Category: Nevin Manimala

Int J Clin Pharmacol Ther. 2022 Dec 2. doi: 10.5414/CP204299. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the pharmacokinetics (PK), safety, and bioequivalence of two formulations of apixaban in healthy Chinese subjects under fasting and fed conditions.

MATERIALS AND METHODS: A single-center, randomized, open, single-dose, two-period crossover PK study was carried out under fasting and fed conditions in 64 healthy subjects enrolled in either the fasting (36 subjects) or the fed (28 subjects) arms of the study. Subjects received a single oral dose of 2.5 mg apixaban tablets as test (T) or reference (R) formulation. The primary PK parameters determined were the area under the plasma concentration-time curve from zero to t and ∞ (AUC_0-t and AUC_0-∞) and the maximal plasma concentration (C_max). Safety was assessed mainly from the occurrence of adverse events (AEs).

RESULTS: A single drop-out in the fed arm of the trial was excluded from the statistical evaluation. The 90% confidence intervals (CIs) for the geometric mean ratio (GMR) for T/R using AUC_0-t were 95.4 – 100.9% and 97.8 – 103.8%, and for AUC_0-∞ were 95.3 – 100.6% and 98.3 – 104.3% under fasting (36 subjects) and fed (27 subjects) conditions, respectively. Similarly, the 90% CIs for C_max were 94.6 – 103.1% and 88.8 – 102.0% under fasting (36 subjects) and the fed (27 subjects) conditions, respectively. Therefore, the 90% CIs for the T/R AUC and C_max ratios were within the standard range for bioequivalence (80.0 – 125.0%). There were no serious adverse events (SAEs).

CONCLUSION: The test and reference 2.5 mg apixaban tablets were bioequivalent and both showed good tolerability and safety.

PMID:36458443 | DOI:10.5414/CP204299

Int J Clin Pharmacol Ther. 2022 Dec 2. doi: 10.5414/CP204300. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate the rate and determinants of non-adherence to antipsychotic medications in Saudi Arabia.

MATERIALS AND METHODS: This was a cross-sectional study that included a questionnaire, interview, and data extraction from medical records of adult patients on antipsychotic medications. The study was conducted at outpatient clinics at the psychological care department at King Fahad Medical City, Riyadh, Saudi Arabia, between October 25 and November 26, 2020. Data collection included three parts: patients’ sociodemographic characteristics; antipsychotic medications used and patients’ clinical characteristics; and adherence to antipsychotic medications measured by the Medication Adherence Rating Scale (MARS).

RESULTS: Out of 220 patients, 122 (55.5%) were considered non-adherent (MARS scores 6 or less). The MARS items contributing most to non-adherence were “the medication makes me feel tired and sluggish” and “forget to take the medication”, 55 and 40.9%, respectively. Additionally, adverse drug effect significantly increased the risk of poor adherence in regression analysis (odds ratio = 1.97, p = 0.028). The model also showed that female sex, low income, cigarette smoking, substance abuse, uncontrolled disease, comorbidity, and use of Ruqyah religious therapy were associated with increased risk of poor adherence, but were however not statistically significant (p < 0.05).

CONCLUSION: This study showed high non-adherence rate to antipsychotic medications. Adverse drug effects and forgetting to take medications were the main patient-reported barriers to adherence. Likewise, sociodemographic, clinical, and spiritual factors affected medication adherence. Knowing these predictors helps in early identification of patients who are predisposed to medication non-adherence and allows personalized interventions that improve adherence and treatment outcomes.

PMID:36458442 | DOI:10.5414/CP204300

Alcohol Alcohol. 2022 Dec 1:agac062. doi: 10.1093/alcalc/agac062. Online ahead of print.

ABSTRACT

AIMS: To determine whether there is a difference in pituitary gland volumes in patients with alcohol use disorder compared to healthy people.

METHODS: The subjects included in the study consisted of 15 individuals who met the criteria for alcohol use disorder according to the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM 5) diagnostic criteria based on the Structured Clinical Interview for DSM 5 and were admitted to Firat University School of Medicine, Department of Psychiatry, or were hospitalized, and 17 healthy controls. The volumes of pituitary were measured in subjects.

RESULTS: Absolute pituitary gland volumes of patients with alcohol use disorder and healthy controls were compared in the analysis performed using the independent samples t-test. The mean volume of the patient group was significantly smaller than the healthy controls (58.02 ± 7.24 mm3 in patients with alcohol use disorder vs. 83.08 ± 12.11 mm3, P < 0.01), a difference which persisted after controlling for age, gender and total brain size.

CONCLUSIONS: Patients with alcohol use disorder in this study had smaller pituitary gland volumes compared to those of healthy control subjects. However, this study has limitations including small sample size and not adjusting for previous or current medication use or current anxiety and depression.

PMID:36458440 | DOI:10.1093/alcalc/agac062

J Hepatobiliary Pancreat Sci. 2022 Dec 2. doi: 10.1002/jhbp.1294. Online ahead of print.

ABSTRACT

PURPOSE: Delayed hemorrhage (DH) is a rare and yet well-known fatal complication associated with postoperative pancreatic fistula (POPF) in pancreatoduodenectomy (PD). The study aimed to investigate whether arterial reinforcement (AR) using polyglycolic acid sheets (PAS) followed by fibrin sealant (FS) to the hepatic artery could prevent DH in the setting of POPF after PD.

METHODS: A total of 345 patients underwent PD for periampullary tumors from March 2011 to March 2022. From March 2011 to March 2018, 225 patients underwent PD, and AR was not performed (non-AR group). From April 2018 to March 2022, 120 patients underwent PD, and AR was performed (AR group). AR was achieved by wrapping the proper hepatic artery all the way down to the celiac artery with PAS followed by coating with FS. Demographic profile and various outcomes including DH of these two groups were compared and analyzed retrospectively.

RESULTS: In non-AR group, 48 (21.3%) and 12 (5.3%) patients had grade B and C POPF respectively. In AR group, 26 (21.7%) and 4 (3.3%) patients had grade B and C POPF respectively. The incidence of POPF was not was not statistically significant (p = 0.702) between the groups. Among the patients with grade B or C POPF, DH occurred in 14 (23.3%) patients in non-AR group and only one patient in AR group (p = 0.016). Of the 15 patients with DH, four (26.7%) patients died.

CONCLUSION: AR using PAS and FS is effective in preventing DH in the setting of POPF.

PMID:36458401 | DOI:10.1002/jhbp.1294

J Musculoskelet Neuronal Interact. 2022 Dec 1;22(4):498-503.

ABSTRACT

OBJECTIVE: To determine the efficacy of a five-week core stability training program for collegiate athletes on upper extremity performance measures.

METHODS: Seventy healthy collegiate athletes (age 21.6±1.7years; height 175±4.63 cm; body mass 65.31±5.63 kg) were randomly allocated to experimental (n=35) and control group (n=35). The experimental group has undergone a five-week core stabilisation protocol (three days /week) and regular training, whereas the control group maintained their regular training. The upper quarter Y balance test (UQ-YBT) and Functional throwing performance index (FTPI) were assessed pre and post-training.

RESULTS: The results of mixed ANOVA show that there was a significant interaction between time and group variables on YBT (p<0.001, η_p² =0.759) and FTPI (p<0.001, η_p² =0.411) after five weeks of core stability training. Statistically, significant improvement was shown in YBT (mean change=15.2, p<0.001) and FTPI (mean change=14.4, p<0.001) in the experimental group; however, there was no significant change observed in both outcomes in the control groups.

CONCLUSION: After five weeks of core stabilisation training program, the measures of UQ-YBT and FTPI were improved, thus advocating the use of a core stabilisation training program among collegiate athletes to enhance their upper extremity performance.

PMID:36458387

Ecology. 2022 Dec 1:e3934. doi: 10.1002/ecy.3934. Online ahead of print.

ABSTRACT

Open-population spatial capture-recapture (OPSCR) models use the spatial information contained in individual detections collected over multiple consecutive occasions to estimate occasion-specific density, but also demographic parameters. OPSCR models can also estimate spatial variation in vital rates, but such models are neither widely used nor thoroughly tested. We developed a Bayesian OSPCR model that not only accounts for spatial variation in survival using spatial covariates, but also estimates local density-dependent effects on survival within a unified framework. Using simulations, we show that OPSCR models provide sound inferences on the effect of spatial covariates on survival, including multiple competing sources of mortality, each with potentially different spatial determinants. Estimation of local density-dependent survival was possible but required more data due to the greater complexity of the model. Not accounting for spatial heterogeneity in survival led to up to 10% positive bias in abundance estimates. We provide an empirical demonstration of the model by estimating the effect of country and density on cause-specific mortality of female wolverines (Gulo gulo) in central Sweden and Norway. The ability to make population-level inferences of spatial variation in survival is an essential step towards a fully spatially-explicit OPSCR model that can disentangle the role of multiple spatial drivers on population dynamics. This article is protected by copyright. All rights reserved.

PMID:36458376 | DOI:10.1002/ecy.3934

Ultrasonography. 2022 Jul 19. doi: 10.14366/usg.22082. Online ahead of print.

ABSTRACT

PURPOSE: Although the taller-than-wide (TTW) sign has been regarded as one of the most specific ultrasound (US) features of thyroid malignancy, uncertainty still exists regarding the US probe’s orientation when evaluating it. This study investigated which US plane would be optimal to identify the TTW sign based on malignancy risk stratification using a registry-based imaging dataset.

METHODS: A previous study by 17 academic radiologists retrospectively analyzed the US images of 5,601 thyroid nodules (≥1 cm, 1,089 malignant and 4,512 benign) collected in the webbased registry of Thyroid Imaging Network of Korea through the collaboration of 26 centers. The present study assessed the diagnostic performance of the TTW sign itself and fine needle aspiration (FNA) indications via a comparison of four international guidelines, depending on the orientation of the US probe (criterion 1, transverse plane; criterion 2, either transverse or longitudinal plane).

RESULTS: Overall, the TTW sign was more frequent in malignant than in benign thyroid nodules (25.3% vs. 4.6%). However, the statistical differences between criteria 1 and 2 were negligible for sensitivity, specificity, and area under the curve (AUC) based on the size effect (all P<0.05, Cohen’s d=0.19, 0.10, and 0.07, respectively). Moreover, the sensitivity, specificity, and AUC of the four FNA guidelines were similar between criteria 1 and 2 (all P>0.05, respectively).

CONCLUSION: A longitudinal US probe orientation provided little additional diagnostic value over the transverse orientation in detecting the TTW sign of thyroid nodules.

PMID:36458371 | DOI:10.14366/usg.22082

Proc Inst Mech Eng H. 2022 Dec 1:9544119221139593. doi: 10.1177/09544119221139593. Online ahead of print.

ABSTRACT

Prostheses control using electromyography signals have shown promising aspects in various fields including rehabilitation sciences and assistive technology controlled devices. Pattern recognition and machine learning methods have been observed to play a significant role in evaluating features and classifying different limb motions for enhanced prosthetic executions. This paper proposes feature extraction and evaluation method using intramuscular electromyography (iEMG) signals at different arm positions and hand postures based on the RES Index value statistical criterion method. Sixteen-time domain features were selected for the study at two main circumstances; fixed arm position (FAP) and fixed hand posture (FHP). Eight healthy male participants (30.62 ± 3.87 years) were asked to execute five motion classes including hand grip, hand open, rest, hand extension, and hand flexion at four different arm positions that comprise of 0°, 45°, 90°, and 135°. The classification process is accomplished via the application of the k-nearest neighbor (KNN) classifier. Then RES index was calculated to investigate the optimal features based on the proposed statistical criterion method. From the RES Index, we concluded that Variance (VAR) is the best feature while WAMP, Zero Crossing (ZC), and Slope Sign Change (SSC) are the worst ones in FAP conditions. On the contrary, we concluded that Average Amplitude Change (AAC) is the best feature while WAMP and Simple Square Integral (SSI) resulted in least RES Index values for FHP conditions. The proposed study has possible iEMG based applications such as assistive control devices, robotics. Also, working with the frequency domain features encapsulates the future scope of the study.

PMID:36458327 | DOI:10.1177/09544119221139593

Heliyon. 2022 Nov 18;8(11):e11672. doi: 10.1016/j.heliyon.2022.e11672. eCollection 2022 Nov.

ABSTRACT

The aim of this research is to examine the trend of water use efficiency (WUE) and the spillover effect of its determinants in 28 sub-Saharan Africa (SSA) countries over the period 2007 to 2018 using the directional distance function (DDF) and the spatial Durbin model. Results of the DDF revealed that the most efficient countries include Botswana, and Liberia whereas countries with poor performance include Niger and South Africa. Also, the average efficiency scores over the study period improved steadily from 0.582 in 2007 to 0.698 in 2018. The study showed that under economic distance weight in the spatial Durbin model, the values of the spatial lag coefficients of urbanisation (URB), export (EX), and education (EDU) depict positive and statistically significant effects on WUE, while industrial activities (IND), foreign direct investment (FDI), and government interference (COR) had an adverse influence on WUE in SSA. Results of the spatial decomposition effect of URB demonstrated a major impact on WUE in both the local and adjacent countries. However, a significant decline of WUE through the direct and indirect impacts of FDI, EX, and COR in the local and neighboring countries was recorded which indicate the presence of a negative spatial dependency on WUE in SSA. The outcome of this study implies that policymakers in SSA countries must strengthen sustainable water resources management decisions with neighbouring countries to achieve sustainable development goal 6 by 2030 and beyond.

PMID:36458314 | PMC:PMC9706135 | DOI:10.1016/j.heliyon.2022.e11672

Heliyon. 2022 Nov 23;8(11):e11862. doi: 10.1016/j.heliyon.2022.e11862. eCollection 2022 Nov.

ABSTRACT

Cryptocurrency is an advanced digital currency that is secured by encryption, making it nearly impossible to forge or duplicate. Many cryptocurrencies are blockchain-based with decentralized networks. The prediction of cryptocurrency prices is a very difficult task because of the absence of an appropriate analytical basis to substantiate their claims. Cryptocurrencies are also dependent on several variables, such as technical advancement, internal competition, market pressure, economic concerns, security, and political considerations. This paper proposed the hybrid walk-forward ensemble optimization technique and applied it to predict the daily prices of fifteen cryptocurrencies, such as Cardano (ADA-USD), Bitcoin (BTC-USD), Dogecoin (DOGE-USD), Ethereum Classic (ETC-USD), Chainlink (LINK-USD), Litecoin (LTC-USD), NEO (NEO-USD), Tron (TRX-USD), Tether (USDT-USD), NEM (XEM-USD), Stellar (XLM-USD), Ripple (XRP-USD), and Tezos (XTZ-USD). A performance comparison of these cryptocurrencies was done using classical statistical models, machine learning algorithms, and deep learning algorithms on different cryptocurrency time series. Simulation results show that our proposed model performed better in terms of cryptocurrency prediction accuracy compared to the classical statistical model and machine and deep learning algorithms used in this paper.

PMID:36458312 | PMC:PMC9706710 | DOI:10.1016/j.heliyon.2022.e11862