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  1. Zakaria WMZ, Mansor Z
    PLoS One, 2024;19(7):e0307199.
    PMID: 39024265 DOI: 10.1371/journal.pone.0307199
    The acceptability of latent tuberculosis infection (LTBI) therapy remains low among healthcare workers (HCWs). Up to 10% of LTBI cases can reactivate into active tuberculosis, posing risks to HCWs and patients. Understanding HCWs' intention to undergo LTBI treatment is crucial for designing effective management policies, especially where no LTBI policy exists. This cross-sectional study investigated the intention to receive LTBI therapy and its associated factors among HCWs in a Malaysian teaching hospital. The study was conducted from 5th to 30th May 2023, in a hospital without an LTBI screening program. Stratified random sampling was used to select HCWs, excluding those undergoing TB or LTBI therapy. Respondents completed a questionnaire measuring intention to receive LTBI treatment, LTBI knowledge, attitude, perceived norm, and perceived behavioral control. Of the 256 respondents, the majority were female (63.7%), under 35 years old (64.45%), had no comorbidities (82.0%), and worked in clinical settings (70.3%). However, 60.5% of respondents had low LTBI knowledge and 60.5% held unfavorable attitudes toward LTBI treatment. Despite this, 53.5% of respondents intended to undergo LTBI therapy if diagnosed. Factors positively associated with this intention included being female [aOR: 2.033, 95% CI: 1.080-3.823], having high LTBI knowledge [aOR 1.926, 95% CI: 1.093-3.397], had favorable attitude [aOR 3.771, 95% CI: 1.759-8.084], and strongly perceiving social norms supportive of LTBI treatment [aOR 4.593, 95% CI: 2.104-10.023]. These findings emphasize the need for an LTBI management policy in the teaching hospital. To boost HCWs' intention and acceptance of LTBI treatment, a focused program improving knowledge, attitude, and perception of social norms could be introduced.
  2. Mansor Z, Rosnah I, Ismail NH, Hashim JH
    Med J Malaysia, 2019 08;74(4):275-280.
    PMID: 31424033
    INTRODUCTION: The continue rise in temperatures due to climate change increases the risk of heat-related illness (HRI) among outdoor workers. This study aims to evaluate the effects of hydration practices on the severity of HRI during a heat wave episode among municipal workers in Negeri Sembilan.

    METHOD: A cross-sectional study was performed in March and April 2016. The outdoor temperatures were measured using the wet-bulb globe temperature (WBGT) tool. The participants completed a self-administered questionnaire containing sociodemographic factors prior to work shift; while working profile, hydration practices, and HRI symptoms at the end of work shift. The hydration status of the respondents was assessed by direct observation of their urine colour. Multiple logistic regression was performed to ascertain the effects of age, working profile, hydration practice, history of previous HRI, and hydration status on the likelihood that outdoor workers having moderate to severe HRI.

    RESULTS: A total of 320 respondents completed the questionnaire. The mean (standard deviation) outdoor workplace temperature was 30.5°C (SD 0.53°C). The percentage of respondents who experienced moderate to severe HRI was 44.1%. The likelihood that outdoor workers experienced moderate to severe HRI symptoms was associated with irregular fluid intake [odds ratio (OR): 16.11, 95% confidence interval (95%CI): 4.11; 63.20]; consumption of non-plain water (OR: 5.92, 95%CI: 2.79; 12.56); dehydration (OR: 3.32, 95%CI: 1.92; 5.74); and increasing outdoor workplace temperature (OR: 1.85, 95%CI: 1.09; 3.11).

    CONCLUSION: Irregular drinking pattern and non-plain fluid intake was found to have a large effect on HRI severity among outdoor workers exposed high temperatures during a heat wave phenomenon.

  3. Mansor Z, Ismail NH, Rosnah I, Hashim JH
    Med J Malaysia, 2019 02;74(1):1-7.
    PMID: 30846654
    INTRODUCTION: The heat-related illness (HRI) is a continuum illness ranging from minor health effects to life-threatening medical emergencies when the pathological effects of heat load are not prevented. The aim of this study was to demonstrate the threshold HRI symptom for deciding to take simple preventative actions both by the individual workers and employers.

    METHOD: A total of 328 municipal workers were enrolled in April to March 2016 were asked to recall if they experienced eleven HRI symptoms during the previous work day. Rasch Measurement Model was used to examine the unidimensional parameters and bias for gender before identifying the threshold of HRI symptoms. We determined the threshold symptom based on the person-item map distribution on a logit ruler value.

    RESULTS: A total of 320 respondents were analysed. The psychometric features HRI symptoms suggested evidence of unidimensionality and free of bias for gender (DIF size =0.57; DIF t value =1.03). Based on the person-item map distribution, the thirst item was determined as the threshold item (Cut-off point = -2.17 logit) for the preventative action purposes to group the person as mild and moderate/severe HRI groups.

    CONCLUSION: Thirst item is viewed as threshold symptoms between mild and moderate or severe HRI symptoms. It is a reliable symptom to initiate behavioural response to quench the thirst by adequate fluids. Failure to recognise the thirst symptom may lead to devastating unwanted health complications.

  4. Shamshirband S, Joloudari JH, Shirkharkolaie SK, Mojrian S, Rahmani F, Mostafavi S, et al.
    Math Biosci Eng, 2021 Oct 25;18(6):9190-9232.
    PMID: 34814342 DOI: 10.3934/mbe.2021453
    Today's intelligent computing environments, including the Internet of Things (IoT), Cloud Computing (CC), Fog Computing (FC), and Edge Computing (EC), allow many organizations worldwide to optimize their resource allocation regarding the quality of service and energy consumption. Due to the acute conditions of utilizing resources by users and the real-time nature of the data, a comprehensive and integrated computing environment has not yet provided a robust and reliable capability for proper resource allocation. Although traditional resource allocation approaches in a low-capacity hardware resource system are efficient for small-scale resource providers, for a complex system in the conditions of dynamic computing resources and fierce competition in obtaining resources, they cannot develop and adaptively manage the conditions optimally. To optimize the resource allocation with minimal delay, low energy consumption, minimum computational complexity, high scalability, and better resource utilization efficiency, CC/FC/EC/IoT-based computing architectures should be designed intelligently. Therefore, the objective of this research is a comprehensive survey on resource allocation problems using computational intelligence-based evolutionary optimization and mathematical game theory approaches in different computing environments according to the latest scientific research achievements.
  5. Mosavi A, Shokri M, Mansor Z, Qasem SN, Band SS, Mohammadzadeh A
    Entropy (Basel), 2020 Sep 18;22(9).
    PMID: 33286810 DOI: 10.3390/e22091041
    In this study, a new approach to basis of intelligent systems and machine learning algorithms is introduced for solving singular multi-pantograph differential equations (SMDEs). For the first time, a type-2 fuzzy logic based approach is formulated to find an approximated solution. The rules of the suggested type-2 fuzzy logic system (T2-FLS) are optimized by the square root cubature Kalman filter (SCKF) such that the proposed fineness function to be minimized. Furthermore, the stability and boundedness of the estimation error is proved by novel approach on basis of Lyapunov theorem. The accuracy and robustness of the suggested algorithm is verified by several statistical examinations. It is shown that the suggested method results in an accurate solution with rapid convergence and a lower computational cost.
  6. Mahmoudi MR, Baleanu D, Mansor Z, Tuan BA, Pho KH
    Chaos Solitons Fractals, 2020 Nov;140:110230.
    PMID: 32863611 DOI: 10.1016/j.chaos.2020.110230
    The numbers of confirmed cases of new coronavirus (Covid-19) are increased daily in different countries. To determine the policies and plans, the study of the relations between the distributions of the spread of this virus in other countries is critical. In this work, the distributions of the spread of Covid-19 in Unites States America, Spain, Italy, Germany, United Kingdom, France, and Iran were compared and clustered using fuzzy clustering technique. At first, the time series of Covid-19 datasets in selected countries were considered. Then, the relation between spread of Covid-19 and population's size was studied using Pearson correlation. The effect of the population's size was eliminated by rescaling the Covid-19 datasets based on the population's size of USA. Finally, the rescaled Covid-19 datasets of the countries were clustered using fuzzy clustering. The results of Pearson correlation indicated that there were positive and significant between total confirmed cases, total dead cases and population's size of the countries. The clustering results indicated that the distribution of spreading in Spain and Italy was approximately similar and differed from other countries.
  7. Mohamad NF, Mansor Z, Mahmud A, Mohamed Ghazali IM, Sarimin R
    Int J Technol Assess Health Care, 2024 Feb 28;40(1):e18.
    PMID: 38415300 DOI: 10.1017/S0266462324000102
    OBJECTIVES: To determine the level of awareness of health technology assessment (HTA) and its predictors among clinical year medical students in public universities in Klang Valley, Malaysia.

    METHODS: A cross-sectional study using the stratified random sampling method was conducted among clinical year medical students in four public universities in Klang Valley, Malaysia. Data on the level of awareness of HTA and its associated factors were collected using a self-administered online questionnaire. Descriptive, bivariate, and multivariate analyses were performed using IBM SPSS version 27 to determine the level of awareness of HTA and its predictors.

    RESULTS: Majority (69 percent) of participants had a low level of awareness of HTA. The predictors of high-level awareness of HTA were attitude toward HTA (adjusted odds ratio (AOR) = 7.417, 95 percent confidence interval (CI): 3.491, 15.758), peer interaction on HTA (AOR = 0.320, 95 percent CI: 0.115, 0.888), and previous training on HTA (AOR = 4.849, 95 percent CI: 1.096, 21.444).

    CONCLUSIONS: Most future doctors in public universities exhibit a low awareness of HTA. This study highlights the interplay between attitudes toward HTA, peer interaction, and previous training as influential predictors of HTA awareness. An integrated and comprehensive educational approach is recommended to cultivate a positive attitude and harness the positive aspects of peer interaction while mitigating the potential negative impact of misconceptions. Emphasizing early exposure to HTA concepts through structured programs is crucial for empowering the upcoming generation of healthcare professionals, enabling them to navigate HTA complexities and contribute to evidence-based healthcare practices in Malaysia and beyond.

  8. Zhang Q, Lee K, Mansor Z, Ismail I, Guo Y, Xiao Q, et al.
    Heart Lung, 2024;63:51-64.
    PMID: 37774510 DOI: 10.1016/j.hrtlng.2023.09.007
    BACKGROUND: Despite the widespread adoption of the rapid response team (RRT) by many hospitals, questions remain regarding their effectiveness in improving several aspects of patient outcomes, such as hospital mortality, cardiopulmonary arrests, unplanned intensive care unit (ICU) admissions, and length of stay (LOS).

    OBJECTIVES: To conduct a systematic review to understand the rapid response team's (RRT) effect on patient outcomes.

    METHODS: A systematic search was conducted using PubMed, Cochrane, Embase, CINAHL, Web of Science, and two trial registers. The studies published up to May 6, 2022, from the inception date of the databases were included. Two researchers filtered the title, abstract and full text. The Version 2 of the Cochrane Risk of Bias tool and Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool were used separately for randomized and non-randomized controlled trials for quality appraisal.

    RESULTS: Sixty-one eligible studies were identified, four randomized controlled trials(RCTs), four non-randomized controlled trials, six interrupted time-series(ITS) design , and 47 pretest-posttest studies. A total of 52 studies reported hospital mortality, 51 studies reported cardiopulmonary arrests, 18 studies reported unplanned ICU admissions and ten studies reported LOS.

    CONCLUSION: This systematic review found the variation in context and the type of RRT interventions restricts direct comparisons. The evidence for improving several aspects of patient outcomes was inconsistent, with most studies demonstrating that RRT positively impacts patient outcomes.

  9. Zhang Q, Lee K, Qian P, Mansor Z, Ismail I, Guo Y, et al.
    J Adv Nurs, 2024 Nov 28.
    PMID: 39607180 DOI: 10.1111/jan.16541
    AIMS: To investigate the prevalence of rapid response team delays, survival distribution of admission to rapid response team delay and its prognostic factors.

    DESIGN: A retrospective single-centre study.

    METHODS: Data on rapid response team activations from 1 January 2018 to 31 December 2022 were retrieved from electronic medical records at a tertiary hospital in Hangzhou, China. All patients who met the eligibility criteria were included. Multivariable Cox regression analysis was conducted to analyse the data.

    RESULTS: Out of 636 patients included, 18.4% (117) experienced a delay, with a median (interquartile range) of 8.5 (12) days from admission to rapid response team activation. Six significant prognostic factors were found to be associated with the higher hazard ratio of rapid response team delay, including call time (05:01 PM and 7:59 AM), emergency admission, a higher Modified Early Warning Score, an admission diagnosis of infection, a comorbidity of respiratory failure/Acute Respiratory Distress Syndrome and the absence of lung infection.

    CONCLUSION: The prevalence of rapid response team delays was lower, and the days from admission to rapid response team delay was longer than in previous studies. Healthcare providers are suggested to prioritise the care of high-risk patient groups and provide proactive monitoring to ensure timely identification and management.

    IMPLICATIONS FOR PATIENT CARE: Implementing artificial intelligence in continuous monitoring systems for high-risk patients is recommended. The findings help nurses anticipate potential delays in rapid response team activation, enabling better preparedness.

    IMPACT: The study highlights the prevalence of rapid response team delays, timing from admission to rapid response team activation and six prognostic factors influencing delays. It could shape patient care and inform future research. Hospital administrators should review staffing, especially during night shifts, to minimise delays. Further qualitative research is needed to explore why nurses may delay rapid response team activation.

    REPORTING METHOD: The STROBE checklist was adhered to when reporting this study. 'No patient or public contribution'.

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