Displaying publications 61 - 80 of 313 in total

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  1. Siddiqui S, Zainal H, Harun SN, Sheikh Ghadzi SM
    Clin Nutr ESPEN, 2019 02;29:213-223.
    PMID: 30661689 DOI: 10.1016/j.clnesp.2018.10.002
    BACKGROUND: The contribution of dietary factors in the development and progression of pre-diabetes has been increasingly recognized. However, due to high variability in dietary habits measurement of dietary intake remains one of the most challenging tasks in this population. Food frequency questionnaire (FFQ) which investigates usual dietary intake can be used to identify frequent consumption of foods such as dietary fat, fiber, grains that are linked to the risk of pre-diabetes.

    METHOD: This systematic review was conducted to identify and describe FFQs that measure dietary intake of pre-diabetic patients and to examine their relative validity and reliability. The systematic search was done through electronic databases such as PubMed, CINAHL, PsycINFO, ProQuest and Scopus. Methodological quality of included studies and results of study outcome was also summarized in this review.

    RESULT: The search identified 445 papers, of which 18 studies reported 15 FFQs, met inclusion criteria. Most of the FFQs (n = 12) were semi-quantitative while three were frequency measures with portion size estimation of selected food items. Test-retest reliability of FFQ was reported in 7 (38.3%) studies with the correlation coefficient of 0.33-0.92. Relative validity of FFQ was reported in 16 (88.8%) studies with the range of correlation coefficient of 0.08-0.83. Dietary patterns rich in carbohydrate, fat, animal protein and n-3 fatty acids were associated with increased risk of pre-diabetes.

    CONCLUSION: No well-established disease-specific FFQ identified in the literature. Development of a valid, practical and reliable tool is needed for better understanding of the impact of diet in pre-diabetic population.

    Matched MeSH terms: Databases, Factual
  2. Shyam S, Wai TN, Arshad F
    Asia Pac J Clin Nutr, 2012;21(2):201-8.
    PMID: 22507605
    This paper outlines the methodology to add glycaemic index (GI) and glycaemic load (GL) functionality to food DietPLUS, a Microsoft Excel-based Malaysian food composition database and diet intake calculator. Locally determined GI values and published international GI databases were used as the source of GI values. Previously published methodology for GI value assignment was modified to add GI and GL calculators to the database. Two popular local low GI foods were added to the DietPLUS database, bringing up the total number of foods in the database to 838 foods. Overall, in relation to the 539 major carbohydrate foods in the Malaysian Food Composition Database, 243 (45%) food items had local Malaysian values or were directly matched to International GI database and another 180 (33%) of the foods were linked to closely-related foods in the GI databases used. The mean ± SD dietary GI and GL of the dietary intake of 63 women with previous gestational diabetes mellitus, calculated using DietPLUS version3 were, 62 ± 6 and 142 ± 45, respectively. These values were comparable to those reported from other local studies. DietPLUS version3, a simple Microsoft Excel-based programme aids calculation of diet GI and GL for Malaysian diets based on food records.
    Matched MeSH terms: Databases, Factual*
  3. Sharma M, Goyal D, Achuth PV, Acharya UR
    Comput Biol Med, 2018 07 01;98:58-75.
    PMID: 29775912 DOI: 10.1016/j.compbiomed.2018.04.025
    Sleep related disorder causes diminished quality of lives in human beings. Sleep scoring or sleep staging is the process of classifying various sleep stages which helps to detect the quality of sleep. The identification of sleep-stages using electroencephalogram (EEG) signals is an arduous task. Just by looking at an EEG signal, one cannot determine the sleep stages precisely. Sleep specialists may make errors in identifying sleep stages by visual inspection. To mitigate the erroneous identification and to reduce the burden on doctors, a computer-aided EEG based system can be deployed in the hospitals, which can help identify the sleep stages, correctly. Several automated systems based on the analysis of polysomnographic (PSG) signals have been proposed. A few sleep stage scoring systems using EEG signals have also been proposed. But, still there is a need for a robust and accurate portable system developed using huge dataset. In this study, we have developed a new single-channel EEG based sleep-stages identification system using a novel set of wavelet-based features extracted from a large EEG dataset. We employed a novel three-band time-frequency localized (TBTFL) wavelet filter bank (FB). The EEG signals are decomposed using three-level wavelet decomposition, yielding seven sub-bands (SBs). This is followed by the computation of discriminating features namely, log-energy (LE), signal-fractal-dimensions (SFD), and signal-sample-entropy (SSE) from all seven SBs. The extracted features are ranked and fed to the support vector machine (SVM) and other supervised learning classifiers. In this study, we have considered five different classification problems (CPs), (two-class (CP-1), three-class (CP-2), four-class (CP-3), five-class (CP-4) and six-class (CP-5)). The proposed system yielded accuracies of 98.3%, 93.9%, 92.1%, 91.7%, and 91.5% for CP-1 to CP-5, respectively, using 10-fold cross validation (CV) technique.
    Matched MeSH terms: Databases, Factual
  4. Shakor ASA, Samsudin EZ, Chen XW, Ghazali MH
    J Infect Public Health, 2023 Dec;16(12):2068-2078.
    PMID: 37950972 DOI: 10.1016/j.jiph.2023.10.016
    BACKGROUND: The phenomenon of Coronavirus disease 2019 (COVID-19) brought-in-dead (BID), i.e., COVID-19 deaths occurring outside hospital settings, suggests missed opportunities for life-saving care. However, much is still unknown with regards to its potential determinants. The present study aimed to examine the factors associated with COVID-19 BID by integrating new variables from multiple databases.

    METHODS: This multi-database comparative cross-sectional study examined COVID-19 in-patient deaths (IPD) and COVID-19 BID (n = 244 in each group) in Selangor, Malaysia. BID cases, IPD cases, and their sociodemographic, clinical, and health behaviour factors were identified from the COVID-19 mortality investigation reports submitted to the Selangor State Health Department between 14 February 2022 and 31 March 2023. Data linkage was used to connect three open-source databases-GitHub-MOH, Socioeconomic Data and Applications Center, and OpenStreetMap-and identify health infrastructure and geospatial factors. The groups were compared using chi-square tests, independent t-tests, and logistic regression analyses to identify factors associated with COVID-19 BID.

    RESULTS: The COVID-19 IPD and BID cases were comparable. After adjusting for confounders, non-Malaysian nationality (AOR: 3.765, 95% CI: 1.163, 12.190), obesity (AOR: 5.272, 95% CI: 1.131, 24.567), not seeking treatment while unwell (AOR: 5.385, 95% CI: 3.157, 9.186), and a higher percentage of COVID-19-dedicated beds occupied on the date of death (AOR: 1.165, 95% CI: 1.078, 1.259) were associated with increased odds of COVID-19 BID. On the other hand, being married (AOR: 0.396, 95% CI: 0.158, 0.997) and the interaction between the percentage of COVID-19-dedicated beds occupied and the percentage of ventilators in use (AOR: 0.996, 95% CI: 0.994, 0.999) emerged as protective factors.

    CONCLUSION: These findings indicated that certain groups have higher odds of COVID-19 BID and thus, require closer monitoring. Considering that COVID-19 BID is influenced by various elements beyond clinical factors, intensifying public health initiatives and multi-organisational collaboration is necessary to address this issue.

    Matched MeSH terms: Databases, Factual
  5. Shakhshir MH, Vanoh D, Hassan M, Zyoud SH
    J Health Popul Nutr, 2023 Sep 23;42(1):101.
    PMID: 37742012 DOI: 10.1186/s41043-023-00445-8
    BACKGROUND: Chronic kidney disease (CKD) is seen as a diverse disease and a primary contributor to global mortality. Malnutrition arises within chronic illness, which involves protein energy depletion and inadequate levels of essential nutrients. These factors increase the likelihood of death and the overall impact of the disease on affected individuals. Consequently, this study aims to utilize bibliometric and visual analysis to assess the current state of research, the latest advances and emerging patterns in the fields of CKD and malnutrition.

    METHODS: Extensive research was conducted using the Scopus database, which is the most authoritative database of research publications and citations, to focus on CKD research between 2003 and 2022, as indicated by title and author keywords. Then, within this vast collection of academic publications, a notable subset of articles was exclusively dedicated to investigating the relationship between CKD and malnutrition. Finally, we performed bibliometric analysis and visualization using VOSviewer 1.6.19 and Microsoft Excel 2013.

    RESULTS: Large global research between 2003 and 2022 resulted in 50,588 documents focused on CKD, as indicated by title and author keywords. In this extensive collection of scientific publications, a staggering portion of 823 articles is devoted exclusively to investigating the link between CKD and malnutrition. Further analysis reveals that this body of work consists of 565 articles (68.65%), 221 reviews (26.85%), and 37 miscellaneous entries (4.50%), which encompass letters and editorials. The USA was found to be the most productive country (n = 173; 21.02%), followed by Italy (n = 83; 10.09%), Sweden (n = 56; 6.80%), Brazil (n = 54; 6.56%) and China (n = 51; 6.20%). The most common terms on the map include those related to the topic of (a) malnutrition in hemodialysis patients and predicting factors; terms associated with the (b) impact of malnutrition on cardiovascular risk and complications in CKD patients; and terms related to the (c) dietary protein intake and malnutrition in CKD.

    CONCLUSIONS: This study is the first of its kind to analyze CKD and malnutrition research using data from Scopus for visualization and network mapping. Recent trends indicate an increasing focus on protein-energy wasting/malnutrition in hemodialysis patients and predicting factors, dietary protein intake, and malnutrition in CKD. These topics have gained significant attention and reflect the latest scientific advances. Intervention studies are crucial to examining diet therapy's impact on patients with stages 1 to 5 CKD. We hope this study will offer researchers, dietitians and nephrologists valuable information.

    Matched MeSH terms: Databases, Factual
  6. Shah SAA, Tang TB, Faye I, Laude A
    Graefes Arch Clin Exp Ophthalmol, 2017 Aug;255(8):1525-1533.
    PMID: 28474130 DOI: 10.1007/s00417-017-3677-y
    PURPOSE: To propose a new algorithm of blood vessel segmentation based on regional and Hessian features for image analysis in retinal abnormality diagnosis.

    METHODS: Firstly, color fundus images from the publicly available database DRIVE were converted from RGB to grayscale. To enhance the contrast of the dark objects (blood vessels) against the background, the dot product of the grayscale image with itself was generated. To rectify the variation in contrast, we used a 5 × 5 window filter on each pixel. Based on 5 regional features, 1 intensity feature and 2 Hessian features per scale using 9 scales, we extracted a total of 24 features. A linear minimum squared error (LMSE) classifier was trained to classify each pixel into a vessel or non-vessel pixel.

    RESULTS: The DRIVE dataset provided 20 training and 20 test color fundus images. The proposed algorithm achieves a sensitivity of 72.05% with 94.79% accuracy.

    CONCLUSIONS: Our proposed algorithm achieved higher accuracy (0.9206) at the peripapillary region, where the ocular manifestations in the microvasculature due to glaucoma, central retinal vein occlusion, etc. are most obvious. This supports the proposed algorithm as a strong candidate for automated vessel segmentation.

    Matched MeSH terms: Databases, Factual
  7. Shah B, Kirpalani A, Sunder S, Gupta A, Khanna U, Chafekar D, et al.
    BMC Nephrol, 2015;16:215.
    PMID: 26696239 DOI: 10.1186/s12882-015-0191-5
    The objective of this article is to describe the organisation of an international, clinical registry, the Chronic Kidney Disease Observational Database (CKDOD), the processes of enrolling patients and entering data and preliminary results to date.
    Matched MeSH terms: Databases, Factual
  8. Shabanzadeh P, Yusof R
    Comput Math Methods Med, 2015;2015:802754.
    PMID: 26336509 DOI: 10.1155/2015/802754
    Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO) algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.
    Matched MeSH terms: Databases, Factual/statistics & numerical data
  9. Seal A, Reddy PPN, Chaithanya P, Meghana A, Jahnavi K, Krejcar O, et al.
    Comput Math Methods Med, 2020;2020:8303465.
    PMID: 32831902 DOI: 10.1155/2020/8303465
    Human emotion recognition has been a major field of research in the last decades owing to its noteworthy academic and industrial applications. However, most of the state-of-the-art methods identified emotions after analyzing facial images. Emotion recognition using electroencephalogram (EEG) signals has got less attention. However, the advantage of using EEG signals is that it can capture real emotion. However, very few EEG signals databases are publicly available for affective computing. In this work, we present a database consisting of EEG signals of 44 volunteers. Twenty-three out of forty-four are females. A 32 channels CLARITY EEG traveler sensor is used to record four emotional states namely, happy, fear, sad, and neutral of subjects by showing 12 videos. So, 3 video files are devoted to each emotion. Participants are mapped with the emotion that they had felt after watching each video. The recorded EEG signals are considered further to classify four types of emotions based on discrete wavelet transform and extreme learning machine (ELM) for reporting the initial benchmark classification performance. The ELM algorithm is used for channel selection followed by subband selection. The proposed method performs the best when features are captured from the gamma subband of the FP1-F7 channel with 94.72% accuracy. The presented database would be available to the researchers for affective recognition applications.
    Matched MeSH terms: Databases, Factual
  10. Schönbach C, Tan TW, Kelso J, Rost B, Nathan S, Ranganathan S
    BMC Genomics, 2011 Nov 30;12 Suppl 3:S1.
    PMID: 22369160 DOI: 10.1186/1471-2164-12-S3-S1
    In 2009 the International Society for Computational Biology (ISCB) started to roll out regional bioinformatics conferences in Africa, Latin America and Asia. The open and competitive bid for the first meeting in Asia (ISCB-Asia) was awarded to Asia-Pacific Bioinformatics Network (APBioNet) which has been running the International Conference on Bioinformatics (InCoB) in the Asia-Pacific region since 2002. InCoB/ISCB-Asia 2011 is held from November 30 to December 2, 2011 in Kuala Lumpur, Malaysia. Of 104 manuscripts submitted to BMC Genomics and BMC Bioinformatics conference supplements, 49 (47.1%) were accepted. The strong showing of Asia among submissions (82.7%) and acceptances (81.6%) signals the success of this tenth InCoB anniversary meeting, and bodes well for the future of ISCB-Asia.
    Matched MeSH terms: Databases, Factual
  11. Sarojini S, Faridah A, Lim CM, Sameerah SA, Lim TO, Lai LS, et al.
    Med J Malaysia, 2008 Aug;63(3):203-6.
    PMID: 19248690 MyJurnal
    The National Medicines Use Survey (NMUS) which started in 2004 and is still ongoing was conducted with the intent to continuously and systematically collect data on the use of medicines, to provide an overview on the use of medicines in Malaysia. The objective of the NMUS is therefore to quantify the present state and time trends of medicines utilization at various levels of our health care system whether national, regional, local or institutional. From the data available, for the Year 2005, the most commonly used medicine in Malaysia were anti-diabetic medications, of which glibenclamide is the most common followed by metformin, were the top 2 of the list of drugs utilized in DDD/1000 population/day. Collectively, however, taking into account the various antihypertensives by therapeutic groups, anti-hypertensive medicines were more commonly used than anti-diabetics. Hypertension and diabetes mellitus are the two most prevalent chronic disorders in the country and thus, such high medicines utilization rates for these conditions are to be expected. From the general practice prescription data, it was estimated that a patient with hypertension was prescribed a median of only one (1) anti-hypertensive medication. This means, the vast majority of patients (81%) were on monotherapy, which is hardly sufficient to achieve treatment target. Clearly then, given the prevalence of hypertension, many patients were not on drug treatment at all, and of those treated, their drug treatment are likely to be inadequate.
    Matched MeSH terms: Databases, Factual
  12. Saraswathy J, Hariharan M, Nadarajaw T, Khairunizam W, Yaacob S
    Australas Phys Eng Sci Med, 2014 Jun;37(2):439-56.
    PMID: 24691930 DOI: 10.1007/s13246-014-0264-y
    Wavelet theory is emerging as one of the prevalent tool in signal and image processing applications. However, the most suitable mother wavelet for these applications is still a relative question mark amongst researchers. Selection of best mother wavelet through parameterization leads to better findings for the analysis in comparison to random selection. The objective of this article is to compare the performance of the existing members of mother wavelets and to select the most suitable mother wavelet for accurate infant cry classification. Optimal wavelet is found using three different criteria namely the degree of similarity of mother wavelets, regularity of mother wavelets and accuracy of correct recognition during classification processes. Recorded normal and pathological infant cry signals are decomposed into five levels using wavelet packet transform. Energy and entropy features are extracted at different sub bands of cry signals and their effectiveness are tested with four supervised neural network architectures. Findings of this study expound that, the Finite impulse response based approximation of Meyer is the best wavelet candidate for accurate infant cry classification analysis.
    Matched MeSH terms: Databases, Factual
  13. Saokaew S, Sugimoto T, Kamae I, Pratoomsoot C, Chaiyakunapruk N
    PLoS One, 2015;10(11):e0141993.
    PMID: 26560127 DOI: 10.1371/journal.pone.0141993
    Health technology assessment (HTA) has been continuously used for value-based healthcare decisions over the last decade. Healthcare databases represent an important source of information for HTA, which has seen a surge in use in Western countries. Although HTA agencies have been established in Asia-Pacific region, application and understanding of healthcare databases for HTA is rather limited. Thus, we reviewed existing databases to assess their potential for HTA in Thailand where HTA has been used officially and Japan where HTA is going to be officially introduced.
    Matched MeSH terms: Databases, Factual/statistics & numerical data*
  14. Samsiah A, Othman N, Jamshed S, Hassali MA, Wan-Mohaina WM
    Eur J Clin Pharmacol, 2016 Dec;72(12):1515-1524.
    PMID: 27637912
    PURPOSE: Reporting and analysing the data on medication errors (MEs) is important and contributes to a better understanding of the error-prone environment. This study aims to examine the characteristics of errors submitted to the National Medication Error Reporting System (MERS) in Malaysia.

    METHODS: A retrospective review of reports received from 1 January 2009 to 31 December 2012 was undertaken. Descriptive statistics method was applied.

    RESULTS: A total of 17,357 MEs reported were reviewed. The majority of errors were from public-funded hospitals. Near misses were classified in 86.3 % of the errors. The majority of errors (98.1 %) had no harmful effects on the patients. Prescribing contributed to more than three-quarters of the overall errors (76.1 %). Pharmacists detected and reported the majority of errors (92.1 %). Cases of erroneous dosage or strength of medicine (30.75 %) were the leading type of error, whilst cardiovascular (25.4 %) was the most common category of drug found.

    CONCLUSIONS: MERS provides rich information on the characteristics of reported MEs. Low contribution to reporting from healthcare facilities other than government hospitals and non-pharmacists requires further investigation. Thus, a feasible approach to promote MERS among healthcare providers in both public and private sectors needs to be formulated and strengthened. Preventive measures to minimise MEs should be directed to improve prescribing competency among the fallible prescribers identified.

    Matched MeSH terms: Databases, Factual
  15. Salmasi S, Wimmer BC, Khan TM, Zaidi STR, Ming LC
    Res Social Adm Pharm, 2018 Feb;14(2):207-209.
    PMID: 28330781 DOI: 10.1016/j.sapharm.2017.02.015
    Matched MeSH terms: Databases, Factual
  16. Saleh MD, Eswaran C, Mueen A
    J Digit Imaging, 2011 Aug;24(4):564-72.
    PMID: 20524139 DOI: 10.1007/s10278-010-9302-9
    This paper focuses on the detection of retinal blood vessels which play a vital role in reducing the proliferative diabetic retinopathy and for preventing the loss of visual capability. The proposed algorithm which takes advantage of the powerful preprocessing techniques such as the contrast enhancement and thresholding offers an automated segmentation procedure for retinal blood vessels. To evaluate the performance of the new algorithm, experiments are conducted on 40 images collected from DRIVE database. The results show that the proposed algorithm performs better than the other known algorithms in terms of accuracy. Furthermore, the proposed algorithm being simple and easy to implement, is best suited for fast processing applications.
    Matched MeSH terms: Databases, Factual
  17. Salari N, Ghasemi H, Mohammadi L, Behzadi MH, Rabieenia E, Shohaimi S, et al.
    J Orthop Surg Res, 2021 Oct 17;16(1):609.
    PMID: 34657598 DOI: 10.1186/s13018-021-02772-0
    BACKGROUND: Osteoporosis affects all sections of society, including families with people affected by osteoporosis, government agencies and medical institutes in various fields. For example, it involves the patient and his/her family members, and government agencies in terms of the cost of treatment and medical care. Providing a comprehensive picture of the prevalence of osteoporosis globally is important for health policymakers to make appropriate decisions. Therefore, this study was conducted to investigate the prevalence of osteoporosis worldwide.

    METHODS: A systematic review and meta-analysis were conducted in accordance with the PRISMA criteria. The PubMed, Science Direct, Web of Science, Scopus, Magiran, and Google Scholar databases were searched with no lower time limit up till 26 August 2020. The heterogeneity of the studies was measured using the I2 test, and the publication bias was assessed by the Begg and Mazumdar's test at the significance level of 0.1.

    RESULTS: After following the systematic review processes, 86 studies were selected for meta-analysis. The sample size of the study was 103,334,579 people in the age range of 15-105 years. Using meta-analysis, the prevalence of osteoporosis in the world was reported to be 18.3 (95% CI 16.2-20.7). Based on 70 studies and sample size of 800,457 women, and heterogenicity I2: 99.8, the prevalence of osteoporosis in women of the world was reported to be 23.1 (95% CI 19.8-26.9), while the prevalence of osteoporosis among men of the world was found to be 11.7 (95% CI 9.6-14.1 which was based on 40 studies and sample size of 453,964 men.). The highest prevalence of osteoporosis was reported in Africa with 39.5% (95% CI 22.3-59.7) and a sample size of 2989 people with the age range 18-95 years.

    CONCLUSION: According to the medical, economic, and social burden of osteoporosis, providing a robust and comprehensive estimate of the prevalence of osteoporosis in the world can facilitate decisions in health system planning and policymaking, including an overview of the current and outlook for the future; provide the necessary facilities for the treatment of people with osteoporosis; reduce the severe risks that lead to death by preventing fractures; and, finally, monitor the overall state of osteoporosis in the world. This study is the first to report a structured review and meta-analysis of the prevalence of osteoporosis worldwide.

    Matched MeSH terms: Databases, Factual
  18. Saikia A, Patil SS, Ms M, Cv D, Sabarish R, Pandian S, et al.
    Dent Traumatol, 2023 Aug;39(4):371-380.
    PMID: 36920339 DOI: 10.1111/edt.12838
    BACKGROUND/AIMS: Traumatic dental injuries (TDI) are considered a public health problem due to their high prevalence and associated physical, economic, psychological and social consequences. Hence, good Clinical Practice Guidelines are essential to achieving a favourable prognosis. The aim of this review was to appraise the existing Clinical Practice Guidelines (CPGs) on TDI using AGREE II and AGREE-REX.

    MATERIALS AND METHODS: A systematic search for existing guidelines on TDI was performed on PubMed, EMBASE, CINAHL, Cochrane Library, ProQuest, National Institute for Health Care Excellence, BMJ Best Practice, Trip database, Guideline International Network, Scottish Intercollegiate Guidelines Network, World Health Organisation, Web of Science and 'Ministry of Health worldwide' databases. Four appraisers independently appraised the included CPGs. The AGREE II tool was applied to assess the methodological quality, while AGREE REX assessed the quality of recommendations of the included guidelines.

    RESULTS: Of the 7736 titles screened, three guidelines, namely the International Association of Dental Traumatology Guidelines (IADT), and the Italian and Malaysian guidelines, were included for the final analysis. These guidelines were published between 2019 and 2020. The AGREE II analysis demonstrated scores above 80% for the IADT and Italian guidelines for the scope and purpose domain. Overall, the Malaysian guidelines achieved the highest score for all domains. The AGREE REX analysis indicated variability in implementation across the nine items, with five that scored above the midpoint of 4.0 on the response scale. Both the Italian and the IADT guidelines had a similar score for the values and preference domains (36.36%).

    CONCLUSIONS: Several deficiencies exist in the methodological quality of existing CPGs on TDI. Future guidelines should consider improvements for domains such as 'rigour of development', 'stakeholder involvement' and 'applicability' to overcome the existing limitations.

    Matched MeSH terms: Databases, Factual
  19. Said MM, Gibbons S, Moffat AC, Zloh M
    Int J Pharm, 2011 Aug 30;415(1-2):102-9.
    PMID: 21645600 DOI: 10.1016/j.ijpharm.2011.05.057
    The influx of medicines from different sources into healthcare systems of developing countries presents a challenge to monitor their origin and quality. The absence of a repository of reference samples or spectra prevents the analysis of tablets by direct comparison. A set of paracetamol tablets purchased in Malaysian pharmacies were compared to a similar set of sample purchased in the UK using near-infrared spectroscopy (NIRS). Additional samples of products containing ibuprofen or paracetamol in combination with other actives were added to the study as negative controls. NIR spectra of the samples were acquired and compared by using multivariate modeling and classification algorithms (PCA/SIMCA) and stored in a spectral database. All analysed paracetamol samples contained the purported active ingredient with only 1 out of 20 batches excluded from the 95% confidence interval, while the negative controls were clearly classified as outliers of the set. Although the substandard products were not detected in the purchased sample set, our results indicated variability in the quality of the Malaysian tablets. A database of spectra was created and search methods were evaluated for correct identification of tablets. The approach presented here can be further developed as a method for identifying substandard pharmaceutical products.
    Matched MeSH terms: Databases, Factual*
  20. Sabatino A, Regolisti G, Karupaiah T, Sahathevan S, Sadu Singh BK, Khor BH, et al.
    Clin Nutr, 2017 06;36(3):663-671.
    PMID: 27371993 DOI: 10.1016/j.clnu.2016.06.007
    BACKGROUND & AIMS: Protein-Energy Wasting (PEW) is the depletion of protein/energy stores observed in the most advanced stages of Chronic Kidney Disease (CKD). PEW is highly prevalent among patients on chronic dialysis, and is associated with adverse clinical outcomes, high morbidity/mortality rates and increased healthcare costs. This narrative review was aimed at exploring the pathophysiology of PEW in end-stage renal disease (ESRD) on hemodialysis. The main aspects of nutritional status evaluation, intervention and monitoring in this clinical setting were described, as well as the current approaches for the prevention and treatment of ESRD-related PEW.

    METHODS: An exhaustive literature search was performed, in order to identify the relevant studies describing the epidemiology, pathogenesis, nutritional intervention and outcome of PEW in ESRD on hemodialysis.

    RESULTS AND CONCLUSION: The pathogenesis of PEW is multifactorial. Loss of appetite, reduced intake of nutrients and altered lean body mass anabolism/catabolism play a key role. Nutritional approach to PEW should be based on a careful and periodic assessment of nutritional status and on timely dietary counseling. When protein and energy intakes are reduced, nutritional supplementation by means of specific oral formulations administered during the hemodialysis session may be the first-step intervention, and represents a valid nutritional approach to PEW prevention and treatment since it is easy, effective and safe. Omega-3 fatty acids and fibers, now included in commercially available preparations for renal patients, could lend relevant added value to macronutrient supplementation. When oral supplementation fails, intradialytic parenteral nutrition can be implemented in selected patients.

    Matched MeSH terms: Databases, Factual
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