Category: Nevin Manimala

Med Phys. 2022 Jan 30. doi: 10.1002/mp.15506. Online ahead of print.

ABSTRACT

PURPOSE: Magnetic resonance (MR) imaging is the gold standard in image-guided brachytherapy (IGBT) due to its superior soft-tissue contrast for target and organ-at-risk (OARs) delineation. Accurate and fast segmentation of MR images are very important for high-quality IGBT treatment planning. The purpose of this work is to implement and evaluate deep learning models for the automatic segmentation of targets and OARs in MR image-based high-dose-rate (HDR) brachytherapy for cervical cancer.

METHODS: A 2D deep learning (DL) model using residual neural network architecture (ResNet50) was developed to contour the targets (GTV, HR CTV, and IR CTV) and OARs (bladder, rectum, sigmoid, and small intestine) automatically on axial MR slices of HDR brachytherapy patients. Furthermore, two additional 2D DL models using sagittal and coronal images were also developed. A 2.5D model was generated by combining the outputs from axial, sagittal, and coronal DL models. Similarly, a 2D and 2.5D DL models were also generated for the inception residual neural network (InceptionResNetv2 (InRN)) architecture. The geometric (dice similarity coefficient (DSCs), 95^th percentile of Hausdorff distance (HD)) and dosimetric accuracy of 2D (axial only) and 2.5D (axial + sagittal + coronal) DL model generated contours were calculated and compared.

RESULTS: The mean (range) DSCs of ResNet50 across all contours were 0.674 (0.05-0.96) and 0.715 (0.26-0.96) for the 2D and 2.5D models, respectively. For InRN, these were 0.676 (0.11-0.96) and 0.723 (0.35-0.97) for the 2D and 2.5D models, respectively. The mean HD of ResNet50 across all contours was 15.6 mm (1.8-69 mm) and 12.1 mm (1.7-44 mm) for the 2D and 2.5D models, respectively. The similar results for InRN were 15.4 mm (2-68 mm) and 10.3 mm (2.7-39 mm) for the 2D and 2.5D models, respectively. The dosimetric parameters (D90) of GTV and HR CTV for manually contoured plans matched better with the 2.5D model (P > 0.6) and the results from the 2D model were slightly lower (P < 0.08). On the other hand, the IR CTV doses (D90) for all of the models were slightly lower (2D: -1.3 to -1.5 Gy and 2.5D: -0.5 to -0.6 Gy) and the differences were statistically significant for the 2D model (2D: P < 0.000002 and 2.5D: P > 0.06). In case of OARs, the 2.5D model segmentations resulted in closer dosimetry than 2D models (2D: P = 0.07-0.91 and 2.5D: P = 0.16-1.0).

CONCLUSIONS: The 2.5D deep learning models outperformed their respective 2D models for the automatic contouring of targets and OARs in MR image-based high-dose-rate (HDR) brachytherapy for cervical cancer. The InceptionResNetv2 model performed slightly better than ResNet50. This article is protected by copyright. All rights reserved.

PMID:35094405 | DOI:10.1002/mp.15506

Nurs Forum. 2022 Jan 30. doi: 10.1111/nuf.12698. Online ahead of print.

ABSTRACT

BACKGROUND: It is crucial to evaluate student academic motivation and self-directed learning (SDL) readiness while teaching online or flexibly. During the coronavirus disease 2019 epidemic, there were few investigations on the link between academic motivation and SDL readiness.

AIM: This study investigated the connection between academic motivation and SDL readiness and the three academic motivation domains’ predictive features.

METHODS: This cross-sectional study used convenience sampling to recruit 1187 nursing students from four nursing colleges in three countries. We utilized the Academic Motivation Scale College Version and Self-directed Learning Readiness Scale for Nurse Education to collect data. Descriptive and inferential statistics were employed to analyze the data.

RESULTS: Extrinsic motivation received the highest mean. Most nursing students exhibited SDL readiness, whereas “desire for learning” was rated the highest dimension of SDL readiness. We found significant differences in nursing students’ intrinsic and extrinsic motivation and amotivation between the three countries. Finally, country, gender, and intrinsic motivation were significant predictors of the nursing students’ SDL readiness.

CONCLUSION: Among Filipino, Saudi, and Thai nursing students, their SDL readiness is influenced by the intrinsic motivation domain. Therefore, nursing students with higher levels of intrinsic motivation are proactive learners for SDL.

PMID:35094399 | DOI:10.1111/nuf.12698

Urol J. 2022 Jan 30. doi: 10.22037/uj.v19i.7039. Online ahead of print.

ABSTRACT

PURPOSE: To compare two methods of laparoscopic sacrocolpopexy (LSCP) and sacrospinous ligament fixation (SSLF) in terms of efficacy and safety in the treatment of vaginal apical prolapse. Materials and Methods This prospective, randomized controlled clinical trial was conducted on 32 patients with symptomatic vaginal apical prolapse, referred to the female urology clinic of …, during 2018-2019. The patients were re-examined at 12 months after surgery. Objective success was recorded using Pelvic Organ Prolapse Quantification (POP-Q) classification as primary outcome. The subjective success of the methods was determined with the quality-of-life parameters, based on Pelvic Floor Impact Questionnaire (PFIQ-7), Pelvic Floor Distress Inventory (PFDI-20), and Organ Prolapse/Urinary Incontinence Sexual Questionnaire (PISQ-12) scores as secondary outcome. Moreover, complications were recorded in both groups.

RESULTS: The amount of intraoperative bleeding was significantly higher in the SSLF group, compared to the LSCP group (P=0.01). Persistent pain was observed in two (12%) patients in the LSCP group and five (31%) patients in the SSLF group (P=0.2). The decrease in the total PFIQ-7 score was in favor of the LSCP group but not statistically significant (p= 0.06). The LSCP group showed bigger improvement in vaginal (p=0.04) and bowel (p=0.03) scores. The results of the PISQ-12 and PFDI-20 questionnaires as well as POP-Q examination were not different in two groups.

CONCLUSION: Although the surgical methods of LSCP and SSLF can be equally effective in the treatment of apical prolapse, LSCP appears to be superior to SSLF regarding less bleeding.

PMID:35094377 | DOI:10.22037/uj.v19i.7039

Br J Math Stat Psychol. 2022 Jan 30. doi: 10.1111/bmsp.12263. Online ahead of print.

ABSTRACT

Cochran’s Q statistic is routinely used for testing heterogeneity in meta-analysis. Its expected value is also used in several popular estimators of the between-study variance, ${\tau }^2$ . Those applications generally have not considered the implications of its use of estimated variances in the inverse-variance weights. Importantly, those weights make approximating the distribution of Q (more explicitly, $Q_{\text{IV}}$ ) rather complicated. As an alternative, we investigate a new Q statistic, $Q_F$ , whose constant weights use only the studies’ effective sample sizes. For the standardized mean difference as the measure of effect, we study, by simulation, approximations to distributions of $Q_{\text{IV}}$ and $Q_F$ , as the basis for tests of heterogeneity and for new point and interval estimators of ${\tau }^2$ . These include new DerSimonian-Kacker-type moment estimators based on the first moment of $Q_F$ , and novel median-unbiased estimators. The results show that: an approximation based on an algorithm of Farebrother follows both the null and the alternative distributions of $Q_F$ reasonably well, whereas the usual chi-squared approximation for the null distribution of $Q_{\text{IV}}$ and the Biggerstaff-Jackson approximation to its alternative distribution are poor; in estimating ${\tau }^2$ , our moment estimator based on $Q_F$ is almost unbiased, the Mandel – Paule estimator has some negative bias in some situations, and the DerSimonian-Laird and restricted maximum likelihood estimators have considerable negative bias; and all 95% interval estimators have coverage that is too high when ${\tau }^2=0$ , but otherwise the Q-profile interval performs very well.

PMID:35094381 | DOI:10.1111/bmsp.12263

Ther Innov Regul Sci. 2022 Jan 30. doi: 10.1007/s43441-021-00368-8. Online ahead of print.

ABSTRACT

BACKGROUND: In recent years, population pharmacokinetics (PK) has been widely used in neonatal pharmacology. However, the sample size selection for neonatal PK studies has been highly variable and without clear consensus, especially for drugs with large individual variability. Therefore, this study’s objective was to investigate the optimal sample size for use in neonatal PK studies.

METHODS: A comprehensive and reliable population PK model (1631 neonates) of vancomycin was selected as a reference model. The original sparse PK dataset was divided into several sub-datasets according to different sample sizes. NONMEM was used for sub-datasets PK analysis. Statistical powers were calculated to evaluate different sample sizes (> 80% was expected).

RESULTS: During population clearance estimations, the average power was 40%, 85%, 100%, and 100% for sample sizes of 10, 25, 50, and 100 neonates, respectively. And the frequency of model-estimated median clearance values within ± 10% (relative errors) of target value (0.057 L/h) were 75.0%, 68.8%, 57.8%, and 35.0%, respectively. Regarding age sub-groups (postmenstrual age (PMA) < or ≥ 37 weeks) clearance estimation, a sample size of 50 was better to complete the assessment of the neonatal age sub-group even in some cases of unbalanced age distribution.

CONCLUSION: A sample size of 25 neonates provided a consistent estimation of the overall population (PMA: 23.3-52.4 weeks) clearance for a drug with high individual variability using a sparse PK sampling design. A sample size of 50 was recommended to complete neonatal age sub-group assessments.

PMID:35094368 | DOI:10.1007/s43441-021-00368-8

Daru. 2022 Jan 30. doi: 10.1007/s40199-021-00423-7. Online ahead of print.

ABSTRACT

OBJECTIVES: There are a multitude of different modelling techniques that have been used for inhaled drugs. The main objective of this review was to conduct an exhaustive survey of published mathematical models in the area of asthma and chronic obstructive pulmonary disease (COPD) for inhalation drugs. Additionally, this review will attempt to assess the applicability of these models to assess bioequivalence (BE) of orally inhaled products (OIPs).

EVIDENCE ACQUISITION: PubMed, Science Direct, Web of Science, and Scopus databases were searched from 1996 to 2020, to find studies that described mathematical models used for inhaled drugs in asthma/COPD.

RESULTS: 50 articles were finally included in this systematic review. This research identified 22 articles on in silico aerosol deposition models, 20 articles related to population pharmacokinetics and 8 articles on physiologically based pharmacokinetic modelling (PBPK) modelling for inhaled drugs in asthma/COPD. Among all the aerosol deposition models, computational fluid dynamics (CFD) simulations are more likely to predict regional aerosol deposition pattern in human respiratory tracts. Across the population PK articles, body weight, gender, age and smoking status were the most common covariates that were found to be significant. Further, limited published PBPK models reported approximately 29 parameters relevant for absorption and distribution of inhaled drugs. The strengths and weaknesses of each modelling technique has also been reviewed.

CONCLUSION: Overall, while there are different modelling techniques that have been used for inhaled drugs in asthma and COPD, there is very limited application of these models for assessment of bioequivalence of OIPs. This review also provides a ready reference of various parameters that have been considered in various models which will aid in evaluation if one model or hybrid in silico models need to be considered when assessing bioequivalence of OIPs.

PMID:35094370 | DOI:10.1007/s40199-021-00423-7

Updates Surg. 2022 Jan 30. doi: 10.1007/s13304-021-01201-5. Online ahead of print.

ABSTRACT

Metabolic surgery has become a powerful treatment for obese type 2 diabetes (T2DM). Experts have been devoting to the research of metabolic surgery in the treatment of T2DM. The debate continues, and there is no comprehensive statistical and intuitive analysis for it. To explore the current research status, the latest hotspots and the changing trend in this field, we conducted a bibliometric analysis. This paper made a bibliometric analysis based on the data source from Science Core Collection Network (WoSCC). Vosviewer v.1.6.10 software is used to construct a knowledge map. From 2011 to 2020, 1424 peer-reviewed papers on metabolic surgery for T2DM were retrieved. The United States contributed the most publications and gained global impact with the most citations. Obesity Surgery was the most prolific journal in this field. Prof. Schauer Philip R., Prof. Buchwald H. and Prof. Sjostrom L. were the most renowned experts in this aspect. The top cited references discussed the status of metabolic surgery for the treatment of T2DM worldwide and the importance of regular evaluation. The extracted keywords mainly formed three clusters: (1) research on the selection of different metabolic surgery methods; (2) possible mechanisms; (3) improvement of T2DM complications by metabolic surgery. Our study makes a comprehensive and objective analysis of metabolic surgery in obese patients with T2DM, providing valuable information for further clinical application and related scientific research. Researchers can quickly locate research hotspots in a large number of relevant literature.

PMID:35094308 | DOI:10.1007/s13304-021-01201-5

Endocrine. 2022 Jan 30. doi: 10.1007/s12020-021-02975-9. Online ahead of print.

ABSTRACT

PURPOSE: Achieving preoperative euthyroidism in patients with hyperthyroidism for whom antithyroid drugs (ATDs) cannot be used for treatment is a serious clinical problem. We aimed to evaluate the effectiveness of therapeutic plasma exchange (TPE) in hyperthyroid patients scheduled for surgery and predictive factors for a high number of TPE sessions.

METHODS: We retrospectively analyzed the data of 21 patients with hyperthyroidism who were treated with TPE for preoperative euthyroidism in our institution. Pre- and post-TPE thyroid function tests were compared to assess efficacy. Binary logistic regression analysis was applied to determine predictors of patients requiring a high number of TPE sessions.

RESULTS: All patients (20 patients with Graves’ disease and 1 patient with toxic multinodular goiter; 12 women and 9 men; mean age 35.71 ± 12.38 years) had severe hyperthyroidism before TPE. The changes before and after TPE in fT3, fT4, and TSH levels were statistically significant (p < 0.001, p < 0.001, p = 0.002, respectively). The median number of TPE sessions was 8 (range: 1-24). Levels of fT3 before TPE were significantly higher in patients for whom higher numbers of TPE sessions were required (≥8) (OR: 1.427, 95% CI: 1.038-1.961, p = 0.028). Receiver operating characteristic curve analysis revealed an optimum cut-off value of 12.8 pg/ml for fT3 before TPE (91% sensitivity, 80% specificity, area under the curve: 0.927).

CONCLUSION: TPE should be considered as an effective alternative treatment option that can be used to rapidly achieve euthyroidism before surgery when ATDs cannot be used. Pre-TPE fT3 levels of >12.8 pg/ml may be an independent factor predicting the need for higher numbers of TPE sessions (≥8).

PMID:35094312 | DOI:10.1007/s12020-021-02975-9

Dermatol Ther (Heidelb). 2022 Jan 29. doi: 10.1007/s13555-022-00682-5. Online ahead of print.

ABSTRACT

INTRODUCTION: Notwithstanding their numerous advantages, biological treatments have many limitations when treating patients with psoriasis (PsO) and hepatitis B (HB). Clinicians need to pay careful attention to the issue of hepatitis B virus (HBV) reactivation.

METHODS: In accordance with the PRISMA guidelines, we systematically searched Pubmed, Scopus, Embase, Cochrane Library, and Web of Science databases for observational studies on the topic of HBV reactivation among patients with PsO and HB treated with biologics. The random-effects model was used to pool the reactivation rate by the Freeman-Tukey double arcsine transformation method. We selected Fisher’s exact test to compare multiple rates. To determine the sources of heterogeneity, sensitivity analysis and meta-regression were performed.

RESULTS: Ten studies with a total of 238 subjects that met the inclusion criteria were included. The pooled reactivation rate was 1.8% [95% confidence interval (CI) 0.0-5.6%] in patients with PsO and HB. Among them, the viral reactivation rates of HBsAg-positive and HBsAg-negative patients were 4.1% (95% CI 0.0-17.9%) and 0.2% (95% CI 0.0-2.8%). The difference between HBsAg-positive and HBsAg-negative patients was statistically significant (p = 0.002). The viral reactivation rate of individuals who needed antiviral prophylaxis but did not receive it was 26.6% (95% CI 5.8-53.5%), while it decreased to 0.0% (95% CI 0.0-6.6%) after accepting antiviral treatment. The two-sided Fisher’s test exact values between different durations of biological therapy showed no statistical significance (p = 0.104).

CONCLUSIONS: Without antiviral prophylaxis, HBsAg-positive patients with psoriasis are at high risk of virus reactivation when treated with biological agents. Early and sufficient antiviral prophylaxis will effectively reduce the risk of HBV reactivation and serious complications in HBsAg-positive patients. Prolonging the duration of biological treatment will not increase the risk of reactivation.

PMID:35094295 | DOI:10.1007/s13555-022-00682-5

Environ Sci Pollut Res Int. 2022 Jan 30. doi: 10.1007/s11356-021-18210-x. Online ahead of print.

ABSTRACT

Climate change continues to pose a threat to the agricultural sectors worldwide, jeopardizing food and nutritional security, which is a critical component of the sustainable development agenda. Consequently, this study attempts to examine the impact of climatic variables (CO₂ emissions, energy resources, rainfall, temperature, fossil fuel consumption, and humidity) on agricultural production of rice, cereals, vegetables, coffee, and agriculture value added (as a percentage of GDP) in the Malaysian context. To this end, this study applied a generalized method of moments (GMM) estimator on the data obtained from the metrological station Malaysia, Department of Statistics Malaysia and World Development Indicators (WDI) spanning the period 1985-2016. The results revealed that temperature and energy consumption negatively and significantly affect rice and vegetable production, while the negative effect of rainfall, temperature, fossil fuel consumption, and humidity on cereal production is insignificant. The results also confirmed that CO₂ emissions have a negative and significant impact on coffee production. Likewise, temperature, energy consumption, and fossil fuel consumption exhibit a negative and significant influence on agriculture value added. These observations evidenced the adverse effect of climate change on various agricultural products in Malaysia. Therefore, in order to ensure robust and sustainable agricultural output in Malaysia, policymakers as well as environmentalists should work together to formulate appropriate adaptation strategies.

PMID:35094275 | DOI:10.1007/s11356-021-18210-x