Displaying publications 1 - 20 of 73 in total

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  1. Musa KI, Keegan TJ
    PLoS One, 2018;13(12):e0208594.
    PMID: 30571691 DOI: 10.1371/journal.pone.0208594
    BACKGROUND: Acute stroke results in functional disability measurable using the well-known Barthel Index. The objectives of the study are to describe the change in the Barthel Index score and to model the prognostic factors for Barthel Index change from discharge up to 3 months post-discharge using the random intercept model among patients with acute first ever stroke in Kelantan, Malaysia.

    METHODS: A total 98 in-hospital first ever acute stroke patients were recruited, and their Barthel Index scores were measured at the time of discharge, at 1 month and 3 months post-discharge. The Barthel Index was scored through telephone interviews. We employed the random intercept model from linear mixed effect regression to model the change of Barthel Index scores during the three months intervals. The prognostic factors included in the model were acute stroke subtypes, age, sex and time of measurement (at discharge, at 1 month and at 3 month post-discharge).

    RESULTS: The crude mean Barthel Index scores showed an increased trend. The crude mean Barthel Index at the time of discharge, at 1-month post-discharge and 3 months post-discharge were 35.1 (SD = 39.4), 64.4 (SD = 39.5) and 68.8 (SD = 38.9) respectively. Over the same period, the adjusted mean Barthel Index scores estimated from the linear mixed effect model increased from 39.6 to 66.9 to 73.2. The adjusted mean Barthel Index scores decreased as the age increased, and haemorrhagic stroke patients had lower adjusted mean Barthel Index scores compared to the ischaemic stroke patients.

    CONCLUSION: Overall, the crude and adjusted mean Barthel Index scores increase from the time of discharge up to 3-month post-discharge among acute stroke patients. Time after discharge, age and stroke subtypes are the significant prognostic factors for Barthel Index score changes over the period of 3 months.

  2. Musa KI, Abdullah JM
    Malays J Med Sci, 2020 Dec;27(6):1-6.
    PMID: 33447129 DOI: 10.21315/mjms2020.27.6.1
    The recent spike of transmissibility of COVID-19 was evident by a large number of COVID-19 cases and apparent quick spread of SARS-CoV-2 in the state of Sabah, Selangor and Negeri Sembilan in Malaysia. The question remains as to what are the main contributory factors for the impending COVID-19 second wave in Malaysia and why the current surveillance system fails to show signs of the impending second - or the third - COVID-19 wave. In public health surveillance, data are the ultimate indicator, and in the era of big data and the Industrial Revolution 4.0, data has become a valuable commodity. The COVID-19 data keeper must fulfil some criteria to ensure COVID-19 data are useful. Researchers are obligated to share their COVID-19 data responsibly. The surveillance for COVID-19 is paramount, and the guidelines such as the one published by the World Health Organization 'Public health surveillance for COVID-19: interim guidance' must be referred to. Data must be taken seriously and shared to enable scientists, clinicians, epidemiologists and public health experts fight COVID-19.
  3. Hanis TM, Islam MA, Musa KI
    Curr Med Chem, 2021 Nov 07.
    PMID: 34749608 DOI: 10.2174/0929867328666211108110731
    BACKGROUND: Rapid advancement in computing technology and digital information leads to the possible use of machine learning on breast cancer.

    OBJECTIVE: This study aimed to evaluate the research output of the top 100 publications and further identify a research theme of breast cancer and machine-learning studies.

    METHODS: Databases of Scopus and Web of Science were used to extract the top 100 publications. These publications were filtered based on the total citation of each paper. Additionally, a bibliometric analysis was applied to the top 100 publications.

    RESULTS: The top 100 publications were published between 1993 and 2019. The most productive author was Giger ML, and the top two institutions were the University of Chicago and the National University of Singapore. The most active countries were the USA, Germany and China. Ten clusters were identified as both basic and specialised themes of breast cancer and machine learning.

    CONCLUSION: Various countries demonstrated comparable interest in breast cancer and machine-learning research. A few Asian countries, such as China, India and Singapore, were listed in the top 10 countries based on the total citation. Additionally, the use of deep learning and breast imaging data was trending in the past 10 years in the field of breast cancer and machine-learning research.

  4. Ghazali AK, Musa KI, Naing NN, Mahmood Z
    Asian J Surg, 2010 Jul;33(3):127-33.
    PMID: 21163410 DOI: 10.1016/S1015-9584(10)60022-X
    To determine the 5-year survival rate and prognostic factors for survival in patients with colorectal cancer treated at the Surgical Unit, Hospital Universiti Sains Malaysia (HUSM), Kelantan, Malaysia.
  5. Hamzah FH, Mohd Hairon S, Yaacob NM, Musa KI
    PMID: 31295907 DOI: 10.3390/ijerph16142453
    Prompt investigation of food poisoning outbreak are essential, as it usually involves a short incubation period. Utilizing the advancement in mobile technology, a mobile application named MyMAFI (My Mobile Apps for Field Investigation) was developed with the aim to be an alternative and better tool for current practices of field investigation of food poisoning outbreak. A randomized cross-over trial with two arms and two treatment periods was conducted to assess the effectiveness of the newly developed mobile application as compared to the standard paper-based format approach. Thirty-six public health inspectors from all districts in Kelantan participated in this study and they were randomized into two equal sized groups. Group A started the trial as control group using the paper-format investigation form via simulated outbreaks and group B used the mobile application. After a one-month 'washout period', the group was crossed over. The primary outcome measured was the time taken to complete the outbreak investigation. The treatment effects, the period effects and the period-by-treatment interaction were analyzed using Pkcross command in Stata software. There was a significant treatment effect with mean square 21840.5 and its corresponding F statistic 4.47 (p-value = 0.038), which indicated that the mobile application had significantly improve the reporting timeliness. The results also showed that there was a significant period effect (p-value = 0.025); however, the treatment by period interaction was not significant (p-value = 0.830). The newly developed mobile application-MyMAFI-can improve the timeliness in reporting for investigation of food poisoning outbreak.
  6. A Rahim AI, Ibrahim MI, Musa KI, Chua SL
    PMID: 34299905 DOI: 10.3390/ijerph18147454
    Patient satisfaction is one indicator used to assess the impact of accreditation on patient care. However, traditional patient satisfaction surveys have a few disadvantages, and some researchers have suggested that social media be used in their place. Social media usage is gaining popularity in healthcare organizations, but there is still a paucity of data to support it. The purpose of this study was to determine the association between online reviews and hospital patient satisfaction and the relationship between online reviews and hospital accreditation. We used a cross-sectional design with data acquired from the official Facebook pages of 48 Malaysian public hospitals, 25 of which are accredited. We collected all patient comments from Facebook reviews of those hospitals between 2018 and 2019. Spearman's correlation and logistic regression were used to evaluate the data. There was a significant and moderate correlation between hospital patient satisfaction and online reviews. Patient satisfaction was closely connected to urban location, tertiary hospital, and previous Facebook ratings. However, hospital accreditation was not found to be significantly associated with online reports of patient satisfaction. This groundbreaking study demonstrates how Facebook reviews can assist hospital administrators in monitoring their institutions' quality of care in real time.
  7. Chen XW, Shafei MN, Abdullah JM, Musa KI
    Neuroepidemiology, 2019;52(3-4):214-219.
    PMID: 30799411 DOI: 10.1159/000497238
    BACKGROUND: A comprehensive evaluation of interrater reliability is crucial when it comes to multiple coders assessing the stroke outcomes using telephone interview. The reliability between telephone raters is important, as it could affect the accuracy of the findings published.

    OBJECTIVE: This study aimed to establish the interrater reliability between multiple telephone interviewers when assessing long-term stroke outcomes.

    METHODS: Patients alive at discharge selected in a retrospective cohort stroke project were recruited in this study. Their contact numbers were obtained from the medical record unit. The patients and/or proxies were interviewed based on a standardized script in Malay or English. Stroke outcomes assessed were modified Rankin Scale (mRS) and Barthel Index (BI) at 1-year post discharge. Fully crossed design was applied and 3 assessors collected the data simultaneously. Data was analysed using the software R version 3.4.4.

    RESULTS: Out of 207 subjects recruited, 132 stroke survivors at the time of interview were analysed. We found a significant excellent interrater reliability between telephone interviewers assessing BI, with intraclass correlation coefficient at 0.996 (95% CI 0.995-0.997). Whereas substantial agreement between the telephone interviewers was revealed in assessing mRS, with Fleiss', Conger's and Light's Kappa statistics reporting 0.719 and the Nelson's model-based κm kappa statistic reporting 0.689 (95% CI 0.667-0.711).

    CONCLUSION: It is reliable to get multiple raters in assessing mRS and BI using the telephone system. It is worthwhile to make use of a telephone interview to update clinicians on their acute clinical management towards long-term stroke prognosis.

  8. Masrani AS, Nik Husain NR, Musa KI, Yasin AS
    Biomed Res Int, 2021;2021:3540964.
    PMID: 34734083 DOI: 10.1155/2021/3540964
    Introduction: Dengue, a vector-borne viral illness, shows worldwide widening spatial distribution beyond its point of origination, namely, the tropical belt. The persistent hyperendemicity in Malaysia has resulted in the formation of the dengue early warning system. However, weather variables are yet to be fully utilized for prevention and control activities, particularly in east-coast peninsular Malaysia where limited studies have been conducted. We aim to provide a time-based estimate of possible dengue incidence increase following weather-related changes, thereby highlighting potential dengue outbreaks.

    Method: All serologically confirmed dengue patients in Kelantan, a northeastern state in Malaysia, registered in the eDengue system with an onset of disease from January 2016 to December 2018, were included in the study with the exclusion of duplicate entry. Using a generalized additive model, climate data collected from the Kota Bharu weather station (latitude 6°10'N, longitude 102°18'E) was analysed with dengue data.

    Result: A cyclical pattern of dengue cases was observed with annual peaks coinciding with the intermonsoon period. Our analysis reveals that maximum temperature, mean temperature, rainfall, and wind speed have a significant nonlinear effect on dengue cases in Kelantan. Our model can explain approximately 8.2% of dengue incidence variabilities.

    Conclusion: Weather variables affect nearly 10% of the dengue incidences in Northeast Malaysia, thereby making it a relevant variable to be included in a dengue early warning system. Interventions such as vector control activities targeting the intermonsoon period are recommended.

  9. Masrani AS, Nik Husain NR, Musa KI, Yasin AS
    J Prev Med Public Health, 2022 Jan;55(1):80-87.
    PMID: 35135051 DOI: 10.3961/jpmph.21.461
    OBJECTIVES: Dengue remains hyperendemic in Malaysia despite extensive vector control activities. With dynamic changes in land use, urbanisation and population movement, periodic updates on dengue transmission patterns are crucial to ensure the implementation of effective control strategies. We sought to assess shifts in the trends and spatial patterns of dengue in Kelantan, a north-eastern state of Malaysia (5°15'N 102°0'E).

    METHODS: This study incorporated data from the national dengue monitoring system (eDengue system). Confirmed dengue cases registered in Kelantan with disease onset between January 1, 2016 and December 31, 2018 were included in the study. Yearly changes in dengue incidence were mapped by using ArcGIS. Hotspot analysis was performed using Getis-Ord Gi to track changes in the trends of dengue spatial clustering.

    RESULTS: A total of 10 645 dengue cases were recorded in Kelantan between 2016 and 2018, with an average of 10 dengue cases reported daily (standard deviation, 11.02). Areas with persistently high dengue incidence were seen mainly in the coastal region for the 3-year period. However, the hotspots shifted over time with a gradual dispersion of hotspots to their adjacent districts.

    CONCLUSIONS: A notable shift in the spatial patterns of dengue was observed. We were able to glimpse the shift of dengue from an urban to peri-urban disease with the possible effect of a state-wide population movement that affects dengue transmission.

  10. Rahim AIA, Ibrahim MI, Chua SL, Musa KI
    Healthcare (Basel), 2021 Dec 03;9(12).
    PMID: 34946405 DOI: 10.3390/healthcare9121679
    While experts have recognised the significance and necessity of social media integration in healthcare, no systematic method has been devised in Malaysia or Southeast Asia to include social media input into the hospital quality improvement process. The goal of this work is to explain how to develop a machine learning system for classifying Facebook reviews of public hospitals in Malaysia by using service quality (SERVQUAL) dimensions and sentiment analysis. We developed a Machine Learning Quality Classifier (MLQC) based on the SERVQUAL model and a Machine Learning Sentiment Analyzer (MLSA) by manually annotated multiple batches of randomly chosen reviews. Logistic regression (LR), naive Bayes (NB), support vector machine (SVM), and other methods were used to train the classifiers. The performance of each classifier was tested using 5-fold cross validation. For topic classification, the average F1-score was between 0.687 and 0.757 for all models. In a 5-fold cross validation of each SERVQUAL dimension and in sentiment analysis, SVM consistently outperformed other methods. The study demonstrates how to use supervised learning to automatically identify SERVQUAL domains and sentiments from patient experiences on a hospital's Facebook page. Malaysian healthcare providers can gather and assess data on patient care via the use of these content analysis technology to improve hospital quality of care.
  11. Mat Said N, Musa KI, Mohamed Daud MA, Haron J
    Malays J Med Sci, 2016 Jul;23(4):26-32.
    PMID: 27660542 MyJurnal DOI: 10.21315/mjms2016.23.4.4
    We compared the patency and the suitability of arteriovenous fistula (AVF) created for vascular access by two approaches: (a) physical examination with preoperative vascular mapping and (b) physical examination alone.
  12. Rus RM, Daud A, Musa KI, Naing L
    Malays J Med Sci, 2008 Oct;15(4):28-34.
    PMID: 22589635
    The purpose of this study was to determine the sawmill workers' knowledge, attitude and practice (KAP) in relation to noise-induced hearing loss (NIHL). A cross-sectional study was conducted involving 83 workers from 3 factories in Kota Bharu, Kelantan. Questionnaires were distributed to obtain the socio-demography, knowledge, attitude and practice level in relation to noise-induced hearing loss (NIHL). The weak areas identified in the knowledge section were treatment aspects (15.5%), signs and symptoms of NIHL (20.2%) and risk factors (31%). As for attitude; the prevention aspects were the lowest (25.3%), followed by risk taking attitude (26.2%), and causes of hearing loss (42.1%). Overall, the practice was not encouraging at all. It is important to have an education program to raise workers' awareness and to improve their attitude and practices towards noise-induced hearing loss.
  13. Sukeri S, Daud A, Musa KI, Idris N
    Malays J Med Sci, 2019 Nov;26(6):1-4.
    PMID: 31908582 DOI: 10.21315/mjms2019.26.6.1
    The article introduces readers to the Master of Public Health and Doctor of Public Health programmes, offered by the Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia. The programme vision, structure and accomplishments over the decade are presented to provide an understanding of the programme. It is hoped that this professional programme will continue to flourish and produce new generations of public health medicine specialist equipped with the necessary knowledge and skills to make significant contribution towards improving the health of the population.
  14. Alarhabi AY, Mohamed MS, Ibrahim S, Hun TM, Musa KI, Yusof Z
    J Clin Hypertens (Greenwich), 2009 Jan;11(1):17-21.
    PMID: 19125854 DOI: 10.1111/j.1751-7176.2008.00061.x
    To determine whether pulse wave velocity (PWV) as a measure of arterial stiffness is a marker of coronary artery diseases (CAD), the authors did a cross-sectional study in 92 patients undergoing coronary angiography for suspected CAD. Arterial stiffness was assessed through recording PWV from the left carotid-right femoral arteries using an automated machine. The mean PWV was higher in patients with CAD than in those without CAD (11.13+/-0.91 vs 8.14+/-1.25 m/sec; P
  15. Idris Z, Ghani RI, Musa KI, Ibrahim MI, Abdullah M, Nyi NN, et al.
    Asian J Surg, 2007 Jul;30(3):200-8.
    PMID: 17638640
    To determine whether or not multimodality monitoring technique would result in a better outcome score than single modality monitoring in severely head injured patients.
  16. Biswal BM, Sulaiman SA, Ismail HC, Zakaria H, Musa KI
    Integr Cancer Ther, 2013 Jul;12(4):312-22.
    PMID: 23142798 DOI: 10.1177/1534735412464551
    Hypothesis. Withania somnifera is an herb with antioxidant, anti-inflammatory, anticancer, antistress, and adaptogenic properties. Previous studies have shown its antistress effects in animals. Traditional Indian medicine has used it for centuries to alleviate fatigue and improve general well-being.
  17. Jannoo Z, Yap BW, Musa KI, Lazim MA, Hassali MA
    Qual Life Res, 2015 Sep;24(9):2297-302.
    PMID: 25800728 DOI: 10.1007/s11136-015-0969-8
    PURPOSE: The aim of this study was to evaluate and validate the ADDQoL and to assess the impact of diabetes on QoL among the type 2 diabetes mellitus patients in Malaysia.

    METHODS: The Malay and English versions of the ADDQoL questionnaire were administered to patients attending routine outpatient visits in three primary hospitals and a public clinic. The construct validity of the ADDQoL was validated using confirmatory factor analysis (CFA). The sample comprised 350 Malay respondents who rated the ADDQoL Malay version and 246 non-Malay respondents (Chinese or Indian) who answered using the ADDQoL original English version.

    RESULTS: CFA confirmed the presence of one-factor structure for both samples. The internal consistency was high with Cronbach's alpha values of 0.945 and 0.907 for the ADDQoL Malay and English versions, respectively. Results showed that for all three ethnicities, the most important domain is 'family life'. Overall, Malay patients stated their 'living conditions' is the most negatively affected, while for Chinese and Indians, diabetes has the greatest impact on their 'freedom to eat'.

    CONCLUSIONS: The ADDQoL was found to be culturally appropriate, valid and reliable among Malay- and English-speaking type 2 diabetes mellitus patients in Malaysia.

    Study site: routine outpatient visits in three primary hospitals and a public clinic
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