In Malaysia, tissue banking activities began in Universiti Sains Malaysia (USM) Tissue Bank in early 1990s. Since then a few other bone banks have been set up in other government hospitals and institutions. However, these banks are not governed by the national authority. In addition there is no requirement set by the national regulatory authority on coding and traceability for donated human tissues for transplantation. Hence, USM Tissue Bank has taken the initiatives to adopt a system that enables the traceability of tissues between the donor, the processed tissue and the recipient based on other international standards for tissue banks. The traceability trail has been effective and the bank is certified compliance to the international standard ISO 9001:2008.
Perforation of the sigmoid colon is an occasional complication of blunt injury to the abdomen. We report three cases following abdominal massage (urut) by traditional healers (bomohs) in which no other underlying pathology was found.
The aim of this study was to investigate the work-related musculoskeletal disorders (WMSDs) among workers in wall plastering jobs within the construction industry.
This paper describes the development of the Workplace Ergonomic Risk Assessment (WERA) for investigating the physical risk factor associated with work-related musculoskeletal disorders (WMSDs). The initial development of WERA tool involved the following procedures: (1) first stage, development of WERA prototype from literature review, (2) second stage, evaluation of the psychometric properties including (a) validity trials and (b) reliability and usability trials. In the validity trials, the relationship of the individual WERA body part scores to the development of pain or discomfort is statistically significant for the wrist, shoulder and back regions. It shows that the WERA assessment provided a good indication of work-related musculoskeletal disorders which might be reported as pain, ache or discomfort in the relevant body regions. In the reliability trials, the results of inter-observer reliability shows that moderate agreement among the observers while from the feedback questionnaire survey about the usability of WERA tool, all participants including expert and management teams agreed that the prototype of WERA tool was easy and quick to use, applicable to workplace assessment for the wide range of job/task and valuable at work. It was confirmed that there was no need of training required to do WERA assessment. Therefore, the WERA assessment has been designed for easy and quick use, and for those who are trained to use it do not need previous skills in observation techniques although this would be an advantage. As WERA is a pen and paper technique that can be used without any special equipment, WERA assessment can be done in any space of workplaces without disruption to the task that have been observed.
The purpose of this study was to investigate the prevalence of body part symptoms and sources of injury/discomfort among workers in a car tyre service centre. Questionnaire survey and interview session were used to identify the level of body discomfort areas and sources of injury or discomfort. From questionnaire survey findings, 12 of respondents have body discomfort in the neck (66.7%%), shoulder (83.3%), elbow/forearm (75%), hand/wrist (91.7%), knee (58.3%), lower leg (75%), ankle/foot (33%) and lower back (30%). The main sources of injury/discomfort in the workplace were poor body posture (75%), bending the back (75%), highly repetitive motions (75%), lifting heavy objects (83.3%), the long-term standing (66.7%), long-term squatting (58.3%), bending the neck (66.7%) and high hand force (58.3%). About 50% reported that poor workplace design also contributed to injury while 41.7% mentioned the use of hand tools. To address modifying the ergonomic hazards, engineering controls and administrative controls can be used. The study will be useful to ergonomists, researchers, consultants, workshop managers, maintenance workers and others concerned with identifying body part symptoms and sources of injury/discomfort at the workplace.
Patients with Benign Prostatic Hyperplasia (BPH) commonly presents with lower urinary tract symptoms (LUTS), which can be of obstructive symptoms such as hesitancy, incomplete voiding, post void dribbling or of irritative symptoms such as urgency, frequency and nocturia. Various recent studies indicate that nocturia is a very important and bothersome lower urinary tract symptom especially among patients with Benign Prostatic Hyperplasia (BPH). The aims of the study was to determine the frequency of common urinary symptoms among patients with BPH in HUSM as well as to evaluate the extent of bothersomeness of each and every symptom to these patients. This study too was aimed at evaluating the success of TURP in resolving pre operative LUTS. This was a questionnaire-based survey using a validated ICSBPH model whereby patients with BPH were selected and quizzed personally by an investigator. A subset of patients who had undergone TURP were further questioned regarding their satisfaction with the procedure. When nocturia is defined as waking up at night once or more to pass urine, the prevalence of nocturia was about 90%, but only 1 in 6 patients considered this is a very serious symptom. Even if the definition was changed to waking up twice or more, the prevalence is still quite high at over 80%. Urgency were noted in half of the patients, but only a quarter of them consider it a serious problem. 1 in 5 patients experienced significant leak and almost all consider it serious. About one third of the studied population had to be catheterized due to urinary obstruction and interestingly only about half of them considered it as a very serious event. Overall, a great majority of these patients considered suffering from these urinary symptoms for the rest of their life as very devastating. This study conclude that although the prevalence of nocturia was high among BPH patients, but it was not considered serious by majority of them. In fact, LUTS in our BPH patients did not differ much from BPH patients elsewhere. On the whole, TURP resolved most of the LUTS effectively.
A digit 8-shaped resonator inspired metamaterial is proposed herein for sensor applications. The resonator is surrounded by a ground frame and excited by a microstrip feedline. The measurement of the sensor can be performed using common laboratory facilities in lieu of using the waveguide, as the resonator, ground frame, and feedline are all on the same microstrip. To achieve metamaterial properties, more than one unit cell is usually utilized, whereas, in this work, a single cell was used to achieve the metamaterial characteristics. The properties of the metamaterial were investigated to find the relationship between the simulation and measurements. The proposed metamaterial sensor shows considerable sensitivity in sensor application. For the sensor application, FR4 and Rogers RO4350 materials were used as the over-layer. The sensor can measure dielectric thickness with a sensitivity of 625 MHz/mm, 468 MHz/mm, and 354 MHz/mm for the single over-layer, double over-layers, and multiple over-layers, respectively. The proposed prototype can be utilized in several applications where metamaterial characteristics are required.
Flashover on transmission line insulators is one of the major causes of line outages due to contamination from the environment or ageing. Power utility companies practicing predictive maintenance are currently exploring novel non-contact methods to monitor insulator surface discharge activities to prevent flashover. This paper presents an investigation on the UV pulse signals detected using UV pulse sensor due to the discharges on the insulator surfaces under varying contamination levels and insulator ages. Unaged and naturally aged insulators (0 to >20 years) were artificially contaminated (none, light to heavy contamination). The electrical stresses on the insulator surfaces were varied to generate varying discharge intensity levels on the surfaces of the insulator. The DC and harmonic components of UV pulse signals detected during surface discharges were recorded and analysed. Results show a positive correlation between the discharge intensity level of contaminated and aged transmission insulators with the DC and harmonic components of the UV pulse signals. Furthermore, the study revealed that under dry insulator surface conditions, insulator ageing has a more profound effect during discharges than contamination level. The findings from this study suggest that the use of UV pulse sensors to monitor UV pulse signals emitted during insulator surface discharges can be another novel non-contact method of monitoring transmission line insulator surface conditions.
Medication Errors (MEs) are still significant challenges, especially in nonautomated health systems. Qualitative studies are mostly used to identify the parameters involved in MEs. Failing to provide accurate information in expert-based decisions can provoke unrealistic results and inappropriate corrective actions eventually. However, mostly, some levels of uncertainty accompany the decisions in real practice. This study tries to present a hybrid decision-making approach to assigning different weights to risk factors and considering the uncertainty in the ranking process in the Failure Modes and Effect Analysis (FMEA) technique. Initially, significant MEs are identified by three groups of qualified experts (doctors, nurses, and pharmacists). Afterward, for assigning weights to the risk factors, Z-number couples with the Stepwise Weight Assessment Ratio Analysis (SWARA) method, named Z-SWARA, to add reliability concept in the decision-making process. Finally, the identified MEs are ranked through the developed Weighted Aggregated Sum Product Assessment (WASPAS) method, namely, Z-WASPAS. To demonstrate the applicability of the proposed approach, the ranking results compare with typical methods, such as fuzzy-WASPAS and FMEA. The findings of the present study highlight improper medication administration as the main failure mode, which can result in a fatality or patient injury. Moreover, the utilization of multiple-criteria decision-making methods in combination with Z-number can be a useful tool in the healthcare management field since it can address the problems by considering reliability and uncertainty simultaneously.
Cardiothoracic intensive care unit (CICU) nurses have shared the role and responsibility for ventilator-weaning to expedite decision-making in patient care. However, the actions taken are based on individual's unstructured training experience as there is no clinical practice guideline (CPG) for nurses in Malaysia. Hence, this study aims to design a CPG for the process of weaning from mechanical ventilation (MV) for a structured nursing training in a CICU at the National Heart Institute (Institut Jantung Negara, IJN) Malaysia. The Fuzzy Delphi Method (FDM) was employed to seek consensus among a panel of 30 experts in cardiac clinical practice on the guidelines. First, five experts were interviewed and their responses were transcribed and analyzed to develop the items for a FDM questionnaire. The questionnaire, comprising of 73 items, was distributed to the panel and their responses were analyzed for consensus on the design of the CPG. The findings suggested that the requirements expected for the nurses include: (a) the ability to interpret arterial blood gases, (b) knowledge and skills on the basics of mechanical ventilation, and (c) having a minimum 1-year working experience in the ICU. On the other hand, the CPG should mainly focus on developing an ability to identify criteria of patient eligible for weaning from MV. The learning content should focus on: (a) developing the understanding and reasoning for weaning and extubating and (b) technique/algorithm for extubating and weaning. Also, the experts agreed that the log book/competency book should be used for evaluation of the program. The CPG for structured nursing training at IJN in the context of the study is important for developing the professionalism of CICU nurses in IJN and could be used for training nurses in other CICUs, so that decision for ventilator-weaning from postcardiac surgery could be expedited.
The COVID-19 pandemic is a global, national, and local public health concern which has caused a significant outbreak in all countries and regions for both males and females around the world. Automated detection of lung infections and their boundaries from medical images offers a great potential to augment the patient treatment healthcare strategies for tackling COVID-19 and its impacts. Detecting this disease from lung CT scan images is perhaps one of the fastest ways to diagnose patients. However, finding the presence of infected tissues and segment them from CT slices faces numerous challenges, including similar adjacent tissues, vague boundary, and erratic infections. To eliminate these obstacles, we propose a two-route convolutional neural network (CNN) by extracting global and local features for detecting and classifying COVID-19 infection from CT images. Each pixel from the image is classified into the normal and infected tissues. For improving the classification accuracy, we used two different strategies including fuzzy c-means clustering and local directional pattern (LDN) encoding methods to represent the input image differently. This allows us to find more complex pattern from the image. To overcome the overfitting problems due to small samples, an augmentation approach is utilized. The results demonstrated that the proposed framework achieved precision 96%, recall 97%, F score, average surface distance (ASD) of 2.8 ± 0.3 mm, and volume overlap error (VOE) of 5.6 ± 1.2%.