Tag: statistics

Diabetes Metab Syndr. 2021 Sep 11;15(6):102280. doi: 10.1016/j.dsx.2021.102280. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Reproductive-aged women are prone to type 2 diabetes mellitus. This study aims to evaluate the optimal cut off point of Triglyceride/Glucose Index for predicting glucose status conversion among women of reproductive age.

METHODS: This study involved normoglycemic and prediabetes women aged 20-49 years from the Bogor Non-Communicable Diseases Cohort Study (West Java, Indonesia) conducted from 2011 to 2016. Statistical analysis was performed using Receiver Operating Characteristics curve analysis with STATA version 15.

RESULTS: Among prediabetes subjects (n = 371), the cut-off point of TyG index for regression from prediabetes to normoglycemic subjects was <4.51 [sensitivity, specificity, AUC (95%CI) 83.9%, 80.1%, 0.913 (0.875-0.943), respectively] and the cut-off point for progression from prediabetes to diabetes was >4.54 [80.0%, 73.1%, 0.858 (0.807-0.900)]. Among normoglycemic subjects (n = 1300), the cut-off point of TyG index for progression to prediabetes and diabetes were >4.44 [80.1%, 71.1%, 0.834 (0.812-0.854)] and >4.47 [80.6%, 80.8%, 0.909 (0.890-0.926)] respectively.

CONCLUSION: Based on sample of subjects evaluated between 2011 and 2016, TyG index appears to be a promising marker for glucose status conversion among reproductive-aged women in Jakarta, Indonesia.

PMID:34562866 | DOI:10.1016/j.dsx.2021.102280

Clin Imaging. 2021 Sep 21;80:454-458. doi: 10.1016/j.clinimag.2021.09.003. Online ahead of print.

ABSTRACT

PURPOSE: Prostate volume and PSA density (PSAd) are important in the risk stratification of suspected prostate cancer (Pca). PI-RADS v2.1 allows for determining volume via segmentation or ellipsoid calculation. The purpose of our study was to compare ellipsoid and segmentation volume calculation methods and evaluate if PSAd diagnostic performance is altered.

METHODS: We retrospectively assessed 397 patients (mean age/standard deviation: 63.7/7.4 years) who underwent MRI and prostate biopsy or prostatectomy, with Pca classified by Gleason ≥3 + 4 and ≥4 + 4 disease. Prostate total volumes were determined with ellipsoid calculations (TVe) and with semi-automated segmentation (TVs), along with inter-rater reliability with intraclass correlation coefficient (ICC). PSAd was calculated for TVe and TVs and ROC curves were created to compare performance for Gleason ≥3 + 4 and ≥4 + 4 disease.

RESULTS: TVe was significantly higher than TVs (p < 0.0001), with mean TVe = 55.4 mL and TVs = 51.0 mL. ROC area under the curve for PSAd derived with TVe (0.63, 95%CI:0.59-0.68) and TVs (0.64, 95%CI:0.59-0.68) showed no significant difference for Gleason ≥3 + 4 disease (p = 0.45), but PSAd derived with TVs (0.63, 95%CI: 0.58-0.68) significantly outperformed TVe (0.61, 95%CI: 0.57-0.67) for Gleason ≥4 + 4 disease (p = 0.02). Both methods demonstrated excellent inter-rater reliability with TVe with ICC of 0.93(95%CI: 0.92-0.94) and TVs with ICC of 0.98(95%CI: 0.98-0.99).

CONCLUSION: Traditional ellipsoid measurements tend to overestimate total prostate volume compared to segmentation, but both methods demonstrate similar diagnostic performance of derived PSA density for PI-RADS clinically significant disease. For higher grade disease, PSAd derived from segmentation volumes demonstrates statistically significant superior performance. Both methods are viable, but segmentation volume is potentially better.

PMID:34562834 | DOI:10.1016/j.clinimag.2021.09.003

J Mol Graph Model. 2021 Sep 18;109:108022. doi: 10.1016/j.jmgm.2021.108022. Online ahead of print.

ABSTRACT

Targeting Polo-like kinase 1 (Plk1) by molecular inhibitors is being a promising approach for tumor therapy. Nevertheless, insufficient methodical analyses have been done to characterize the interactions inside the Plk1 binding pocket. In this study, an extensive combined ligand and structure-based drug design workflow was conducted to data-mine the structural requirements for Plk1 inhibition. Consequently, the binding modes of 368 previously known Plk1 inhibitors were investigated by pharmacophore generation technique. The resulted pharmacophores were engaged in the context of Genetic function algorithm (GFA) and Multiple linear regression (MLR) analyses to search for a prognostic QSAR model. The most successful QSAR model was with statistical criteria of (r²₂₇₇ = 0.76, r²adj = 0.76, r²pred = 0.75, Q² = 0.73). Our QSAR-selected pharmacophores were validated by Receiver Operating Characteristic (ROC) curve analysis. Later on, the best QSAR model and its associated pharmacophoric hypotheses (HypoB-T4-5, HypoI-T2-7, HypoD-T4-3, and HypoC-T3-3) were used to identify new Plk1 inhibitory hits retrieved from the National Cancer Institute (NCI) database. The most potent hits exhibited experimental anti-Plk1 IC₅₀ of 1.49, 3.79. 5.26 and 6.35 μM. Noticeably, our hits, were found to interact with the Plk1 kinase domain through some important amino acid residues namely, Cys67, Lys82, Cys133, Phe183, and Asp194.

PMID:34562852 | DOI:10.1016/j.jmgm.2021.108022

Schizophr Res. 2021 Sep 22;238:10-19. doi: 10.1016/j.schres.2021.08.026. Online ahead of print.

ABSTRACT

Nonlinear dynamical analysis has been used to quantify the complexity of brain signal at temporal scales. Power law scaling is a well-validated method in physics that has been used to describe the dynamics of a system in the frequency domain, ranging from noisy oscillation to complex fluctuations. In this research, we investigated the power-law characteristics in a large-scale resting-state fMRI data of schizophrenia and healthy participants derived from Taiwan Aging and Mental Illness cohort. We extracted the power spectral density (PSD) of resting signal by Fourier transform. Power law scaling of PSD was estimated by determining the slope of the regression line fitting to the logarithm of PSD. t-Test was used to assess the statistical difference in power law scaling between schizophrenia and healthy participants. The significant differences in power law scaling were found in six brain regions. Schizophrenia patients have significantly more positive power law scaling (i.e., more homogenous frequency components) at four brain regions: left precuneus, left medial dorsal nucleus, right inferior frontal gyrus, and right middle temporal gyrus and less positive power law scaling (i.e., more dominant at lower frequency range) in bilateral putamen compared with healthy participants. Moreover, significant correlations of power law scaling with the severity of psychosis were found. These findings suggest that schizophrenia has abnormal brain signal complexity linked to psychotic symptoms. The power law scaling represents the dynamical properties of resting-state fMRI signal may serve as a novel functional brain imaging marker for evaluating patients with mental illness.

PMID:34562833 | DOI:10.1016/j.schres.2021.08.026

Neural Netw. 2021 Sep 9;144:394-406. doi: 10.1016/j.neunet.2021.09.005. Online ahead of print.

ABSTRACT

Uncertainty evaluation is a core technique when deep neural networks (DNNs) are used in real-world problems. In practical applications, we often encounter unexpected samples that have not seen in the training process. Not only achieving the high-prediction accuracy but also detecting uncertain data is significant for safety-critical systems. In statistics and machine learning, Bayesian inference has been exploited for uncertainty evaluation. The Bayesian neural networks (BNNs) have recently attracted considerable attention in this context, as the DNN trained using dropout is interpreted as a Bayesian method. Based on this interpretation, several methods to calculate the Bayes predictive distribution for DNNs have been developed. Though the Monte-Carlo method called MC dropout is a popular method for uncertainty evaluation, it requires a number of repeated feed-forward calculations of DNNs with randomly sampled weight parameters. To overcome the computational issue, we propose a sampling-free method to evaluate uncertainty. Our method converts a neural network trained using dropout to the corresponding Bayesian neural network with variance propagation. Our method is available not only to feed-forward NNs but also to recurrent NNs such as LSTM. We report the computational efficiency and statistical reliability of our method in numerical experiments of language modeling using RNNs, and the out-of-distribution detection with DNNs.

PMID:34562813 | DOI:10.1016/j.neunet.2021.09.005

J Natl Black Nurses Assoc. 2021 Sep;32(1):35-40.

ABSTRACT

Nurses experience high levels of stress. In this study, functional social support and perceived stress of nurses working in secular and religious hospitals were examined. The social support model, the job demands-resources theory, and the transactional model of stress guided this study. The population that was examined was comprised of a convenience and snowballing sample of 84 registered nurses from across the United States. The data collected using the Expanded Nursing Stress Scale, the Inventory of Socially Supportive Behavior survey, and a demographic questionnaire were statistically analyzed using Pearson’s correlation and Fisher’s Test. Results showed no significant relationship between support and nurses’ stress in secular hospitals and no significant relationship between the same variables for nurses’ in religious hospitals. Findings also revealed that there was no significant difference in the compared correlations for nurses’ support and stress between the two groups. The outcomes will inform healthcare professionals about the association between nurses’ support and stress in hospitals with unique missions.

PMID:34562351

J Paediatr Child Health. 2021 Sep 25. doi: 10.1111/jpc.15748. Online ahead of print.

ABSTRACT

AIM: We aimed to investigate the influenza immunisation status of caregivers and household contacts of children with congenital heart disease (CHD) and potential barriers to vaccine uptake.

METHODS: Prospective questionnaire-based survey over two influenza seasons (2019-2020 and 2020-2021) on 161 children with CHD attending a tertiary paediatric cardiology clinic and their families. Logistic regression and factor analysis were performed to identify factors associated with influenza vaccine uptake.

RESULTS: Influenza vaccination coverage of children was 65%, whereas that of their fathers and mothers was 34% and 26%, respectively. Children with unvaccinated siblings represented 43% and those with unvaccinated adults in the household 79% of our study population. No statistically significant differences were found before and during COVID-19 pandemic on vaccine uptake. Logistic regression analysis showed that higher education level, understanding the risk of contracting the disease and vaccination status of the child determined the vaccination status of parents, regardless of their age, age of their child, severity of CHD, beliefs about vaccine safety and efficacy and risk of transmission if not vaccinated. Factor analysis revealed distinct groups among unvaccinated parents (76.3% of the variation in the responses).

CONCLUSIONS: Vaccination coverage of caregivers and household contacts of children with CHD is suboptimal. Influenza vaccination campaigns should take into consideration the specific characteristics of parental groups and target interventions accordingly to increase their vaccine uptake and indirectly protect children with CHD.

PMID:34562323 | DOI:10.1111/jpc.15748

CPT Pharmacometrics Syst Pharmacol. 2021 Sep 25. doi: 10.1002/psp4.12714. Online ahead of print.

ABSTRACT

Metaheuristics is a powerful optimization tool that is increasingly used across disciplines to tackle general purpose optimization problems. Nature-inspired metaheuristic algorithms is a subclass of metaheuristic algorithms and have been shown to be particularly flexible and useful in solving complicated optimization problems in computer science and engineering. A common practice with metaheuristics is to hybridize it with another suitably chosen algorithm for enhanced performance. This paper reviews metaheruristic algorithms and demonstrates some of its utility in tackling pharmacometric problems. Specifically, we provide three applications using one of its most celebrated members, particle swarm optimization (PSO), and show that PSO can effectively estimate parameters in complicated nonlinear mixed-effects models and to gain insights into statistical identifiability issues in a complex compartment model. In the third application, we demonstrate how to hybridize PSO with sparse grid, which is an often used technique to evaluate high dimensional integrals, to search for D-efficient designs for estimating parameters in nonlinear mixed-effects models with a count outcome. We also show the proposed hybrid algorithm outperforms its competitors when sparse grid is replaced by its competitor, adaptive gaussian quadrature to approximate the integral, or when PSO is replaced by three notable nature-inspired metaheuristic algorithms.

PMID:34562342 | DOI:10.1002/psp4.12714

J Appl Clin Med Phys. 2021 Sep 25. doi: 10.1002/acm2.13427. Online ahead of print.

ABSTRACT

PURPOSE: To demonstrate fast treatment planning feasibility of stereotactic body radiation therapy (SBRT) for centrally located lung tumors on Halcyon Linac via a previously validated knowledge-based planning (KBP) model to support offline adaptive radiotherapy.

MATERIALS/METHODS: Twenty previously treated non-coplanar volumetric-modulated arc therapy (VMAT) lung SBRT plans (c-Truebeam) on SBRT-dedicated C-arm Truebeam Linac were selected. Patients received 50 Gy in five fractions. c-Truebeam plans were re-optimized for Halcyon manually (m-Halcyon) and with KBP model (k-Halcyon). Both m-Halcyon and k-Halcyon plans were normalized for identical or better target coverage than clinical c-Truebeam plans and compared for target conformity, dose heterogeneity, dose fall-off, and dose tolerances to the organs-at-risk (OAR). Treatment delivery parameters and planning times were evaluated.

RESULTS: k-Halcyon plans were dosimetrically similar or better than m-Halcyon and c-Truebeam plans. k-Halcyon and m-Halcyon plan comparisons are presented with respect to c-Truebeam. Differences in conformity index were statistically insignificant in k-Halcyon and on average 0.02 higher (p = 0.04) in m-Halcyon plans. Gradient index was on average 0.43 (p = 0.006) lower and 0.27 (p = 0.02) higher for k-Halcyon and m-Halcyon, respectively. Maximal dose 2 cm away in any direction from target was statistically insignificant. k-Halcyon increased maximal target dose on average by 2.9 Gy (p < 0.001). Mean lung dose was on average reduced by 0.10 Gy (p = 0.004) in k-Halcyon and increased by 0.14 Gy (p < 0.001) in m-Halcyon plans. k-Halcyon plans lowered bronchial tree dose on average by 1.2 Gy. Beam-on-time (BOT) was increased by 2.85 and 1.67 min, on average for k-Halcyon and m-Halcyon, respectively. k-Halcyon plans were generated in under 30 min compared to estimated dedicated 180 ± 30 min for m-Halcyon or c-Truebeam plan.

CONCLUSION: k-Halcyon plans were generated in under 30 min with excellent plan quality. This adaptable KBP model supports high-volume clinics in the expansion or transfer of lung SBRT patients to Halcyon.

PMID:34562308 | DOI:10.1002/acm2.13427

Clin Exp Immunol. 2021 Sep 25. doi: 10.1111/cei.13665. Online ahead of print.

ABSTRACT

This large cohort study from the US Premier Healthcare Database evaluated the risk and predictors of anaphylaxis in association with intravenous immunoglobulin (IVIg) therapy in the inpatient and outpatient setting. Data were collected retrospectively (01/2009-12/2018) from 24,919 patients administered IgPro10 IVIg, median age 54 years. Immunoglobulins of interest were IgPro10 and other IVIg given before or after IgPro10. Moderate and severe anaphylaxis was identified from same-day parenteral epinephrine and IVIg use and reviews of patient record summaries. Predictors for first anaphylactic reactions associated with IVIg administration were derived from adjusted incidence rate ratios (IRR) using Poisson regression. Moderate anaphylaxis in IVIg use was rare, severe anaphylaxis very rare based on a total of 124 moderate and four non-fatal severe first anaphylactic events, incidence rate of 7.11 and 0.23/10,000 IVIg administrations respectively. Age under 18 was an independent predictor of moderate or severe anaphylactic events, adjusted IRR 2.94 (0.95-CI, 1.91-4.52) compared with those 18 years and older. First IVIg administration was a strong predictor of anaphylaxis. The IRR in those with a subsequent IVIg administration in the preceding 42 days, decreased to 0.27 (0.17-0.42) and in those effectively IVIg-naïve (no IVIg for > 42 days) to 0.76 (0.44-1.32) compared with first IVIg use. The key conclusions from this study are that the risk of anaphylaxis has progressively reduced over the last decade, from 14.87/10,000 in 2009-2010 to 4.39/10,000 IVIg administrations in 2017-2018 and is rare overall, and that the risk of anaphylaxis is increased in those aged under 18.

PMID:34562316 | DOI:10.1111/cei.13665