Displaying publications 61 - 80 of 389 in total

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  1. Sthaneshwar P, Shanmugam H, Swan VG, Nasurdin N, Tanggaiah K
    Pathology, 2013 06;45(4):417-9.
    PMID: 23635828 DOI: 10.1097/PAT.0b013e32836142eb
    AIM: Measurement of HbA1c provides an excellent measure of glycaemic control for diabetic patients. However, haemoglobin (Hb) variants are known to interfere with HbA1c analysis. In our laboratory HbA1c measurement is performed by Variant II turbo 2.0. The aim of this study is to investigate the influence of HbE trait on HbA1c analysis.

    METHODS: Haemoglobin variants were identified by HbA1c analysis in 93 of 3522 samples sent to our laboratory in a period of 1 month. Haemoglobin analysis identified HbE trait in 81 of 93 samples. To determine the influence of HbE trait on HbA1c analysis by Variant II Tubo 2.0, boronate affinity high performance liquid chromatography (HPLC) method (Primus PDQ) was used as the comparison method. Two stage linear regression analysis, Bland Altman plot and Deming regression analysis were performed to analyse whether the presence of HbE trait produced a statistically significant difference in the results. The total allowable error for HbA1c by the Royal Australasian College of Pathologists (RCPA) external quality assurance is 5%. Hence clinically significant difference is more than 5% at the medical decision level of 6% and 9%.

    RESULTS: Statistically and clinically significant higher results were observed in Variant II Turbo 2.0 due to the presence of HbE trait. A positive bias of ∼10% was observed at the medical decision levels.

    CONCLUSION: Laboratories should be cautious when evaluating HbA1c results in the presence of haemoglobin variants.

    Matched MeSH terms: Linear Models
  2. Stear A, Ali AOA, Brujeni GN, Buitkamp J, Donskow-Łysoniewska K, Fairlie-Clarke K, et al.
    Int J Parasitol, 2019 09;49(10):797-804.
    PMID: 31306661 DOI: 10.1016/j.ijpara.2019.05.003
    Lambs with the Major Histocompatibility Complex DRB1*1101 allele have been shown to produce fewer nematode eggs following natural and deliberate infection. These sheep also possess fewer adult Teladorsagia circumcincta than sheep with alternative alleles at the DRB1 locus. However, it is unclear if this allele is responsible for the reduced egg counts or merely acts as a marker for a linked gene. This study defined the MHC haplotypes in a population of naturally infected Scottish Blackface sheep by PCR amplification and sequencing, and examined the associations between MHC haplotypes and faecal egg counts by generalised linear mixed modelling. The DRB1*1101 allele occurred predominately on one haplotype and a comparison of haplotypes indicated that the causal mutation or mutations occurred in or around this locus. Additional comparisons with another resistant haplotype indicated that mutations in or around the DQB2*GU191460 allele were also responsible for resistance to nematode infections. Further analyses identified six amino acid substitutions in the antigen binding site of DRB1*1101 that were significantly associated with reductions in the numbers of adult T. circumcincta.
    Matched MeSH terms: Linear Models
  3. Souad Neffar, Haroun Chenchouni, Arifa Beddiar
    Sains Malaysiana, 2015;44:671-680.
    Mycorrhizal fungi are an essential component to consider for better management of soil fertility, particularly in
    degraded rangelands of drylands. The present article presents a field survey of colonization and intensity of arbuscular
    mycorrhizal fungi (AMF) on prickly pear (Opuntia ficus-indica) roots from young (5 years old) and old (more than 20
    years) plantations. The results observed were explained by seasonality and edaphic factors. Prickly pear roots showed
    a mycorrhizal frequency (F%) up to 100% of colonization and a mycorrhizal intensity (M%) that may exceed 70%.
    According to ANOVAs, both F% and M% varied significantly between Prickly pear plantation ages, but only M% between
    seasons. The Generalized linear model showed that edaphic factors have no effect on the variation of F%. However
    the statistical model showed that M% were significantly influenced by active CaCO3
    , organic matter, carbon, nitrogen,
    phosphorus contents and C/N. Our findings highlight the importance of mycorrhization in rehabilitation programs of
    degraded rangelands by prickly pear plantations in semiarid and arid lands, particularly during early plant ages and
    under environmental abiotic stresses such as climate and soil type.
    Matched MeSH terms: Linear Models
  4. Soliman K, Jirjees F, Sonawane R, Sheshala R, Wang Y, Jones D, et al.
    J Chromatogr Sci, 2021 Jan 01;59(1):64-70.
    PMID: 33047781 DOI: 10.1093/chromsci/bmaa078
    Anti-glaucoma latanoprost-loaded ocular implants provide prolonged delivery and enhanced bioavailability relative to the conventional eye drops. This study aims at the development and validation of a reversed-phase high-performance liquid chromatography method for quantitative analysis of nanogram levels of latanoprost in the eye, and for the first time, compares the use of fluorescence vs ultraviolet (UV) detectors in latanoprost quantification. The mobile phase was composed of acetonitrile:0.1% v/v formic acid (60:40, v/v) with a flow rate of 1 mL/min and separation was done using a C18 column at temperature 40°C. The fluorescence excitation and emission wavelengths were set at 265 and 285 nm, respectively, while the UV absorption was measured at 200 nm. The latanoprost concentration-peak area relationship maintained its linearity (R2 = 0.9999) over concentration ranges of 0.063-10 μg/mL and 0.212-10 μg/mL for the fluorescence and UV detectors, respectively. The UV detector showed better precision, while the fluorescence detector exhibited higher robustness and greater sensitivity, with a detection limit of 0.021 μg/mL. The fluorescence detector was selected for quantification of latanoprost released from ocular implants in vitro and in porcine ocular tissues. The developed method is a robust, rapid and cost-effective alternative to liquid chromatography-mass spectrometry for routine analysis of latanoprost released from ocular implants.
    Matched MeSH terms: Linear Models
  5. Smith JD
    Math Biosci, 1998 Nov;153(2):151-61.
    PMID: 9825637
    The Gibbs canonical ensemble of statistical mechanics is used to describe the probability distribution of the age classes of mothers of new-borns in an age-structured population. The Malthusian parameter emerges as a Lagrange multiplier corresponding to a generation time constraint, while a new perturbation parameter appears as the Lagrange multiplier corresponding to a maternity constraint. Classical Lotka stability reduces to the unperturbed case of the more general canonical ensemble model. The model is used in a case study of the female (peninsular) Malaysian population of 1970. The Malthusian parameter and perturbation are calculated easily by linear regression. Use of the model identifies an anomaly in the population due to the effects of World War II.
    Matched MeSH terms: Linear Models
  6. Skau JK, Nordin AB, Cheah JC, Ali R, Zainal R, Aris T, et al.
    Trials, 2016;17(1):215.
    PMID: 27117703 DOI: 10.1186/s13063-016-1345-x
    Over the past two decades, the population of Malaysia has grown rapidly and the prevalence of diabetes mellitus in Malaysia has dramatically increased, along with the frequency of obesity, hyperlipidaemia and hypertension. Early-life influences play an important role in the development of non-communicable diseases. Indeed, maternal lifestyle and conditions such as gestational diabetes mellitus or obesity can affect the risk of diabetes in the next generation. Lifestyle changes can help to prevent the development of type 2 diabetes mellitus. This is a protocol for an unblinded, community-based, randomised controlled trial in two arms to evaluate the efficacy of a complex behavioural change intervention, combining motivational interviewing provided by a community health promoter and access to a habit formation mobile application, among young Malaysian women and their spouses prior to pregnancy.
    Matched MeSH terms: Linear Models
  7. Siti Zuliana Md Z, Siti Fardaniah Abdul A
    The effectiveness of training is an important aspect in the development of training. After investing a lot of money to organize a training program, the organization often wants to know about the effectiveness of training given to trainee as well as how it can gives impact to the organization. This study was conducted to evaluate the effectiveness of training tested through learning performance among trainees that undergo a transition in the Perbadanan Hal Ehwal Bekas Angkatan Tentera (PERHEBAT). In this study, personal characteristics and training program characteristics acted as the independent variables in predicting learning performance. The instrument used in this study was adapted from Trainee Characteristic Scale, Training Program Characteristic Scale and Training Effectiveness Scale by Siti Fardaniah (2013) for personal characteristics, training program characteristics and learning performance. Questionnaires to measure the dimension of training transfer for the training characteristics was adapted from the Learning Transfer System Inventory (LTSI) by Holton et al. (2000). Data obtained were analyzed using Statistical Package for Social Sciences (SPSS) version 23. The multiple linear regression analysis indicated that extrinsic orientation, self-efficacy and organizational commitment have significant influence on learning performance. Relevance of training content and learning transfer design also affecedt learning performance. Findings in this study can be used as a reference to improve training effectiveness by focusing on personal characteristics and training characteristics conducted in PERHEBAT.
    Matched MeSH terms: Linear Models
  8. Siti Hajar MH, Zulkefli S, Juwita S, Norhayati MN, Siti Suhaila MY, Rasool AHG, et al.
    PeerJ, 2018;6:e5758.
    PMID: 30356972 DOI: 10.7717/peerj.5758
    Background: Secondhand smoke (SHS) exposure has adverse effects on the cardiovascular system. This study aimed to determine the effects of SHS on the cardiovascular disease biomarkers, namely the metabolic, inflammatory, and oxidative stress markers in healthy adult women.

    Methods: This comparative cross-sectional study was conducted among healthy women. The cases included those women exposed to SHS, and the controls included those women not exposed to SHS. SHS exposure was defined as being exposed to SHS for at least 15 min for 2 days per week. Venous blood was taken to measure the metabolic markers (high molecular weight adiponectin, insulin level, insulin resistance, and nonesterified fatty acids), oxidative stress markers (oxidized low density lipoprotein cholesterol and 8-isoprostane), and inflammatory markers (high-sensitivity C-reactive protein and interleukin-6). A hair nicotine analysis was also performed. An analysis of covariance and a simple linear regression analysis were conducted.

    Results: There were 101 women in the SHS exposure group and 91 women in the non-SHS exposure group. The mean (with standard deviation) of the hair nicotine levels was significantly higher in the SHS exposure group when compared to the non-SHS exposure group [0.22 (0.62) vs. 0.04 (0.11) ng/mg; P = 0.009]. No significant differences were observed in the high molecular weight adiponectin, insulin and insulin resistance, nonesterified fatty acids, 8-isoprostane, oxidized low density lipoprotein cholesterol, interleukin-6, and high-sensitivity C-reactive protein between the two groups. The serum high molecular weight adiponectin was negatively associated with the insulin level and insulin resistance in the women exposed to SHS. However, no significant relationships were seen between the high molecular weight adiponectin and nonesterified fatty acids, 8-isoprostane, oxidized low density lipoprotein cholesterol, high-sensitivity C-reactive protein in the SHS group.

    Discussion: There were no significant differences in the metabolic, oxidative stress, and inflammatory markers between the SHS exposure and non-SHS exposure healthy women. A low serum level of high molecular weight adiponectin was associated with an increased insulin level and resistance in the women exposed to SHS.

    Matched MeSH terms: Linear Models
  9. Siti Hafizan Hassan, Hamidi Abdul Aziz, Mohd Samsudin Abdul Hamid, Siti Rashidah Mohd Nasir, Suhailah Mohamed Noor
    ESTEEM Academic Journal, 2019;15(2):11-23.
    MyJurnal
    The effect of unmanageable construction waste is an unstable land settlement and groundwater pollution. In addition to environmental pollution, construction waste could incur construction cost. The most construction waste is the material used at sites and tile is also a part of the waste generated in construction. The objectives of this study are to determine the tile waste generated in construction stages and linear regression analysis for the amount of tile waste generated. The method used in this study was the Linear Regression Model. The regression model established in the sample data reported an R2 value of 0.793; therefore, the model can predict approximately 79.3% of the factor (area) of tile waste generation. The linear regressions can be applied as tools to predict the tile waste generated at construction sites and help the contractor to track the sources of missing waste.
    Matched MeSH terms: Linear Models
  10. Siong, Wee Boon, Ebihara, Mitsuru
    MyJurnal
    Prompt gamma-ray analysis (PGA) and instrumental neutron activation analysis (INAA) are essential for the study of rare samples such as meteorites because of non-destructivity and relatively being free from contaminations. The objective of this research is to utilize PGA and INAA techniques for comparative study and apply them to meteorite analyses. In this study, 11 meteorite samples received from the Meteorite Working Group of NASA were analyzed. The Allende meteorite powder was included as quality control material. Results from PGA and INAA for Allende showed in good agreement with literature values, signifying the reliabilities of these two methods. Elements Al, Ca, Mg, Mn, Na and Ti were determined by both methods and their results are compared. Comparison of PGA and INAA data using linear regression analysis showed correlations coefficients r2 > 0.90 for Al, Ca, Mn and Ti, 0.85 for Mg, and 0.38 for Na. The PGA results for Na using 472 keV were less accurate due to the interference from the broad B peak. Therefore, Na results from INAA method are preferred. For other elements (Al, Ca, Mg, Mn and Ti), PGA and INAA results can be used as cross-reference for consistency. The PGA and INAA techniques have been applied to meteorite samples and results are comparable to literature values compiled from previously analyzed meteorites. In summary, both PGA and INAA methods give reasonably good agreement and are indispensable in the study of meteorites.
    Matched MeSH terms: Linear Models
  11. Singh R, Singh HJ, Sirisinghe RG
    PMID: 7855654
    Spirometry was performed on 1,485 male subjects ranging in age from 13 years to 78 years and comprising of all the main ethnic groups in Malaysia. They were divided into six age categories. Mean forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV1) were 3.45 +/- 0.02 and 3.10 +/- 0.02, respectively. Both FVC and FEV1 correlated negatively with age. Regression analysis revealed an age-related decline in FVC of 295 ml per decade of life. Multiple stepwise regression of the data for the prediction of an individual's FVC above the age of 20 years gave the equation FVC (1) = 0.0404 (height in cm)-0.0295 (age in years)-2.2892. Predicted FVC values derived from equations based on other populations were considerably higher than the observed mean in this study. This study therefore, reemphasises the need to be cautions when applying formulae derived from one population to another. Grossly erroneous conclusions may be reached unless predicted equations for lung-function tests for a given population group are derived from studies based upon the same population group.
    Matched MeSH terms: Linear Models
  12. Siavash NK, Ghobadian B, Najafi G, Rohani A, Tavakoli T, Mahmoodi E, et al.
    Environ Res, 2021 05;196:110434.
    PMID: 33166537 DOI: 10.1016/j.envres.2020.110434
    Wind power is one of the most popular sources of renewable energies with an ideal extractable value that is limited to 0.593 known as the Betz-Joukowsky limit. As the generated power of wind machines is proportional to cubic wind speed, therefore it is logical that a small increment in wind speed will result in significant growth in generated power. Shrouding a wind turbine is an ordinary way to exceed the Betz limit, which accelerates the wind flow through the rotor plane. Several layouts of shrouds are developed by researchers. Recently an innovative controllable duct is developed by the authors of this work that can vary the shrouding angle, so its performance is different in each opening angle. As a wind tunnel investigation is heavily time-consuming and has a high cost, therefore just four different opening angles have been assessed. In this work, the performance of the turbine was predicted using multiple linear regression and an artificial neural network in a wide range of duct opening angles. For the turbine power generation and its rotor angular speed in different wind velocities and duct opening angles, regression and an ANN are suggested. The developed neural network model is found to possess better performance than the regression model for both turbine power curve and rotor speed estimation. This work revealed that in higher ranges of wind velocity, the turbine performance intensively will be a function of shrouding angle. This model can be used as a lookup table in controlling the turbines equipped with the proposed mechanism.
    Matched MeSH terms: Linear Models
  13. Shyam S, Arshad F, Abdul Ghani R, Wahab NA, Safii NS, Nisak MY, et al.
    Nutr J, 2013 May 24;12:68.
    PMID: 23705645 DOI: 10.1186/1475-2891-12-68
    BACKGROUND: Gestational Diabetes Mellitus (GDM) increases risks for type 2 diabetes and weight management is recommended to reduce the risk. Conventional dietary recommendations (energy-restricted, low fat) have limited success in women with previous GDM. The effect of lowering Glycaemic Index (GI) in managing glycaemic variables and body weight in women post-GDM is unknown.

    OBJECTIVE: To evaluate the effects of conventional dietary recommendations administered with and without additional low-GI education, in the management of glucose tolerance and body weight in Asian women with previous GDM.

    METHOD: Seventy seven Asian, non-diabetic women with previous GDM, between 20- 40y were randomised into Conventional healthy dietary recommendation (CHDR) and low GI (LGI) groups. CHDR received conventional dietary recommendations only (energy restricted, low in fat and refined sugars, high-fibre). LGI group received advice on lowering GI in addition. Fasting and 2-h post-load blood glucose after 75 g oral glucose tolerance test (2HPP) were measured at baseline and 6 months after intervention. Anthropometry and dietary intake were assessed at baseline, three and six months after intervention. The study is registered at the Malaysian National Medical Research Register (NMRR) with Research ID: 5183.

    RESULTS: After 6 months, significant reductions in body weight, BMI and waist-to-hip ratio were observed only in LGI group (P<0.05). Mean BMI changes were significantly different between groups (LGI vs. CHDR: -0.6 vs. 0 kg/m2, P= 0.03). More subjects achieved weight loss ≥5% in LGI compared to CHDR group (33% vs. 8%, P=0.01). Changes in 2HPP were significantly different between groups (LGI vs. CHDR: median (IQR): -0.2(2.8) vs. +0.8 (2.0) mmol/L, P=0.025). Subjects with baseline fasting insulin≥2 μIU/ml had greater 2HPP reductions in LGI group compared to those in the CHDR group (-1.9±0.42 vs. +1.31±1.4 mmol/L, P<0.001). After 6 months, LGI group diets showed significantly lower GI (57±5 vs. 64±6, P<0.001), GL (122±33 vs. 142±35, P=0.04) and higher fibre content (17±4 vs.13±4 g, P<0.001). Caloric intakes were comparable between groups.

    CONCLUSION: In women post-GDM, lowering GI of healthy diets resulted in significant improvements in glucose tolerance and body weight reduction as compared to conventional low-fat diets with similar energy prescription.

    Matched MeSH terms: Linear Models
  14. Shazlin Umar, Azriani Ab Rahman, Aziah Daud, Azizah Othman, Normastura Abd Rahman, Azizah Yusoff, et al.
    MyJurnal
    Objective: The objectives of this study were to determine the effect of a one and a half year educational intervention on the job dissatisfaction of teachers in 30 Community Based Rehabilitation (CBR) centres in Kelantan, Malaysia, and to identify the factors influencing changes in job dissatisfaction following the intervention. Method: Ten educational modules were administered to the teachers. A validated Malay version of Job Content Questionnaire (JCQ) was used pre intervention, mid intervention and post intervention. Result: Repeated Measure ANOVA revealed there was a statistically significant reduction in the mean of job dissatisfaction (p = 0.048). Multiple Linear Regression revealed that co- worker support (β= 0.034 (95% CI = 0.009, 0.059)), having less decision authority (β: -0.023; 95% CI: -0.036, -0.01) and being single (β: -0.107; 95% CI: -0.176,-0.038) were significantly associated with decreases in job dissatisfaction. Conclusion: The intervention program elicited improvement in job satisfaction. Efforts should be made to sustain the effect of the intervention in reducing job dissatisfaction by continuous support visits to CBR centres.
    Matched MeSH terms: Linear Models
  15. Shashvat K, Basu R, Bhondekar PA, Kaur A
    Trop Biomed, 2019 Dec 01;36(4):822-832.
    PMID: 33597454
    Time series modelling and forecasting plays an important role in various domains. The objective of this paper is to construct a simple average ensemble method to forecast the number of cases for infectious diseases like dengue and typhoid and compare it by applying models for forecasting. In this paper we have also evaluated the correlation between the number of typhoid and dengue cases with the ecological variables. The monthly data of dengue and typhoid cases from 2014 to 2017 were taken from integrated diseases surveillance programme, Government of India. This data was analysed by three models namely support vector regression, neural network and linear regression. The proposed simple average ensemble model was constructed by ensemble of three applied regression models i.e. SVR, NN and LR. We combine the regression models based upon the error metrics such as Mean Square Error, Root Mean Square Error and Mean Absolute Error. It was found that proposed ensemble method performed better in terms of forecast measures. The finding demonstrates that the proposed model outperforms as compared to already available applied models on the basis of forecast accuracy.
    Matched MeSH terms: Linear Models
  16. Shariati NH, Zahedi E, Jajai HM
    Physiol Meas, 2008 Mar;29(3):365-74.
    PMID: 18367811 DOI: 10.1088/0967-3334/29/3/007
    Bilateral PPG signals have been used for comparative study of two groups of healthy (free from any cardiovascular risk factors) and diabetic (as cardiovascular disease risk group) subjects in the age-matched range 40-50 years. The peripheral blood pulsations were recorded simultaneously from right and left index fingers for 90 s. Pulses have been modeled with the ARX440 model in the interval of 300 sample points with 100 sample points overlap between segments. Model parameters of three segments based on the highest fitness (higher than 80%) of modeled segments were retained for each subject. Subsequently, principal component analysis (PCA) was applied to the parameters of retained segments to eliminate the existing correlation among parameters and provide uncorrelated variables. The first principal component (contains 78.2% variance of data) was significantly greater in diabetic than in control groups (P < 0.0001, 0.74 +/- 2.01 versus -0.53 +/- 1.66). In addition the seventh principal component, which contains 0.02% of the data variance, was significantly lower in diabetic than in control groups (P < 0.05, -0.007 +/- 0.03 versus 0.005 +/- 0.03). Finally, linear discrimination analysis (LDA) was used to classify the subjects. The classification was done using the robust leaving-one-subject-out method. LDA could classify the subjects with 71.7% sensitivity and 70.2% specificity while the male subjects resulted in a highly acceptable result for the sensitivity (81%). The present study showed that PPG signals can be used for vascular function assessment and may find further application for detection of vascular changes before onset of clinical diseases.
    Matched MeSH terms: Linear Models
  17. Shammugasamy B, Ramakrishnan Y, Ghazali HM, Muhammad K
    J Chromatogr A, 2013 Jul 26;1300:31-7.
    PMID: 23587317 DOI: 10.1016/j.chroma.2013.03.036
    A simple sample preparation technique coupled with reversed-phase high-performance liquid chromatography was developed for the determination of tocopherols and tocotrienols in cereals. The sample preparation procedure involved a small-scale hydrolysis of 0.5g cereal sample by saponification, followed by the extraction and concentration of tocopherols and tocotrienols from saponified extract using dispersive liquid-liquid microextraction (DLLME). Parameters affecting the DLLME performance were optimized to achieve the highest extraction efficiency and the performance of the developed DLLME method was evaluated. Good linearity was observed over the range assayed (0.031-4.0μg/mL) with regression coefficients greater than 0.9989 for all tocopherols and tocotrienols. Limits of detection and enrichment factors ranged from 0.01 to 0.11μg/mL and 50 to 73, respectively. Intra- and inter-day precision were lower than 8.9% and the recoveries were around 85.5-116.6% for all tocopherols and tocotrienols. The developed DLLME method was successfully applied to cereals: rice, barley, oat, wheat, corn and millet. This new sample preparation approach represents an inexpensive, rapid, simple and precise sample cleanup and concentration method for the determination of tocopherols and tocotrienols in cereals.
    Matched MeSH terms: Linear Models
  18. Shahmoradi N, Kandiah M, Peng LS
    Asian Pac J Cancer Prev, 2009;10(6):1003-09.
    PMID: 20192573
    BACKGROUND: Cancer patients frequently experience malnutrition and this is an important factor in impaired quality of life.

    OBJECTIVE: This cross-sectional study examined the association between global quality of life and its various subscales with nutritional status among 61 (33 females and 28 males) advanced cancer patients cared for by selected hospices in peninsular Malaysia.

    METHODS: The Patient Generated-Subjective Global Assessment (PG-SGA) and the Hospice Quality of Life Index (HQLI) were used to assess nutritional status and quality of life, respectively.

    RESULTS: Nine (14.7%) patients were well-nourished, 32 (52.5%) were moderately or suspected of being malnourished while 20 (32.8%) of them were severely malnourished. The total HQLI mean score for these patients was 189.9-/+51.7, with possible scores ranging from 0 to 280. The most problem areas in these patients were in the domain of functional well-being and the least problems were found in the social/spiritual domain. PG-SGA scores significantly correlated with total quality of life scores (r2= 0.38, p<0.05), psychophysiological well-being (r2= 0.37, p<0.05), functional well-being (r2= 0.42, p<0.05) and social/ spiritual well-being (r2= 0.07, p<0.05). Thus, patients with a higher PG-SGA score or poorer nutritional status exhibited a lower quality of life.

    CONCLUSION: Advanced cancer patients with poor nutritional status have a diminished quality of life. These findings suggest that there is a need for a comprehensive nutritional intervention for improving nutritional status and quality of life in terminally ill cancer patients under hospice care.

    Matched MeSH terms: Linear Models
  19. Shahid Hassan, Mohamad Najib Mat Pa, Muhamad Saiful Bahri Yusoff
    MyJurnal
    Background: Summative assessment in postgraduate examination globally employs multiple measures. A standard-setting method decides on pass or fail based on an arbitrarily defined cut-off point on a test score, which is often content expert’s subjective judgment. Contrary to this a standard-setting strategy primarily practices two approaches, a compensatory approach, which decides on overall performance as a sum of all the test scores and a conjunctive approach that requires passing performance for each instrument. However, the challenge using multiple measures is not due to number of measurement tools but due to logic by which the measures are combined to draw inferences on pass or fail in summative assessment. Conjoint University Board of Examination of Masters’ of Otolaryngology and Head-Neck Surgery (ORL-HNS) in Malaysia also uses multiple measures to reach a passing or failing decision in summative assessment. However, the standard setting strategy of assessment is loosely and variably applied to make ultimate decision on pass or fail. To collect the evidences, the summative assessment program of Masters’ of ORL-HNS in School of Medical Sciences at Universiti Sains Malaysia was analyzed for validity to evaluate the appropriateness of decisions in postgraduate medical education in Malaysia. Methodology: A retrospective study was undertaken to evaluate the validity of the conjoint summative assessment results of part II examination of USM candidates during May 2000-May 2011. The Pearson correlation and multiple linear regression tests were used to determine the discriminant and convergent validity of assessment tools. Pearson’s correlation coefficient analyzed the association between assessment tools and the multiple linear regression compared the dominant roles of factor variables in predicting outcomes. Based on outcome of the study, reforms for standard-setting strategy are also recommended towards programming the assessment in a surgical-based discipline. Results: The correlation coefficients of MCQ and essay questions were found not significant (0.16). Long and short cases were shown to have good correlations (0.53). Oral test stood as a component to show fair correlation with written (0.39-0.42) as well as clinical component (0.50-0.66). The predictive values in written tests suggested MCQ predicted by oral (B=0.34, P
    Matched MeSH terms: Linear Models
  20. Shahar S, Pooy NS
    Asia Pac J Clin Nutr, 2003;12(1):80-4.
    PMID: 12737015
    Height is an important clinical indicator to derive body mass index (BMI), creatinine height index and also to estimate basal energy expenditure, basal metabolic rate and vital capacity through lung function. However, height measurement in the elderly may impose some difficulties and the reliability is doubtful. Equations estimating height from other anthropometric measures have been developed for Caucasians, but only one study has developed an equation (based on arm span only) for an Asian population. Therefore, a cross sectional study was conducted to develop equations using several anthropometric measurements for estimating stature in Malaysian elderly. A total of 100 adults (aged 30 to 49 y) and 100 elderly subjects (aged 60 to 86 y) from three major ethnic groups of Malays (52%), Chinese (38.5%) and Indians (9.5%) participated in this study. Anthropometric measurements included body weight, height, arm span, half arm span, demi span and knee height were carried out by trained nutritionists. Inter and intra observer errors and also % Coefficient Variation (%CV) were calculated for each anthropometric measurement. Equations to estimate stature were developed from the anthropometric measurements of arm span, demi span and knee height of adults using linear regression analysis according to sex. Elderly subjects were shorter and lighter compared to their younger counterparts. The %CV of anthropometric measurements in adults and elderly subjects ranged between 5 to 6%, with standing height having the lowest %CV. When the equations derived from adults were applied to elderly subjects, it was found that percentage difference between actual height and the estimated value ranged from 1.0 to 3.3%. However, the percentage difference between estimated height from the equations developed in this study compared to those derived from the equations of other populations ranged between 0.2 to 8.7%. In conclusion, standing height is an ideal technique for estimating the stature of individuals. However, in cases where its measurement is not possible or reliable, such as in elderly subjects, height can be estimated from proxy indicators of stature. In this study arm span showed the highest correlation with standing height, which is in agreement with other studies. It should be borne in mind that equations derived from taller statured populations (e.g. Caucasians) may be less accurate when applied to shorter statured populations.
    Matched MeSH terms: Linear Models
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