Tag: statistics

PLoS One. 2022 Nov 3;17(11):e0276365. doi: 10.1371/journal.pone.0276365. eCollection 2022.

ABSTRACT

People of all ages and genders utilize herbal medicine to treat varieties of problems all around the world. The accumulation of Cd and Cr in therapeutic herbs (Adansonia digitata, Psidium guajava, and Carica papaya) can lead to a variety of health complications. These leaf extracts are used to treat varieties of ailments, including cancer, in the northern Nigerian states of Borno, Jigawa, and Kano. The researchers employed high-resolution continuous source atomic absorption spectrometry. The statistical parameters such as mean, range, minimum and maximum were computed along with one-way analysis of variance (ANOVA) to assess activity concentrations of Major Chemical Carcinogens (MCCs) in the herb extracts from the three states. The result demonstrated substantial statistical variation in the concentration of Chromium between groups with C. papaya (F = 190.683, p = 0.000), P. guajava (F = 5.698, p = 0.006), A. digitata (F = 243.154, p = 0.000). The post hoc test revealed that the C. papaya and A. digitata observed concentrations were statistically significant across the three states (p = 0.000). It was observed that there is no statistically significant difference between concentrations of the extracts between Kano and Borno states for P. guajava (p = 0.686). For Cd, the one-way ANOVA showed significant statistically variation in the concentration between groups with C. papaya (F = 77.393, p = 0.000), P. guajava (F = 4.496, p = 0.017), A. digitata (F = 69.042, p = 0.000). The post hoc test with multiple comparisons revealed that the activity concentration of all extracts was statistically significant across the three states (p<0.05). The target risk quotient (THQ) for Cd was more than unity in A. digitata and C. papaya, except for P. guajava from Borno State. The probable cancer risk was observed for consumption of plant extracts as a result of Cr and Cd.

PMID:36327284 | DOI:10.1371/journal.pone.0276365

PLoS One. 2022 Nov 3;17(11):e0277079. doi: 10.1371/journal.pone.0277079. eCollection 2022.

ABSTRACT

Atmospheric air temperature is the most crucial metrological parameter. Despite its influence on multiple fields such as hydrology, the environment, irrigation, and agriculture, this parameter describes climate change and global warming quite well. Thus, accurate and timely air temperature forecasting is essential because it provides more important information that can be relied on for future planning. In this study, four Data-Driven Approaches, Support Vector Regression (SVR), Regression Tree (RT), Quantile Regression Tree (QRT), ARIMA, Random Forest (RF), and Gradient Boosting Regression (GBR), have been applied to forecast short-, and mid-term air temperature (daily, and weekly) over North America under continental climatic conditions. The time-series data is relatively long (2000 to 2021), 70% of the data are used for model calibration (2000 to 2015), and the rest are used for validation. The autocorrelation and partial autocorrelation functions have been used to select the best input combination for the forecasting models. The quality of predicting models is evaluated using several statistical measures and graphical comparisons. For daily scale, the SVR has generated more accurate estimates than other models, Root Mean Square Error (RMSE = 3.592°C), Correlation Coefficient (R = 0.964), Mean Absolute Error (MAE = 2.745°C), and Thiels’ U-statistics (U = 0.127). Besides, the study found that both RT and SVR performed very well in predicting weekly temperature. This study discovered that the duration of the employed data and its dispersion and volatility from month to month substantially influence the predictive models’ efficacy. Furthermore, the second scenario is conducted using the randomization method to divide the data into training and testing phases. The study found the performance of the models in the second scenario to be much better than the first one, indicating that climate change affects the temperature pattern of the studied station. The findings offered technical support for generating high-resolution daily and weekly temperature forecasts using Data-Driven Methodologies.

PMID:36327280 | DOI:10.1371/journal.pone.0277079

PLoS One. 2022 Nov 3;17(11):e0276763. doi: 10.1371/journal.pone.0276763. eCollection 2022.

ABSTRACT

BACKGROUND: Coronavirus disease has spread worldwide since late 2019. Vaccination is critical in controlling this pandemic. However, vaccine acceptance among pregnant women is not well-studied. Therefore, this study aimed to assess the COVID-19 vaccine acceptance and associated factors among pregnant women attending antenatal care clinics in Gondar town, Northwest Ethiopia.

METHODS: An institution-based cross-sectional study was conducted among pregnant women attending antenatal care clinics at Gondar town, Northwest Ethiopia, 2021. About 510 study subjects were selected using a systematic random sampling technique from August 25 to September 10/2021. Data collection was done by using an interviewer-administered, structured questionnaire. Epi-info 7.2 was used to enter data and then exported to SPSS version 25 software for analysis. Bivariable and multivariable binary logistic regression models were used to identify factors associated with the outcome variable. Variables with a p-value < 0.2 in the bivariable analysis were entered into the multivariable analysis to control for possible confounders. Statistical significance is determined using an adjusted odds ratio and 95% confidence interval (CI) at a p-value of < 0.05.

RESULTS: Of 510 participants, 211 (41.4%) were willing to take COVID-19 vaccines. Maternal age ≥ 35 years (AOR: 5.678, 95% CI: 1.775-18.166), having contact history with COVID-19 diagnosed people (AOR: 7.724, 95% CI: 2.183, 27.329), having a pre-existing chronic disease (AOR: 3.131, 95% CI: 1.700-5.766), good knowledge about COVID-19 vaccine (AOR: 2.391, 95% CI: 1.144, 4.998) and good attitude towards COVID-19 vaccine (AOR: 2.128, 95% CI: 1.348) were significantly associated with the outcome variable.

CONCLUSIONS: The willingness to take COVID-19 vaccine among pregnant mothers was low. Age, contact history with COVID-19 diagnosed people, chronic disease, knowledge, and attitude towards COVID-19 vaccine were factors associated with COVID-19 vaccine willingness. To enhance the COVID-19 vaccine acceptance, the government with different stakeholders should strengthen public education about the importance of getting COVID-19 vaccine.

PMID:36327276 | DOI:10.1371/journal.pone.0276763

PLoS One. 2022 Nov 3;17(11):e0276613. doi: 10.1371/journal.pone.0276613. eCollection 2022.

ABSTRACT

BACKGROUND: First-time mothers are prone to prolonged labor, defined as the crossing of partograph alert or action lines. Prolonged labor may occur among as many as one out of five women, and is associated with a range of adverse birth outcomes. Oxytocin is the standard treatment for prolonged labor, but has a narrow therapeutic window, several adverse effects and limited efficacy. Despite poor evidence, labor wards often use antispasmodic agents to treat prolonged labor. The antispasmodic drug butylscopolamine bromide (Buscopan®) may shorten duration of labor, but studies on prevention of prolonged labor are lacking. In this randomized double-blind placebo-controlled clinical trial, we aim to evaluate the effect of butylscopolamine bromide on duration of labor in first-time mothers showing first signs of slow labor progress by crossing the World Health Organization partograph alert line.

METHODS AND ANALYSIS: The study is a single center study at Oslo University Hospital, Oslo, Norway. We will recruit 250 primiparous women with spontaneous labor start at term. Women are included in the first stage of labor if they show signs of slow labor progress, defined as the crossing of the partograph alert line with a cervical dilation between 3-9 cm. Participants are randomized 1:1 to either 20 mg intravenous butylscopolamine bromide or intravenous placebo (1 mL sodium chlorine 9 mg/mL). We considered a mean difference of 60 minutes in labor duration clinically relevant. The primary outcome is duration of labor from the provision of the investigational medicinal product to vaginal delivery. The secondary outcomes include change in labor pain, use of oxytocin augmentation, delivery mode, and maternal birth experience. The primary data for the statistical analysis will be the full analysis set and will occur on completion of the study as per the prespecified statistical analysis plan. The primary outcome will be analyzed using Weibull regression, and we will treat cesarean delivery as a censoring event.

PMID:36327275 | DOI:10.1371/journal.pone.0276613

PLoS One. 2022 Nov 3;17(11):e0251470. doi: 10.1371/journal.pone.0251470. eCollection 2022.

ABSTRACT

IMPORTANCE: The rapid proliferation of COVID-19 has left governments scrambling, and several data aggregators are now assisting in the reporting of county cases and deaths. The different variables affecting reporting (e.g., time delays in reporting) necessitates a well-documented reliability study examining the data methods and discussion of possible causes of differences between aggregators.

OBJECTIVE: To statistically evaluate the reliability of COVID-19 data across aggregators using case fatality rate (CFR) estimates and reliability statistics.

DESIGN, SETTING, AND PARTICIPANTS: Cases and deaths were collected daily by volunteers via state and local health departments, as primary sources and newspaper reports, as secondary sources. In an effort to begin comparison for reliability statistical analysis, BroadStreet collected data from other COVID-19 aggregator sources, including USAFacts, Johns Hopkins University, New York Times, The COVID Tracking Project.

MAIN OUTCOMES AND MEASURES: COVID-19 cases and death counts at the county and state levels.

RESULTS: Lower levels of inter-rater agreement were observed across aggregators associated with the number of deaths, which manifested itself in state level Bayesian estimates of COVID-19 fatality rates.

CONCLUSIONS AND RELEVANCE: A national, publicly available data set is needed for current and future disease outbreaks and improved reliability in reporting.

PMID:36327273 | DOI:10.1371/journal.pone.0251470

PLoS One. 2022 Nov 3;17(11):e0275532. doi: 10.1371/journal.pone.0275532. eCollection 2022.

ABSTRACT

In this paper, we propose a portmanteau test for whether a graph-structured network dataset without replicates exhibits autocorrelation across units connected by edges. Specifically, the well known Ljung-Box test for serial autocorrelation of time series data is generalized to the network setting using a specially derived central limit theorem for a weakly stationary random field. The asymptotic distribution of the test statistic under the null hypothesis of no autocorrelation is shown to be chi-squared, yielding a simple and easy-to-implement procedure for testing graph-structured autocorrelation, including spatial and spatial-temporal autocorrelation as special cases. Numerical simulations are carried out to demonstrate and confirm the derived asymptotic results. Convergence is found to occur quickly depending on the number of lags included in the test statistic, and a significant increase in statistical power is also observed relative to some recently proposed permutation tests. An example application is presented by fitting spatial autoregressive models to the distribution of COVID-19 cases across counties in New York state.

PMID:36327270 | DOI:10.1371/journal.pone.0275532

PLoS One. 2022 Nov 3;17(11):e0277230. doi: 10.1371/journal.pone.0277230. eCollection 2022.

ABSTRACT

BACKGROUND: External eye infection caused by bacteria can lead to reduced vision and blindness. Therefore, pathogen isolation and antimicrobial susceptibility testing are vital for the prevention and control of ocular diseases.

OBJECTIVE: The main aim of this study was to assess bacterial isolates, their antimicrobial susceptibility pattern, and associated factors of external ocular infection (EOI) among patients attended eye clinic at Debre Markos Comprehensive Specialized Hospital (DMCSH), Northwest Ethiopia.

METHODS: We conducted a cross-sectional study in patients with external ocular infections from January 1, 2021, to June 30, 2021, at DMCSH. Socio-demographic and clinical data were collected using semi-structured questionnaires. Following standard protocols, external ocular swabs were collected and inoculated onto blood agar, chocolate agar, MacConkey agar and mannitol salt agar (MSA). Finally, bacterial isolates were identified by Gram stain, colony morphology, and biochemical tests. Antimicrobial susceptibility testing was done by using the modified Kirby-Bauer disk diffusion technique according to Clinical and Laboratory Standards Institute (CLSI) guideline. Cleaned and coded data were entered into EpiData version 4.2 software and exported to Statistical Packages for Social Sciences (SPSS) version 22 for analysis. Bivariate logistic regression was applied to investigate the association between predictors and outcome variables. P-values ≤ 0.05 with 95% confidence interval were considered statistically significant.

RESULTS: Two hundred seven study participants were enrolled in this study. More than half of them (57.5%, 119/207) were males, and 37.7% (78/207) of them were ≥ 65 years old. A total of 130 (62.8%) bacterial isolates were identified, with Gram-positive bacteria accounting for 78.5% (102/130) of the isolates. Staphylococcus aureus was the most common isolate with a 46.2% (60/130) prevalence. Ciprofloxacin was comparatively effective against Gram-positive and Gram-negative bacteria. The prevalence of culture-confirmed bacteria was significantly associated with age groups 15-24 (AOR: 9.18, 95%CI: 1.01-82.80; P = 0.049) and 25-64 (AOR: 7.47, 95%CI: 1.06-52.31; P = 0.043). Being farmer (AOR: 5.33, 95% CI: 1.04-37.33; P = 0.045), previous history of eye surgery (AOR: 5.39, 95% CI: 1.66-17.48; P = 0.005), less frequency of face washing (AOR: 5.32, 95% CI: 1.31-7.23; P = 0.010) and face washing once a day (AOR: 3.07, 95% CI: 1.13-25.13; P = 0.035) were also significantly associated with the prevalence of culture-confirmed bacteria.

CONCLUSION: The prevalence of culture-confirmed bacteria among patients with EOI was high in the study area. A considerable proportion of bacterial isolates exhibited mono and/or multi-drug resistance. Age (15-64 years), being farmer, previous history of eye surgery and less frequency of face washing were significantly associated with the prevalence of culture-confirmed bacteria. Bacterial isolation and antibiotic susceptibility testing should be routinely performed in the study area to combat the emergence of antibiotic resistance.

PMID:36327266 | DOI:10.1371/journal.pone.0277230

PLoS One. 2022 Nov 3;17(11):e0276695. doi: 10.1371/journal.pone.0276695. eCollection 2022.

ABSTRACT

In many practical situations, there is an interest in modeling bounded random variables in the interval (0, 1), such as rates, proportions, and indexes. It is important to provide new continuous models to deal with the uncertainty involved by variables of this type. This paper proposes a new quantile regression model based on an alternative parameterization of the unit Burr XII (UBXII) distribution. For the UBXII distribution and its associated regression, we obtain score functions and observed information matrices. We use the maximum likelihood method to estimate the parameters of the regression model, and conduct a Monte Carlo study to evaluate the performance of its estimates in samples of finite size. Furthermore, we present general diagnostic analysis and model selection techniques for the regression model. We empirically show its importance and flexibility through an application to an actual data set, in which the dropout proportion of Brazilian undergraduate animal sciences courses is analyzed. We use a statistical learning method for comparing the proposed model with the beta, Kumaraswamy, and unit-Weibull regressions. The results show that the UBXII regression provides the best fit and the most accurate predictions. Therefore, it is a valuable alternative and competitive to the well-known regressions for modeling double-bounded variables in the unit interval.

PMID:36327245 | DOI:10.1371/journal.pone.0276695

PLoS One. 2022 Nov 3;17(11):e0277098. doi: 10.1371/journal.pone.0277098. eCollection 2022.

ABSTRACT

OBJECTIVE: To determine the expression profile of microRNAs in the peripheral blood of pregnant women with preterm premature rupture of membranes (PPROM) compared to that of healthy pregnant women.

STUDY DESIGN: This was a pilot study with case-control design in pregnant patients enrolled between January 2017 and June 2019. Patients with healthy pregnancies and those affected by PPROM between 20- and 33+6 weeks of gestation were matched by gestational age and selected for inclusion to the study. Patients were excluded for multiple gestation and presence of a major obstetrical complication such as preeclampsia, diabetes, fetal growth restriction and stillbirth. A total of ten (n = 10) controls and ten (n = 10) patients with PPROM were enrolled in the study. Specimens were obtained before administration of betamethasone or intravenous antibiotics. MicroRNA expression was analyzed for 800 microRNAs in each sample using the NanoString nCounter Expression Assay. Differential expression was calculated after normalization and log2- transformation using the false discovery rate (FDR) method at an alpha level of 5%.

RESULTS: Demographic characteristics were similar between the two groups. Of the 800 miRNAs analyzed, 116 were differentially expressed after normalization. However, only four reached FDR-adjusted statistical significance. Pregnancies affected by PPROM were characterized by upregulation of miR-199a-5p, miR-130a-3p and miR-26a-5p and downregulation of miR-513b-5p (FDR adjusted p-values <0.05). The differentially expressed microRNAs participate in pathways associated with altered collagen and matrix metalloprotease expression in the extracellular matrix.

CONCLUSION: Patients with PPROM have a distinct peripheral blood microRNA profile compared to healthy pregnancies as measured by the NanoString Expression Assay.

PMID:36327243 | DOI:10.1371/journal.pone.0277098

PLoS One. 2022 Nov 3;17(11):e0277103. doi: 10.1371/journal.pone.0277103. eCollection 2022.

ABSTRACT

OBJECTIVE: The medical history of injury given by parents of infants and toddlers with head trauma may not be accurate or completely true. The purpose of this study was to examine the relationship between subdural hematoma (SDH) due to nonaccidental injury and mechanisms of injury provided by caregivers.

METHODS: Our multicenter study group retrospectively reviewed the clinical records of children younger than 4 years with head trauma who have been diagnosed with any finding on head computed tomography (CT) and/or magnetic resonance imaging (MRI). A total of 84 cases of subdural hematomas with retinal findings, including cases reported to the child guidance center and traffic and birth injuries, were included in the study. They were classified by the mechanism of injury provided by the caregivers. Clinical findings were reviewed and classified into nonaccidental and accidental groups. The mechanisms of the injuries were examined by multivariable analysis to identify which ones were statistically associated with nonaccidental injuries.

RESULTS: Of the 84 patients with SDHs, 51 were classified into the nonaccidental group, and 33 children were classified into the accidental group. In 19 patients with a chief complaint of convulsion who had SDH but no episode of trauma, 18 were classified into the nonaccidental group. On multivariable analysis, unexplained convulsions (odds ratio: 12.04, 95% confidence interval: 1.44-100.49) were significantly associated with increased odds of nonaccidental injury.

CONCLUSIONS: In the present study, there was a relationship between nonaccidental injury and unexplained SDH with a chief complaint of convulsion.

PMID:36327242 | DOI:10.1371/journal.pone.0277103