Category: Statistics

PLoS Comput Biol. 2022 Aug 19;18(8):e1009421. doi: 10.1371/journal.pcbi.1009421. Online ahead of print.

ABSTRACT

Cancer is a complex disease with usually multiple disease mechanisms. Target combination is a better strategy than a single target in developing cancer therapies. However, target combinations are generally more difficult to be predicted. Current CRISPR-cas9 technology enables genome-wide screening for potential targets, but only a handful of genes have been screend as target combinations. Thus, an effective computational approach for selecting candidate target combinations is highly desirable. Selected target combinations also need to be translational between cell lines and cancer patients. We have therefore developed DSCN (double-target selection guided by CRISPR screening and network), a method that matches expression levels in patients and gene essentialities in cell lines through spectral-clustered protein-protein interaction (PPI) network. In DSCN, a sub-sampling approach is developed to model first-target knockdown and its impact on the PPI network, and it also facilitates the selection of a second target. Our analysis first demonstrated a high correlation of the DSCN sub-sampling-based gene knockdown model and its predicted differential gene expressions using observed gene expression in 22 pancreatic cell lines before and after MAP2K1 and MAP2K2 inhibition (R2 = 0.75). In DSCN algorithm, various scoring schemes were evaluated. The ‘diffusion-path’ method showed the most significant statistical power of differentialting known synthetic lethal (SL) versus non-SL gene pairs (P = 0.001) in pancreatic cancer. The superior performance of DSCN over existing network-based algorithms, such as OptiCon and VIPER, in the selection of target combinations is attributable to its ability to calculate combinations for any gene pairs, whereas other approaches focus on the combinations among optimized regulators in the network. DSCN’s computational speed is also at least ten times fast than that of other methods. Finally, in applying DSCN to predict target combinations and drug combinations for individual samples (DSCNi), DSCNi showed high correlation between target combinations predicted and real synergistic combinations (P = 1e-5) in pancreatic cell lines. In summary, DSCN is a highly effective computational method for the selection of target combinations.

PMID:35984840 | DOI:10.1371/journal.pcbi.1009421

PLoS One. 2022 Aug 19;17(8):e0273383. doi: 10.1371/journal.pone.0273383. eCollection 2022.

ABSTRACT

Neonatal necrotizing enterocolitis (NEC) occurs worldwide and is a major source of neonatal morbidity and mortality. Researchers have developed many methods for predicting NEC diagnosis and prognosis. However, most people use statistical methods to select features, which may ignore the correlation between features. In addition, because they consider a small dimension of characteristics, they neglect some laboratory parameters such as white blood cell count, lymphocyte percentage, and mean platelet volume, which could be potentially influential factors affecting the diagnosis and prognosis of NEC. To address these issues, we include more perinatal, clinical, and laboratory information, including anemia-red blood cell transfusion and feeding strategies, and propose a ridge regression and Q-learning strategy based bee swarm optimization (RQBSO) metaheuristic algorithm for predicting NEC diagnosis and prognosis. Finally, a linear support vector machine (linear SVM), which specializes in classifying high-dimensional features, is used as a classifier. In the NEC diagnostic prediction experiment, the area under the receiver operating characteristic curve (AUROC) of dataset 1 (feeding intolerance + NEC) reaches 94.23%. In the NEC prognostic prediction experiment, the AUROC of dataset 2 (medical NEC + surgical NEC) reaches 91.88%. Additionally, the classification accuracy of the RQBSO algorithm on the NEC dataset is higher than the other feature selection algorithms. Thus, the proposed approach has the potential to identify predictors that contribute to the diagnosis of NEC and stratification of disease severity in a clinical setting.

PMID:35984833 | DOI:10.1371/journal.pone.0273383

PLoS One. 2022 Aug 19;17(8):e0273297. doi: 10.1371/journal.pone.0273297. eCollection 2022.

ABSTRACT

BACKGROUND: Preconception care is highly important in reducing a number of adverse pregnancy outcomes and helps to improve maternal health. Preconception care optimizes women’s health and improves pregnancy outcomes. It is a cost-effective first-line preventive strategy for birth defects. However, preconception care utilization in Ethiopia was very low. Studies on these issues are limited in Ethiopia in general and in Mizan-Aman town in particular.

OBJECTIVE: To assess preconception care utilization and associated factors among reproductive age women in Mizan-Aman town, Bench-Sheko Zone, Southwest Ethiopia.

METHODS: A community based cross-sectional study design was employed from April 16 to May 26, 2020 in Mizan-Aman town. The total study participants were 624 reproductive age women. Data were collected by using pre-tested interviewer administered questionnaires and entered into Epi-data version 3.1 then exported to STATA version 14 and analyzed accordingly. Univeriate and Bivariable analysis was done by analysis of variance (ANOVA) and independent t-test. Multivariable statistical analysis using generalized linear regression model (GLM) approach was used to classify factors of preconception care utilization. Since our response variable is measured in terms of count variable, we used a Poisson regression model with a log link function. Finally, Statistical significance between dependent and independent variables were assessed by odds ratios and 95% confidence intervals.

RESULTS: Overall, 28.6% of the women receipt atleast one item of preconception care while only 1.5% were taken the whole recommended components of preconception care services. The most common item received in the study area was taking micronutrient supplementation (18.5%). Age of women, educational status, husbands educational status, husbands occupation, wealth status, distance from the health facility, waiting time to get services, planning to pregnancy, age at first pregnancy, previous ANC use, Previous PNC use, adverse pregnancy experience, women’s knowledge of preconception care, and attitude on preconception care were determinants of preconception service utilization.

CONCLUSIONS: Preconception care component utilization was lower as compare with recommended service with different disparities. Multipurpose tailored strategies which incorporate a woman with no formal education, poor knwledge on preconception care,never take maternal services previously and distant from health facility could improve preconception care service utilization. Advocative strategies on preconception care component and planning pregnancy may elicite more women to use the services of preconception care.

PMID:35984828 | DOI:10.1371/journal.pone.0273297

PLoS One. 2022 Aug 19;17(8):e0272936. doi: 10.1371/journal.pone.0272936. eCollection 2022.

ABSTRACT

Rational use of medicine (RUM) for all medical conditions is crucial in attaining quality of healthcare and medical care for patients and the community as a whole. However, the actual medicine use pattern is not consistent with that of the World Health Organization (WHO) guideline and is often irrational in many healthcare setting, particularly in developing countries. Thus, the aim of the study was to evaluate rational medicine use based on WHO/International Network of Rational Use of Drugs (INRUD) core drug use indicators in Eritrean National and Regional Referral hospitals. A descriptive and cross-sectional approach was used to conduct the study. A sample of 4800 (600 from each hospital) outpatient prescriptions from all disciplines were systematically reviewed to assess the prescribing indicators. A total of 1600 (200 from each hospital) randomly selected patients were observed for patient indicators and all pharmacy personnel were interviewed to obtain the required information for facility-specific indicators. Data were collected using retrospective and prospective structured observational checklist between September and January, 2018. Descriptive statistics, Welch’s robust test of means and Duncan’s post hoc test were performed using IBM SPSS (version 22). The average number of medicines per prescription was 1.78 (SD = 0.79). Prescriptions that contained antibiotic and injectable were 54.50% and 6.60%, respectively. Besides, the percentage of medicines prescribed by generic name and from an essential medicine list (EML) was 98.86% and 94.73%, respectively. The overall average consultation and dispensing time were 5.46 minutes (SD = 3.86) and 36.49 seconds (SD = 46.83), respectively. Moreover, 87.32% of the prescribed medicines were actually dispensed. Only 68.24% of prescriptions were adequately labelled and 78.85% patients knew about the dosage of the medicine(s) in their prescriptions. More than half (66.7%) of the key medicines were available in stock. All the hospitals used the national medicine list but none of them had their own medicine list or guideline. In conclusion, majority of WHO stated core drug use indicators were not fulfilled by the eight hospitals. The results of this study suggest that a mix of policies needs to be implemented to make medicines more accessible and used in a more rational way.

PMID:35984825 | DOI:10.1371/journal.pone.0272936

Global Spine J. 2022 Aug 19:21925682221120400. doi: 10.1177/21925682221120400. Online ahead of print.

ABSTRACT

STUDY DESIGN: Retrospective cohort.

OBJECTIVE: Lateral lumbar interbody fusion (LLIF) commonly involves a transpsoas approach. Despite the association between LLIF, postoperative iliopsoas weakness, and iatrogenic neuropraxia, no study has yet examined the effect of psoas or multifidus muscle quality on patient-reported outcomes (PROs).

METHODS: This study retrospectively reviewed patients who underwent LLIF with 1-year minimum follow-up. Psoas and multifidus muscle qualities were graded on preoperative magnetic resonance imaging using two validated classification systems for muscle atrophy. Average muscle quality was calculated as the mean score from all levels (L1-2 through L5-S1). Univariate and multivariate statistics were utilized to investigate the relationship between psoas/multifidus muscle quality and preoperative, 6-weeks postoperative, and final postoperative PROs.

RESULTS: 74 patients (110 levels) with a mean follow-up of 18.71 ± 8.02 months were included for analysis. Greater multifidus atrophy was associated with less improvement on ODI, SF12, and VR12 (P < .05) on univariate analysis. On multivariate analysis, worse multifidus atrophy predicted less improvement on SF12 and VR12 (P < .05).

CONCLUSION: Despite the direct manipulation of the psoas muscle inherent to LLIF, preoperative psoas muscle quality did not affect postoperative outcomes. Rather, the extent of preoperative multifidus fatty infiltration and atrophy was more likely to predict postoperative pain and disability. These findings suggest that multifidus atrophy may be more pertinent than psoas atrophy in its association with patient-reported outcome measures after LLIF.

PMID:35984823 | DOI:10.1177/21925682221120400

PLoS One. 2022 Aug 19;17(8):e0272807. doi: 10.1371/journal.pone.0272807. eCollection 2022.

ABSTRACT

INTRODUCTION: In observational studies, venous thromboembolism (VTE) has been associated with Cushing’s syndrome and with persistent mental stress, two conditions associated with higher cortisol levels. However, it remains unknown whether high cortisol levels within the usual range are causally associated with VTE risk. We aimed to assess the association between plasma cortisol levels and VTE risk using Mendelian randomization.

METHODS: Three genetic variants in the SERPINA1/SERPINA6 locus (rs12589136, rs11621961 and rs2749527) were used to proxy plasma cortisol. The associations of the cortisol-associated genetic variants with VTE were acquired from the INVENT (28 907 cases and 157 243 non-cases) and FinnGen (6913 cases and 169 986 non-cases) consortia. Corresponding data for VTE subtypes were available from the FinnGen consortium and UK Biobank. Two-sample Mendelian randomization analyses (inverse-variance weighted method) were performed.

RESULTS: Genetic predisposition to higher plasma cortisol levels was associated with a reduced risk of VTE (odds ratio [OR] per one standard deviation increment 0.73, 95% confidence interval [CI] 0.62-0.87, p<0.001). The association was stronger for deep vein thrombosis (OR 0.69, 95% CI 0.55-0.88, p = 0.003) than for pulmonary embolism which did not achieve statistical significance (OR 0.83, 95% CI 0.63-1.09, p = 0.184). Adjusting for genetically predicted systolic blood pressure inverted the direction of the point estimate for VTE, although the resulting CI was wide (OR 1.06, 95% CI 0.70-1.61, p = 0.780).

CONCLUSIONS: This study provides evidence that genetically predicted plasma cortisol levels in the high end of the normal range are associated with a decreased risk of VTE and that this association may be mediated by blood pressure. This study has implications for the planning of observational studies of cortisol and VTE, suggesting that blood pressure traits should be measured and accounted for.

PMID:35984822 | DOI:10.1371/journal.pone.0272807

PLoS One. 2022 Aug 19;17(8):e0273427. doi: 10.1371/journal.pone.0273427. eCollection 2022.

ABSTRACT

The purpose of the present study was to examine differences in game-related statistical parameters between National Basketball Association (NBA) regular and post-season competitive periods and to determine which variables have the greatest contribution in discriminating between winning and losing game outcomes. The data scraping technique was used to obtain publicly available NBA game-related statistics over a three-year span (2016-2019). The total number of games examined in the present investigation was 3933 (3690 regular season and 243 post-season games). Despite small to moderate effect sizes, the findings suggest that NBA teams’ style of play (i.e., tactical strategies) changes when transitioning from the regular to post-season competitive period. It becomes more conservative (i.e., fewer field goal attempts, assists, steals, turnovers, and points scored), most likely due to greater defensive pressure. Discriminant function analysis correctly classified winning and losing game outcomes during the regular and post-season competitive periods in 82.8% and 87.2% of cases, respectively. Two key game-related statistics capable of discriminating between winning and losing game outcomes were field goal percentage and defensive rebounding, accounting for 13.6% and 14.2% of the total percentage of explained variance during the regular season and 11.5% and 14.7% during post-season competitive periods. Also, overall shooting efficiency (i.e., free-throw, 2-point, and 3-point combined) accounted for 23-26% of the total percentage of explained variance.

PMID:35984813 | DOI:10.1371/journal.pone.0273427

PLoS Negl Trop Dis. 2022 Aug 19;16(8):e0010709. doi: 10.1371/journal.pntd.0010709. eCollection 2022 Aug.

ABSTRACT

BACKGROUND: Infections with Ascaris lumbricoides and Trichuris trichiura remain significant contributors to the global burden of neglected tropical diseases. Infection may in particular affect child development as they are more likely to be infected with T. trichiura and/or A. lumbricoides and to carry higher worm burdens than adults. Whilst the impact of heavy infections are clear, the effects of moderate infection intensities on the growth and development of children remain elusive. Field studies are confounded by a lack of knowledge of infection history, nutritional status, presence of co-infections and levels of exposure to infective eggs. Therefore, animal models are required. Given the physiological similarities between humans and pigs but also between the helminths that infect them; A. suum and T. suis, growing pigs provide an excellent model to investigate the direct effects of Ascaris spp. and Trichuris spp. on weight gain.

METHODS AND RESULTS: We employed a trickle infection protocol to mimic natural co-infection to assess the effect of infection intensity, determined by worm count (A. suum) or eggs per gram of faeces (A. suum and T. suis), on weight gain in a large pig population (n = 195) with variable genetic susceptibility. Pig body weights were assessed over 14 weeks. Using a post-hoc statistical approach, we found a negative association between weight gain and T. suis infection. For A. suum, this association was not significant after adjusting for other covariates in a multivariable analysis. Estimates from generalized linear mixed effects models indicated that a 1 kg increase in weight gain was associated with 4.4% (p = 0.00217) decrease in T. suis EPG and a 2.8% (p = 0.02297) or 2.2% (p = 0.0488) decrease in A. suum EPG or burden, respectively.

CONCLUSIONS: Overall this study has demonstrated a negative association between STH and weight gain in growing pigs but also that T. suis infection may be more detrimental that A. suum on growth.

PMID:35984809 | DOI:10.1371/journal.pntd.0010709

Transl Vis Sci Technol. 2022 Aug 1;11(8):19. doi: 10.1167/tvst.11.8.19.

ABSTRACT

PURPOSE: Phenotype alterations of the retinal pigment epithelium (RPE) are a main characteristic of age-related macular degeneration (AMD). Individual RPE cell shape descriptors may help to delineate healthy from AMD-affected cells in early disease stages.

METHODS: Twenty-two human RPE flatmounts (7 eyes with AMD [early, 3; geographic atrophy, 1; neovascular, 3); 15 unaffected eyes [8 aged ≤51 years; 7 aged >80 years)] were imaged at the fovea, perifovea, and near periphery (predefined sample locations) using a laser-scanning confocal fluorescence microscope. RPE cell boundaries were manually marked with computer assistance. For each cell, 11 shape descriptors were calculated and correlated with donor age, cell autofluorescence (AF) intensity, and retinal location. Statistical analysis was performed using an ensemble classifier based on logistic regression.

RESULTS: In AMD, RPE was altered at all locations (most pronounced at the fovea), with area, solidity, and form factor being the most discriminatory descriptors. In the unaffected macula, aging had no significant effect on cell shape factors; however, with increasing distance to the fovea, area, solidity, and convexity increased while form factor decreased. Reduced AF in AMD was significantly associated with decreased roundness and solidity.

CONCLUSIONS: AMD results in an altered RPE with enlarged and deformed cells that could precede clinically visible lesions and thus serve as early biomarkers for AMD onset. Our data may also help guide the interpretation of RPE morphology in in vivo studies utilizing high-resolution single-cell imaging.

TRANSLATIONAL RELEVANCE: Our histologic RPE cell shape data have the ability to identify robust biomarkers for the early detection of AMD-affected cells, which also could serve as a basis for automated segmentation of RPE sheets.

PMID:35984669 | DOI:10.1167/tvst.11.8.19

JAMA Netw Open. 2022 Aug 1;5(8):e2227779. doi: 10.1001/jamanetworkopen.2022.27779.

ABSTRACT

IMPORTANCE: Various model reporting guidelines have been proposed to ensure clinical prediction models are reliable and fair. However, no consensus exists about which model details are essential to report, and commonalities and differences among reporting guidelines have not been characterized. Furthermore, how well documentation of deployed models adheres to these guidelines has not been studied.

OBJECTIVES: To assess information requested by model reporting guidelines and whether the documentation for commonly used machine learning models developed by a single vendor provides the information requested.

EVIDENCE REVIEW: MEDLINE was queried using machine learning model card and reporting machine learning from November 4 to December 6, 2020. References were reviewed to find additional publications, and publications without specific reporting recommendations were excluded. Similar elements requested for reporting were merged into representative items. Four independent reviewers and 1 adjudicator assessed how often documentation for the most commonly used models developed by a single vendor reported the items.

FINDINGS: From 15 model reporting guidelines, 220 unique items were identified that represented the collective reporting requirements. Although 12 items were commonly requested (requested by 10 or more guidelines), 77 items were requested by just 1 guideline. Documentation for 12 commonly used models from a single vendor reported a median of 39% (IQR, 37%-43%; range, 31%-47%) of items from the collective reporting requirements. Many of the commonly requested items had 100% reporting rates, including items concerning outcome definition, area under the receiver operating characteristics curve, internal validation, and intended clinical use. Several items reported half the time or less related to reliability, such as external validation, uncertainty measures, and strategy for handling missing data. Other frequently unreported items related to fairness (summary statistics and subgroup analyses, including for race and ethnicity or sex).

CONCLUSIONS AND RELEVANCE: These findings suggest that consistent reporting recommendations for clinical predictive models are needed for model developers to share necessary information for model deployment. The many published guidelines would, collectively, require reporting more than 200 items. Model documentation from 1 vendor reported the most commonly requested items from model reporting guidelines. However, areas for improvement were identified in reporting items related to model reliability and fairness. This analysis led to feedback to the vendor, which motivated updates to the documentation for future users.

PMID:35984654 | DOI:10.1001/jamanetworkopen.2022.27779