Improving Trauma Care in India: the Potential Role of the Rural Trauma Team Development Course (RTTDC)

The Rural Trauma Team Development Course (RTTDC) was devised to optimize trauma resuscitation training in under-resourced rural institutions. This program appears ideal for India because of its dense traffic, large population, and high frequency of rural trauma. We report on the feasibility and desirability of introducing RTTDC in India. An instructor course for 20 faculties and a provider course for 23 were conducted in New Delhi, India. The courses were evaluated by multiple choice question (MCQ) performance, by rating the modules on a three-point scale (1 = very relevant, 2 = relevant, and 3 = not relevant) for communication skills, principles of performance improvement and patient safety (PIPS), and clinical scenarios. Evaluation questionnaires including desirability of promulgation in India were completed using a five-point Likert Scale (1 = strongly agree, 2 = agree, 3 = neutral, 4 = disagree, and 5 = strongly disagree). Overall written comments were also provided. Both faculty and providers improved post-course MCQ scores (p?<?0.05) with lower scores in the provider group. Seventy-eight percent faculty and 74 % providers rated the communication module very relevant. PIPS was rated very relevant by 72 % faculty and 65 % providers. There were over 150 comments, generally positive with over 90 % of both faculty and providers rating strongly agree to agree that the course be promulgated widely in India. The RTTDC including plans for promulgation was enthusiastically received in India, and its potential for improving trauma care including communication skills and PIPS appears excellent.     

Reconstruction of Chest Wall Using a Two-Layer Prolene Mesh and Bone Cement Sandwich

Wide surgical resection is the most effective treatment for the vast majority of chest wall tumors. This study evaluated the clinical success of chest wall reconstruction using a Prolene mesh and bone cement prosthetic sandwich. The records of all patients undergoing chest wall resection and reconstruction were reviewed. Surgical indications, the location and size of the chest wall defect, diaphragm resection, pulmonary performance, postoperative complications, and survival of each patient were recorded. From 1998 to 2008, 43 patients (27 male, 16 female; mean age of 48 years) underwent surgery in our department to treat malignant chest wall tumors: chondrosarcoma (23), osteosarcoma (8), spindle cell sarcoma (6), Ewing''s sarcoma (2), and others (4). Nine sternectomies and 34 antero-lateral and postero-lateral chest wall resections were performed. Postoperatively, nine patients experienced respiratory complications, and one patient died because of respiratory failure. The overall 4-year survival rate was 60 %. Chest wall reconstruction using a Prolene mesh and bone cement prosthetic sandwich is a safe and effective surgical procedure for major chest wall defects.     

Hypothenar island flap: A safe and excellent choice for little finger defects

Soft-tissue defects of the little finger are challenging especially when bone, tendon or vascular pedicle is exposed because of trauma. The hypothenar island flap is easy to harvest and has a good colour and texture match to the little finger pulp. We present nine clinical cases of soft tissue defects of the little finger covered using the reversed hypothenar fasciocutaneous island flap. This article intends to highlight the ease of elevation and good clinical results of the hypothenar flap which is rarely used.KEY WORDS: Hypothenar island flap, island flap, soft-tissue defects of the little finger     

Neural Network Based Response Prediction of rTMS in Major Depressive Disorder Using QEEG Cordance

Objective

The combination of repetitive transcranial magnetic stimulation (rTMS), a non-pharmacological form of therapy for treating major depressive disorder (MDD), and electroencephalogram (EEG) is a valuable tool for investigating the functional connectivity in the brain. This study aims to explore whether pre-treating frontal quantitative EEG (QEEG) cordance is associated with response to rTMS treatment among MDD patients by using an artificial intelligence approach, artificial neural network (ANN).

Methods

The artificial neural network using pre-treatment cordance of frontal QEEG classification was carried out to identify responder or non-responder to rTMS treatment among 55 MDD subjects. The classification performance was evaluated using k-fold cross-validation.

Results

The ANN classification identified responders to rTMS treatment with a sensitivity of 93.33%, and its overall accuracy reached to 89.09%. Area under Receiver Operating Characteristic (ROC) curve (AUC) value for responder detection using 6, 8 and 10 fold cross validation were 0.917, 0.823 and 0.894 respectively.

Conclusion

Potential utility of ANN approach method can be used as a clinical tool in administering rTMS therapy to a targeted group of subjects suffering from MDD. This methodology is more potentially useful to the clinician as prediction is possible using EEG data collected before this treatment process is initiated. It is worth using feature selection algorithms to raise the sensitivity and accuracy values.