Clinical review of pediatric pilocytic astrocytomas treated at a tertiary care hospital in Pakistan

Abstract Background: Pilocytic Astrocytoma (PA) is a common type of brain tumor in the pediatric population. They have a fairly good prognosis. This study describes PAs in detail, with a focus on the demographic factors, presenting features, management and prognosis, and aims, to identify the negative outcome predictors in our population, which can affect the course of the disease. This article will add to the understanding of PAs from a third world perspective. Methods: The Aga Khan University medical records (1995 – 2007) were reviewed, to study the clinical features, management, and outcome of patients (0 – 15 years) with Pilocytic Astrocytomas (PAs) in our population. After a thorough review of the medical records, all the PAs diagnosed on the basis of histopathology at our Pathology Laboratory, during this period, were included in the study. Results: Twenty-two patients were included with a mean age of 9.25 years. Male-to-female ratio was 1 : 1. The most common presenting feature was a sign of increased intracranial pressure. The most common location was the cerebellum followed by the cerebrum. Fifteen patients underwent maximum surgical resection. Three had recurrence, despite no residual tumor. There were 10 Intensive Care Unit (ICU) admissions and one inpatient mortality. Fifteen patients followed up in the clinic: Eight had recurrence and four underwent repeat surgery (three showed clinical improvement). Hydrocephalus was a predictor of ICU admission. Solid consistency was found to be a marker of recurrence. Conclusion: Pilocytic Astrocytomas are the most common pediatric brain tumors in our population, commonly located in the cerebellum. Complete resection is the best treatment option, but some tumors are aggressive and recurrence is not uncommon. The possible negative outcome predictors are age, source of admission, extent of resection, hydrocephalus, and solid consistency

Cranial reconstruction after decompressive craniectomy: Prediction of complications using fuzzy logic

Introduction: Cranial reconstruction after decompressive craniectomy (DC) has been shown to be associated with a relatively high complication rate (16.4%-34%) compared with standard neurosurgical procedures (2%-5%). Most studies that have previously attempted to formulate a multivariate model for identifying factors predictive of postoperative complications of cranioplasty either were unsuccessful or yielded conflicting results. Therefore, fuzzy logic-based fuzzy inference system (FIS), which has proven to be a useful tool for risk prediction in medical and surgical conditions, was used in this study to identify predictors of complications of cranioplasty.Methods: A retrospective chart review of all the patients who underwent DC followed by elective cranioplasty at Aga Khan University Hospital, during a 10-year period (2000-2010), was carried out to collect data on 24 carefully selected preoperative variables or inputs. The proposed FIS had 24 inputs, 3 outputs, and a set of 7 fuzzy-based rules. All inputs were assigned degrees of membership, and complications were further divided into severe, minor, and least output classes with each of them representing 2 membership functions: less and more. For each set of inputs, a specific portion of the hypersurface was masked out. The centroid of this subsurface represented the defuzzified output corresponding to 1 percentage value for each output. The maximum of these outputs for each of the 3 output classes was selected to be the final output class. Each output class was compared to the actual outcome of patients, and positive predictive value, negative predictive value, sensitivity, and specificity of FIS for predicting complications were calculated.Results: A total of 89 patients (mean [SD] age, 33.1 [15.0] y; male-to-female ratio, 3:1) were included in the study. The common postoperative complications included seizures (14.6%), cerebrospinal fluid leak (4.5%), neurologic deficits (3.4%), hydrocephalus (3.4%), superficial wound infection (3.4%), and osteomyelitis (2.2%). The FIS correctly identified all 7 patients who developed severe complications after cranioplasty (true positives) and all 82 patients who did not develop severe complications (true negatives). Thus, the FIS has a sensitivity and specificity of 100% in predicting severe complications.Conclusions: Our study shows that the procedure of cranioplasty is associated with a high complication rate and that FIS has a 100% sensitivity and specificity in predicting severe complications after cranioplasty. It will prove to be an invaluable tool for clinicians once the results are validated by a similar prospective study with a larger sample size

Retrieval and classification methods for textured 3D models: a comparative study

International audienceThis paper presents a comparative study of six methods for the retrieval and classification of tex-tured 3D models, which have been selected as representative of the state of the art. To better analyse and control how methods deal with specific classes of geometric and texture deformations, we built a collection of 572 synthetic textured mesh models, in which each class includes multiple texture and geometric modifications of a small set of null models. Results show a challenging, yet lively, scenario and also reveal interesting insights in how to deal with texture information according to different approaches, possibly working in the CIELab as well as in modifications of the RGB colour space

Knowledge, attitudes, and practices among nurses in Pakistan towards diabetic foot

Introduction: Diabetic foot ulcers are a pressing complication of diabetes mellitus. Wound care requires a significant proportion of healthcare resources. It is imperative, therefore, for healthcare professionals to possess sound knowledge of the disease along with a positive attitude to ensure better clinical practice. Our literature search revealed a scarcity of data pertaining to diabetic foot ulcers. Therefore, this study aims to evaluate the knowledge and attitudes of nurses regarding diabetic foot care. Methods: A cross-sectional study design was employed, a pre-validated and pre-tested questionnaire was used to collect data from a sample size of 250 nurses working at two tertiary care hospitals in Karachi, Pakistan. The study was conducted over a period of three months (January to March 2018) and included all nurses who possessed at least one year of clinical experience in diabetic ulcer care. The statistical software employed was SPSS version 19 (IBM Corp., Armonk, NY, US). Non-parametric tests and descriptive statistics were used for data analysis and statistical significance was assumed at a p-value of less than 0.5. Results: Only 54% of the nurses in our study possessed adequate knowledge of diabetic foot ulcers. The mean score of knowledge was 74.9 (±9.5). Macdonald’s standard criteria for learning outcomes was used to gauge the knowledge levels of our study population. Nurses performed best in the domain of ulcer care with 65.3% of the participants possessing good knowledge of the topic. The overall attitude of nurses towards patients with diabetic ulcers was positive. Conclusion: This study highlights important gaps in nurses’ knowledge and sheds light on the lack of evidence-based practice. Poor knowledge can compromise healthcare standards, even with the presence of positive attitudes. Hence, a comprehensive revision of nursing curricula across local tertiary hospitals for allowing nurses to update their knowledge is warrante

Shape Retrieval of Non-rigid 3D Human Models

3D models of humans are commonly used within computer graphics and vision, and so the ability to distinguish between body shapes is an important shape retrieval problem. We extend our recent paper which provided a benchmark for testing non-rigid 3D shape retrieval algorithms on 3D human models. This benchmark provided a far stricter challenge than previous shape benchmarks. We have added 145 new models for use as a separate training set, in order to standardise the training data used and provide a fairer comparison. We have also included experiments with the FAUST dataset of human scans. All participants of the previous benchmark study have taken part in the new tests reported here, many providing updated results using the new data. In addition, further participants have also taken part, and we provide extra analysis of the retrieval results. A total of 25 different shape retrieval methods are compared

A methodology to estimate the potential to move inpatient to one day surgery

BACKGROUND: The proportion of surgery performed as a day case varies greatly between countries. Low rates suggest a large growth potential in many countries. Measuring the potential development of one day surgery should be grounded on a comprehensive list of eligible procedures, based on a priori criteria, independent of local practices. We propose an algorithmic method, using only routinely available hospital data to identify surgical hospitalizations that could have been performed as one day treatment. METHODS: Moving inpatient surgery to one day surgery was considered feasible if at least one surgical intervention was eligible for one day surgery and if none of the following criteria were present: intervention or affection requiring an inpatient stay, patient transferred or died, and length of stay greater than four days. The eligibility of a procedure to be treated as a day case was mainly established on three a priori criteria: surgical access (endoscopic or not), the invasiveness of the procedure and the size of the operated organ. Few overrides of these criteria occurred when procedures were associated with risk of immediate complications, slow physiological recovery or pain treatment requiring hospital infrastructure. The algorithm was applied to a random sample of one million inpatient US stays and more than 600 thousand Swiss inpatient stays, in the year 2002. RESULTS: The validity of our method was demonstrated by the few discrepancies between the a priori criteria based list of eligible procedures, and a state list used for reimbursement purposes, the low proportion of hospitalizations eligible for one day care found in the US sample (4.9 versus 19.4% in the Swiss sample), and the distribution of the elective procedures found eligible in Swiss hospitals, well supported by the literature. There were large variations of the proportion of candidates for one day surgery among elective surgical hospitalizations between Swiss hospitals (3 to 45.3%). CONCLUSION: The proposed approach allows the monitoring of the proportion of inpatient stay candidates for one day surgery. It could be used for infrastructure planning, resources negotiation and the surveillance of appropriate resource utilization