a retrospective review of 85 consecutive OSA patients who had completed diagnostic and CPAP titration polysomnograms and were equipped with a CPAP-adherence monitoring system for a minimum of 1 month of observation. Sphygmomanometer-obtained BP readings were compared at baseline and after 4-6 weeks of CPAP therapy. Presentation BP was significantly and strongly associated with the change in BP seen with treatment. Those with an elevated systolic and diastolic BP and those with an elevation of either systolic or diastolic BP showed a significant fall in BP on CPAP. Those with a BP below the hypertensive range of 140/90 on presentation did not have a significant drop in BP with CPAP. There were no significant changes in systolic, diastolic, or mean BP when patients were categorized by the severity of HTN, as determined by the number of antihypertensive medications prescribed or if they were categorized by the degree of CPAP adherence, objectively determined by the average use of more or less than 4 h/night. We conclude that HTN at initial presentation is among the most important indicators of potential benefit of CPAP administration on BP.

Comparison of Accuracy Between a Conventional and Two Digital Intraoral Impression Techniques.

PURPOSE: To compare the accuracy (ie, precision and trueness) of full-arch impressions fabricated using either a conventional polyvinyl siloxane (PVS) material or one of two intraoral optical scanners. MATERIALS AND METHODS: Full-arch impressions of a reference model were obtained using addition silicone impression material (Aquasil Ultra; Dentsply Caulk) and two optical scanners (Trios, 3Shape, and CEREC Omnicam, Sirona). Surface matching software (Geomagic Control, 3D Systems) was used to superimpose the scans within groups to determine the mean deviations in precision and trueness (µm) between the scans, which were calculated for each group and compared statistically using one-way analysis of variance with post hoc Bonferroni (trueness) and Games-Howell (precision) tests (IBM SPSS ver 24, IBM UK). Qualitative analysis was also carried out from three-dimensional maps of differences between scans. RESULTS: Means and standard deviations (SD) of deviations in precision for conventional, Trios, and Omnicam groups were 21.7 (± 5.4), 49.9 (± 18.3), and 36.5 (± 11.12) µm, respectively. Means and SDs for deviations in trueness were 24.3 (± 5.7), 87.1 (± 7.9), and 80.3 (± 12.1) µm, respectively. The conventional impression showed statistically significantly improved mean precision (P < .006) and mean trueness (P < .001) compared to both digital impression procedures. There were no statistically significant differences in precision (P = .153) or trueness (P = .757) between the digital impressions. The qualitative analysis revealed local deviations along the palatal surfaces of the molars and incisal edges of the anterior teeth of < 100 µm. CONCLUSION: Conventional full-arch PVS impressions exhibited improved mean accuracy compared to two direct optical scanners. No significant differences were found between the two digital impression methods.

Stylalgia Revisited: Clinical Profile and Management.

INTRODUCTION: Eagle's syndrome is a constellation of signs secondary to an elongated styloid process or due to mineralization of the stylohyoid or stylomandibular ligament or the posterior belly of the digastric muscle. The syndrome includes symptoms ranging from stylalgia (i.e. pain in the tonsillar fossa, pharyngeal or hyoid region) to foreign-body sensation in the throat, cervicofacial pain, otalgia, or even increased salivation or giddiness. MATERIALS AND METHODS: We describe a clinical study of 12 patients with Eagle's syndrome, along with their clinical profile and the treatment offered. Patients were diagnosed based on history and clinical examination, as well as the Xylocaine 2% tonsillar fossa injection test. A visual analog scale (VAS) was used for comparison of pain before and up to 3 months after treatment. Radiology (orthopantomogram or three-dimensional computed tomography) was used for further exploration. Nine patients underwent tonsillo-styloidectomy surgery and three underwent medical treatment with pregabalin (75 mg/day). RESULTS: The majority of surgically-managed cases (88%) achieved a definitive benefit by tonsillo-styloidectomy surgery, whereas all medically managed cases achieved only short-term pain relief. CONCLUSIONS: Besides the common throat diseases, the symptoms associated with Eagle's syndrome may be similar to those due to cervicofacial neuralgias, dental, or temporo-mandibular joint diseases. Diagnosis is primarily based on symptomatology, physical examination and radiographic investigations, and should not be missed. Treatment by tonsillo-styloidectomy produces satisfactory results in stylalgia.

Analysis of the efficacy of the pectoralis major myocutaneous flap in reconstructive head and neck surgery

Introduction: Although free flaps have been used predominantly in past decades for the soft tissue reconstruction of head and neck malignancies, Pectoralis major myocutaneous flap (PMMF) is still a reliable workhorse for patients with co-existing co-morbidities or low economic status where free flaps are not feasible. Patients and methods: It was a retrospective study done on 36 patients of head and neck malignancies over the period of 5 years in which PMMF was used as a method of reconstruction in our hospital. Patients were followed up for a period of one year and outcome of PMMF was evaluated. Results: Out of 36 patients 31 were of oral cancer and 5 were of carcinoma hypopharynx. Incidence of total flap necrosis was nil and partial flap necrosis was 16.6%. Orocutaneous fistula was found in 16.6%, wound dehiscence was in 19.4% and infection was found in 13.5% of patients. Non-flap related complications were found in 13.8% of patients. 35 out of 36 patients (97.2%) eventually achieved satisfactory surgical outcome of PMMF reconstruction. Conclusion: PMMF is a reliable method of reconstruction for head and neck malignancies especially in basic healthcare settings. With minimal expertise and groundwork, it is still a cost-effective workhorse flap for head and neck reconstruction.(AU)

Introducción: Aunque se han utilizado colgajos libres, fundamentalmente en las últimas décadas, para la reconstrucción de tejido blando en tumores malignos de cabeza y cuello, el colgajo miocutáneo de pectoral mayor (PMMF) sigue siendo un método fidedigno para los pacientes con comorbilidades coexistentes o baja situación económica en la que no se tiene acceso a los colgajos libres. Pacientes y métodos: Estudio retrospectivo realizado en 36 pacientes con tumores malignos de cabeza y cuello a lo largo de un periodo de 5 años, en los que se utilizó PMMF como método de reconstrucción en nuestro hospital. Se realizó un seguimiento a los pacientes durante un periodo de un año, evaluándose el resultado de PMMF. Resultados: De los 36 pacientes, 31 tenían cáncer oral y 5 cáncer de hipofaringe. La incidencia de necrosis total del colgajo fue nula, y la de necrosis parcial fue del 16,6%. Se encontró fístula orocutánea en el 16,6% de los casos, dehiscencia de la herida en el 19,4% e infección en el 13,5% de los pacientes. Se encontraron complicaciones no relacionadas con el colgajo en un 13,8% de los pacientes. Treinta y cinco de los 36 pacientes (97,2%) lograron finalmente un resultado quirúrgico satisfactorio de reconstrucción con PMMF. Conclusión: El PMMF es un método de reconstrucción fiable para los tumores malignos de cabeza y cuello, especialmente en los entornos sanitarios básicos. Con experiencia y base preparatoria mínimas sigue siendo un colgajo fiable para la reconstrucción de cabeza y cuello.(AU)