OBJECTIVE: The aim of this systematic review and meta-analysis is to compare the effectiveness of amiodarone, dexmedetomidine and magnesium in preventing JET following congenital heart surgery.
METHODS: This meta-analysis was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement, where 11 electronic databases were searched from date of inception to August 2020. The incidence of JET was calculated with the relative risk of 95% confidence interval (CI). Quality assessment of the included studies was assessed using the Consolidated Standards of Reporting Trials (CONSORT) 2010 statement.
RESULTS: Eleven studies met the predetermined inclusion criteria and were included in this meta-analysis. Amiodarone, dexmedetomidine and magnesium significantly reduced the incidence of postoperative JET [Amiodarone: risk ratio 0.34; I2= 0%; Z=3.66 (P=0.0002); 95% CI 0.19-0.60. Dexmedetomidine: risk ratio 0.34; I2= 0%; Z=4.77 (P<0.00001); 95% CI 0.21-0.52. Magnesium: risk ratio 0.50; I2= 24%; Z=5.08 (P<0.00001); 95% CI 0.39-0.66].
CONCLUSION: All three drugs show promise in reducing the incidence of JET. Our systematic review found that dexmedetomidine is better in reducing the length of ICU stays as well as mortality. In addition, dexmedetomidine also has the least pronounced side effects among the three. However, it should be noted that this conclusion was derived from studies with small sample sizes. Therefore, dexmedetomidine may be considered as the drug of choice for preventing JET.
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.