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  • 1
    Online Resource
    Online Resource
    Drug-Related Problems in Prescribing for Pediatric Outpatients in Vietnam
    MDPI AG ; 2021
    In:  Healthcare Vol. 9, No. 3 ( 2021-03-14), p. 327-
    Details
    In: Healthcare, MDPI AG, Vol. 9, No. 3 ( 2021-03-14), p. 327-
    Abstract: Background: Our study was conducted to determine the prevalence of drug-related problems (DRPs) in outpatient prescriptions, the impact of DRPs on treatment efficacy, safety, and cost, and the determinants of DRPs in prescribing for pediatric outpatients in Vietnam. Methods: A retrospective cross-sectional study was conducted on pediatric outpatients at a pediatric hospital in Can Tho, Vietnam. DRPs were classified according to the Pharmaceutical Care Network Europe classification (PCNE) of 2020. The study determined prevalence of DRPs and their impacts on efficacy, safety, and cost. Multivariate regression was used to identify the determinants of DRPs. Results: The study included 4339 patients (mean age 4.3, 55.8% male), with a total of 3994 DRPs, averaging 0.92 DRP/prescription. The proportion of prescriptions with at least one DRP was 65.7%. DRPs included inappropriate drug selection (35.6%), wrong time of dosing relative to meals (35.6%), inappropriate dosage form (9.3%), inappropriate indication (7.1%), and drug-drug interactions (0.3%). The consensus of experts was average when evaluating each aspect of efficiency reduction, safety reduction, and treatment cost increase, with Fleiss’ coefficients of 0.558, 0.511, and 0.541, respectively (p 〈 0.001). Regarding prescriptions, 50.1% were assessed as reducing safety. The figures for increased costs and decreased treatment effectiveness were 29.0% and 23.9%, respectively. Patients who were ≤2 years old were more likely to have DRPs than patients aged 2 to 6 years old (OR = 0.696; 95% CI = 0.599–0.809) and patients aged over 6 years old (OR = 0.801; 95% CI = 0.672–0.955). Patients who had respiratory system disease were more likely to have DRPs than patients suffering from other diseases (OR = 0.715; 95% CI = 0.607–0.843). Patients with comorbidities were less likely to have DRPs than patients with no comorbidities (OR = 1.421; 95% CI = 1.219–1.655). Patients prescribed ≥5 drugs were more likely to have DRPs than patients who took fewer drugs (OR = 3.677; 95% CI = 2.907–4.650). Conclusion: The proportion of prescriptions in at least one DRP was quite high. Further studies should evaluate clinical significance and appropriate interventions, such as providing drug information and consulting doctors about DRPs.
    Type of Medium: Online Resource
    ISSN: 2227-9032
    URL: Article
    DOI: 10.3390/healthcare9030327
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2721009-1
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  • 2
    Online Resource
    Online Resource
    Analysis of Microalgal Density Estimation by Using LASSO and Image Texture Features
    MDPI AG ; 2023
    In:  Sensors Vol. 23, No. 5 ( 2023-02-24), p. 2543-
    Details
    In: Sensors, MDPI AG, Vol. 23, No. 5 ( 2023-02-24), p. 2543-
    Abstract: Monitoring and estimating the density of microalgae in a closed cultivation system is a critical task in culturing algae since it allows growers to optimally control both nutrients and cultivating conditions. Among the estimation techniques proposed so far, image-based methods, which are less invasive, nondestructive, and more biosecure, are practically preferred. Nevertheless, the premise behind most of those approaches is simply averaging the pixel values of images as inputs of a regression model to predict density values, which may not provide rich information of the microalgae presenting in the images. In this work, we propose to exploit more advanced texture features extracted from captured images, including confidence intervals of means of pixel values, powers of spatial frequencies presenting in images, and entropies accounting for pixel distribution. These diverse features can provide more information of microalgae, which can lead to more accurate estimation results. More importantly, we propose to use the texture features as inputs of a data-driven model based on L1 regularization, called least absolute shrinkage and selection operator (LASSO), where their coefficients are optimized in a manner that prioritizes more informative features. The LASSO model was then employed to efficiently estimate the density of microalgae presenting in a new image. The proposed approach was validated in real-world experiments monitoring the Chlorella vulgaris microalgae strain, where the obtained results demonstrate its outperformance compared with other methods. More specifically, the average error in the estimation obtained by the proposed approach is 1.54, whereas those obtained by the Gaussian process and gray-scale-based methods are 2.16 and 3.68, respectively
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s23052543
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2052857-7
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  • 3
    Online Resource
    Online Resource
    Negative Impact of Fear of COVID-19 on Health-Related Quality of Life Was Modified by Health Literacy, eHealth Literacy, and Digital Healthy Diet Literacy: A Multi-Hospital Survey
    MDPI AG ; 2021
    In:  International Journal of Environmental Research and Public Health Vol. 18, No. 9 ( 2021-05-06), p. 4929-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 18, No. 9 ( 2021-05-06), p. 4929-
    Abstract: Background: The COVID-19 pandemic has been disseminating fear in the community, which has affected people’s quality of life, especially those with health problems. Health literacy (HL), eHealth literacy (eHEAL), and digital healthy diet literacy (DDL) may have potential impacts on containing the pandemic and its consequences. This study aimed to examine the association between the fear of COVID-19 scale (FCoV-19S) and the health-related quality of life (HRQoL), and to examine the effect modification by HL, eHEAL, and DDL on this association. Methods: A cross-sectional study was conducted in 11 hospitals across Vietnam from 7 April to 31 May 2020. Data were collected on 4348 outpatients, including demographic characteristics, HL, eHEAL, DDL, FCoV-19S, and HRQoL. Multiple linear regression and interaction models were used to explore associations. Results: Patients with higher FCoV-19S scores had lower HRQoL scores (unstandardized coefficient, B = −0.78, p 〈 0.001). HL (B = 0.20, p 〈 0.001), eHEAL (B = 0.24, p 〈 0.001), and DDL (B = 0.20, p 〈 0.001) were positively associated with higher HRQoL scores. The negative impact of FCoV-19S on HRQoL was significantly attenuated by higher eHEAL score groups (from one standard deviation (SD) below the mean, B = −0.93, p 〈 0.001; to the mean, B = −0.85, p 〈 0.001; and one SD above the mean, B = −0.77, p 〈 0.001); and by higher DDL score groups (from one SD below the mean, B = −0.92, p 〈 0.001; to the mean, B = −0.82, p 〈 0.001; and one SD above the mean, B = −0.72, p 〈 0.001). Conclusions: eHealth literacy and digital healthy diet literacy could help to protect patients’ health-related quality of life from the negative impact of the fear of COVID-19 during the pandemic.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph18094929
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2175195-X
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  • 4
    Online Resource
    Online Resource
    Impacts of Digital Healthy Diet Literacy and Healthy Eating Behavior on Fear of COVID-19, Changes in Mental Health, and Health-Related Quality of Life among Front-Line Health Care Workers
    MDPI AG ; 2021
    In:  Nutrients Vol. 13, No. 8 ( 2021-07-30), p. 2656-
    Details
    In: Nutrients, MDPI AG, Vol. 13, No. 8 ( 2021-07-30), p. 2656-
    Abstract: Background: We aimed to examine the impacts of digital healthy diet literacy (DDL) and healthy eating behaviors (HES) on fear of COVID-19, changes in mental health, and health-related quality of life (HRQoL) among front-line healthcare workers (HCWs). Methods: An online survey was conducted at 15 hospitals and health centers from 6–19 April 2020. Data of 2299 front-line HCWs were analyzed—including socio-demographics, symptoms like COVID-19, health literacy, eHealth literacy, DDL, HES, fear of COVID-19, changes in mental health, and HRQoL. Regression models were used to examine the associations. Results: HCWs with higher scores of DDL and HES had lower scores of FCoV-19S (regression coefficient, B, −0.04; 95% confidence interval, 95% CI, −0.07, −0.02; p = 0.001; and B, −0.10; 95% CI, −0.15, −0.06; p 〈 0.001); had a higher likelihood of stable or better mental health status (odds ratio, OR, 1.02; 95% CI, 1.00, 1.05; p = 0.029; and OR, 1.04; 95% CI, 1.00, 1.07; p = 0.043); and HRQoL (OR, 1.02; 95% CI, 1.01, 1.03; p = 0.006; and OR, 1.04; 95% CI, 1.02, 1.06; p = 0.001), respectively. Conclusions: DDL and HES were found as independent predictors of fear of COVID−19, changes in mental health status, and HRQoL in front-line HCWs. Improving DDL and HES should be considered as a strategic approach for hospitals and healthcare systems.
    Type of Medium: Online Resource
    ISSN: 2072-6643
    URL: Article
    DOI: 10.3390/nu13082656
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2518386-2
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  • 5
    Online Resource
    Online Resource
    Anthropometric Cut-Off Values for Detecting the Presence of Metabolic Syndrome and Its Multiple Components among Adults in Vietnam: The Role of Novel Indices
    MDPI AG ; 2022
    In:  Nutrients Vol. 14, No. 19 ( 2022-09-28), p. 4024-
    Details
    In: Nutrients, MDPI AG, Vol. 14, No. 19 ( 2022-09-28), p. 4024-
    Abstract: Recent studies have shown that using international guidelines to diagnose metabolic syndrome (MetS) may underestimate its prevalence in different Asian populations. This study aims to determine the validity of anthropometric indicators and appropriate cut-off values to predict MetS for Vietnamese adults. We analyzed data on 4701 adults across four regions of Vietnam. Four conventional and five novel anthropometric indexes were calculated. The area under a receiver operating characteristic (ROC) curve (AUC) and Youden’s J statistic were applied to evaluate the diagnostic ability and optimal cut-off values. Regardless of diagnostic criteria and gender, Abdominal volume index (AVI), Body roundness index (BRI), and Waist-height ratio (WHtR) had the highest AUC values, followed by Body mass index (BMI) and Waist-hip ratio (WHR). However, it was seen that differences among the AUC values of most indices were minor. In men, using International Diabetes Federation (IDF) criteria, the threshold of indices was 3.86 for BRI, 16.20 for AVI, 0.53 for WHtR, 22.40 for BMI, and 0.90 for WHR. In women, the threshold for these figures were 3.60, 12.80, 0.51, 23.58, and 0.85, respectively. It is recommended that health personnel in Vietnam should apply appropriate thresholds of anthropometry, which are lower than current international guidelines, for MetS screening to avoid under-diagnosis.
    Type of Medium: Online Resource
    ISSN: 2072-6643
    URL: Article
    DOI: 10.3390/nu14194024
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518386-2
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