MyMedR

Displaying publications 1 - 20 of 226 in total

Abstract:

Sort:

A Comprehensive Review on the Role of Polymers in Ocular Drug Delivery

Paramjot, Wadhwa S, Sharma A, Singh SK, Vishwas S, Kumar R, et al.

Curr Drug Deliv, 2024;21(1):16-37.
PMID: 36627785 DOI: 10.2174/1567201820666230110140312

Amongst different routes of drug delivery systems, ophthalmic drug delivery still requires a careful investigation and strict parameter measurements because the eyes are one of the most sensitive parts of the body and require special attention. The conventional systems for eyes lead to rapid elimination of formulation and hence very small contact time on the ocular epithelium. The current review article covers various types of polymers used in ocular drug delivery along with their applications/ limitations. Polymers are widely used by researchers in prodrug techniques and as a penetration enhancer in ocular delivery. This article covers the role and use of different polymeric systems which makes the final formulation a promising candidate for ophthalmic drug delivery. The researchers are still facing multiple challenges in order to maintain the therapeutic concentration of the drug in the eyes because of its complex structure. There are several barriers that further restrict the intraocular entry of the drug. In order to remove/reduce such challenges, these days various types of polymers are used for ocular delivery in order to develop different drug carrier systems for better efficacy and stability. The polymers used are highly helpful in increasing residence time by increasing the viscosity at the ocular epithelium layer. Such preparations also get easily permeated in ocular cells. The combination of different polymeric properties makes the final formulation stable with prolonged retention, high viscosity, high permeability, and better bioavailability, making the final formulation a promising candidate for ocular drug delivery.
A Review of Phytochemical and Pharmacological Properties of Alpinia malaccensis (Burm. F.) Roscoe. (Zingiberaceae)

Mahawer S, Kumar R, Prakash O, Singh S, Singh Rawat D, Dubey SK, et al.

Curr Top Med Chem, 2023;23(20):1964-1972.
PMID: 37218200 DOI: 10.2174/1568026623666230522104104

Alpinia malaccensis, commonly known as "Malacca ginger" and "Rankihiriya," is an important medicinal plant of Zingiberaceae. It is native to Indonesia and Malaysia and widely distributed in countries including Northeast India, China, Peninsular Malaysia and Java. Due to vide pharmacological values, it is necessary to recognize this species for its significance of pharmacological importance. This article provides the botanical characteristics, chemical compounds of vegetation, ethnopharmacological values, therapeutic properties, along with the potential pesticidal properties of this important medicinal plant. The information in this article was gathered by searching the online journals in the databases such as PubMed, Scopus, Web of Science etc. The terms such as Alpinia malaccensis, Malacca ginger, Rankihiriya, pharmacology, chemical composition, ethnopharmacology, etc., were used in different combinations. A detailed study of the available resources for A. malaccensis confirmed its native and distribution, traditional values, chemical properties, and medicinal values. Its essential oils and extracts are the reservoir of a wide range of important chemical constituents. Traditionally, it is being used to treat nausea, vomiting and wounds along with as a seasoning agent in meat processing and as perfume. Apart from traditional values, it has been reported for several pharmacological activities such as antioxidant, antimicrobial, anti-inflammatory etc. We believe that this review will help to provide the collective information of A. malaccensis to further explore it in the prevention and treatment of various diseases and help to the systematic study of this plant to utilize its potential in various areas of human welfare.
Fulltext A Sustainable Approach to the Stereoselective Synthesis of Diazaheptacyclic Cage Systems Based on a Multicomponent Strategy in an Ionic Liquid

Suresh Kumar R, Almansour AI, Arumugam N, Altaf M, Menéndez JC, Kumar RR, et al.

Molecules, 2016 Jan 29;21(2):165.
PMID: 26840282 DOI: 10.3390/molecules21020165

The microwave-assisted three-component reactions of 3,5-bis(E)-arylmethylidene]tetrahydro-4(1H)-pyridinones, acenaphthenequinone and cyclic α-amino acids in an ionic liquid, 1-butyl-3-methylimidazolium bromide, occurred through a domino sequence affording structurally intriguing diazaheptacyclic cage-like compounds in excellent yields.
A decolonised Commission agenda: the missing ingredients

Kumar R, Arya N

Lancet, 2023 Nov 11;402(10414):1747-1748.
PMID: 37865109 DOI: 10.1016/S0140-6736(23)02054-8
A deep neural network-based approach for prediction of mutagenicity of compounds

Kumar R, Khan FU, Sharma A, Siddiqui MH, Aziz IB, Kamal MA, et al.

Environ Sci Pollut Res Int, 2021 Sep;28(34):47641-47650.
PMID: 33895950 DOI: 10.1007/s11356-021-14028-9

We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound's safety. Exposure and handling of mutagenic chemicals in the environment pose a high health risk; therefore, identification and screening of these chemicals are essential. Considering the time constraints and the pressure to avoid laboratory animals' use, the shift to alternative methodologies that can establish a rapid and cost-effective detection without undue over-conservation seems critical. In this regard, computational detection and identification of the mutagens in environmental samples like drugs, pesticides, dyes, reagents, wastewater, cosmetics, and other substances is vital. From the last two decades, there have been numerous efforts to develop the prediction models for mutagenicity, and by far, machine learning methods have demonstrated some noteworthy performance and reliability. However, the accuracy of such prediction models has always been one of the major concerns for the researchers working in this area. The mutagenicity prediction models were developed using deep neural network (DNN), support vector machine, k-nearest neighbor, and random forest. The developed classifiers were based on 3039 compounds and validated on 1014 compounds; each of them encoded with 1597 molecular feature vectors. DNN-based prediction model yielded highest prediction accuracy of 92.95% and 83.81% with the training and test data, respectively. The area under the receiver's operating curve and precision-recall curve values were found to be 0.894 and 0.838, respectively. The DNN-based classifier not only fits the data with better performance as compared to traditional machine learning algorithms, viz., support vector machine, k-nearest neighbor, and random forest (with and without feature reduction) but also yields better performance metrics. In current work, we propose a DNN-based model to predict mutagenicity of compounds.
Fulltext A novel method for blood volume estimation using trivalent chromium in rabbit models

Baby PM, Kumar P, Kumar R, Jacob SS, Rawat D, Binu VS, et al.

Indian J Plast Surg, 2014 May;47(2):242-8.
PMID: 25190922 DOI: 10.4103/0970-0358.138961

BACKGROUND: Blood volume measurement though important in management of critically ill-patients is not routinely estimated in clinical practice owing to labour intensive, intricate and time consuming nature of existing methods.
AIMS: The aim was to compare blood volume estimations using trivalent chromium [(51)Cr(III)] and standard Evans blue dye (EBD) method in New Zealand white rabbit models and establish correction-factor (CF).
MATERIALS AND METHODS: Blood volume estimation in 33 rabbits was carried out using EBD method and concentration determined using spectrophotometric assay followed by blood volume estimation using direct injection of (51)Cr(III). Twenty out of 33 rabbits were used to find CF by dividing blood volume estimation using EBD with blood volume estimation using (51)Cr(III). CF is validated in 13 rabbits by multiplying it with blood volume estimation values obtained using (51)Cr(III).
RESULTS: The mean circulating blood volume of 33 rabbits using EBD was 142.02 ± 22.77 ml or 65.76 ± 9.31 ml/kg and using (51)Cr(III) was estimated to be 195.66 ± 47.30 ml or 89.81 ± 17.88 ml/kg. The CF was found to be 0.77. The mean blood volume of 13 rabbits measured using EBD was 139.54 ± 27.19 ml or 66.33 ± 8.26 ml/kg and using (51)Cr(III) with CF was 152.73 ± 46.25 ml or 71.87 ± 13.81 ml/kg (P = 0.11).
CONCLUSIONS: The estimation of blood volume using (51)Cr(III) was comparable to standard EBD method using CF. With further research in this direction, we envisage human blood volume estimation using (51)Cr(III) to find its application in acute clinical settings.
Fulltext A search for new phenomena in pp collisions at [Formula: see text] in final states with missing transverse momentum and at least one jet using the [Formula: see text] variable

Khachatryan V, Sirunyan AM, Tumasyan A, Adam W, Asilar E, Bergauer T, et al.

Eur Phys J C Part Fields, 2017;77(5):294.
PMID: 28579921 DOI: 10.1140/epjc/s10052-017-4787-8

A search for new phenomena is performed in final states containing one or more jets and an imbalance in transverse momentum in pp collisions at a centre-of-mass energy of 13[Formula: see text]. The analysed data sample, recorded with the CMS detector at the CERN LHC, corresponds to an integrated luminosity of 2.3[Formula: see text]. Several kinematic variables are employed to suppress the dominant background, multijet production, as well as to discriminate between other standard model and new physics processes. The search provides sensitivity to a broad range of new-physics models that yield a stable weakly interacting massive particle. The number of observed candidate events is found to agree with the expected contributions from standard model processes, and the result is interpreted in the mass parameter space of fourteen simplified supersymmetric models that assume the pair production of gluinos or squarks and a range of decay modes. For models that assume gluino pair production, masses up to 1575 and 975[Formula: see text] are excluded for gluinos and neutralinos, respectively. For models involving the pair production of top squarks and compressed mass spectra, top squark masses up to 400[Formula: see text] are excluded.
Fulltext AI-based diagnosis of COVID-19 patients using X-ray scans with stochastic ensemble of CNNs

Arora R, Bansal V, Buckchash H, Kumar R, Sahayasheela VJ, Narayanan N, et al.

Phys Eng Sci Med, 2021 Dec;44(4):1257-1271.
PMID: 34609703 DOI: 10.1007/s13246-021-01060-9

According to the World Health Organization (WHO), novel coronavirus (COVID-19) is an infectious disease and has a significant social and economic impact. The main challenge in fighting against this disease is its scale. Due to the outbreak, medical facilities are under pressure due to case numbers. A quick diagnosis system is required to address these challenges. To this end, a stochastic deep learning model is proposed. The main idea is to constrain the deep-representations over a Gaussian prior to reinforce the discriminability in feature space. The model can work on chest X-ray or CT-scan images. It provides a fast diagnosis of COVID-19 and can scale seamlessly. The work presents a comprehensive evaluation of previously proposed approaches for X-ray based disease diagnosis. The approach works by learning a latent space over X-ray image distribution from the ensemble of state-of-the-art convolutional-nets, and then linearly regressing the predictions from an ensemble of classifiers which take the latent vector as input. We experimented with publicly available datasets having three classes: COVID-19, normal and pneumonia yielding an overall accuracy and AUC of 0.91 and 0.97, respectively. Moreover, for robust evaluation, experiments were performed on a large chest X-ray dataset to classify among Atelectasis, Effusion, Infiltration, Nodule, and Pneumonia classes. The results demonstrate that the proposed model has better understanding of the X-ray images which make the network more generic to be later used with other domains of medical image analysis.
Fulltext An Image Processing Approach for Detection of Prenatal Heart Disease

Selvan S, Thangaraj SJJ, Samson Isaac J, Benil T, Muthulakshmi K, Almoallim HS, et al.

Biomed Res Int, 2022;2022:2003184.
PMID: 35958813 DOI: 10.1155/2022/2003184

Prenatal heart disease, generally known as cardiac problems (CHDs), is a group of ailments that damage the heartbeat and has recently now become top deaths worldwide. It connects a plethora of cardiovascular diseases risks to the urgent in need of accurate, trustworthy, and effective approaches for early recognition. Data preprocessing is a common method for evaluating big quantities of information in the medical business. To help clinicians forecast heart problems, investigators utilize a range of data mining algorithms to examine enormous volumes of intricate medical information. The system is predicated on classification models such as NB, KNN, DT, and RF algorithms, so it includes a variety of cardiac disease-related variables. It takes do with an entire dataset from the medical research database of patients with heart disease. The set has 300 instances and 75 attributes. Considering their relevance in establishing the usefulness of alternate approaches, only 15 of the 75 criteria are examined. The purpose of this research is to predict whether or not a person will develop cardiovascular disease. According to the statistics, naïve Bayes classifier has the highest overall accuracy.
Fulltext Anti Diabetic and Hypolipidemic Activity of Bark of Ethanolic Extract of Ougeinia Oojeinensis (ROXB.)

Velmurugan C, Sundaram T, Sampath Kumar R, Vivek B, Sheshadrishekar D, Ashok Kumar BS

Med J Malaysia, 2011 Mar;66(1):22-6.
PMID: 23765138

The hypoglycemic and hypolipidemic effect of Ethanolic extract of Ougeinia oojeinensis (200mg/kg) bark was evaluated with measurements including, Body weight, blood glucose level, urine glucose and biochemical parameters. The ethanolic extracts of the powdered bark was tested for its efficacy in alloxan-induced diabetic rats. Animals were induced for diabetes with Alloxan (150 mg/kg of body weight- i.p.) and treated orally with Ethanolic extract of Ougeinia oojeinensis. The extracts were also evaluated for acute oral toxicity studies and its effect on different biochemical parameters. The extracts showed significant (p<0.01) antihyperglycemic and hypolipidemic activity as compared to diabetic control. The extract shows beneficial effects on blood glucose and urine glucose level. It also reduces the elevated biochemical parameters such as triglycerides (TGL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), Total Cholesterol (TC) and increased the reduced level of high density lipoprotein (HDL) and body weight, which might be due to presence of steroids, tannins, alkaloids and triterpenoids present in that extract. Thus ethanolic extract could serve as good oral hypoglycemic agents and seems to be promising for the development of phytomedicines for diabetes mellitus.
Anti-ulcerogenic effect of methanolic extract of Elaeagnus conferta Roxb. seeds in Wistar rats

Gupta M, Gulati M, Kapoor B, Kumar B, Kumar R, Kumar R, et al.

J Ethnopharmacol, 2021 Jul 15;275:114115.
PMID: 33852947 DOI: 10.1016/j.jep.2021.114115

ETHNOPHARMACOLOGICAL RELEVANCE: Elaeagnus conferta Roxb. (Elaeagnaceae) is a subtropical shrub mainly native to India, Vietnam, Malaysia and South China, whose various parts are used for treatment of diabetes, gastric ulcers, pain, oxidative stress and pulmonary disorders. Though the other parts of the plant have been reported for their ethnic use i.e. fruits as astringent locally and for cancer systemically, leaves for body pain and flowers for pain in chest and the seeds are mentioned as edible, there is no report per se on the medicinal use of seeds. Based on the fact that seeds of closely resembling species i.e. Elaeagnus rhamnoides has demonstrated significant anti-gastroulcerative property, the probability of the seeds of E. conferta possessing similar activity seemed quite significant.
AIM OF THE STUDY: Phytochemical investigation and assessment of pharmacological mechanism(s) involved in anti-ulcer effect of methanolic extract of the seeds of E. conferta.
MATERIALS AND METHODS: Bioactive phytoconstituents were isolated by column chromatography. These were identified by spectroscopic techniques including infrared (IR) spectroscopy, nuclear magnetic resonance (NMR) and mass spectrometry. Methanolic extract (MEC) of the seeds was prepared by cold maceration and its anti-ulcerogenic potential was evaluated using indomethacin (50 mg/kg) and water immersion stress models in male rats. The animals were pre-treated with different doses of MEC (400 and 800 mg/kg) and the therapeutic effect was compared with standard drug i.e. ranitidine (RANT; 50 mg/kg). The ameliorative effects of MEC were investigated on gastric juice pH, total acidity, free acidity and ulcer index. The assays of malionaldehyde (MDA), catalase (CAT), superoxide dismutase (SOD), glutathione (GSH) and pro-inflammatory cytokines i.e. interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) were carried out to find out the possible mechanism(s) of protection. Further, histopathological changes were also studied.
RESULTS: Chromatography studies and further confirmation by spectroscopic techniques revealed the presence of four different compounds in MEC i.e oleic acid (1), stearic acid (2), ascorbic acid (3) and quercetin (4). MEC exhibited anti-ulcerogenic effect in dose dependent manner which may be attributed to suppression of pro-inflammatory cytokines (IL-6, TNF-α) and MDA (112.7%), and up-regulation of protective factors such as CAT (90.48%), SOD (92.77%) and GSH (90.01%). Ulcer inhibition, reduction in total and free acidity and increase in gastric juice pH were observed in MEC treated rats as compared to disease control animals. Histopathological findings confirmed decreased cell infiltration, less epithelial cell damage and regeneration of gastric mucosa in dose dependent manner.
CONCLUSIONS: The anti-ulcer effect of MEC may be attributed to its ability to scavenge free radicals and anti-inflammatory property via suppression of TNF-α and IL-6, thus offers a complete and holistic approach for management of peptic ulcer.
Antimycobacterial evaluation of novel hybrid arylidene thiazolidine-2,4-diones

Ponnuchamy S, Kanchithalaivan S, Ranjith Kumar R, Ali MA, Choon TS

Bioorg Med Chem Lett, 2014 Feb 15;24(4):1089-93.
PMID: 24472146 DOI: 10.1016/j.bmcl.2014.01.007

A series of novel hybrid heterocycles comprising arylidene thiazolidine-2,4-dione and 1-cyclopropyl-2-(2-fluorophenyl)ethanone were synthesized. These compounds were evaluated for their antimycobacterial activity against Mycobacterium tuberculosis H37Rv in High Throughput Screen. Most of the hybrid arylidene thiazolidine-2,4-diones displayed moderate to good activity with MIC of less than 50 μM. Compound 1m exhibited maximum potency being 5.87 fold more active at EC50 and 6.26 fold more active at EC90 than the standard drug pyrimethamine.
Fulltext Antituberculosis: synthesis and antimycobacterial activity of novel benzimidazole derivatives

Keng Yoon Y, Ashraf Ali M, Choon TS, Ismail R, Chee Wei A, Suresh Kumar R, et al.

Biomed Res Int, 2013;2013:926309.
PMID: 24381946 DOI: 10.1155/2013/926309

A total of seven novel benzimidazoles were synthesized by a 4-step reaction starting from 4-fluoro-3-nitrobenzoic acid under relatively mild reaction conditions. The synthesized compounds were screened for their antimycobacterial activity against M. tuberculosis H₃₇Rv (MTB-H₃₇Rv) and INH-resistant M. tuberculosis (INHR-MTB) strains using agar dilution method. Three of them displayed good activity with MIC of less than 0.2 μM. Compound ethyl 1-(2-(4-(4-(ethoxycarbonyl)-2-aminophenyl)piperazin-1-yl)ethyl)-2-(4-(5-(4-fluorophenyl)pyridin-3-ylphenyl-1H-benzo[d]imidazole-5-carboxylate (5 g) was found to be the most active with MIC of 0.112 μM against MTB-H₃₇Rv and 6.12 μM against INHR-MTB, respectively.
Are Technology-Based Interventions Effective in Reducing Dental Anxiety in Children and Adults? A Systematic Review

Gujjar KR, van Wijk A, Kumar R, de Jongh A

J Evid Based Dent Pract, 2019 06;19(2):140-155.
PMID: 31326046 DOI: 10.1016/j.jebdp.2019.01.009

OBJECTIVES: The aim of this study was to evaluate the effectiveness of technology-based interventions for the treatment of dental anxiety in children and adults.
DATA SOURCES: A systematic search using relevant keywords was conducted in PubMed-Medline, EMBASE, PsycINFO, CINAHL, Scopus, and The Cochrane Library.
INCLUSION CRITERIA: Randomized controlled trials (RCTs) that compared technology-based interventions with inactive controls in the treatment of moderate to severe dental anxiety were included.
RESULTS: A total of seven RCTs were included in the review. These studies investigated the effectiveness of video modeling, computerized cognitive behavioral therapy, virtual reality exposure therapy, and distraction with music and audiovisual video material. Six studies examining video modeling, computerized cognitive behavioral therapy, virtual reality exposure therapy, and distraction (audiovisual) showed significantly greater reductions in dental anxiety than inactive controls in both children and adults. None of the included studies followed Consolidated Standards of Reporting Trials guidelines completely or reported sufficient data, thereby precluding a possible meta-analysis. Four out of seven included studies were assessed to be at high risk of bias.
CONCLUSIONS: A limited number of studies supported the effectiveness of technology-based interventions in the treatment of dental anxiety in children and adults.
CLINICAL SIGNIFICANCE: The quality of the methods of studies on the effects of technology-based interventions allows only limited inferences on the effects of these interventions. However, within the limitations of the systematic review, the results converge to suggest that technology-based interventions may be useful as an adjunct to standard dental care. High-quality RCTs are needed to determine the (relative) effectiveness of these interventions.
PROSPERO REGISTRATION NUMBER: CRD42017064810.
Assessing global risk factors for non-fatal injuries from road traffic accidents and falls in adults aged 35-70 years in 17 countries: a cross-sectional analysis of the Prospective Urban Rural Epidemiological (PURE) study

Raina P, Sohel N, Oremus M, Shannon H, Mony P, Kumar R, et al.

Inj Prev, 2016 Apr;22(2):92-98.
PMID: 26512093 DOI: 10.1136/injuryprev-2014-041476

To assess risk factors associated with non-fatal injuries (NFIs) from road traffic accidents (RTAs) or falls.
Assessment Of Pharmacist-Led Home-Based Educational Intervention Among Type 2 Diabetes Patients In The State of Penang, Malaysia

Chow EP, Hassali MA, Saleem F, Kumar R

Value Health, 2015 Nov;18(7):A866.
PMID: 26534635 DOI: 10.1016/j.jval.2015.09.519
Fulltext Assessment and valuation of health impacts of fine particulate matter during COVID-19 lockdown: a comprehensive study of tropical and sub tropical countries

Bherwani H, Kumar S, Musugu K, Nair M, Gautam S, Gupta A, et al.

Environ Sci Pollut Res Int, 2021 Aug;28(32):44522-44537.
PMID: 33852112 DOI: 10.1007/s11356-021-13813-w

A novel coronavirus disease (COVID-19) continues to challenge the whole world. The disease has claimed many fatalities as it has transcended from one country to another since it was first discovered in China in late 2019. To prevent further morbidity and mortality associated with COVID-19, most of the countries initiated a countrywide lockdown. While physical distancing and lockdowns helped in curbing the spread of this novel coronavirus, it led to massive economic losses for the nations. Positive impacts have been observed due to lockdown in terms of improved air quality of the nations. In the current research, ten tropical and subtropical countries have been analysed from multiple angles, including air pollution, assessment and valuation of health impacts and economic loss of countries during COVID-19 lockdown. Countries include Brazil, India, Iran, Kenya, Malaysia, Mexico, Pakistan, Peru, Sri Lanka, and Thailand. Validated Simplified Aerosol Retrieval Algorithm (SARA) binning model is used on data collated from moderate resolution imaging spectroradiometer (MODIS) for particulate matters with a diameter of less than 2.5 μm (PM2.5) for all the countries for the month of January to May 2019 and 2020. The concentration results of PM2.5 show that air pollution has drastically reduced in 2020 post lockdown for all countries. The highest average concentration obtained by converting aerosol optical depth (AOD) for 2020 is observed for Thailand as 121.9 μg/m3 and the lowest for Mexico as 36.27 μg/m3. As air pollution is found to decrease in the April and May months of 2020 for nearly all countries, they are compared with respective previous year values for the same duration to calculate the reduced health burden due to lockdown. The present study estimates that cumulative about 100.9 Billion US$ are saved due to reduced air pollution externalities, which are about 25% of the cumulative economic loss of 435.9 Billion US$.
Assessment of Dimensional Stability, Biodegradability, and Fracture Energy of Bio-Composites Reinforced with Novel Pine Cone

Jha K, Tyagi YK, Kumar R, Sharma S, Huzaifah MRM, Li C, et al.

Polymers (Basel), 2021 Sep 24;13(19).
PMID: 34641075 DOI: 10.3390/polym13193260

In this investigation, biodegradable composites were fabricated with polycaprolactone (PCL) matrix reinforced with pine cone powder (15%, 30%, and 45% by weight) and compatibilized with graphite powder (0%, 5%, 10%, and 15% by weight) in polycaprolactone matrix by compression molding technique. The samples were prepared as per ASTM standard and tested for dimensional stability, biodegradability, and fracture energy with scanning electron micrographs. Water-absorption and thickness-swelling were performed to examine the dimensional stability and tests were performed at 23 °C and 50% humidity. Results revealed that the composites with 15 wt % of pine cone powder (PCP) have shown higher dimensional stability as compared to other composites. Bio-composites containing 15-45 wt % of PCP with low graphite content have shown higher disintegration rate than neat PCL. Fracture energy for crack initiation in bio-composites was increased by 68% with 30% PCP. Scanning electron microscopy (SEM) of the composites have shown evenly-distributed PCP particles throughout PCL-matrix at significantly high-degrees or quantities of reinforcing.
Association among calendar packaging and medication adherence: Findings from a focus group discussion among hypertensive patients in Penang, Malaysia. [Abstract]

Tan BY, Shafie AA, Hassali MA, Saleem F, Kumar R

Value Health, 2015 Nov;18(7):A831.
PMID: 26534439 DOI: 10.1016/j.jval.2015.09.317

Objectives: Medication adherence to treatment recommendations has major impact on health outcomes. Numerous interventions to improve medication adherence among the patients have been studied in clinical trials, including calendar packaging and patient reminder letters. Therefore, this study is aimed to explore hypertensive patient’s perceptions towards calendar packaging and its impact on medication adherence.
Methods: A qualitative method was adopted, whereby two focus group sessions were conducted among 16 conveniently sampled hypertensive patients from a community based non-governmental organisation in the state of Penang, Malaysia. A pre validated focus group guide was constructed and used for data collection. Collected data was transcribed verbatim and analysed by thematic content analysis to identify the emerging themes.
Results: Each focus group consisted of 8 hypertensive patients. Thematic content analysis resulted into 3 major themes (knowledge and familiarity with the medicines names and their packaging; perception about the packaging and labelling of medicines; knowledge and views of calendar packaging) and each theme was further divided into 2 sub themes. Majority of the hypertensive patients were not familiar with their medication names, however they were able to identify their medications based on the appearance and packaging. Participants agreed that calendar packaging is a great intervention to increase awareness among patients about regular medicine use and increase medication adherence.
Conclusions: The study concluded that hypertensive patients relied on the packaging and labelling on the medications to identify their medications. Thus, packaging and labelling of the medications play an important role in improving medication adherence and reduce medication errors. This finding can help to enhance the drug manufacturers to pay attention on the drug packaging in order to increase medication adherence among the patients.
Fulltext Association of dairy consumption with metabolic syndrome, hypertension and diabetes in 147 812 individuals from 21 countries

Bhavadharini B, Dehghan M, Mente A, Rangarajan S, Sheridan P, Mohan V, et al.

BMJ Open Diabetes Res Care, 2020 04;8(1).
PMID: 32423962 DOI: 10.1136/bmjdrc-2019-000826

OBJECTIVE: Our aims were to assess the association of dairy intake with prevalence of metabolic syndrome (MetS) (cross-sectionally) and with incident hypertension and incident diabetes (prospectively) in a large multinational cohort study.
METHODS: The Prospective Urban Rural Epidemiology (PURE) study is a prospective epidemiological study of individuals aged 35 and 70 years from 21 countries on five continents, with a median follow-up of 9.1 years. In the cross-sectional analyses, we assessed the association of dairy intake with prevalent MetS and its components among individuals with information on the five MetS components (n=112 922). For the prospective analyses, we examined the association of dairy with incident hypertension (in 57 547 individuals free of hypertension) and diabetes (in 131 481 individuals free of diabetes).
RESULTS: In cross-sectional analysis, higher intake of total dairy (at least two servings/day compared with zero intake; OR 0.76, 95% CI 0.71 to 0.80, p-trend<0.0001) was associated with a lower prevalence of MetS after multivariable adjustment. Higher intakes of whole fat dairy consumed alone (OR 0.72, 95% CI 0.66 to 0.78, p-trend<0.0001), or consumed jointly with low fat dairy (OR 0.89, 95% CI 0.80 to 0.98, p-trend=0.0005), were associated with a lower MetS prevalence. Low fat dairy consumed alone was not associated with MetS (OR 1.03, 95% CI 0.77 to 1.38, p-trend=0.13). In prospective analysis, 13 640 people with incident hypertension and 5351 people with incident diabetes were recorded. Higher intake of total dairy (at least two servings/day vs zero serving/day) was associated with a lower incidence of hypertension (HR 0.89, 95% CI 0.82 to 0.97, p-trend=0.02) and diabetes (HR 0.88, 95% CI 0.76 to 1.02, p-trend=0.01). Directionally similar associations were found for whole fat dairy versus each outcome.
CONCLUSIONS: Higher intake of whole fat (but not low fat) dairy was associated with a lower prevalence of MetS and most of its component factors, and with a lower incidence of hypertension and diabetes. Our findings should be evaluated in large randomized trials of the effects of whole fat dairy on the risks of MetS, hypertension, and diabetes.

Filters

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links