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  1. Nindrea RD, Aryandono T, Lazuardi L, Dwiprahasto I
    Iran J Public Health, 2019 Feb;48(2):198-205.
    PMID: 31205873
    Background: Breast cancer is the most common cancer type in women not only in world but also in Malays ethnicity between Malaysia and Indonesia. Breast cancer has varying incidence in every country, but genetic factor by family history influence the incidence of breast cancer. This systematic review and meta-analysis was performed to determine family history of breast cancer and breast cancer risk between Malays ethnicity in Malaysia and Indonesia.

    Methods: This meta-analysis was conducted on published research articles on family history of breast cancer and breast cancer risk between Malays ethnicity in Malaysia and Indonesia published between Jan 1999 and Jul 2018 in the online article databases of PubMed, ProQuest and EBSCO. Pooled odds ratios (OR) were calculated with fixed and random-effect models. Publication bias was visually evaluated by using funnel plots and statistically assessed through Egger's and Begg's tests. Data were processed using Review Manager 5.3 (RevMan 5.3) and Stata version 14.2 (Stata Corporation).

    Results: We reviewed 1123 articles. There are 10 studies with number of samples 4511 conducted a systematic review and continued with Meta-analysis of relevant data. The results showed significant association between family history of breast cancer with breast cancer risk in Malays ethnicity in Malaysia and Indonesia (OR = 3.34 [95% CI 2.68-4.15, P<0.00001]). There was not significant publication bias for studies included in family history of breast cancer and breast cancer risk in Malays ethnicity in Malaysia and Indonesia.

    Conclusion: This analysis confirmed the association of family history of breast cancer and breast cancer risk between Malays ethnicity in Malaysia and Indonesia.
  2. Larasati N, Satibi S, Kristina SA, Lazuardi L
    Malays J Med Sci, 2024 Aug;31(4):162-173.
    PMID: 39247104 DOI: 10.21315/mjms2024.31.4.13
    INTRODUCTION: Drug-related problems (DRPs) are treatment-related occurrences that affect therapeutic efficacy. In a previous study, approximately 279 out of 330 (84.5%) patients with type 2 diabetes mellitus (T2DM) had experienced at least one DRP, including non-optimal drug effects (n = 240, 52.7%) and indications without medication (n = 137, 30.1%). Patients who were hospitalised for 5-10 days had the highest number of DRPs. Therefore, this study investigates the association between DRPs and length of stay (LoS) in patients with T2DM.

    METHODS: A cross-sectional study was conducted from January 2020 to May 2023 at Rumah Sakit Akademik, Universitas Gadjah Mada, Yogyakarta, Indonesia. Clinical pharmacists reviewed electronic health data to examine DRPs. The Fisher's exact test evaluated the association between DRPs and LoS.

    RESULTS: A total of 60.7% (n = 17) of the participants were females, with the majority falling into the age group ≥ 65 years old (n = 11, 29.7%). A significant portion experienced LoS > 7 days (n = 17, 60.7%). Antidiabetic monotherapy was predominant, and the categories of DRPs included adverse drug reaction (n = 15, 40.5%), dosage too high (n = 6, 16.2%), wrong drug (n = 6, 16.2%), non-adherence (n = 4, 10.8%), need for additional therapy (n = 4, 10.8%) and dosage too low (n = 2, 5.4%). A significant association was observed between non-adherence and LoS (P = 0.016). The possibility of experiencing LoS of 1-7 days increased by 3.43 times with improved non-adherence (OR = 3.43; 95% CI: 1.83, 6.39). In this context, non-adherence refers to DRPs associated with the non-compliance of patients with the prescribed treatment plan.

    CONCLUSION: This study concludes that non-adherence was significantly associated with hospital LoS.

  3. Pramestutie HR, Kristina SA, Lazuardi L, Widayanti AW
    Malays J Med Sci, 2023 Oct;30(5):52-69.
    PMID: 37928786 DOI: 10.21315/mjms2023.30.5.5
    The simulated patient method has been widely used to assess community pharmacy practice in the management of childhood diarrhoea. In such a process, a community pharmacist is required to explore a patient's history, choose the right medication and provide drug-related information. The aim of this review was to evaluate the aforementioned practice. A comprehensive literature search was carried out over Sage Journal, PubMed, ScienceDirect and Google Scholar, and the analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Eligible articles were those published from 2011 to 2021 and original studies that used the simulated patient method to examine the pharmaceutical services provided by pharmacists in relation to childhood diarrhoea. The eight studies that satisfied the eligibility criteria were reviewed. These investigations were undertaken in Brazil, Nigeria, Turkey, Ethiopia and Pakistan. Five of the studies focused on history taking with regard to the characteristics of diarrhoea and revealed that the evaluated pharmacists asked about patient histories. In terms of therapy, three studies indicated that the evaluated pharmacists recommended the administration of oral rehydration salts. Pharmacies should improve their history-taking process, provide drug-related information and recommend therapies to increase the knowledge of simulated patients about diarrhoea treatment in children.
  4. Sanjaya GY, Fauziah K, Pratama RA, Fitriani NA, Setiawan MY, Fauziah IA, et al.
    Med J Malaysia, 2024 Mar;79(2):176-183.
    PMID: 38553923
    INTRODUCTION: Assessment of data quality in the era of big data is crucial for effective data management and use. However, there are gaps in data quality assessment for routine health data to ensure accountability. Therefore, this research aims to improve the routine health data quality that have been collected and integrated into Aplikasi Satu Data Kesehatan (ASDK) as the primary health data system in Indonesia.

    MATERIALS AND METHODS: This descriptive study utilises a desk review approach and employs the WHO Data Quality Assurance (DQA) Tool to assess data quality of ASDK. The analysis involves measuring eight health indicators from ASDK and Survei Status Gizi Indonesia (SSGI) conducted in 2022. The assessment focuses on various dimensions of data quality, including completeness of variables, consistency over time, consistency between indicators, outliers and external consistency.

    RESULTS: Current study shows that routine health data in Indonesia performs high-quality data in terms of completeness and internal consistency. The dimension of data completeness demonstrates high levels of variable completeness with most variables achieving 100% of the completeness.

    CONCLUSION: Based on the analysis of eight routine health data variables using five dimensions of data quality namely completeness of variables, consistency over time, consistency between indicators, outliers. and external consistency. It shows that completeness and internal consistency of data in ASDK has demonstrated a high data quality.

  5. Arguni E, Dewi FST, Fachiroh J, Paramita DK, Lestari SK, Wiratama BS, et al.
    PLoS One, 2022;17(8):e0272690.
    PMID: 35972930 DOI: 10.1371/journal.pone.0272690
    The long-term antibody response to the novel SARS-CoV-2 in infected patients and their residential neighborhood remains unknown in Indonesia. This information will provide insights into the antibody kinetics over a relatively long period as well as transmission risk factors in the community. We aim to prospectively observe and determine the kinetics of the anti-SARS-CoV-2 antibody for 2 years after infection in relation to disease severity and to determine the risk and protective factors of SARS CoV-2 infections in the community. A cohort of RT-PCR confirmed SARS-CoV-2 patients (case) will be prospectively followed for 2 years and will be compared to a control population. The control group comprises SARS-CoV-2 non-infected people who live within a one-kilometer radius from the corresponding case (location matching). This study will recruit at least 165 patients and 495 controls. Demographics, community variables, behavioral characteristics, and relevant clinical data will be collected. Serum samples taken at various time points will be tested for IgM anti-Spike protein of SARS-CoV-2 and IgG anti-Spike RBD of SARS-CoV-2 by using Chemiluminescent Microparticle Immunoassay (CMIA) method. The Kaplan-Meier method will be used to calculate cumulative seroconversion rates, and their association with disease severity will be estimated by logistic regression. The risk and protective factors associated with the SARS-CoV-2 infection will be determined using conditional (matched) logistic regression and presented as an odds ratio and 95% confidence interval.
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