In this study, a projection of effective blood concentration (EBC) readings of digoxin is made using the inverse problem algorithm based on clinical data for patients with heart failure diseases. Seven factors, including body surface area (BSA), blood urine nitrogen (BUN), creatinine, sodium (Na), potassium (K), magnesium (Mg) ion readings, and mean arterial pressure (MAP) were compiled with nonlinear regression fit to develop a projection function having 29 terms obtained from an inverse problem algorithm via the default function run in STATISTICA. Accordingly, data collected from the clinical 168 heart failure patients were normalized to be included in same domain range ([Formula: see text]1 to +1), and then calculated by the specific algorithm to optimize the numerical solution to evaluate EBC readings of digoxin. The evaluated first-order regression fit owned an optimal loss function ([Formula: see text]) coupled with correlation coefficient [Formula: see text] = 0.892 and variance of 89.20%. Furthermore, 45 patients having similar clinical syndromes were also adopted to verify the projection and implied with high agreement. The BUN factor dominated the projection and defined as the most significant coefficient in the analysis, and K ion, MAP, BSA, and Mg ion factors exhibited minor contributions to the projection. The repeated trials to lower number of factors from seven to a smaller number (namely 6, 5, 4, 3, 2, and 1) for simplifying method but resulting with unaccepted outcomes, with high loss function values and low linearity. However, the algorithm held its accuracy to handle the verified data that were out of the original bounds. The proposed algorithm demonstrated a useful analysis to handle the drug administration in pharmaceutical field.
ImportanceThe association between sodium-glucose transport protein 2 inhibitor (SGLT2i) use and the incidence of acute kidney injury (AKI) remains controversial. The benefits of SGLT2i use in patients to reduce AKI requiring dialysis (AKI-D) and concomitant diseases with AKI as well as improve AKI prognosis have not yet been established.ObjectiveTo investigate the association between SGLT2i use and AKI incidence in patients with type 2 diabetes (T2D).Design, Setting, and ParticipantsThis nationwide retrospective cohort study used the National Health Insurance Research Database in Taiwan. The study analyzed a propensity score–matched population of 104 462 patients with T2D treated with SGLT2is or dipeptidyl peptidase 4 inhibitors (DPP4is) between May 2016 and December 2018. All participants were followed up from the index date until the occurrence of outcomes of interest, death, or the end of the study, whichever was earliest. Analysis was conducted between October 15, 2021, and January 30, 2022.Main Outcomes and MeasuresThe primary outcome was the incidence of AKI and AKI-D during the study period. AKI was diagnosed using International Classification of Diseases diagnostic codes, and AKI-D was determined using the diagnostic codes and dialysis treatment during the same hospitalization. Conditional Cox proportional hazard models assessed the associations between SGLT2i use and the risks of AKI and AKI-D. The concomitant diseases with AKI and its 90-day prognosis, ie, the occurrence of advanced chronic kidney disease (CKD stage 4 and 5), end-stage kidney disease, or death, were considered when exploring the outcomes of SGLT2i use.ResultsIn a total of 104 462 patients, 46 065 (44.1%) were female patients, and the mean (SD) age was 58 (12) years. After a follow-up of approximately 2.50 years, 856 participants (0.8%) had AKI and 102 (<0.1%) had AKI-D. SGLT2i users had a 0.66-fold risk for AKI (95% CI, 0.57-0.75; P < .001) and 0.56-fold risk of AKI-D (95% CI, 0.37-0.84; P = .005) compared with DPP4i users. The numbers of patients with AKI with heart disease, sepsis, respiratory failure, and shock were 80 (22.73%), 83 (23.58%), 23 (6.53%), and 10 (2.84%), respectively. SGLT2i use was associated with lower risk of AKI with respiratory failure (hazard ratio [HR], 0.42; 95% CI, 0.26-0.69; P < .001) and shock (HR, 0.48; 95% CI, 0.23-0.99; P = .048) but not AKI with heart disease (HR, 0.79; 95% CI, 0.58-1.07; P = .13) and sepsis (HR, 0.77; 95% CI, 0.58-1.03; P = .08). The 90-day AKI prognosis for the risk of advanced CKD indicated a 6.53% (23 of 352 patients) lower incidence in SGLT2i users than in DPP4i users (P = .045).Conclusions and RelevanceThe study findings suggest that patients with T2D who receive SGLT2i may have lower risk of AKI and AKI-D compared with those who receive DPP4i.
The overall survival (OS) prediction for nonsmall cell lung carcinoma (NSCLC) patients of clinical IIIA-N2 stage undergone various treatments was investigated through a refined Taylor series expansion algorithm. The model was created according to a population-based study in Taiwan. The proposed prediction algorithm is based on the well-known hit and target model adopted for analyzing the cell death from the microscopic viewpoint. It also implies the application of the Taylor series expansion to the population-based survey dataset. In the proposed algorithm, the basic degradation of a patient’s health is represented via a specific function comprising a single exponential term exp([Formula: see text]). The refined algorithm successfully predicted NSCLC IIIA-N2 patients’ OS rate. A total of 127,301 patients were collected from 2010 to 2017. Then, 2655 patients were recognized as effective events and classified into eight classes according to various medical treatments, namely surgical operation, radiotherapy, and chemotherapy. For each class of patients, the average life was evaluated, according to Taylor’s expansion algorithm, and the average derived life range spread from 3.51 to 7.81 years. An index of life gain with specific treatment was defined according to the Taguchi optimization analysis. The life gains provided by the surgical operation, chemotherapy, and radiotherapy were 2.74, 1.18, and 0.48 years. The surgical operation was the most beneficial treatment, which is in concert with recommendations of European experts. A similar finding was also reflected in four out of eight classes, which included the surgical operation in the treatment plans of most Taiwanese hospitals.
This study optimized the ultrasound image of carotid artery stenosis using Taguchi dynamic analysis and an indigenous water phantom. Eighteen combinations of seven essential factors of the ultrasound scan facility were organized according to Taguchi’s L18 orthogonal array. The seven factors were assigned as follows: (1) angle of probe; (2) signal gain; (3) resolution vs. speed; (4) dynamic range; (5) XRES; (6) zoom; (7) time gain compensation. An indigenous water phantom was customized to satisfy the quantified need in Taguchi’s analysis. Unlike the conventional dynamic Taguchi analysis, an innovative quantified index, the figure of merit (FOM), was proposed to integrate four specific quality characteristics, namely (i) average difference between the practical scan and theoretically preset area (78.5, 50.2 and 12.6 mm2) of stenosis, (ii) standard deviation of the average, (iii) practical scan’s sensitivity β to various stenosis diameters (10, 8, and 4 mm), and (iv) correlation coefficient r2 of the linear regressed sensitivity curve. The highest value (FOM = 0.413) was furnished by the optimal combination of factors on 18 groups under study, yielding high r2 and low β or standard deviation values and the best quality of ultrasound images for the further clinical diagnosis. The comparison between FOM and the conventional signal-to-noise (S/N) ratio in Taguchi’s analysis revealed that FOM compiled more quality characteristics that were superior by nature to fulfill the practical need in clinical diagnosis. The alternative choice in ultrasound scan optimization can be based on stenosis diameter variation from a different perspective to be explored in the follow-up study.
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