Continuous Venovenous Hemodiafiltration Versus Standard Medical Therapy for the Prevention of Rhabdomyolysis-Induced Acute Kidney Injury: A Retrospective Cohort Study

Aim: To determine whether continuous venovenous hemodiafiltration (CVVHDF) plus standard medical therapy (SMT) vs. SMT alone prevents rhabdomyolysis (RM)-induced acute kidney injury (AKI) and to analyze the related health economics.Methods: This retrospective cohort study involved patients with RM without AKI, coronary heart disease, or chronic kidney disease treated with CVVHDF plus SMT (treatment group, n = 9). Matched patients with RM without AKI treated with SMT only served as controls (1:1 ratio). Baseline characteristics, biochemical indexes, renal survival data, and health economic data were compared between groups. In the treatment group, some biochemical data were compared at different time points.Results: At 2 and 7 days after admission, serum biochemical indices (e.g., myoglobin, creatine kinase, creatinine, and blood urea nitrogen) did not differ between the two groups. Total (P = 0.011) and daily hospitalization costs (P = 0.002) were higher in the treatment group than in the control group. After 53 months of follow-up, no patient developed increased serum creatinine, except for 1 treatment-group patient who died of acute myocardial infarction. In the treatment group, myoglobin levels significantly differed before and after the first CVVHDF treatment (P = 0.008), and serum myoglobin, serum creatinine, and blood urea nitrogen decreased significantly at different time points after CVVHDF.Conclusions: Although CVVHDF facilitated myoglobin elimination, its addition to SMT did not improve serum myoglobin or other biochemical indices or the long-term renal prognosis. Despite similar hospitalization durations, both total and daily hospitalization costs were higher in the treatment group.

Cost minimization analysis of two chemotherapy regimens in the treatment of colorectal cancer in a public reimbursement hospital in Brazil

Objective: To conduct a pharmacoeconomic evaluation between XELOX and mFOLFOX6 in the adjuvant and metastatic treatment of colorectal cancer from the perspective of a public reimbursement hospital. Methods: The cost minimization analysis was conducted for patients who started treatment in 2013 and 2014. The micro-costing technique was used to verify expenditures on drugs, materials, laboratory and imaging tests, ambulatory and daily hospitalization, human and administrative resources and determine the individual cost of each alternative, per patient. To evaluate the robustness of the economic analysis, multivariate sensitivity analysis was performed in six different scenarios. Results: There was an average cost for XELOX of U$ 4,637.14 in adjuvant and U$ 3,831.48 for palliative treatment, and a cost for mFOLFOX6 of U$ 5,474.89 in adjuvant and U$ 4,432.95 in palliative treatment. Sensitivity analysis maintained the dominance of XELOX. Material and drug costs accounted for about 85% of the total cost of XELOX; for mFOLFOX6 this cost was around 36%. On the other hand, the cost of hospitalization and placement of a catheter occured exclusively for mFOLFOX6, which also presented a higher cost with human resources. Conclusion: From the perspective of the hospital, XELOX proved to be the least costly alternative on the treatment of colorectal cancer.

Application of Distribution-Delay Models to Estimating the Hospitalized Mortality Rate of Covid-19 According to Delay Effect of Hospitalizations Counts

Introduction:The COVID-19 infectious epidemic has become a serious worry all over the world, including Iran. The high outbreak of disease ranked Iran as second in Asia and 11th in the world. Given the growing progress of this epidemic in infecting and killing individuals, it is essential to forecast the delay effect of the number of hospitalized upon the hospitalized mortality rate. Methods: In this study, we used the daily Hospitalization cases of COVID-19 of IRAN for the period of 15-May 2020 to 5-Oct 2020 which were obtained from the online database. Five distribution delay models were compared for estimating and forecasting. Results: Based on measurement errors DDM selected as the best model for forecasting the number of death. According to this model, the long-run effects show that observing the effect of hospitalization counts on death counts takes an average of five days and the long-run hospitalized mortality rate was 12%. Conclusion: The overall hospitalized mortality rate of COVID-19 in Iran is less than the global rate of 15%. The mean of delay effect of daily hospitalization on mortality is approximately 5 days. Our findings showed distributed delay model (DDM) has better performance in the forecasting of the future behavior of the Coronavirus mortality, and providing to government and health care decision- makers the possibility to predict the outcomes of their decision on public health.

A Time-dependent mathematical model for COVID-19 transmission dynamics and analysis of critical and hospitalized cases with bed requirements

A time-dependent SEAIHCRD model is the extension of the SEIR model, which includes some new compartment that is asymptomatic infectious people, hospitalized people, critical people, and dead compartments. In this article, we analyzed six countries, namely the United States, Brazil, India, South Africa, Russia, and Mexico. A time-dependent SEAIHCRD model calculates the magnitude of peaks for exposed people, asymptomatic infectious people, symptomatic infectious people, hospitalized people, the number of people admitted to ICUs, and the number of COVID-19 deaths over time. It also computes the spread scenario and endpoints of disease. The proposed model also involves asymptomatic infectious individuals. To estimate the various parameters, we first collect the data and fit that using the Lavenberg-Marquardt model for death cases. Then we calculate infection rate, recovery rate, case fatality rate, and the basic reproduction number over time. We calculate two types of case fatality rates: one is the daily case fatality rate, and the other is the total case fatality rate. The proposed model includes the social distance parameter, various age classes, hospital beds for severe cases, and ICU beds or ventilators for critical cases. This model will be useful to determine various essential parameters such as daily hospitalization rate, daily death rates, including the requirement of normal and ICU beds during peak days of infection.

Modeling and forecasting hospitalized mortality rate of COVID-19 according to delay effect of daily hospitalization

Introduction: The COVID-19 infectious epidemic has become a serious worry all over the world, including Iran. The high outbreak of disease ranked Iran as second in Asia and 11th in the world. Given the growing progress of this epidemic in infecting and killing individuals, it is essential to forecast the delay effect of the number of hospitalized upon the hospitalized mortality rate. Methods: In this study, we used the daily Hospitalization cases of COVID-19 of IRAN for the period of 15-May 2020 to 5-Oct 2020 which were obtained from the "Iran-COVID-19-Data[1]" database. Five distribution delay models were compared for estimating and forecasting. Results: based on measurement errors DDM selected as the best model for forecasting the number of death. According to this model, the long-run effects show that observing the effect of hospitalization counts on death counts takes an average of five days and the overall hospitalized mortality rate was 12%.Conclusion: The overall hospitalized mortality rate of COVID-19 in Iran is less than the global rate of 15%. The mean of delay effect of daily hospitalization on mortality is approximately 5 days. Our findings showed distributed delay model (DDM) has better performance in the forecasting of the future behavior of the Coronavirus mortality, and providing to government and health care decision- makers the possibility to predict the outcomes of their decision on public health.

Association of diurnal temperature range with daily hospitalization for exacerbation of chronic respiratory diseases in 21 cities, China

Background The association between diurnal temperature range (DTR) and hospitalization for exacerbation of chronic respiratory diseases (CRD) was rarely reported. Objectives To examine the association between DTR and daily hospital admissions for exacerbation of CRD and find out the potential effect of modifications on this association. Method Data on daily hospitalization for exacerbation of chronic obstructive pulmonary disease (COPD), asthma and bronchiectasis and meteorology measures from 2013 through 2017 were obtained from 21 cities in South China. After controlling the effects of daily mean temperature, relative humidity (RH), particulate matter < 2.5 μm diameter (PM2.5) and other confounding factors, a standard generalized additive model (GAM) with a quasi-Poisson distribution was performed to evaluate the relationships between DTR and daily hospital admissions of CRD in a two-stage strategy. Subgroup analysis was performed to find potential modifications, including seasonality and population characteristics. Result Elevated risk of hospitalization for exacerbation of CRD (RR = 1.09 [95%CI: 1.08 to 1.11]) was associated with the increase in DTR (the 75th percentile versus the 25th percentile of DTR at lag0–6). The effects of DTR on hospital admissions for CRD were strong at low DTR in the hot season and high DTR in the cold season. The RR (the 75th percentile versus the 25th percentile of DTR at lag0–6) of hospitalization was 1.11 (95%CI: 1.08 to 1.12) for exacerbations of COPD and 1.09 (95%CI: 1.05 to 1.13) for asthma. The adverse effect of DTR on hospitalization for bronchiectasis was only observed in female patients (RR = 1.06 [95%CI: 1.03 to 1.10]). Conclusion Our study provided additional evidence for the association between DTR and daily hospitalization for exacerbation of CRD, and these associations are especially stronger in COPD patients and in the cold season than the hot season. Preventive measures to reduce the adverse impacts of DTR were needed for CRD patients.

Association of diurnal temperature range with daily hospitalization for exacerbation of chronic respiratory diseases in 21 cities, China

Background: The association between diurnal temperature range (DTR) and hospitalization for exacerbation of chronic respiratory diseases (CRD) was rarely reported. Objectives: To examine the association between DTR and daily hospital admission for exacerbations of CRD and find out the potential effect of modifications on this association.Method: Data on daily hospitalization for exacerbation of chronic obstructive pulmonary disease (COPD), asthma and bronchiectasis and meteorology measures from 2013 through 2017 were obtained from 21 cities in South China. After controlling the effects of daily mean temperature, relative humidity (RH), particulate matter < 2.5 µm diameter (PM2.5) and other confounding factors, a standard generalized additive model (GAM) with a quasi-Poisson distribution was performed to evaluate the relationships between DTR and daily hospital admissions of CRD in a two-stage strategy. Subgroup analysis was performed to find potential modifications, including seasonality and population characteristics.Result: Elevated risk of hospitalization for exacerbation of CRD (RR=1.09 [95%CI: 1.08 to 1.11]) was associated with interquartile range (IQR)the increase in DTR (the 75th percentile versus the 25th percentile of DTR at lag0-6). The effects of DTR on hospital admissions for CRD were strong at low DTR in the hot season and high DTR in the cold season. The relative risk (RR (the 75th percentile versus the 25th percentile of DTR at lag0-6)) of hospitalization was 1.11 (95%CI: 1.08 to 1.12) for exacerbations of COPD and 1.09 (95%CI: 1.05 to 1.13) for asthma per IQR increase in DTR. The adverse effect of DTR on hospitalization for bronchiectasis was only observed in female patients (RR=1.06 [95%CI: 1.03 to 1.10]). Conclusion: Our study provided additional evidence for the association between DTR and daily hospitalization for exacerbation of CRD, and these associations are especially stronger in COPD patients and in the cold season than the hot season. Preventive measures to reduce the adverse impacts of DTR were needed for CRD patients.

Effects of medical insurance system and nursing care on the hospitalization cost effectiveness of acute myocardial infarction patients

Background Acute myocardial infarction is still a burden on Chinese patients. Whether different medical insurance system have any influence on the hospitalization cost and therapeutic effect of acute myocardial infarction patient needs further investigation. Methods In this study, 600 patients were stratified by health insurance status to investigate the cost effectiveness. Results Compared with free medical care, patients with other health insurance status have a significantly lower age (P ˂ 0.05~0.001), the youngest of which is new rural cooperative medical system. The hospital expense, nursing fee, length of stay, daily hospitalization cost, daily drug cost, daily nursing cost and percent of nursing cost of different health insurance status were statistically significant. ANCOVA analyses controlling for age showed that the differences of hospital expenses, nursing fee, length of stay and daily hospitalization cost were still statistically significant. Further studies found that health insurance status was the leading factors influencing length of stay (β =-0.305, P=0.0000001), nursing costs (β =-0.319, P=0.004), daily hospitalization costs (β =0.296, P=0.0001) and occurrence of clinical events (β =-0.186, OR=0.830, 95%CI 0.694-0.993, P=0.041). Conclusions The hospitalization cost, length of stay, nursing work and therapeutic effect of acute myocardial infarction patients are affected by different health insurance status and age.

Association of diurnal temperature range with daily hospitalization for exacerbation of chronic respiratory diseases in 21 cities, China

Background: The association between diurnal temperature range (DTR) and hospitalization for exacerbation of chronic respiratory diseases (CRD) was rarely reported. Objectives: To examine the association between DTR and daily hospital admission for exacerbations of CRD and find out the potential effect of modifications on this association.Method: Data on daily hospitalization for exacerbation of chronic obstructive pulmonary disease (COPD), asthma and bronchiectasis and meteorology measures from 2013 through 2017 were obtained from 21 cities in South China. After controlling the effects of daily mean temperature, relative humidity (RH), particulate matter < 2.5 µm diameter (PM2.5) and other confounding factors, a standard generalized additive model (GAM) with a quasi-Poisson distribution was performed to evaluate the relationships between DTR and daily hospital admissions of CRD in a two-stage strategy. Subgroup analysis was performed to find potential modifications, including seasonality and population characteristics.Result: Elevated risk of hospitalization for exacerbation of CRD (RR=1.09 [95%CI: 1.08 to 1.11]) was associated with interquartile range (IQR) increase in DTR. The effects of DTR on hospital admissions for CRD were strong at low DTR in the hot season and high DTR in the cold season. The relative risk (RR) of hospitalization was 1.11 (95%CI: 1.08 to 1.12) for exacerbations of COPD and 1.09 (95%CI: 1.05 to 1.13) for asthma per IQR increase in DTR. The adverse effect of DTR on hospitalization for bronchiectasis was only observed in female patients (RR=1.06 [95%CI: 1.03 to 1.10]). Conclusion: Our study provided additional evidence for the association between DTR and daily hospitalization for exacerbation of CRD, and these associations are especially stronger in COPD patients and in the cold season than the hot season. Preventive measures to reduce the adverse impacts of DTR were needed for CRD patients.