Tag: statistics

Eur J Cancer. 2022 Feb 16;164:88-94. doi: 10.1016/j.ejca.2021.12.034. Online ahead of print.

ABSTRACT

BACKGROUND: Advances in biomedical artificial intelligence may introduce or perpetuate sex and gender discriminations. Convolutional neural networks (CNN) have proven a dermatologist-level performance in image classification tasks but have not been assessed for sex and gender biases that may affect training data and diagnostic performance. In this study, we investigated sex-related imbalances in training data and diagnostic performance of a market-approved CNN for skin cancer classification (Moleanalyzer Pro®, Fotofinder Systems GmbH, Bad Birnbach, Germany).

METHODS: We screened open-access dermoscopic image repositories widely used for CNN training for distribution of sex. Moreover, the sex-related diagnostic performance of the market-approved CNN was tested in 1549 dermoscopic images stratified by sex (female n = 773; male n = 776).

RESULTS: Most open-access repositories showed a marked under-representation of images originating from female (40%) versus male (60%) patients. Despite these imbalances and well-known sex-related differences in skin anatomy or skin-directed behaviour, the tested CNN achieved a comparable sensitivity of 87.0% [80.9%-91.3%] versus 87.1% [81.1%-91.4%], specificity of 98.7% [97.4%-99.3%] versus 96.9% [95.2%-98.0%] and ROC-AUC of 0.984 [0.975-0.993] versus 0.979 [0.969-0.988] in dermoscopic images of female versus male origin, respectively. In the sample at hand, sex-related differences in ROC-AUCs were not statistically significant in the per-image analysis nor in an additional per-individual analysis (p ≥ 0.59).

CONCLUSION: Design and training of artificial intelligence algorithms for medical applications should generally acknowledge sex and gender dimensions. Despite sex-related imbalances in open-access training data, the diagnostic performance of the tested CNN showed no sex-related bias in the classification of skin lesions.

PMID:35182926 | DOI:10.1016/j.ejca.2021.12.034

Spectrochim Acta A Mol Biomol Spectrosc. 2022 Feb 12;272:120998. doi: 10.1016/j.saa.2022.120998. Online ahead of print.

ABSTRACT

Simultaneous measurement of saxagliptin hydrochloride (SAG) and dapagliflozin propanediol monohydrate (DAG) in bulk powder, laboratory-prepared mixtures, and pharmaceutical dosage form were applied by utilizing three precise and sensitive spectrophotometric techniques which were developed and validated. The first method was the induced dual-wavelength approach (IDW), which relied primarily on the use of alternative equality factors (F) to abolish the effect of DAG when determining SAG and vice versa. The ratio difference method (RDM) was the second method, which used 25 μg/ml of DAG and 20 μg/ml of SAG as divisors to determine the amplitude difference on the ratio spectrum of SAG and DAG, respectively. SAG was determined at λ_max 221 nm after plateau subtraction followed by multiplication by the divisor of DAG 25 μg/ml using the third method, ratio subtraction coupled with extended ratio subtraction method (RSER). Subsequently, using an extension ratio subtraction of the spectra, DAG was determined at λ_max 225 nm was determined. The developed methods were effectively used to estimate SAG and DAG in laboratory-prepared mixtures and pharmaceutical dosage forms, with satisfactory recoveries. The methodologies were assessed for their environmental friendliness using the analytical eco-scale, analytical GREEnness calculator, and green analytical procedureindex (GAPI). These methodologies were validated following the International Conference on Harmonisation (ICH) requirements. A statistical comparison of the obtained findings to those of the published method revealed no significant differences in precision and accuracy. Because of their high precision and cost-effectiveness, the developed methods can be used in quality control laboratories to determine the binary mixture.

PMID:35182920 | DOI:10.1016/j.saa.2022.120998

Am J Emerg Med. 2022 Jan 23;54:228-231. doi: 10.1016/j.ajem.2022.01.015. Online ahead of print.

ABSTRACT

BACKGROUND: There is a paucity of data looking at resident error or contrasting errors and adverse events among residents and attendings. This type of data could be vital in developing and enhancing educational curricula OBJECTIVES: Using an integrated, readily accessible electronic error reporting system the objective of this study is to compare the frequency and types of error and adverse events attributed to emergency medicine residents with those attributed to emergency medicine attendings.

METHODS: Individual events were classified into errors and/or adverse events, and were attributed to one of three groups-residents only, attendings only, or both (if the event had both resident and attending involvement). Error and adverse events were also classified into five different categories of events-systems, documentation, diagnostic, procedural and treatment. The proportion of error events were compared between the residents only and the attendings only group using a one-sample test of proportions. Categorical variables were compared using Fisher’s exact test.

RESULTS: Of a total of 115 observed events over the 11-month data collection period, 96 (83.4%) were errors. A majority of these errors, 40 (41.7%), were attributed to both residents and attendings, 20 (20.8%) were attributed to residents only, and 36 (37.5%) were attributed to attendings only. Of the 19 adverse events, 14 (73.7%) were attributed to both residents and attendings, and 5 (26.3%) adverse events were attributed to attendings only. No adverse events were attributed solely to residents (Table 1). Excluding events attributed to both residents and attendings, there was a significant difference between the proportion of errors attributed to attendings only (64.3%, CI: 50.6, 76.0), and residents only (35.7%, CI: 24.0, 49.0), p = 0.03. (Table 2). There was no significant difference between the residents only and the attendings only group in the distribution of errors and adverse events (Fisher’s exact, p = 0.162). (Table 2). There was no statistically significant difference between the two groups in errors that did not result in adverse events and the rate of errors proceeding to adverse events (Fisher’s exact, p = 0.15). (Table 3). There was no statistically significant difference between the two groups in the distribution of the types of errors and adverse events (Fisher’s exact, p = 0.09). Treatment related errors were the most common error types, for both the attending and the resident groups.

CONCLUSIONS: Resident error, somewhat expectedly, is most commonly related to treatment interventions, and rarely is due to an individual resident mistake. Resident error instead seems to reflect concomitant error on the part of the attending. Error, in general as well as adverse events, are more likely to be attributed to an attending alone rather than to a resident.

PMID:35182916 | DOI:10.1016/j.ajem.2022.01.015

Gen Hosp Psychiatry. 2022 Feb 4;75:61-67. doi: 10.1016/j.genhosppsych.2022.01.010. Online ahead of print.

ABSTRACT

OBJECTIVE: Schizophrenia has been associated with patients’ poor quality of life, disability, and hospitalization. As of today, evidence that highlights the association between schizophrenia and coronavirus disease (Covid-19) outcomes remains unclear. This study sought to analyze whether patients with pre-existing schizophrenia are at higher risk for Covid-19 mortality.

METHODS: Using specific keywords, we comprehensively searched PubMed, Scopus, OVID, and Cochrane Library sources until November 15th, 2021. All published studies on schizophrenia and Covid-19 were collected. We used Review Manager 5.4 and Comprehensive Meta-Analysis 3 software to conduct statistical analysis.

RESULTS: There were 10 studies with 263,207 Covid-19 patients included in the analysis. Evaluation of the data gathered yielded an association between schizophrenia and increased mortality from Covid-19 (RR 2.22; 95%CI: 1.54-3.20, p < 0.00001, I² = 82% random-effect model). The increased risk of developing mortality from Covid-19 in patients with schizophrenia was significantly influenced by older age (p = 0.0004) and smoking (p = 0.0048).

CONCLUSIONS: This study proposes that patients with pre-existing schizophrenia are at risk of developing higher Covid-19 mortality. Patients with schizophrenia need special attention and should be prioritized to receive the SARS-CoV-2 vaccine. Registration details: CRD42021293997.

PMID:35182908 | DOI:10.1016/j.genhosppsych.2022.01.010

J Chromatogr A. 2022 Feb 8;1667:462868. doi: 10.1016/j.chroma.2022.462868. Online ahead of print.

ABSTRACT

Integration of rice and fish farming, e.g., pacu fish in Argentina, has raised concern that herbicides used for rice paddies may adversely affect the fish metabolome. To study this issue, tile-based Fisher ratio (F-ratio) analysis was applied to comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS) data of pacu fish raised in an integrated rice-fish farming system (farmed class) versus fish raised in tanks (tank-raised class) to discover class-distinguishing analytes. F-ratio analysis resulted in hit lists initially dominated by artifact peaks from the sample derivatization process, as well as some redundant hits. These challenges were addressed by developing an automated artifact removal algorithm and an improvement to redundant hit removal in the tile-based F-ratio analysis using a pooled farmed fish sample, either spiked with 29 metabolites (spiked class) or unspiked (i.e., the background serving as the control class). Of the 29 spiked metabolites, 23 were discovered by standard F-ratio analysis, improving to 28 discovered using control-normalized F-ratio analysis. Standard and control-normalized F-ratio hit lists initially with 185 and 246 hits, were reduced to 56 and 49 hits, respectively, after artifact removal and removing redundant hits. Next, we returned to the F-ratio analysis of the farmed fish versus the control fish. Here, we introduce a minimum variance optimized (MVO) F-ratio calculation (^MVOF-ratio) that provides a comprehensive hit list ranking. The initial ^MVOF-ratio analysis hit list of 537 hits was reduced to 110 hits following artifact removal. Of the 110 hits, 70 expressed a concentration ratio statistically different than 1 (p < 0.05). The ^MVOF-ratio hit list discovered more true positives compared to the standard, tank-normalized, and farm-normalized F-ratio hit lists, providing the combination of results from the farm-normalized and tank-normalized hit lists. A majority of analytes (54 out of 70) important for normal biological functioning of pacu fish were significantly downregulated in the farmed fish, suggesting the integrated farming system may negatively impact pacu fish quality.

PMID:35182910 | DOI:10.1016/j.chroma.2022.462868

Phytomedicine. 2022 Feb 5;99:153967. doi: 10.1016/j.phymed.2022.153967. Online ahead of print.

ABSTRACT

BACKGROUND: Rheum officinale Baill. (ROB), as one of the traditional Chinese medicines for promoting blood circulation and removing blood stasis, has a wide range of pharmacological effects, such as cardiovascular protection, and has become a common drug in the clinical care of thrombosis.

OBJECTIVE: Although there are some pharmacological studies on ROB in the treatment of thrombotic diseases, the mechanism and material basis are still unclear. Based on the arginine biosynthesis signalling pathway, this research explored the target proteins and metabolites related to the intervention of ROB in thrombosis and expounded on the antithrombotic mechanism of ROB from the comprehensive perspectives of target prediction, intermediate metabolites and potential metabolic pathways.

METHODS: In this research, ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) technology was used to qualitatively detect the chemical compounds of ROB, and the antithrombotic activity of ROB was evaluated by establishing a zebrafish model. The target function was predicted by network pharmacology, and differential metabolites were screened by metabolomics and multivariate statistical analysis methods. Correlation analysis of network pharmacology and metabolomics screening results was conducted to identify the potential pathway of ROB intervention in thrombosis, and the prediction results were further verified.

RESULTS: ROB significantly reduced the reactive oxygen species (ROS) staining intensity in zebrafish induced by phenylhydrazine (PHZ) and improved the inhibition rate of thrombosis. By constructing the “herb-disease-component-target” network, it was concluded that the active ingredients of ROB in treating thrombosis involved emodin, aloe-emodin and physcion, and the key targets included nitric oxide synthase 2 (NOS2) and nitric oxide synthase 3 (NOS3). A total of 341 differential metabolites in zebrafish with thrombosis were screened by partial least squares discriminant analysis (PLS-DA). The results of reverse transcription-polymerase chain reaction (RT-PCR) experiments and targeted metabolomics verification showed that ROB was mainly involved in improving thrombosis by upregulating the expression of NOS3 mRNA and regulating the levels of arginine, glutamate and glutamine in the arginine biosynthesis pathway.

CONCLUSIONS: ROB improved thrombosis by regulating the expression of NOS3 mRNA and the contents of arginine, glutamate and glutamine in the arginine biosynthesis signalling pathway.

PMID:35182903 | DOI:10.1016/j.phymed.2022.153967

J Biomech. 2022 Feb 10;134:110993. doi: 10.1016/j.jbiomech.2022.110993. Online ahead of print.

ABSTRACT

Osteoarthritis (OA) development after ACL reconstruction (ACLR) is common. Patellofemoral OA after ACLR is as prevalent as tibiofemoral OA; however, few have explored the mechanisms leading to disease development in this compartment. Biomechanical alterations may be one mechanism responsible for post-traumatic knee OA. Patellofemoral contact forces during dynamic tasks, such as running and single leg hops, have been assessed at return to sport and later time points. The results of these studies, however, contradict each other, are only cross-sectional in nature, and are limited to specific points in time within the movement pattern. The purpose of this study was to assess patellofemoral contact forces 3, 6, and 24 months after ACLR during level walking over the entirety of the movement pattern. Patellofemoral contact forces were calculated after determination of muscle forces from a validated, subject-specific, EMG-driven neuromusculoskeletal model. Statistical parametric mapping was used to compare patellofemoral contact forces between limbs and across time points. Patellofemoral underloading of the involved limb (vs. uninvolved) was present at 3 months (p < 0.001 from 7 to 30% of stance) and 6 months (p = 0.001 from 11 to 23% of stance and p = 0.025 from 27 to 32%) after ACLR but was resolved by 24 months. Both limbs’ load increased from 3 to 6 months. The involved limb displayed relatively consistent loads from 6 months onward, while the uninvolved limb’s decreased back down towards their 3-month values. Overall, these results suggest that early patellofemoral underloading exists after ACLR and may be leading to patellofemoral OA development.

PMID:35182902 | DOI:10.1016/j.jbiomech.2022.110993

Neuropsychopharmacol Rep. 2022 Feb 18. doi: 10.1002/npr2.12241. Online ahead of print.

ABSTRACT

AIM: To determine the effectiveness of the progressive muscle relaxation (PMR) technique on anxiety caused by Covid-19 in pregnant women under the auspices of comprehensive health service centers in the nineteenth district of Tehran University of Medical Sciences.

METHOD: This study is a randomized clinical trial. A total of 126 pregnant women were randomly allocated to the intervention group (N = 63) and control group (N = 63). All participants completed demographic questionnaires and the Corona Disease Anxiety Scale electronically. The intervention was held in six sessions through Sky Room (three times a week). It consisted of training and practicing the PMR. The intervention group was re-evaluated with the related questionnaires immediately after the intervention and 2 weeks later, and the control group 2 and 4 weeks after the baseline.

RESULTS: There was a significant difference between the control and intervention groups at the baseline (P = .05). Nevertheless, analysis of variance test results showed that the difference between the intervention and control groups was found to be significantly different statistically; (22.92 ± 6.07) for intervention versus (28.13 ± 6.93) for control, with the second follow up (P = .01).

CONCLUSIONS: Progressive muscle relaxation is used as a useful intervention to reduce anxiety in pregnant women during coronavirus pandemics educated and recommended with more emphasis and sensitivity in pregnancy care by healthcare providers.

PMID:35182048 | DOI:10.1002/npr2.12241

Cancer Med. 2022 Feb 18. doi: 10.1002/cam4.4618. Online ahead of print.

ABSTRACT

BACKGROUND: To develop a multiparameter-based, easy-to-use nomogram and to predict the prognosis of cancer patients with sepsis in the intensive care unit (ICU).

METHODS: Clinical data on cancer patients with sepsis who met the definition of sepsis 3.0 admitted to the ICU from January 2016 to October 2021 were collected. All patients were randomly entered into the development cohort or validation cohort according to the ratio of 7:3. Patients in the development cohort were divided into the survivors and the nonsurvivors according to the outcome of 28 days in ICU. The independent risk factors of mortality due to sepsis were screened out from the two groups (the survivors and the nonsurvivors) in the development cohort through multivariate logistic regression analysis. A nomogram was established with these independent risk factors, and the calibration plot was subsequently evaluated. Finally, the predictive power of the nomogram was verified in the validation cohort.

RESULTS: A total of 317 cancer patients with sepsis who met the requirements were enrolled in this study, of which 229 entered into the development cohort and 88 entered into the validation cohort. The 28-day mortality rates of the two cohorts were 17.5% and 20.5%, respectively. The neutrophil-to-lymphocyte ratio (NLR) on day 3 (d3), brain natriuretic peptide (BNP) d3, fluid accumulation at 72 hours (h), and Sequential Organ Failure Assessment (SOFA) score were independent risk factors for the 28-day mortality between the survivors and the nonsurvivors in the development cohort. A nomogram was established on the above variables. The calibration plots fit well with the nomogram and had good statistical consistency in predicting the 28-day mortality of sepsis (the C value was 0.938 and 0.968 in the two cohorts, respectively). With a nomogram score of 83.8 points, the diagnostic accuracy was 90.8% vs 92.0%, the sensitivity was 72.5% vs 77.7%, the specificity was 94.7% vs 95.7%, the positive predictive value was 72.3% vs 82.4%, and the negative predictive value was 94.2% vs 94.4% for predicting the 28-day mortality in the development cohort and the validation cohort, respectively.

CONCLUSION: This easy-to-use nomogram based on NLR d3, BNP d3, and fluid accumulation at 72 h and SOFA score provides an accurate 28-day prognosis prediction for cancer patients with sepsis admitted to the ICU.

PMID:35182022 | DOI:10.1002/cam4.4618

Mol Ecol Resour. 2022 Feb 18. doi: 10.1111/1755-0998.13600. Online ahead of print.

ABSTRACT

The revolution in genomics has enabled large-scale population genetic investigations of a wide range of organisms, but there has been a relatively limited focus on improving analytical pipelines. To efficiently analyse large data sets, highly integrated and automated software pipelines, which are easy to use, efficient, reliable, reproducible and run in multiple computational environments, are required. A number of software workflows have been developed to handle and process such data sets for population genetic analyses, but effective, specialised pipelines for genetic and statistical analyses of non-model organisms are lacking. For most species, resources for variomes (sets of genetic variations found in populations of species) are not available, and/or genome assemblies are often incomplete and fragmented, complicating the selection of the most suitable reference genome when multiple assemblies are available. Additionally, often biological samples used contain extraneous DNA from sources other than the species under investigation (e.g., microbial contamination), which needs to be removed prior to genetic analyses. For these reasons, we established a new pipeline, called Escalibur, which includes functionalities, such as data trimming and mapping; selection of a suitable reference genome; removal of contaminating read data; recalibration of base calls; and variant-calling. Escalibur uses a proven GATK variant caller and workflow description language (WDL), and is, therefore, a highly efficient and scalable pipeline for the genome-wide identification of nucleotide variation in eukaryotes. This pipeline is available at https://gitlab.unimelb.edu.au/bioscience/escalibur (v0.3-beta) and is essentially applicable to any prokaryote or eukaryote.

PMID:35182034 | DOI:10.1111/1755-0998.13600