Displaying all 15 publications

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  1. Pang T
    Med J Malaysia, 1979 Dec;34(2):91-4.
    PMID: 398437
    Matched MeSH terms: Diagnostic Techniques and Procedures*
  2. Simoneau G, Levis B, Cuijpers P, Ioannidis JPA, Patten SB, Shrier I, et al.
    Biom J, 2017 Nov;59(6):1317-1338.
    PMID: 28692782 DOI: 10.1002/bimj.201600184
    Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings.
    Matched MeSH terms: Diagnostic Techniques and Procedures*
  3. Fleming KA, Horton S, Wilson ML, Atun R, DeStigter K, Flanigan J, et al.
    Lancet, 2021 Nov 27;398(10315):1997-2050.
    PMID: 34626542 DOI: 10.1016/S0140-6736(21)00673-5
    Matched MeSH terms: Diagnostic Techniques and Procedures*
  4. Zaki R, Bulgiba A, Ismail R, Ismail NA
    PLoS One, 2012;7(5):e37908.
    PMID: 22662248 DOI: 10.1371/journal.pone.0037908
    Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice.
    Matched MeSH terms: Diagnostic Techniques and Procedures/instrumentation*; Diagnostic Techniques and Procedures/standards
  5. Apisarnthanarak A, Kim HB, Moore L, Xiao Y, Singh S, Doi Y, et al.
    Infect Control Hosp Epidemiol, 2021 07;42(7):864-868.
    PMID: 34128462 DOI: 10.1017/ice.2021.149
    Rapid diagnostic testing (RDT) can provide prompt, accurate identification of infectious organisms and be a key component of antimicrobial stewardship (AMS) programs. However, their use is less widespread in Asia Pacific than western countries. Cost can be prohibitive, particularly in less resource-replete settings. A selective approach is required, possibly focusing on the initiation of antimicrobials, for differentiating bacterial versus viral infections and identifying locally relevant tropical diseases. Across Asia Pacific, more data are needed on RDT use within AMS, focusing on the impact on antimicrobial usage, patient morbidity and mortality, and cost effectiveness. Moreover, in the absence of formal guidelines, regional consensus statements to guide clinical practice are warranted. These will provide a regionally relevant definition for RDT; greater consensus on its role in managing infections; advice on implementation and overcoming barriers; and guidance on optimizing human resource capacity. By addressing these issues, the outcomes of AMS programs should improve.
    Matched MeSH terms: Diagnostic Techniques and Procedures
  6. Jun Zhao, Feifei Wang, Yifan Lu
    Sains Malaysiana, 2017;46:2223-2229.
    Formation lithology identification is an indispensable link in oil and gas exploration. Precision of the traditional recognition method is difficult to guarantee when trying to identify lithology of particular formation with strong heterogeneity and complex structure. In order to remove this defect, multivariate membership function discrimination method is proposed, which regard to lithology identification as a linear model in the fuzzy domain and obtain aimed result with the multivariate membership function established. It is indicated by the test on lower carboniferous Bachu group bioclastic limestone section and Donghe sandstone section reservoir on T Field H area that satisfactory accuracy can be achieved in both clastic rock and carbonate formation and obvious advantages are unfold when dealing with complex formations, which shows a good application prospect and provides a new thought to solve complex problems on oilfield exploration and development with fuzzy theory.
    Matched MeSH terms: Diagnostic Techniques and Procedures
  7. Hariharan M, Chee LS, Yaacob S
    J Med Syst, 2012 Jun;36(3):1309-15.
    PMID: 20844933 DOI: 10.1007/s10916-010-9591-z
    Acoustic analysis of infant cry signals has been proven to be an excellent tool in the area of automatic detection of pathological status of an infant. This paper investigates the application of parameter weighting for linear prediction cepstral coefficients (LPCCs) to provide the robust representation of infant cry signals. Three classes of infant cry signals were considered such as normal cry signals, cry signals from deaf babies and babies with asphyxia. A Probabilistic Neural Network (PNN) is suggested to classify the infant cry signals into normal and pathological cries. PNN is trained with different spread factor or smoothing parameter to obtain better classification accuracy. The experimental results demonstrate that the suggested features and classification algorithms give very promising classification accuracy of above 98% and it expounds that the suggested method can be used to help medical professionals for diagnosing pathological status of an infant from cry signals.
    Matched MeSH terms: Diagnostic Techniques and Procedures*
  8. Quek KF, Low WY, Razack AH, Chua CB, Loh CS
    Med J Malaysia, 2003 Aug;58(3):356-64.
    PMID: 14750375
    This study aimed to assess the sensitivity of the Malay version of the Brief Manual Sexual Function Inventory (BMSFI) on patients with and without urinary symptoms in Malaysian population. Validity and reliability were studied in patients with lower urinary tract symptoms (LUTS) and patients without LUTS. Reliability and validity was evaluated by using the test-retest method while internal consistency was assessed by Cronbach's alpha. Sensitivity to change was expressed as the effect size in the pre-intervention versus post-intervention score in patients who underwent transurethral resection of the prostate (TURP). Internal consistency was excellent. A high degree of internal consistency was observed for each of the 11 items and 5 domains (Cronbach's alpha value = 0.67 and higher and 0.73 and higher respectively). Test-retest correlation coefficient for the 11 items scores was highly significant. Intraclass correlation coefficient was high (ICC = 0.68 and above). The sensitivity and specificity showed a high degree of sensitivity and specificity to the effects of treatment. A high degree of significant level between baseline and post-treatment scores were observed across 3 domains in the treatment corresponds cohort but not in the control group. The Mal-BMSFI is a suitable, reliable, valid and sensitive to clinical change in the Malaysian population.
    Matched MeSH terms: Diagnostic Techniques and Procedures*
  9. Albahri AS, Hamid RA, Albahri OS, Zaidan AA
    Artif Intell Med, 2021 Jan;111:101983.
    PMID: 33461683 DOI: 10.1016/j.artmed.2020.101983
    CONTEXT AND BACKGROUND: Corona virus (COVID) has rapidly gained a foothold and caused a global pandemic. Particularists try their best to tackle this global crisis. New challenges outlined from various medical perspectives may require a novel design solution. Asymptomatic COVID-19 carriers show different health conditions and no symptoms; hence, a differentiation process is required to avert the risk of chronic virus carriers.

    OBJECTIVES: Laboratory criteria and patient dataset are compulsory in constructing a new framework. Prioritisation is a popular topic and a complex issue for patients with COVID-19, especially for asymptomatic carriers due to multi-laboratory criteria, criterion importance and trade-off amongst these criteria. This study presents new integrated decision-making framework that handles the prioritisation of patients with COVID-19 and can detect the health conditions of asymptomatic carriers.

    METHODS: The methodology includes four phases. Firstly, eight important laboratory criteria are chosen using two feature selection approaches. Real and simulation datasets from various medical perspectives are integrated to produce a new dataset involving 56 patients with different health conditions and can be used to check asymptomatic cases that can be detected within the prioritisation configuration. The first phase aims to develop a new decision matrix depending on the intersection between 'multi-laboratory criteria' and 'COVID-19 patient list'. In the second phase, entropy is utilised to set the objective weight, and TOPSIS is adapted to prioritise patients in the third phase. Finally, objective validation is performed.

    RESULTS: The patients are prioritised based on the selected criteria in descending order of health situation starting from the worst to the best. The proposed framework can discriminate among mild, serious and critical conditions and put patients in a queue while considering asymptomatic carriers. Validation findings revealed that the patients are classified into four equal groups and showed significant differences in their scores, indicating the validity of ranking.

    CONCLUSIONS: This study implies and discusses the numerous benefits of the suggested framework in detecting/recognising the health condition of patients prior to discharge, supporting the hospitalisation characteristics, managing patient care and optimising clinical prediction rule.

    Matched MeSH terms: Diagnostic Techniques and Procedures/statistics & numerical data*
  10. Malon RS, Sadir S, Balakrishnan M, Córcoles EP
    Biomed Res Int, 2014;2014:962903.
    PMID: 25276835 DOI: 10.1155/2014/962903
    Saliva is increasingly recognised as an attractive diagnostic fluid. The presence of various disease signalling salivary biomarkers that accurately reflect normal and disease states in humans and the sampling benefits compared to blood sampling are some of the reasons for this recognition. This explains the burgeoning research field in assay developments and technological advancements for the detection of various salivary biomarkers to improve clinical diagnosis, management, and treatment. This paper reviews the significance of salivary biomarkers for clinical diagnosis and therapeutic applications, with focus on the technologies and biosensing platforms that have been reported for screening these biomarkers.
    Matched MeSH terms: Diagnostic Techniques and Procedures*
  11. Yusof M, Sahroni MN
    Int J Health Care Qual Assur, 2018 Oct 08;31(8):1014-1029.
    PMID: 30415623 DOI: 10.1108/IJHCQA-07-2017-0125
    PURPOSE: The purpose of this paper is to present a review of health information system (HIS)-induced errors and its management. This paper concludes that the occurrence of errors is inevitable but it can be minimised with preventive measures. The review of classifications can be used to evaluate medical errors related to HISs using a socio-technical approach. The evaluation could provide an understanding of errors as a learning process in managing medical errors.

    DESIGN/METHODOLOGY/APPROACH: A literature review was performed on issues, sources, management and approaches to HISs-induced errors. A critical review of selected models was performed in order to identify medical error dimensions and elements based on human, process, technology and organisation factors.

    FINDINGS: Various error classifications have resulted in the difficulty to understand the overall error incidents. Most classifications are based on clinical processes and settings. Medical errors are attributed to human, process, technology and organisation factors that influenced and need to be aligned with each other. Although most medical errors are caused by humans, they also originate from other latent factors such as poor system design and training. Existing evaluation models emphasise different aspects of medical errors and could be combined into a comprehensive evaluation model.

    RESEARCH LIMITATIONS/IMPLICATIONS: Overview of the issues and discourses in HIS-induced errors could divulge its complexity and enable its causal analysis.

    PRACTICAL IMPLICATIONS: This paper helps in understanding various types of HIS-induced errors and promising prevention and management approaches that call for further studies and improvement leading to good practices that help prevent medical errors.

    ORIGINALITY/VALUE: Classification of HIS-induced errors and its management, which incorporates a socio-technical and multi-disciplinary approach, could guide researchers and practitioners to conduct a holistic and systematic evaluation.

    Matched MeSH terms: Diagnostic Techniques and Procedures/standards; Diagnostic Techniques and Procedures/statistics & numerical data
  12. Nor Fauziah MH, Faizah MZ, Loh CK
    Med J Malaysia, 2017 10;72(5):324-326.
    PMID: 29197894
    A four-year-old Ibanese boy presented with subacute abdominal distension for two months duration. Ultrasound and computed tomography (CT) scan showed solid liver masses as well as bowel and intraperitoneal lesions. Initial diagnosis of intraperitoneal inflammatory process as in tuberculosis with non-liquefied liver abscess with differential diagnosis of neoplastic process was made. Liver biopsy and peritoneal fluid analysis revealed Burkitt's lymphoma (BL). We aim to highlight the diagnostic challenge of BL in this young age group emphasizing on the ultrasound and CT features of intraabdominal BL. We would also want to stress the importance of early diagnosis of BL as it is known to be the most aggressive tumour within 24 hours yet to have good survival if early diagnosis was made.
    Matched MeSH terms: Diagnostic Techniques and Procedures
  13. Atieno OM, Opanga S, Martin A, Kurdi A, Godman B
    J Med Econ, 2018 Sep;21(9):878-887.
    PMID: 29860920 DOI: 10.1080/13696998.2018.1484372
    BACKGROUND: Currently the majority of cancer deaths occur in low- and middle-income countries, where there are appreciable funding concerns. In Kenya, most patients currently pay out of pocket for treatment, and those who are insured are generally not covered for the full costs of treatment. This places a considerable burden on households if family members develop cancer. However, the actual cost of cancer treatment in Kenya is unknown. Such an analysis is essential to better allocate resources as Kenya strives towards universal healthcare.

    OBJECTIVES: To evaluate the economic burden of treating cancer patients.

    METHOD: Descriptive cross-sectional cost of illness study in the leading teaching and referral hospital in Kenya, with data collected from the hospital files of sampled adult patients for treatment during 2016.

    RESULTS: In total, 412 patient files were reviewed, of which 63.4% (n = 261) were female and 36.6% (n = 151) male. The cost of cancer care is highly dependent on the modality. Most reviewed patients had surgery, chemotherapy and palliative care. The cost of cancer therapy varied with the type of cancer. Patients on chemotherapy alone cost an average of KES 138,207 (USD 1364.3); while those treated with surgery cost an average of KES 128,207 (1265.6), and those on radiotherapy KES 119,036 (1175.1). Some patients had a combination of all three, costing, on average, KES 333,462 (3291.8) per patient during the year.

    CONCLUSION: The cost of cancer treatment in Kenya depends on the type of cancer, the modality, cost of medicines and the type of inpatient admission. The greatest contributors are currently the cost of medicines and inpatient admissions. This pilot study can inform future initiatives among the government as well as private and public insurance companies to increase available resources, and better allocate available resources, to more effectively treat patients with cancer in Kenya. The authors will be monitoring developments and conducting further research.

    Matched MeSH terms: Diagnostic Techniques and Procedures/economics
  14. Manurung S, Setyowati S
    Malays Fam Physician, 2021 Mar 25;16(1):64-74.
    PMID: 33948144 DOI: 10.51866/oa1037
    Background: Postpartum blues in Indonesia has a high prevalence at 37% to 67%. Postpartum blues syndrome has been described as varying changes in the affective domain, such as feelings, behavior, or thoughts, that can be influenced by the roles and tasks of women, along with their social, cultural, and economic support. Instruments that measure maternal blues through bonding attachment behavior have never before been developed in Indonesia.

    Objective: This study aimed to develop a maternal blues scale through bonding attachments to predict postpartum blues.

    Method: The research design consisted of three stages: 1) phenomenology design and focus group discussion; 2) development and construction of the maternal blues scale, and 3) a cross-sectional study to measure validation of the scales. Respondents were postpartum mothers in the first week after birth. The sample comprised 501 participants. Sampling was done by consecutive sampling at the Public Health Center (PUSKESMAS) in the South Jakarta area. Data analysis used exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), correlation, and a diagnostic testing .

    Results: Item analysis produced 32 items consisting of 24 items regarding the mother's role and duties as internal factors and eight factors involving social, cultural, and economic support as external factors. Both factors were valid and reliable in predicting postpartum blues with indicators (t loading factors ≥ 1.96, standardized loading factor (SLF) ≥.50, internal factors: construct reliability (CR) ≥ .70 and extraction variants (VE) ≥ .50 and external factors: CR ≥ .74 to .83 VE ≥ .50 to .63). The relationship with Kennerley's maternity blues as a gold standard was significant. Internal factors had a score of 53, with a sensitivity of 60.2%. The external factors score was 19, with a sensitivity of 77.3%.

    Conclusion: The new scale for postpartum blues prediction developed displayed internal consistency and validity of each indicator (internal and external factors) that was good (CR ≥ .70; VE ≥ .50). This scale provides a feasible tool to predict postpartum blues.

    Matched MeSH terms: Diagnostic Techniques and Procedures
  15. Kanabalan RD, Lee LJ, Lee TY, Chong PP, Hassan L, Ismail R, et al.
    Microbiol Res, 2021 May;246:126674.
    PMID: 33549960 DOI: 10.1016/j.micres.2020.126674
    Mycobacterium tuberculosis complex (MTBC) refers to a group of mycobacteria encompassing nine members of closely related species that causes tuberculosis in animals and humans. Among the nine members, Mycobacterium tuberculosis (M. tuberculosis) remains the main causative agent for human tuberculosis that results in high mortality and morbidity globally. In general, MTBC species are low in diversity but exhibit distinctive biological differences and phenotypes among different MTBC lineages. MTBC species are likely to have evolved from a common ancestor through insertions/deletions processes resulting in species speciation with different degrees of pathogenicity. The pathogenesis of human tuberculosis is complex and remains poorly understood. It involves multi-interactions or evolutionary co-options between host factors and bacterial determinants for survival of the MTBC. Granuloma formation as a protection or survival mechanism in hosts by MTBC remains controversial. Additionally, MTBC species are capable of modulating host immune response and have adopted several mechanisms to evade from host immune attack in order to survive in humans. On the other hand, current diagnostic tools for human tuberculosis are inadequate and have several shortcomings. Numerous studies have suggested the potential of host biomarkers in early diagnosis of tuberculosis, in disease differentiation and in treatment monitoring. "Multi-omics" approaches provide holistic views to dissect the association of MTBC species with humans and offer great advantages in host biomarkers discovery. Thus, in this review, we seek to understand how the genetic variations in MTBC lead to species speciation with different pathogenicity. Furthermore, we also discuss how the host and bacterial players contribute to the pathogenesis of human tuberculosis. Lastly, we provide an overview of the journey of "omics" approaches in host biomarkers discovery in human tuberculosis and provide some interesting insights on the challenges and directions of "omics" approaches in host biomarkers innovation and clinical implementation.
    Matched MeSH terms: Diagnostic Techniques and Procedures
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