Statistical Power Research Articles

Gonial Angle in Forensic Anthropology to Determine Age and Gender: A Population-Specific Analysis.

Background The study highlights the gonial angle as a key craniofacial landmark for age and gender determination in forensic cases. It emphasizes population-specific analysis, enhancing precision by recognizing variations between populations. By clarifying the gonial angle's forensic use, the study offers clear guidelines, improving forensic practices. Moreover, the gonial angle and age and gender correlations are thoroughly examined, offering important information on their forensic relevance. The results highlight how crucial population-specific research is to improving the precision and dependability of forensic age and gender estimation techniques, which advances forensic anthropology and supports forensic investigations around the globe. Aim and objective The purpose of this study is to assess the accuracy of age and gender estimates using gonial angles. The objectives of this research are to evaluate the precision of age and gender estimates utilizing the gonial angle. Materials and methods This present study comprises two groups based on age groups: Group I belongs to 51 to 60 years of age, and Group II belongs to 61 to 70 years of age. Making use of G-Power software (version 3.1.9.4, Düsseldorf, Germany), the sample size was determined. The calculation ensured 95% statistical power at a significance level (alpha error probability) of 0.05. To achieve sufficient statistical power, a total of 1000 samples were included, with a projected required sample size of 92. A total of 1000 samples, consisting of 500 male and 500 female panoramic radiographs,were meticulously selected for the study. The samples picked were within the age range of 51 to 70 years. Orthopantomograms were determined using Planmeca software (Planmeca Romexis®, Version 6.0, USAInc.). Descriptive statistics, including prediction classification analysis of age and gender, were conducted using SPSS Statistics version 16.0 (SPSS Inc., Released 2007, SPSS for Windows, Version 16.0, Chicago, SPSS Inc.). Results According to this study, the mean gonial angle of males aged 51 to 60 years is larger (124.7370degrees) than that of females (119.6371degrees). The female group's mean estimates are more accurate, as seen by the smaller standard error (0.20844) compared to the male group's (0.60998). A statistically significant difference in mean gonial angles between the genders is evident, with males having a larger gonial angle (p-value <0.001). In the age range of 61 to 70 years, the mean gonial angle of females is higher (128.4322degrees) than that of males (124.0529degrees). In this instance, the male group's standard error is smaller (0.14968) than the female group's (0.30028), indicating more accurate mean estimates. Once more, a statistically significant difference is indicated by a p-value of less than 0.001, with females having a larger gonial angle than males. Conclusion Our study revealed that the gonial angle of the mandible can be considered a reliable parameter for gender identification. The study's limitation is its inability to reliably identify gender in the subadult population and in cases of edentulousness. An orthopantomogram is a trustworthy and accurate method for taking the different measurements needed to identify the gender of a particular mandible.

Multi-Dimensional Evaluation of an Augmented Reality Head-Mounted Display User Interface for Controlling Legged Manipulators

Controlling assistive robots can be challenging for some users, especially those lacking relevant experience. Augmented Reality (AR) User Interfaces (UIs) have the potential to facilitate this task. Although extensive research regarding legged manipulators exists, comparatively little is on their UIs. Most existing UIs leverage traditional control interfaces such as joysticks, Hand-Held (HH) controllers and 2D UIs. These interfaces not only risk being unintuitive, thus discouraging interaction with the robot partner, but also draw the operator’s focus away from the task and towards the UI. This shift in attention raises additional safety concerns, particularly in potentially hazardous environments where legged manipulators are frequently deployed. Moreover, traditional interfaces limit the operators’ availability to use their hands for other tasks. Towards overcoming these limitations, in this article, we provide a user study comparing an AR Head-Mounted Display (HMD) UI we developed for controlling a legged manipulator against off-the-shelf control methods for such robots. This user study involved 27 participants and 135 trials, from which we gathered over 405 completed questionnaires. These trials involved multiple navigation and manipulation tasks with varying difficulty levels using a Boston Dynamics’s Spot, a 7 df Kinova robot arm and a Robotiq 2F-85 gripper that we integrated into a legged manipulator. We made the comparison between UIs across multiple dimensions relevant to a successful human–robot interaction. These dimensions include cognitive workload, technology acceptance, fluency, system usability, immersion and trust. Our study employed a factorial experimental design with participants undergoing five different conditions, generating longitudinal data. Due to potential unknown distributions and outliers in such data, using parametric methods for its analysis is questionable, and while non-parametric alternatives exist, they may lead to reduced statistical power. Therefore, to analyse the data that resulted from our experiment, we chose Bayesian data analysis as an effective alternative to address these limitations. Our results show that AR UIs can outpace HH-based control methods and reduce the cognitive requirements when designers include hands-free interactions and cognitive offloading principles into the UI. Furthermore, the use of the AR UI together with our cognitive offloading feature resulted in higher usability scores and significantly higher fluency and Technology Acceptance Model scores. Regarding immersion, our results revealed that the response values for the AR Immersion questionnaire associated with the AR UI are significantly higher than those associated with the HH UI, regardless of the main interaction method with the former, i.e., hand gestures or cognitive offloading. Derived from the participants’ qualitative answers, we believe this is due to a combination of factors, of which the most important is the free use of the hands when using the HMD, as well as the ability to see the real environment without the need to divert their attention to the UI. Regarding trust, our findings did not display discernible differences in reported trust scores across UI options. However, during the manipulation phase of our user study, where participants were given the choice to select their preferred UI, they consistently reported higher levels of trust compared to the navigation category. Moreover, there was a drastic change in the percentage of participants that selected the AR UI for completing this manipulation stage after incorporating the cognitive offloading feature. Thus, trust seems to have mediated the use and non-use of the UIs in a dimension different from the ones considered in our study, i.e., delegation and reliance. Therefore, our AR HMD UI for the control of legged manipulators was found to improve human–robot interaction across several relevant dimensions, underscoring the critical role of UI design in the effective and trustworthy utilisation of robotic systems.

A learned score function improves the power of mass spectrometry database search.

One of the core problems in the analysis of protein tandem mass spectrometry data is the peptide assignment problem: determining, for each observed spectrum, the peptide sequence that was responsible for generating the spectrum. Two primary classes of methods are used to solve this problem: database search and de novo peptide sequencing. State-of-the-art methods for de novo sequencing use machine learning methods, whereas most database search engines use hand-designed score functions to evaluate the quality of a match between an observed spectrum and a candidate peptide from the database. We hypothesized that machine learning models for de novo sequencing implicitly learn a score function that captures the relationship between peptides and spectra, and thus may be re-purposed as a score function for database search. Because this score function is trained from massive amounts of mass spectrometry data, it could potentially outperform existing, hand-designed database search tools. To test this hypothesis, we re-engineered Casanovo, which has been shown to provide state-of-the-art de novo sequencing capabilities, to assign scores to given peptide-spectrum pairs. We then evaluated the statistical power of this Casanovo score function, Casanovo-DB, to detect peptides on a benchmark of three mass spectrometry runs from three different species. In addition, we show that re-scoring with the Percolator post-processor benefits Casanovo-DB more than other score functions, further increasing the number of detected peptides.

The VRF-L and VRF-GL IOL power calculation methods after radial keratotomy.

To investigate the accuracy of the VRF-L and VRF-GL IOL power calculation methods in cataract surgery after radial keratotomy (RK). The VRF-L and VRF-GL methods were collated with nine formulas: Barrett True K (No History), Haigis, Hoffer Q, Hoffer Q (Double-K), Holladay 1 (Double-K), Holladay 2 (Double-K), PEARL-DGS (RK), SRK/T (Double-K), and T2 (Double-K). With SS-OCT biometry (IOLMaster 700, Carl Zeiss Meditec), data of 78 eyes from 78 patients with previous RK was included. Optimised lens constants were sourced from the IOL Con website. Subjective refraction was obtained at 4 to 5 months postoperatively. The root mean square absolute error (RMSAE) and median absolute error (MedAE) were chosen as primary outcomes and the percentage of eyes with PEs within ±0.25 D, ±0.50 D, ±0.75 D, and ±1.00 D were analysed. Statistical significance (Bootstrap-t test, P < 0.05) was shown by VRF-GL, VRF-L, and Haigis formulas with the lowest RMSAE (0.813 D, 0.816 D and 0.824 D) and MedAE (0.511 D, 0.497 D and 0.533 D) values. The Barrett True K formula was less predictable (0.836 and 0.580, respectively). The VRF-L, VRF-GL, and Haigis achieved the highest percentage of eyes with a PE within ±0.50 D (52.56%, 50.00%, and 46.15%) and ±1.00 D (79.49%, 79.49%, and 80.77% respectively). The VRF-L and VRF-GL methods demonstrated higher accuracy and were comparable with existing methods in eyes after RK. The Haigis was an alternative option with a higher percentage of eyes with a PE within ±1.00 D (80.77%).

A soil base model of adjacent various story structures

In modern geotechnical engineering, owing to the development of information technology and availability of powerful packages for the calculation of the entire base - foundation - structure system, one of the main research areas is to develop, improve and investigate soil base models to ensure the adequate interaction between the components of the system during the construction and operation of buildings and structures (hereinafter referred to as the “structures”). The paper proposes an improved soil base model in the form of a continuous layer of finite distribution capability to simulate and calculate adjacent multistory structures in the base - foundations - structures system using powerful calculation packages such as SOFiSTiK, ABAQUS, PLAXIS, SCAD, Lira and others. The improved model considers the parameters of the stress-strain properties of the soils of the bases, the geometric profile taking account of the distribution capability of the base and different boundary conditions, but differs from the existing models in that it has a stepped geometric profile at the lower boundary of the model because of different compressible layer depths under each foundation of the structures. The use of this model improves the accuracy of simulating a soil base for large-sized foundations of adjacent structures to obtain reliable results of the stress-strain state of the base - foundations - structures system. An example demonstrates how to simulate and calculate raft foundations of a two-section multistory building in the base - foundations - structures system that interacts with an improved soil base model (linear strains of soils under loads are considered here) with reference to different numbers of stories of the sections. The numerical study results show on a specific calculation example that considering different compressible layers depths in the model under differently loaded foundations results in an increase in moment forces of up to 65% as compared with simulating the whole compressible layer, which may lead to the disruption of large-sized raft foundations.

Allele-specific binding variants causing ChIP-seq peak height of histone modification are not enriched in expression QTL annotations

BackgroundGenome sequence variants affecting complex traits (quantitative trait loci, QTL) are enriched in functional regions of the genome, such as those marked by certain histone modifications. These variants are believed to influence gene expression. However, due to the linkage disequilibrium among nearby variants, pinpointing the precise location of QTL is challenging. We aimed to identify allele-specific binding (ASB) QTL (asbQTL) that cause variation in the level of histone modification, as measured by the height of peaks assayed by ChIP-seq (chromatin immunoprecipitation sequencing). We identified DNA sequences that predict the difference between alleles in ChIP-seq peak height in H3K4me3 and H3K27ac histone modifications in the mammary glands of cows.ResultsWe used a gapped k-mer support vector machine, a novel best linear unbiased prediction model, and a multiple linear regression model that combines the other two approaches to predict variant impacts on peak height. For each method, a subset of 1000 sites with the highest magnitude of predicted ASB was considered as candidate asbQTL. The accuracy of this prediction was measured by the proportion where the predicted direction matched the observed direction. Prediction accuracy ranged between 0.59 and 0.74, suggesting that these 1000 sites are enriched for asbQTL. Using independent data, we investigated functional enrichment in the candidate asbQTL set and three control groups, including non-causal ASB sites, non-ASB variants under a peak, and SNPs (single nucleotide polymorphisms) not under a peak. For H3K4me3, a higher proportion of the candidate asbQTL were confirmed as ASB when compared to the non-causal ASB sites (P < 0.01). However, these candidate asbQTL did not enrich for the other annotations, including expression QTL (eQTL), allele-specific expression QTL (aseQTL) and sites conserved across mammals (P > 0.05).ConclusionsWe identified putatively causal sites for asbQTL using the DNA sequence surrounding these sites. Our results suggest that many sites influencing histone modifications may not directly affect gene expression. However, it is important to acknowledge that distinguishing between putative causal ASB sites and other non-causal ASB sites in high linkage disequilibrium with the causal sites regarding their impact on gene expression may be challenging due to limitations in statistical power.

Transgender Women With Suppressed Testosterone Display Lower Burden of Coronary Disease Than Matched Cisgender Men.

Cardiovascular disease (CVD) in transgender women (TW) may be affected by gender-affirming hormone therapy (GAHT) and HIV, but few data compare TW on contemporary GAHT to well-matched controls. We compared CVD burden and biomarker profiles between TW and matched cisgender men (CM). Adult TW on GAHT (n = 29) were recruited for a cross-sectional study (2018-2020). CM (n = 48) from the former Multicenter AIDS Cohort Study were matched 2:1 to TW on HIV serostatus, age ±5 years, race/ethnicity, BMI category and antiretroviral therapy (ART) type. Cardiac parameters were measured by CT and coronary atherosclerosis by coronary CT angiography; sex hormone and biomarker concentrations were measured centrally from stored samples. Overall, median age was 53 years and BMI 29 kg/m2; 69% were non-white. All participants with HIV (71%) had viral suppression on ART. Only 31% of TW had testosterone suppression (<50 ng/dL, TW-S). Traditional CVD risk factors were similar between groups, except that TW-S had higher BMI than TW with non-suppressed testosterone (TW-T). TW-S had no evidence of non-calcified coronary plaque or advanced coronary stenosis, whereas TW-T and CM had similar burden. TW had lower prevalence of any coronary plaque, calcified plaque and mixed plaque than CM, regardless of testosterone concentrations and HIV serostatus. Estradiol but not testosterone concentrations moderately and negatively correlated with the presence of coronary plaque and stenosis. Small sample size limited statistical power. Older TW with suppressed total testosterone on GAHT had no CT evidence of non-calcified coronary plaque or advanced coronary stenosis. Longitudinal studies to understand relationships between GAHT and CVD risk in TW are needed.

Power of a test for assessing interlaboratory consensus of nominal and ordinal characteristics of a substance, material, or object

A concept of the consensus among different laboratories participating in an interlaboratory comparison, classifying a substance, material, or object according to its nominal and ordinal (i.e. categorical) characteristics, is devised using decomposition of the total variation of the laboratory responses. One of the components of the total variation is caused by the between-laboratory differences, and the second—by conditions associated with the applied experimental design (for example, temperature of test items, technician experience, etc). This decomposition is based on the recently developed two-way CATANOVA for nominal variables and two-way ORDANOVA for ordinal variables. The consensus is tested as hypotheses about homogeneity, i.e. insignificance of the corresponding components of the total variation. The consensus power is taken to be the power of the homogeneity test. A methodology for evaluation of the consensus power and corresponding risks of false decisions versus the dataset size of categorical characteristics obtained in an interlaboratory comparison is detailed. Examples of evaluation of the power and risks are discussed using previously-published datasets of an interlaboratory comparison of identification of weld imperfections, and an examination of the intensity of the odor of drinking water. An example of computer code in the R programming environment is presented for the power calculations in the case of nominal variables, using a chi-square distribution. A newly developed tool for ordinal variables, an Excel spreadsheet with macros, which is based on Monte Carlo draws from a multinomial distribution, is also available.

The Extended Anderson and Hauck Tests and Sample Size Procedures for Equivalence Assessment in Simple Linear Regressions

This study describes extended Anderson and Hauck procedures for equivalence testing of slope coefficients and mean responses in one and two regression lines. The general formulation of asymmetric equivalence ranges permits a wide variety of equivalence questions to be tested for a target magnitude or a negligible value. Specifically, the equivalence tests are useful for assessing negligible trend and similar response in a single regression line, and for evaluating unimportant interaction-moderation effect and comparable simple effect between two linear regression lines. The associated power functions and sample size procedures are also derived and compared under the random and fixed model settings. According to the analytic justification and empirical assessment, the exact approaches have a clear advantage over the approximate formulas for accommodating the full stochastic nature of both the response and predictor variables. Computer algorithms are also provided for conducting the proposed equivalence tests, power calculations, and sample size determinations in simple linear regressions.

Optimal Power Flow of Power System with Unified Power Flow Controller Using Moth Flame Optimization with Locational Marginal Price

Consideration of transmission line capacity and the optimal power flow (OPF) determines the locational marginal price (LMP), which in turn determines the performance and profitability of a producing unit. Reducing the total cost of the generators can lead to a drop in the market price of electricity. It is recommended to use numerical and repetition-based approaches for solving power flow equations due to their nonlinear nature. In order to achieve the ideal power flow at an affordable price, this paper employs a Moth Flame Optimization (MFO) to solve the equations. We then enhance the MFO’s structure to make it more effective at performing the simultaneous calculations of power passing through transmission lines. Flexible AC transmission systems (FACTS) tool that has been utilized to overcome this problem is the Unified Power Flow Controller (UPFC). Lastly, the proposed MFO algorithm would include the following parameters in its output: bus voltages, line losses, generated power, total generating expenditures, and generator profits. In this work, the proposed method is tested on the IEEE 57-bus network also shows that it improves upon the OPF problem.

Amorphous calcium carbonate as a novel potential treatment for osteoarthritis in dogs: a pilot clinical study.

Amorphous calcium carbonate (ACC) is a potential new treatment for canine osteoarthritis (OA) with novel mechanisms based on local pH modulation and targeting bone remodeling, inflammation, and pain. The aim of this pilot exploratory clinical study was to obtain initial data on the potential efficacy and safety of ACC in OA dogs and to determine if further investigation was appropriate using similar assessment methods. In this prospective, randomized, double-blind, controlled pilot study, 41 client-owned dogs were allocated in a 2:1 ratio to ACC: placebo given orally for 56 days. Efficacy assessments included improvements in pain and mobility using owner questionnaires [Canine Brief Pain Inventory (CBPI), Client Specific Outcome Measure (CSOM), and Veterinary Orthopedic Scores (VOS)]. Safety in the study population was monitored by veterinary examinations, clinical pathology, and adverse events. Fifty-three dogs were screened, of which 41 enrolled and served for the safety assessment. Thirty-six dogs were found evaluable for initial efficacy assessment. Three dogs given placebo (21.4%) and one given ACC (4.5%) were removed before day 56 due to owner-perceived pain and were considered treatment failures. There were no serious adverse events or clinically significant treatment-related effects in the study. Overall, ACC was found safe in the small study population. On day 56, proportionally more ACC than placebo dogs were treatment successes based on CBPI (45.5% vs. 21.4%) and CSOM (63.6% vs. 30.8%, respectively); however, these differences were not statistically significant (p = 0.15 and 0.06, respectively). On day 56, within the ACC group but not the placebo group, the CBPI, CSOM, and VOS assessments were lower compared to day 0 and day 14 (p < 0.05). The relatively small number of dogs limited the statistical power of the pilot study in evaluating the efficacy and safety of ACC. Study results support the conduct of larger, appropriately powered studies using similar assessments to confirm whether ACC may be a safe and effective treatment for OA in dogs.

Technology and technical means for the implementation of reproduction methods for soil fertility

Soil fertility is determined by the presence of humus as the main part of organic matter. The extended reproduction of soil fertility is ensured by the introduction of organic and mineral fertilizers, the cultivation of sidereal crops and the decomposition of plant residues. (Research purpose) The research purpose is developing the technologies and means of mechanization for extended reproduction of fertility. (Materials and methods) For the joint application of liquid organic fertilizers and the cultivation of siderates, a unit has been developed that implements a hose technology for transporting liquid organic fertilizers. Fertilizers are fed through pressure hose lines to the working parts deep into the soil layer. The combined unit consists of a tractor K-744 Kirovets and an adapter for deep tillage with liquid fertilizers, as well as a seeder for small-seeded crops. To level the surface of the field after the passage of the unit and the sealing of the sown seeds of the sideral culture, the unit is equipped with a tooth roller. (Results and discussion) Formulas for determining the critical processing depth are given, the power calculation of the unit is performed. The design of the tillage tool allows to install flat-cutting working parts with a grip of 0.80 meters and slits with a grip of 0.45 meters. Tests of the combined unit were carried out. The depth of tillage was 36±1 centimeters, the seeding rate of the sideral crop (oilseed radish) was 25 kilograms per hectare, the operating speed range of the unit was from 0.4 to 0.8 meters per second. (Conclusions) The uniformity of the subsurface distribution of organic fertilizers was 90-95 percent. The specific energy intensity of the technological process of the combined unit based on the K-744 tractor for intra-soil fertilization is 40-65 kilowatt hours per hectare (excluding the capacity for pumping fertilizers). Energy consumption depends on the depth of cultivation and resistivity of the soil. The proposed method allows preventing water and wind erosion of the soil, improving its agronomically valuable properties. Reducing the pesticide load on the soil and its microflora contributes to the transition to a model of sustainable agroecosystems, improving and improving crop quality. The proposed technology provides extended reproduction of soil fertility.

Accuracy of intra ocular lens calculation formulae in patients with pseudoexfoliation syndrome

BackgroundThe purpose of this study was to investigate the visual and refractive outcomes in patients with pseudoexfoliation (PXF) undergoing routine cataract surgery and to compare the accuracy of intraocular lens (IOL) power calculation formulae.MethodsRetrospective case-series study from Shamir medical center, a public hospital, Israel. Medical records of patients who underwent routine cataract surgery between January 2019 and August 2021 were investigated. Postoperative visual acuity and manifest refraction were examined. The error in predicted refraction and IOL power calculation accuracy within a range of ± 0.50 to ± 1.00 diopters were compared between different IOL calculating formulae.Results151 eyes of 151 patients ages 73.9 ± 7.1 years were included in this study- 58 eyes in the PXF group and 93 eyes in the control group. The mean absolute error (MAE) for the BUII formula was 0.63D ± 0.87 for the PXF group and 0.36D ± 0.48 for the control group (p < 0.05). The MAE for the Hill-RBF 3.0 formula was 0.61D ± 0.84 for the PXF group and 0.42D ± 0.55 for the control group (p = 0.05). There were significant differences in MAE and MedAE between PXF group and control group measures (p < 0.05). In the PXF group there were no significant differences between the different formulae.ConclusionsThere were significant differences in accuracy of IOL power calculations in all formulae between PXF group and control group measures. PXF patients show hyperopic shift from predicted refraction. Barret universal II formula had the highest proportion of eyes with absolute error in prediction below or equal to 0.50 D in both PXF and control groups.

High-dimensional causal mediation analysis by partial sum statistic and sample splitting strategy in imaging genetics application.

Causal mediation analysis provides a systematic approach to explore the causal role of one or more mediators in the association between exposure and outcome. In omics or imaging data analysis, mediators are often high-dimensional, which brings new statistical challenges. Existing methods either violate causal assumptions or fail in interpretable variable selection. Additionally, mediators are often highly correlated, presenting difficulties in selecting and prioritizing top mediators. To address these issues, we develop a framework using Partial Sum Statistic and Sample Splitting Strategy, namely PS5, for high-dimensional causal mediation analysis. The method provides a powerful global mediation test satisfying causal assumptions, followed by an algorithm to select and prioritize active mediators with quantification of individual mediation contributions. We demonstrate its accurate type I error control, superior statistical power, reduced bias in mediation effect estimation, and accurate mediator selection using extensive simulations of varying levels of effect size, signal sparsity, and mediator correlations. Finally, we apply PS5 to an imaging genetics dataset of chronic obstructive pulmonary disease (COPD) patients ( N =8,897) in the COPDGene study to examine the causal mediation role of lung images ( p =5,810) in the associations between polygenic risk score and lung function and between smoking exposure and lung function, respectively. Both causal mediation analyses successfully estimate the global indirect effect and detect mediating image regions. Collectively, we find a region in the lower lobe of the right lung with a strong and concordant mediation effect for both genetic and environmental exposures. This suggests that targeted treatment toward this region might mitigate the severity of COPD due to genetic and smoking effects.

Evaluation of pancreatic iodine uptake and related influential factors in multiphase dual-energy CT.

To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT). This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s-40 s, 60 s-70 s, and 150 s-180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses. A total of 562 participants (median age 58 years [interquartile range: 47-67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = -0.240, p = 0.001), and type-II diabetes (β = -0.449, p < 0.001); NICPP by VFA (β = -0.301, p = 0.017) and smoking (β = -0.291, p < 0.001); and NICEP by smoking (β = -0.154, p = 0.10) and alcohol consumption (β = -0.350, p < 0.001) with statistical power values over 0.81. NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake. This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker. Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies. Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake. Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.

Hotspots and trends of artificial intelligence in the field of cataracts: a bibliometric analysis

PurposeTo analyze the hotspots and trends in artificial intelligence (AI) research in the field of cataracts.MethodsThe Science Citation Index Expanded of the Web of Science Core Collection was used to collect the research literature related to AI in the field of cataracts, which was analyzed for valuable information such as years, countries/regions, journals, institutions, citations, and keywords. Visualized co-occurrence network graphs were generated through the library online analysis platform, VOSviewer, and CiteSpace tools.ResultsA total of 222 relevant research articles from 41 countries were selected. Since 2019, the number of related articles has increased significantly every year. China (n = 82, 24.92%), the United States (n = 55, 16.72%) and India (n = 26, 7.90%) were the three countries with the most publications, accounting for 49.54% of the total. The Journal of Cataract and Refractive Surgery (n = 13, 5.86%) and Translational Vision Science & Technology (n = 10, 4.50%) had the most publications. Sun Yat-sen University (n = 25, 11.26%), the Chinese Academy of Sciences (n = 17, 7.66%), and Capital Medical University (n = 16, 7.21%) are the three institutions with the highest number of publications. We discovered through keyword analysis that cataract, diagnosis, imaging, classification, intraocular lens, and formula are the main topics of current study.ConclusionsThis study revealed the hot spots and potential trends of AI in terms of cataract diagnosis and intraocular lens power calculation. AI will become more prevalent in the field of ophthalmology in the future.

Exploring Study Design Foibles in Randomized Controlled Trials on Convalescent Plasma in Hospitalized COVID-19 Patients.

Background: Sample size estimation is an essential step in the design of randomized controlled trials (RCTs) evaluating a treatment effect. Sample size is a critical variable in determining statistical significance and, thus, it significantly influences RCTs' success or failure. During the COVID-19 pandemic, many RCTs tested the efficacy of COVID-19 convalescent plasma (CCP) in hospitalized patients but reported different efficacies, which could be attributed to, in addition to timing and dose, inadequate sample size estimates. Methods: To assess the sample size estimation in RCTs evaluating the effect of treatment with CCP in hospitalized COVID-19 patients, we searched the medical literature between January 2020 and March 2024 through PubMed and other electronic databases, extracting information on expected size effect, statistical power, significance level, and measured efficacy. Results: A total of 32 RCTs were identified. While power and significance level were highly consistent, heterogeneity in the expected size effect was relevant. Approximately one third of the RCTs did not reach the planned sample size for various reasons, with the most important one being slow patient recruitment during the pandemic's peaks. RCTs with a primary outcome in favor of CCP treatment had a significant lower median absolute difference in the expected size effect than unfavorable RCTs (20.0% versus 33.9%, P = 0.04). Conclusions: The analyses of sample sizes in RCTs of CCP treatment in hospitalized COVID-19 patients reveal that many underestimated the number of participants needed because of excessively high expectations on efficacy, and thus, these studies had low statistical power. This, in combination with a lower-than-planned recruitment of cases and controls, could have further negatively influenced the primary outcomes of the RCTs.

Comprehensive signal detection of delirium-associated medication using the Food and Drug Administration Adverse Event Reporting System

ObjectiveSeveral medications are associated with delirium; however, studies with adequate statistical power are limited, and it is difficult to determine the effects of the various concomitant medications used in clinical practice. Therefore, in this study, we aimed to comprehensively evaluate the safety signals of delirium-associated drugs using a spontaneous adverse event reporting system. MethodThe JAPIC AERS (Food and Drug Administration Adverse Event Reporting System pre-processed by the Japan Pharmaceutical Information Center) was used for the analysis in this pharmacovigilance study. The reporting odds ratio (ROR) for delirium was adjusted for using multivariate logistic regression analysis with sex, age, indication, and melatonin receptor agonist use, and 22 drug categories were targeted as covariates. ResultsAfter excluding patients with missing information, 7,527,568 patients were included in the study. Delirium signals were detected even after adjusting for covariates in 17 drug categories, including benzodiazepines (adjusted ROR, 1.76; 95% confidence interval [CI], 1.64–1.89), opioids (adjusted ROR, 4.42; 95% CI, 4.21–4.64), and tricyclic antidepressants (adjusted ROR, 2.44; 95% CI, 2.20–2.71). ConclusionsThese findings suggest that many drug classes, such as benzodiazepines, are independent risk factors for delirium and strengthen the evidence of an association between delirium and medications.

Bayesian Estimation Improves Prediction of Outcomes after Epilepsy Surgery.

Low power is a problem in many fields, as underpowered studies that find a statistically significant result will exaggerate the magnitude of the observed effect size. We quantified the statistical power and magnitude error of studies of epilepsy surgery outcomes. The median power across all studies was 14%. Studies with a median sample size or less (n<=56) and a statistically significant result exaggerated the true effect size by a factor of 5.4 (median odds ratio 9.3 vs. median true odds ratio 1.7), while the Bayesian estimate of the odds ratio only exaggerated the true effect size by a factor of 1.6 (2.7 vs. 1.7). We conclude that Bayesian estimation of odds ratio attenuates the exaggeration of significant effect sizes in underpowered studies. This approach could help improve patient counseling about the chance of seizure freedom after epilepsy surgery.

A Vector Theory of Assessing Clinical Trials: An Application to Bioequivalence.

A novel idea is introduced regarding the statistical comparisons of endpoints in clinical trials. Currently, the (dis)similarity of measured endpoints is not assessed. Instead, statistical analysis is directly applied, which can lead to multiplicity issues, reduced statistical power, and the recruitment of more subjects. The Vector-Based Comparison (VBC) approach originates from vector algebra and considers clinical endpoints as "vectors". In the general case of N clinical endpoints, a Cartesian coordinate system is defined, and the most important primary endpoint (E1) is set. Following an explicitly defined procedure, the pairwise relationships of the remaining N-1 endpoints with E1 are estimated, and the N-1 endpoints are decomposed into axes perpendicular to E1. The angle between vectors provides insight into the level of dependency between variables. Vectors that are perpendicular to each other are considered independent, and only these are used in the statistical analysis. In this work, VBC is applied to bioequivalence studies of three anti-hypertensive drugs: amlodipine, irbesartan, and hydrochlorothiazide. The results suggest that VBC is a reproducible, easily applicable method allowing for the discrimination and utilization of the endpoint component expressing different attributes. All clinical characteristics are assessed with increased statistical power, without inflation of type I error.