Cost-Effectiveness of Clinical Pharmacy Education on Infection Management among Patients with Chronic Kidney Disease in an Indonesian Hospital

AbstractObjectivesThis study evaluated the clinical and economic impacts of clinical pharmacy education (CPE) on infection management among patients with chronic kidney disease (CKD) stages 4 and 5 in Haji Adam Malik Hospital, Indonesia.MethodsA quasi-experimental economic evaluation comparing CPE impact on 6-month CKD mortality was conducted on the basis of payer perspective. The experimental group (n = 63) received care by health care providers who were given CPE on drug-related problems and dose adjustment. The control group (n = 80) was based on the historical cohort of patients who received care before the CPE. Measure of clinical outcome applied in this study was number of lives saved/100 patients treated. Cost-effectiveness ratios for CKD stages 4 and 5 patients without CPE and with CPE and incremental cost-effectiveness ratios (ICERs) for CKD stages 4 and 5 patients were analyzed.ResultsLives saved (%) in the treatment of CKD without CPE: CKD stage 4, 78.57; CKD stage 5, 57.58. Lives saved (%) in the treatment of CKD with CPE: CKD stage 4, 88.89; CKD stage 5, 65.45. Cost-effectiveness ratios for stage 4 with and without CPEs were Rp3,348,733.27 and Rp3,519,931.009, respectively. Cost-effectiveness ratios for stage 5 with and without CPEs were Rp7,137,874.93 and Rp7,871,822.27, respectively. ICERs were Rp2,045,341.22 for CKD stage 4 and Rp1,767,585.60 for CKD stage 5.ConclusionsTreatment of CKD stages 4 and 5 with CPE was more effective and cost-effective compared with treatment of CKD stages 4 and 5 without CPE. The ICERs indicated that extra costs were required to increase life saved in both stages

Eco-structured biosorptive removal of basic fuchsin using pistachio nutshells: A definitive screening design-based approach

Biosorptive removal of basic fuchsin (BF) from wastewater samples was achieved using the recycled agro-wastes of pistachio nut shells (PNS). Seven adsorbents were developed; raw shells (RPNS) and the thermally activated biomasses at six different temperatures (250–500 °C). Two measures were implemented to assess the performance of utilized adsorbents; %removal (%R) and adsorption capacity (qe). RPNS proved to be the best among the tested adsorbents. A smart approach, definitive-screening design (DSD) was operated to test the impact of independent variables on the adsorption capacity of RPNS. pH, adsorbent dose (AD), dye concentration (DC), and stirring time (ST), were the tested variables. Analysis of variance (ANOVA), control, and quality charts helped establishing regression model. Characterization was performed using Fourier- transform infrared (FT-IR)/Raman spectroscopies together with thermogravimetric analysis (TGA) and scanning electron microscopy (SEM)/energy-dispersive X-ray spectroscopy (EDX) analyses. The surface area and other textural properties were determined using the Brunauer Emmett-Teller (BET) analysis. Removal of 99.71% of BF with an adsorption capacity of 118.2 mg/g could be achieved using a factorial blend of pH 12, 100 mg/50 mL of RPNS, and 250 ppm BF for 20 min. Equilibrium studies reveal that the adsorption is physisorption with adsorption energy of 7.45 kJ/mol as indicated by Dubinin-Radushkevich (DR) and Langmuir isotherms. Moreover, adsorption follows pseudo-second-order kinetics with respect to BF and is controlled by the adsorption rate.This work was made possible by Qatar University Internal Student Grant [QUST-2-CAS-2019-18] from Qatar University. The statements made herein are solely the responsibility of the authors. The publication of this article was funded by the Qatar National Library.Scopu

Bio-Waste Aloe vera Leaves as an efficient adsorbent for Titan Yellow from Wastewater: Structuring of a novel adsorbent using Plackett-Burman factorial design

Titan yellow (TY), a triazene azo dye, was removed from contaminated wastewater samples using a green adsorbent recycled from Aloe vera leaves (AV) waste. Two adsorbents were developed-air-dried Aloe vera (ADAV) and thermally treated Aloe vera (TTAV). Adsorption efficacy of both adsorbents was assessed in terms of percent removal (%R) of TY and adsorption capacity (qe). ADAV had a better performance compared to TTAV. Plackett-Burman design (PBD) was exploited to establish the experimental pattern of the study. Four variables were studied: pH, adsorbent dose (AD), dye concentration (DC), and stirring time (ST). Analysis of variance (ANOVA) at 95.0 confidence interval (CI), control, and quality charts helped establish regression model(s). Characterization of both adsorbents was performed using FT-IR/Raman spectroscopy together with TGA/dTGA and SEM/energy dispersive X-ray spectroscopy (EDX) analyses. Textural properties were determined using nitrogen adsorption isotherms at 77 K. Results showed that the surface areas of ADAV and TTAV300 were 3.940 and 7.076 m2/g, respectively. Raman analysis showed that the TTAV had clear Dand G-bands. Equilibrium studies revealed that data were well fitted to Freundlich isotherm with a maximum adsorption capacity of 55.25 mg/g using Langmuir equation, and the adsorption was physisorption. Adsorption followed a pseudo-second order that occurred in two steps-diffusion and then adsorption. - 2019 by the authors.The project members would like to extend their special thanks to the Central Lab Unit (CLU) at the Qatar University. This work was made possible by Qatar University Internal Student Grant [QUST-2-CAS-2019-18] from Qatar University. The statements made herein are solely the responsibility of the authors. The publication of this article was funded by the Qatar National LibraryScopu

RETINA FUNDUS IMAGE MASK GENERATION USING PSEUDO PARAMETRIC MODELING TECHNIQUE

The use of vascular intersection as one of the symptoms for monitoring and diagnosis of diabetic retinopathy from fundus images have been widely reported in literatures. In this work, a new hybrid approach that makes use of three different methods of vascular intersection detection namely Modified cross-point number (MCN), Combine Cross Points (CNN) and Artificial Neural Network (ANN) is hereby proposed. Result obtained from the application of this technique to both simulated and experimental shows a very high accuracy and precision value in detecting both bifurcation and cross over points. Thus an improvement in bifurcation and vascular point detection and a good tool in the monitoring and diagnosis of diabetic retinopathy