Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective To observe the clinical efficacy and adverse drug reactions of recombinant human growth hormone on dwarfism in children with primary nephrotic syndrome.Methods Children with dwarfism in primary nephrotic syndrome were divided into control group and treatment group.Patients in control group were orally administered prednisone acetate tablets,with an initial dose of 2 mg·kg-1·d-1,at once,no more than 60 mg in a single day,and after a duration of 6 weeks of full dosage,the dosage was reduced by 2.5 mg every 2 weeks until the maintenance dose of 5-10 mg·d-1 was administered for 12 months.Patients in treatment group were injected subcutaneously with recombinant human growth hormone 0.15 U·kg-1 at 0.5 h before bedtime every night on the basis of control group for a period of 12 months.The levels of height,bone age,standard deviation fraction of height(HtSDS),insulin-like serum growth factor 1(IGF-1),insulin-like growth factor binding protein 3(IGFBP-3),and the incidence of adverse drug reactions were compared between the two groups.Results There were 63 cases in control group and 63 cases in treatment group.The height of the children in treatment group and control group after treatment were(146.48±6.76)and(138.62±4.95)cm;the HtSDS values were-1.72±0.18 and-1.97±0.20;the IGF-1 values were(158.86±18.24)and(113.14±15.88)ng·mL-1;IGFBP-3 values were(5.21±0.83)and(3.13±0.71)μg·mL-1,the differences were all statistically significant(all P＜0.05).The incidence of adverse drug reaction in treatment group and control group were 9.52％(6 cases/63 cases)and 3.17％(2 cases/63 cases),with no statistically significant difference(P＞0.05).Conclusion Recombinant human growth hormone has a definite clinical efficacy,high safety,and effective promotion of growth and development in the treatment of primary nephrotic syndrome in children with dwarfism.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.