Tag: pubmed

Comput Methods Programs Biomed. 2021 Sep 16;211:106420. doi: 10.1016/j.cmpb.2021.106420. Online ahead of print.

ABSTRACT

OBJECTIVE: Hepatic encephalopathy (HE) is among the most common complications of cirrhosis. Data for cirrhosis with HE is typically unbalanced. Traditional statistical methods and machine learning algorithms thus cannot identify a few classes. In this paper, we use machine learning algorithms to construct a risk prediction model for liver cirrhosis complicated by HE to improve the efficiency of its prediction.

METHOD: We collected medical data from 1,256 patients with cirrhosis and performed preprocessing to extract 81 features from these irregular data. To predict HE in cirrhotic patients, we compared several classification methods: logistic regression, weighted random forest (WRF), SVM, and weighted SVM (WSVM). We also used an additional 722 patients with cirrhosis for external validation of the model.

RESULTS: The WRF, WSVM, and logistic regression models exhibited better recognition ability for patients with HE than traditional machine learning models (sensitivity> 0.70), but their ability to identify patients with uncomplicated HE was slightly lower (specificity approximately 85%). The comprehensive evaluation index of the traditional model was higher than those of other models (G-means> 0.80 and F-measure> 0.40). For the WRF, the G-means (0.82), F-measure (0.46), and AUC (0.82) were superior to those of the logistic regression and WSVM models, which means that it can better predict the incidence of HE in patients.

CONCLUSION: The WRF model is more suitable for the classification of unbalanced medical data and can be used to construct a risk prediction and evaluation system for liver cirrhosis complicated with HE. The probabilistic prediction models of WRF can help clinicians identify high-risk patients with HE.

PMID:34555589 | DOI:10.1016/j.cmpb.2021.106420

Comput Methods Programs Biomed. 2021 Sep 16;211:106418. doi: 10.1016/j.cmpb.2021.106418. Online ahead of print.

ABSTRACT

Backgound and Objective: Detecting differentially expressed genes is an important step in genome wide analysis and expression profiling. There are a wide array of algorithms used in today’s research based on statistical approaches. Even though the current algorithms work, they sometimes miss-predict. There is no framework available for measuring the quality of current algorithms. New machine learning methods (like gradient boost and deep neural networks) were not used to solve this problem. The Gene-Bench open source python package addresses these issues by providing an evaluation and data handling system for differentially expressed genes detection algorithms on microarray data. We also provide MIDGET, a new group of algorithms based on state of the art machine learning approaches Methods: The Gene-Bench package provides data collected from real experiments that consists of 73 transcription-factor perturbation experiments with validation data from Chip-seq experiments and 129 drug perturbation experiments, synthetic data generated with our own method and three evaluation metrics (Kolmogorov, F1 and AUC/ROC). Besides the data and metrics, Gene-Bench also contains well-known algorithms and a new method to identify differentially expressed genes, called MIDGET: Machine learning Identification Differential Gene Expression Tool that is using big-data and machine learning methods to identify differentially expressed genes. The two new groups of machine learning algorithms provided in our package use extreme gradient boosting and deep neural networks to achieve their results. Results: The Gene-Bench package is highly flexible, allows fast prototyping and evaluating of new and old algorithms and provides multiple new machine-learning algorithms (called MIDGET) that perform better on all evaluation metrics than all the other tested alternatives. While everything provided in Gene-Bench is algorithm independent, the user can also use algorithms implemented in the R language even though the package is written in Python. Conclusions: The Gene-Bench package fills a gap in evaluating and benchmarking differential gene detection algorithms. It also provides machine learning methods that perform detection with higher accuracy in all tested metrics. It is available at https://github.com/raduangelescu/GeneBench/ and can be directly installed from the Python Package Index using pip install genebench.

PMID:34555591 | DOI:10.1016/j.cmpb.2021.106418

Chemosphere. 2021 Sep 16;287(Pt 3):132268. doi: 10.1016/j.chemosphere.2021.132268. Online ahead of print.

ABSTRACT

Dissolved salts, colloidal particles, and active microorganisms in brackish surface water distribution systems (BSWD) cause multiple fouling, poses potential threat to the environmental pollution, and raising technical and economic issues as well. So far, the co-occurrence and interactions of multiple fouling remains largely unknown. Multiple fouling behaviors were assessed in agriculture BSWD under different nitrogen (N) fertilizers. X-ray diffraction, Rietveld refinement analysis, 16S rRNA, and microbial network analysis were conducted to determine the fouling characteristics. Statistical analysis was applied to reveal the relative contributions and interaction of multiple fouling. Our results demonstrated, multiple fouling of precipitates, particulates and biofoulings were co-occurred. Fouling growth was largely attributed to the strong interactions of different fouling. The binary interactions of precipitates – particulates contributed 51.1%, and ternary interactions of precipitates – particulates – biofouling contributed 25.4% to explain the decline of system performance, while the contribution of each single type fouling was minimal. Thereby indicating the significant role of calcium silica, biomineralization and bio-silicates in fouling. The lower acid N fertilizer broken the interaction of multiple fouling by increasing the precipitate crystal parameters and repulsive forces amongst particulates, as well as destroyed microbial interactions in biofouling. Overall, this study open frontier for multiple fouling in-depth profiling and antifouling guidance for effective utilization of BSWD.

PMID:34555585 | DOI:10.1016/j.chemosphere.2021.132268

BJOG. 2021 Sep 23. doi: 10.1111/1471-0528.16943. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate the association between hysterectomy with conservation of one or both adnexa and ovarian and tubal cancer.

DESIGN: Prospective cohort study.

SETTING: 13 NHS Trusts in England, Wales and Northern Ireland.

POPULATION: 202,506 postmenopausal women recruited between 2001-2005 to the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) and followed up until 31 December 2014.

METHODS: Multiple sources (questionnaires, hospital notes, Hospital Episodes Statistics, national cancer/death registries, ultrasound reports) were used to obtain accurate data on hysterectomy (with conservation of one or both adnexa) and outcomes censored at bilateral oophorectomy, death, ovarian/tubal cancer diagnosis, loss to follow-up or 31 December 2014. Cox proportional hazards regression models were used to assess the association.

MAIN OUTCOME MEASURES: Invasive epithelial ovarian and tubal cancer (WHO 2014) on independent outcome review.

RESULTS: Hysterectomy with conservation of one or both adnexa was reported in 41,912 (20.7%; 41,912/202,506) women. Median follow up was 11.1years (IQR 9.96-12.04), totalling >2.17million women-years. Among women who had undergone hysterectomy, 0.55% (231/41912) were diagnosed with ovarian/tubal cancer, compared with 0.59% (945/160594) of those with intact uterus. Multivariable analysis showed no evidence of an association between hysterectomy and invasive epithelial ovarian/tubal cancer (RR=0.98, 95%CI 0.85-1.13, p=0.765).

CONCLUSIONS: This large cohort study provides further independent validation that hysterectomy is not associated with alteration of invasive epithelial ovarian and tubal cancer risk. This data is important both for clinical counselling and for refining risk prediction models.

PMID:34555263 | DOI:10.1111/1471-0528.16943

J Vet Emerg Crit Care (San Antonio). 2021 Sep 23. doi: 10.1111/vec.13129. Online ahead of print.

ABSTRACT

OBJECTIVE: To measure and compare viscoelastic coagulation in 2 canine blood donor populations using a novel, point-of-care device (VCM Vet Analyzer, VCM).

DESIGN: Cohort study.

SETTING: Academic and commercial veterinary blood banks.

ANIMALS: Non-Greyhounds from community-based blood donor program and Greyhounds from a blood bank colony.

INTERVENTION: Blood was collected from all dogs via direct venipuncture for a complete hemogram, biochemistry, and point-of-care viscoelastic coagulation.

MEASUREMENT AND MAIN RESULTS: All biochemical measurements for all dogs in Group NG (n = 38, non-Greyhounds) and Group G (n = 53, Greyhounds) were within local reference intervals. Hematology data showed significant statistical differences between groups in hemoglobin, RBC, platelet, and WBC concentrations. Group G demonstrated lower maximum clot firmness (MCF) with 17 VCM units (26 VCM units in Group NG), increased lysis with 30 VCM units at 30 minutes (LI30) and 27 VCM units at 45 minutes (LI45) (86 VCM units LI30 and 85 VCM units LI45 in Group NG), and decreased amplitude of 13 VCM units 10 minutes (A10) after clot time (CT) and 6 VCM units 20 minutes after CT (A20) (18 VCM units [A10] and 22 VCM units [A20] in Group NG).

CONCLUSION: This study found differences between healthy Greyhound and non-Greyhound blood donors in measures of clot strength and fibrinolysis as measured by the VCM. Whereas Greyhound have unique hematologic and hemostatic profiles, these measured viscoelastic differences are important to note prior to and following surgical intervention to aid in clinical decision-making if bleeding complications develop.

PMID:34555256 | DOI:10.1111/vec.13129

BJOG. 2021 Sep 23. doi: 10.1111/1471-0528.16944. Online ahead of print.

ABSTRACT

OBJECTIVE: The My Baby’s Movements (MBM) trial aimed to evaluate the impact on stillbirth rates of a multifaceted awareness package (MBM intervention).

DESIGN: Stepped-wedge cluster-randomised controlled trial.

SETTING: Twenty-seven maternity hospitals in Australia and New Zealand.

POPULATION/SAMPLE: Women with a singleton pregnancy without major fetal anomaly at ≥28 weeks’ gestation from August 2016-May 2019.

METHODS: The MBM intervention was implemented at randomly assigned time points with sequential introduction into 8 groups of 3-5 hospitals at four-monthly intervals. Using generalised linear mixed models, the stillbirth rate was compared in the control and intervention periods adjusting for calendar time, study population characteristics, and hospital effects.

OUTCOME MEASURES: Stillbirth at ≥28 weeks’ gestation.

RESULTS: There were 304,850 births with 290,105 meeting inclusion criteria: 150,053 in control and 140,052 in intervention periods. The stillbirth rate was lower (although not statistically significantly) during the intervention compared with the control period (2.2 versus 2.4/1000 births; aOR 1.18, 95% CI 0.93-1.50; p=0.18) The decrease in stillbirth rates was larger across calendar time: 2.7/1000 in the first versus 2.0/1000 in the last 18 months. No increase in secondary outcomes, including obstetric intervention or adverse neonatal outcome, was evident.

CONCLUSION: The MBM intervention did not reduce stillbirths beyond the downward trend over time. Due to low uptake, the role of the intervention remains unclear, though the downward trend across time suggests some benefit in lowering the stillbirth rate. In this study setting, awareness of fetal movements may have reached pregnant women and clinicians prior to implementation of the intervention.

PMID:34555257 | DOI:10.1111/1471-0528.16944

BJOG. 2021 Sep 23. doi: 10.1111/1471-0528.16924. Online ahead of print.

ABSTRACT

OBJECTIVE: Determination of lactate in fetal scalp blood (FBS) during labour has been recognized since the 1970s. The internationally accepted cut-off of >4.8mmol/L indicating fetal acidosis is exclusive for the point-of-care device (POC) LactatePro^TM , which is no longer in production. The aim of this study was to establish a new cut-off for scalp lactate based on neonatal outcomes with the use of StatstripLactate®/StatstripXpress® Lactate system, the only POC designed for hospital use.

DESIGN: Observational Study SETTING: January 2016 to March 2020 labouring women with indication for FBS were prospectively included from seven Swedish and one Australian delivery unit.

POPULATION: Inclusion criteria: singleton pregnancy, vertex presentation, ≥35+0 weeks.

METHOD: Based on the optimal correlation between FBS lactate and cord pH/lactate, only cases with ≤25 minutes from FBS to delivery were included in the final calculations.

MAIN OUTCOME MEASURES: Metabolic acidosis in cord blood defined as pH <7.05 plus BD_ecf >10 mmol/L and/or lactate >10mmol/L.

RESULTS: 3334 women were enrolled of which 799 were delivered within 25 minutes. The areas under the ROC curves (AUC) and corresponding optimal cut-off values were as follows; metabolic acidosis AUC 0.87 (95% CI:0.77-0.97), cut-off 5.7mmol/L; pH <7.0 AUC 0.83(95% CI:0.68-0.97), cut-off 4.6mmol/L; pH <7.05 plus BD_ecf ≥12mmol/L AUC 0.97(95% CI:0.92-1), cut-off 5.8mmol/L; Apgar score <7 at 5^th minute AUC 0.74(95% CI:0.63-0.86), cut-off 5.2mmol/L; and pH <7.10 plus composite neonatal outcome AUC 0.76(95% CI:0.67-0.85), cut-off 4.8mmol/L.

CONCLUSION: A scalp lactate level of <5.2mmol/L using the StatstripLactate®/StatstripXpress® system will safely rule out fetal metabolic acidosis.

PMID:34555249 | DOI:10.1111/1471-0528.16924

Int J Immunogenet. 2021 Sep 23. doi: 10.1111/iji.12559. Online ahead of print.

ABSTRACT

This study was conducted to describe the association between the genetic variation of the recently identified immune checkpoint molecules B7-H3 and B7-H4, and the susceptibility to ankylosing spondylitis (AS). Two single nucleotide polymorphisms (SNPs) of B7-H3 gene and three SNPs of B7-H4 gene were genotyped in 649 AS patients and 646 age- and sex-matched healthy controls. Allele, genotype frequencies and different inheritance models were performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs), and the demographic and clinical parameters of patients were recorded. Our data indicated that B7-H4 rs10801935 and rs3738414 polymorphisms were correlated with AS susceptibility. In the stratification analyses, the minor A allele and GA genotype of B7-H4 rs3738414 increased the risk of AS in male patients (OR = 1.244, 95%CI = 1.026-1.508; OR = 1.453, 95%CI = 1.120-1.886, respectively). However, the association did not reach statistical significance after Bonferroni correction. Furthermore, haplotype analysis revealed that B7-H4 haplotype block TAG was a risk factor for the onset of AS (OR = 1.190, 95%CI = 1.020-1.389). These findings suggested that B7-H4 gene polymorphism may contribute to AS susceptibility in eastern Chinese Han population.

PMID:34555253 | DOI:10.1111/iji.12559

J Diabetes Investig. 2021 Sep 23. doi: 10.1111/jdi.13680. Online ahead of print.

ABSTRACT

AIM: The aim of the present study was to evaluate the placental expression of glucose transporters GLUT-1, GLUT-3, GLUT-8 and GLUT-12 in term pregnancies complicated by well-controlled gestational (GDM) and type 1 pregestational diabetes mellitus (PGDM).

MATERIALS AND METHODS: A total of 103 placental samples were obtained from patients diagnosed with GDM (n=60), PGDM (n=20) and a non-diabetic control group (n=23). Computer-assisted quantitative morphometry of stained placental sections was performed to determine the expression of selected GLUT proteins.

RESULTS: Immunohistochemical techniques used for the identification of GLUT-1, GLUT-3, GLUT-8 and GLUT-12 revealed the presence of all glucose transporters in the placental tissue. Morphometric evaluation performed for the vascular density-matched placental samples demonstrated a significant increase in the expression of GLUT-1 protein in patients with PGDM as compared to GDM and control groups (p<.05). With regard to the expression of the other GLUT isoforms, no statistically significant differences were observed between patients from the diabetic and control populations. Positive correlations between fetal birth-weight and the expression of GLUT-1 protein in the PGDM group (rho=.463, p<.05) and GLUT-12 in the control group (rho=.481, p<.05) were noted.

CONCLUSIONS: In term pregnancies complicated by well-controlled GDM/PGDM expression of transporters GLUT-3, GLUT-8 and GLUT-12 in the placenta remains unaffected. Increased expression of GLUT-1 among women with type 1 PGDM may contribute to higher rate of macrosomic fetuses in this population.

PMID:34555239 | DOI:10.1111/jdi.13680

J Magn Reson Imaging. 2021 Sep 23. doi: 10.1002/jmri.27928. Online ahead of print.

ABSTRACT

BACKGROUND: Liver iron concentration (LIC) measured by MRI has become the clinical reference standard for managing iron overload in chronically transfused patients. Transverse relaxivity (R₂ or R₂^* ) measurements are converted to LIC units using empirically derived calibration curves.

HYPOTHESIS: That flip angle (FA) error due to B₁⁺ spatial heterogeneity causes significant LIC quantitation error. B₁⁺ scale (b₁ , [FA_actual /FA_specified ]) variation is a major problem at 3 T which could reduce the accuracy of transverse relaxivity measurements.

STUDY TYPE: Prospective.

POPULATION: Forty-seven subjects with chronic transfusional iron overload undergoing clinically indicated LIC assessment.

FIELD STRENGTH/SEQUENCE: 5 T/3 T dual-repetition time B₁⁺ mapping sequence ASSESSMENT: We quantified the average/standard deviation b₁ in the right and left lobes of the liver from B₁⁺ maps acquired at 1.5 T and 3 T. The impact of b₁ variation on spin echo LIC estimates was determined using a Monte Carlo model.

STATISTICAL TESTS: Mean, median, and standard deviation in whole liver and right and left lobes; two-sided t-test between whole-liver b₁ means.

RESULTS: Average b₁ within the liver was 99.3% ± 12.3% at 1.5 T versus 69.6% ± 14.6% at 3 T and was independent of iron burden (P < 0.05). Monte Carlo simulations demonstrated that b₁ systematically increased R₂ estimates at lower LIC (<~25 mg/g at 1.5 T, <~15 mg/g at 3 T) but flattened or even inverted the R₂ -LIC relationship at higher LIC (≥~25 mg/g to 1.5 T, ≥~15 mg/g to 3 T); changes in the R₂ -LIC relationship were symmetric with respect to over and under excitation and were similar at 1.5 T and 3 T (for the same R₂ value). The R₂^* -LIC relationship was independent of b₁ .

CONCLUSION: Spin echo R₂ measurement of LIC at 3 T is error-prone without correction for b₁ errors. The impact of b₁ error on current 1.5 T spin echo-based techniques for LIC quantification is large enough to introduce measurable intersubject variability but the in vivo effect size needs a dedicated validation study.

LEVEL OF EVIDENCE: 1.

TECHNICAL EFFICACY STAGE: 2.

PMID:34555245 | DOI:10.1002/jmri.27928