High levels of anti-dengue IgM or IgG can be detected using numerous rapid diagnostic tests (RDTs). However, the sensitivity and specificity of these tests are reduced by changes in envelope glycoprotein antigenicity that inevitably occur in limited expression systems. A novel RDT was designed to enhance diagnostic sensitivity. Dengue viruses cultured in animal cells were used as antigens to retain the native viral coat protein. Monoclonal antibodies (mAbs) were then developed, for the first time, against domain I of envelope glycoprotein (EDI). The anti-dengue EDI mAb was employed as a capturer, and EDII and EDIII, which are mainly involved in the induction of neutralizing antibodies in patients, were fully available to bind to anti-dengue IgM or IgG in patients. A one-way automatic blood separation device prevented reverse migration of plasma and maximize the capture of anti-dengue antibodies at the test lines. A clinical evaluation in the field proved that the novel RDT (sensitivities of 96.5% and 96.7% for anti-dengue IgM and IgG) is more effective in detecting anti-dengue antibodies than two major commercial tests (sensitivities of 54.8% and 82% for SD BIOLINE; 50.4% and 75.3% for PanBio). The innovative format of RDT can be applied to other infectious viral diseases.
The aim of the study was to validate the Malay version of the General Quentionnaire (GHQ-12) in patients with psychiatric morbidity secondary to urological disorder. Validity and reliability were studied in patients with lower urinary tract symptoms (LUTS) and patients without LUTS. Internal consistency was excellent. A high degree of internal consistency was observed for each of the 12 items and total scores (Cronbach's alpha value = 0.50 and higher and 0.65 respectively. Test-retest correlation coefficient for the 12 items scores was highly significant. Intraclass correlation coefficient was high (ICC=0.47 and above). A significant level between baseline and post-treatment scores were observed across 3 items in the surgical group. The Mal-GHQ-12 is a suitable, reliable, valid and sensitive to clinical change in the Malaysian population.
To evaluate the performance of contrastenhanced ultrasound (CEUS) in the risk stratification of indeterminate renal lesions picked up incidentally on abdominal imaging, in patients with renal impairment.
The primary objective of this study was to evaluate the specificity and sensitivity of diffusion weighted MR imaging (DWI) in the differentiation and characterisation between benign and malignant vertebral compression fractures compared with conventional T1 WI, T2 WI and fat suppressed contrast enhanced T1 WI in the Malaysian population.
Mycobacterium tuberculosis is known to cause pulmonary and extrapulmonary tuberculosis. This organism showed special phylogeographical specificity. Here, we report the complete genome sequence of M. tuberculosis clinical isolate spoligotype SIT745/EAI1-MYS, which was isolated from a Malaysian tuberculosis patient.
Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are 'traffic light ahead' or 'pedestrian crossing' indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications.
Currently, it is almost impossible to diagnose a patient at the onset of
sepsis due to the lack of real-time metrics with high sensitivity and specificity. The
purpose of the present study is to determine the diagnostic value of model-based insulin
sensitivity (SI) as a new sepsis biomarker in critically ill patients, and compare its
performance to classical inflammatory parameters. (Copied from article).
Objective: The primary objective of this study was to describe the neuroimaging changes of tuberculous meningitis (TBM), and to determine the role of neuroimaging in the diagnosis of TBM.
Methods: Between January 2009 and July 2015, we prospectively recruited TBM patients in two hospitals in Malaysia. Neuroimaging was performed and findings were recorded. The control consists of other types of meningo-encephalitis seen over the same period.
Results: Fifty four TBM patients were recruited. Leptomeningeal enhancement was seen in 39 (72.2%) patients, commonly at prepontine cistern and interpeduncular fossa. Hydrocephalus was observed in 38 (70.4%) patients, 25 (46.3%) patients had moderate and severe hydrocephalus. Thirty four patients (63.0%) had cerebral infarction. Tuberculoma were seen in 29 (53.7%) patients; 27 (50.0%) patients had classical tuberculoma, 2 (3.7%) patients
had “other” type of tuberculoma, 18 (33.3%) patients had ≥5 tuberculoma, and 11 (20.4%) patients had < 5 tuberculoma. Fifteen (37.2%) patients had vasculitis, 6 (11.1%) patients had vasospasm. Close to nine tenth (88.9%) of the patients had ≥1 classical neuroimaging features, 77.8% had ≥ 2 classical imaging features of TBM (basal enhancement, hydrocephalus, basal ganglia / thalamic infarct, classical tuberculoma, and vasculitis/vasospasm). Only 4% with other types of meningitis/encephalitis had ≥1 feature, and 1% had two or more classical TBM neuroimaging features. The sensitivity of the imaging features of the imaging features for diagnosis of TBM was 88.9% and the specificity was 95.6%.
Conclusion: The classic imaging features of basal enhancement, hydrocephalus, basal ganglia/thalamic infarct, classic tuberculoma, and vasculitis are sensitive and specific to diagnosis of TBM.
Background: Accuracy of diagnosis with intra-operative frozen sections is extremely important in the evaluation of ovarian tumors so that appropriate surgical procedures can be selected. Study design: All patients who with intra-operative frozen sections for ovarian masses in a tertiary center over nine years from June 2008 until April 2017 were reviewed. Frozen section diagnosis and final histopathological reports were compared. Main outcome measures: Sensitivity, specificity, positive and negative predictive values of intra-operative frozen section as compared to final histopathological results for ovarian tumors. Results: A total of 92 cases were recruited for final evaluation. The frozen section diagnoses were comparable with the final histopathological reports in 83.7% of cases. The sensitivity, specificity, positive predictive value and negative predictive value for benign and malignant ovarian tumors were 95.6%, 85.1%, 86.0% and 95.2% and 69.2%, 100%, 100% and 89.2% respectively. For borderline ovarian tumors, the sensitivity and specificity were 76.2% and 88.7%, respectively; the positive predictive value was 66.7% and the negative predictive value was 92.7%. Conclusion: The accuracy of intra-operative frozen section diagnoses for ovarian tumors is high and this approach remains a reliable option in assessing ovarian masses intra-operatively.
The key component in deep learning research is the availability of training data sets. With a limited number of publicly available COVID-19 chest X-ray images, the generalization and robustness of deep learning models to detect COVID-19 cases developed based on these images are questionable. We aimed to use thousands of readily available chest radiograph images with clinical findings associated with COVID-19 as a training data set, mutually exclusive from the images with confirmed COVID-19 cases, which will be used as the testing data set. We used a deep learning model based on the ResNet-101 convolutional neural network architecture, which was pretrained to recognize objects from a million of images and then retrained to detect abnormality in chest X-ray images. The performance of the model in terms of area under the receiver operating curve, sensitivity, specificity, and accuracy was 0.82, 77.3%, 71.8%, and 71.9%, respectively. The strength of this study lies in the use of labels that have a strong clinical association with COVID-19 cases and the use of mutually exclusive publicly available data for training, validation, and testing.
For effective management of typhoid, diagnosis of the disease must be done with speed and accuracy. Development of such a test would require antigens that are specific for typhoid diagnosis. Attempts at finding the specific antigen have been carried out throughout the years. The finding of such an antigen can lead to carrier detection as well. Candidate antigens have been used in the development of antigen or antibody detection tests with variation in sensitivity and specificity. Further characterization and understanding of the candidate antigens combined with use of innovative technologies will allow for the ideal test for typhoid and typhoid carriers to be within reach.
The effectiveness of two different rapid methods involving the 3M™ molecular detection assay Listeria and the 3M™ Petrifilm environmental Listeria Plate were evaluated for the rapid detection of Listeria from naturally contaminated vegetables and chicken-processing environments against the standard culture-based method. A total of 178 samples were examined for the presence of Listeria. A total of 47/178 (26.4%) by standard ISO culture-based method (EN ISO 11290-1), 42/178 (23.6%) by 3M™ MDA Listeria and 40/178 (22.5%) by 3M™ Petrifilm EL Plate showed positive results, respectively. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for 3M™ MDA Listeria and 3M™ Petrifilm EL Plate were 97.2, 89.4, 99.3, 97.7, 96.4% and 96.1, 85.1, 100.0, 100.0, 94.9%, respectively. Based on the Cohen's Kappa value, there was a complete and robust concordance between 3M™ MDA Listeria (0.911) and 3M™ Petrifilm EL Plates (0.894) as compared to the standard culture-based method.
The radiographer's role in the imaging field is producing the best image to diagnose. Hence, this study is conducted to justify the ability of radiographers in terms of diagnostic performance and visual search patterns during radiographic image interpretation based on their experience. The musculoskeletal radiographic images were chosen as radiographers are expected to perform image interpretation in the red dot system as one of the expanded and extended roles of the radiographer. Sensitivity and specificity in the detection of abnormality are measured. The gaze plot, fixation count and duration are compared between groups of radiographers by using an eye tracker. 19 radiographic images consist of upper and lower extremities are used as stimuli in this study. The result from this study shows no significant difference in terms of sensitivity and specificity with a p-value of 0.818 and 0.146 respectively. For visual search pattern, two images have significant different in term of fixation count (Image 1, p = 0.017; Image 2, p = 0.042) and two images in fixation duration (Image 1, p = 0.001; Image 15, p = 0.021). The gaze plot is not different from an unstructured pattern and less coverage. In conclusion, the experience did not give an influence on the radiographic image interpretation. This may suggest that specific training in areas appropriate to the development of the radiographer could improve the image interpretation.
BACKGROUND: Calcaneal quantitative ultrasound (QUS) is a useful tool in osteoporosis screening. However, QUS device may not be available at all primary health care settings. Osteoporosis self-assessment tool for Asians (OSTA) is a simple algorithm for osteoporosis screening that does not require any sophisticated instruments. This study explored the possibility of replacing QUS with OSTA by determining their agreement in identifying individuals at risk of osteoporosis.
METHODS: A cross-sectional study was conducted to recruit Malaysian men and women aged ≥50 years. Their bone health status was measured using a calcaneal QUS device and OSTA. The association between OSTA and QUS was determined using Spearman's correlation and their agreement was assessed using Cohen Kappa and receiver-operating curve.
RESULTS: All QUS indices correlated significantly with OSTA (p<0.05). The agreement between QUS and OSTA was minimal but statistically significant (p<0.05). The performance of OSTA in identifying subjects at risk of osteoporosis according to QUS was poor-to-fair in women (p<0.05), but not statistically significant for men (p>0.05). Changing the cut-off values improved the performance of OSTA in women but not in men.
CONCLUSION: The agreement between QUS and OSTA is minimal in categorizing individuals at risk of osteoporosis. Therefore, they cannot be used interchangeably in osteoporosis screening.
OBJECTIVE: The aim of this study was to compare the use of semi-automated (Medax Velox 2; Poggio Rusco, Italy) and automated (Bard Magnum Biopsy Instrument; Covington, GA, USA) core biopsy needles, for ultrasound guided breast biopsy.
MATERIALS AND METHODS: A 14G semi-automatic spring loaded core biopsy needle with a 22-mm-throw (Medax Velox 2; Poggio Rusco, Italy) and 14-gauge automated needle device with a 22-mm-throw biopsy gun (Bard-Magnum Biopsy Instrument, Covington, GA, USA) were used for breast biopsies under ultrasound guidance on alternate months during the study period between July 2009 and May 2011. One hundred and sixty lesions were biopsied and specimens were sent for histological evaluation.
RESULTS: The automated needle obtained a higher number of histology reports at 84% (67/80) as compared with the semiautomated needle at 60% (48/80) (Fisher exact test, p value=0.023). Inadequate samples with the automated needle were much less at 9% (7/60) than with the semiautomated needle at 23% (18/60) (Fisher exact test, p value=0.028). The semi-automated needle showed slightly less fragmented samples. However, the number of fragmented samples with definitive diagnosis was slightly higher with the automated compared with the semiautomated needle, at 16% (13/80) and 13% (10/80) respectively. Compared with histology of 29 lesions that were excised, the semi-automated needle had higher sensitivity (100%) but lower specificity (75%) and accuracy (90%) compared with the automated needle (88% sensitivity, 100% specificity, 95% accuracy).
CONCLUSION: Definitive diagnosis from the study samples slightly favours the use of automated core biopsy needle as compared to semi-automated core biopsy needle.
Study site: Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur
BACKGROUND: Triage of patients in the emergency department is a complex task based on several uncertainties and ambiguous information. Triage must be implemented within two to five minutes to avoid potential fatality and increased waiting time.
OBJECTIVE: An intelligent triage system has been proposed for use in a triage environment to reduce human error.
METHODS: This system was developed based on the objective primary triage scale (OPTS) that is currently used in the Universiti Kebangsaan Malaysia Medical Center. Both primary and secondary triage models are required to develop this system. The primary triage model has been reported previously; this work focused on secondary triage modelling using an ensemble random forest technique. The randomized resampling method was proposed to balance the data unbalance prior to model development.
RESULTS: The results showed that the 300% resampling gave a low out-of-bag error of 0.02 compared to 0.37 without pre-processing. This model has a sensitivity and specificity of 0.98 and 0.89, respectively, for the unseen data.
CONCLUSION: With this combination, the random forest reduces the variance, and the randomized resembling reduces the bias, leading to the reduced out-of-bag error.
KEYWORDS: Decision support system; emergency department; random forest; randomized resampling
Thyroid nodules are common but thyroid malignancies are not. Fine needle aspiration (FNA) cytology is a diagnostic tool used to screen patients with thyroid nodules who require surgery. We study the diagnostic accuracy of FNA as the initial diagnostic modality in the clinical assessment of thyroid nodules. Between January 1995 until December 2000, 2131 FNA of thyroid nodules were performed. Four hundred and forty-one (20.7%) of these were unsatisfactory and 1690 (79.3%) cases were satisfactory for cytological evaluation. Histopathological diagnosis were available for 361 cases. Cyto-histopathological correlation was carried out for these cases. Our results showed a diagnostic accuracy of 96.2% with sensitivity and specificity rates of 87.7% and 98.4% res- pectively. Our positive predictive value is 93.4% and our negative predictive value is 96.8%. From this study, we conclude that fine needle aspiration is an important initial screening diagnostic tool for the investigation of thyroid nodules.
This study aimed to validate the Malay Version of Copenhagen Psychosocial Questionnaire for Malaysian use and application for assessing psychosocial work environment factors. Validity and Reliability were studied in 50 staff nurses of Hospital Selayang. The validity of the questionnaire was evaluated by calculating the percentage of sensitivity and specificity at the different score level. Both percentage of sensitivity against specificity were plotted to produce a ROC (Receiver Operating Characteristics) curve, and score 52 has the highest both sensitivity and specificity was used as an overall index that expresses the probability that measure the psychosocial problems. For reliability purposes, a descriptive of Test-Retest Mean Scores and Paired Sample T-Test and the coefficient-correlation test were calculated. The Test-Retest Mean Scores and Paired Sample T-Test for all 26 scales were calculated and showed statistically not significant. The reliability of the questionnaire and its 26 scales was assessed by using Pearson (r) (overall questionnaire r within a range of 0.00 to 1.00). The COPSOQ appears to be a reliable and responsive measure of workers for Malaysian use and can be applied for assessing psychosocial work environment factors.
The purpose of this meta-analysis was to compare the ability of the qSOFA in predicting short- (≤30 days or in-hospital mortality) and long-term (>30 days) mortality among patients outside the intensive care unit setting. Studies reporting on the qSOFA and mortality were searched using MEDLINE and SCOPUS. Studies were included if they involved patients presenting to the ED with suspected infection and usage of qSOFA score for mortality prognostication. Data on qSOFA scores and mortality rates were extracted from 36 studies. The overall pooled sensitivity and specificity for the qSOFA were 48% and 86% for short-term mortality and 32% and 92% for long-term mortality, respectively. Studies reporting on short-term mortality were heterogeneous (Odd ratio, OR = 5.6; 95% CI = 4.6-6.8; Higgins's I2 = 94%), while long-term mortality studies were homogenous (OR = 4.7; 95% CI = 3.5-6.1; Higgins's I2 = 0%). There was no publication bias for short-term mortality analysis. The qSOFA score showed poor sensitivity but moderate specificity for both short and long-term mortality, with similar performance in predicting both short- and long- term mortality. Geographical region was shown to have nominal significant (p = 0.05) influence on qSOFA short-term mortality prediction.
Software optical mark recognition (SOMR) is the process whereby information entered on a survey form or questionnaire is converted using specialized software into a machine-readable format. SOMR normally requires input fields to be completely darkened, have no internal labels, or be filled with a soft pencil, otherwise mark detection will be inaccurate. Forms can also have print and scan artefacts that further increase the error rate. This article presents a new method of mark detection that improves over existing techniques based on pixel counting and simple thresholding. Its main advantage is that it can be used under a variety of conditions and yet maintain a high level of accuracy that is sufficient for scientific applications. Field testing shows no software misclassification in 5695 samples filled by trained personnel, and only two misclassifications in 6000 samples filled by untrained respondents. Sensitivity, specificity, and accuracy were 99.73%, 99.98%, and 99.94% respectively, even in the presence of print and scan artefacts, which was superior to other methods tested. A separate direct comparison for mark detection showed a sensitivity, specificity, and accuracy respectively of 99.7%, 100.0%, 100.0% (new method), 96.3%, 96.0%, 96.1% (pixel counting), and 99.9%, 99.8%, 99.8% (simple thresholding) on clean forms, and 100.0%, 99.1%, 99.3% (new method), 98.4%, 95.6%, 96.2% (pixel counting), 100.0%, 38.3%, 51.4% (simple thresholding) on forms with print artefacts. This method is designed for bubble and box fields, while other types such as handwriting fields require separate error control measures.