Nevin Manimala

Stat Med. 2022 Feb 10. doi: 10.1002/sim.9333. Online ahead of print.

ABSTRACT

A practical limitation of cluster randomized controlled trials (cRCTs) is that the number of available clusters may be small, resulting in an increased risk of baseline imbalance under simple randomization. Constrained randomization overcomes this issue by restricting the allocation to a subset of randomization schemes where sufficient overall covariate balance across comparison arms is achieved. However, for multi-arm cRCTs, several design and analysis issues pertaining to constrained randomization have not been fully investigated. Motivated by an ongoing multi-arm cRCT, we elaborate the method of constrained randomization and provide a comprehensive evaluation of the statistical properties of model-based and randomization-based tests under both simple and constrained randomization designs in multi-arm cRCTs, with varying combinations of design and analysis-based covariate adjustment strategies. In particular, as randomization-based tests have not been extensively studied in multi-arm cRCTs, we additionally develop most-powerful randomization tests under the linear mixed model framework for our comparisons. Our results indicate that under constrained randomization, both model-based and randomization-based analyses could gain power while preserving nominal type I error rate, given proper analysis-based adjustment for the baseline covariates. Randomization-based analyses, however, are more robust against violations of distributional assumptions. The choice of balance metrics and candidate set sizes and their implications on the testing of the pairwise and global hypotheses are also discussed. Finally, we caution against the design and analysis of multi-arm cRCTs with an extremely small number of clusters, due to insufficient degrees of freedom and the tendency to obtain an overly restricted randomization space.

PMID:35146788 | DOI:10.1002/sim.9333

Stat Med. 2022 Feb 10. doi: 10.1002/sim.9304. Online ahead of print.

ABSTRACT

Since its inception in 1969, the MSc in medical statistics program has placed a high priority on training students from Africa. In this article, we review how the program has shaped, and in turn been shaped by, two substantial capacity building initiatives: (a) a fellowship program, funded by the UK Medical Research Council, and run through the International Statistical Epidemiology Group at the LSHTM, and (b) the Sub-Saharan capacity building in Biostatistics (SSACAB) initiative, administered through the Developing Excellence in Leadership, Training and Science in Africa (DELTAS) program of the African Academy of Sciences. We reflect on the impact of both initiatives, and the implications for future work in this area.

PMID:35146786 | DOI:10.1002/sim.9304

J Med Virol. 2022 Feb 10. doi: 10.1002/jmv.27642. Online ahead of print.

ABSTRACT

OBJECTIVE: To understand the clinical characteristics of and analyze viral genes in patients with severe pneumonia due to [H1N1]pdm09 influenza virus in Guangzhou, 2019.

METHODS: The clinical data of 120 inpatients with laboratory-confirmed influenza A H1N1 virus from January to March 2019 were collected and analyzed. The subjects were diagnosed according to the criteria of the “Diagnosis and Treatment Program of Influenza A H1N1 (third Edition 2009)” issued by the Ministry of Health and were divided into severe and nonsevere groups. Serum samples during fever were collected for cytokine analysis, and the viral genes were analyzed after the virus cultured in MDCK cells. The data were analyzed by SPSS 16 software, and the results of gene sequencing were analyzed by MEGA 6 software.

RESULTS: Among the 120 inpatients, 36 (30%) were severe and 84 (70%) were nonsevere patients. The average age of severe patients was 53.11 ±19.94 years, the average age of nonsevere patients, at 44.03 ±24.47 years. There was no significant difference between the two groups (p< 0.05). There were significant differences in the rates of moist rales and dyspnea in critically ill patients (p< 0.05). There were significant differences in the white blood cell count (WBC), lactate dehydrogenase (LDH), creatine kinase (CK), serum creatinine (sCr), procalcitonin (PCT) and C-reactive protein (CRP) in severe patients with type A H1N1. Chest radiologic findings in severe patients showed ground glass shadows or pulmonary solid changes, and the difference was statistically significant for pulmonary fibrosis. Chronic lung disease (52.8%) and cardiovascular disease (27.8%) were independent risk factors for severe disease (p< 0.05). There were significant differences in secondary infections by Staphylococcus aureus (11.1%), pulmonary Aspergillus (22%) and Acinetobacter baumannii (16.7%) in critically ill patients (p< 0.05). Serum IL-8 in critically ill patients was significantly higher than those in nonsevere patients and healthy controls. The origin of virus strains in severe and nonsevere patients was the same, and there was no obvious mutation in the amino acid region of the antigenic site of the HA protein, but compared with the results of gene sequencing in previous years, the mutation sites showed a trend of annual accumulation. In conclusion, there was a high risk of severe pneumonia caused by H1N1 influenza A virus in Guangzhou in spring 2019. Long-term continuous surveillance, prevention and control of the virus should be carried out to predict its epidemiology and distribution. This article is protected by copyright. All rights reserved.

PMID:35146773 | DOI:10.1002/jmv.27642

Fam Process. 2022 Feb 11. doi: 10.1111/famp.12756. Online ahead of print.

ABSTRACT

The field of relationship science has called for more research on the impact of relationship education on child outcomes, yet studies in this area remain sparse, particularly regarding maternal and infant health at birth. Research on group prenatal care demonstrates that individual-oriented group interventions have a positive impact on infant birth outcomes, suggesting the need to consider the impacts of other forms of group programming for women. The current study examined the impact of MotherWise, an individual-oriented relationship education and brief case management/coaching program for minority and low-income pregnant women, on birth outcomes. The study sample included 136 women who enrolled in a larger randomized controlled trial of MotherWise during early pregnancy. Although statistical power was limited due to the sample size and the effects were not outright significant at p < 0.05, results indicated that the effects of MotherWise on birth outcomes were small to moderate in size (0.23 for birthweight, 0.46 for preterm birth) and suggest important avenues for future tests of relationship education programs and their impacts on maternal and infant health. The current study suggests that relationship education during pregnancy could directly impact women’s and infant’s health.

PMID:35146754 | DOI:10.1111/famp.12756

Biometrics. 2022 Feb 11. doi: 10.1111/biom.13633. Online ahead of print.

ABSTRACT

An estimated quadratic inference function method is proposed for correlated failure time data with auxiliary covariates. The proposed method makes efficient use of the auxiliary information for the incomplete exposure covariates, and preserves the property of the quadratic inference function method that requires the covariates to be completely observed. It can improve the estimation efficiency and easily deal with the situation when the cluster size is large. The proposed estimator which minimizes the estimated quadratic inference function is shown to be consistent and asymptotically normal. A chi-squared test based on the estimated quadratic inference function is proposed to test hypotheses about the regression parameters. The small-sample performance of the proposed method is investigated through extensive simulation studies. The proposed method is then applied to analyze the SOLVD data as an illustration. This article is protected by copyright. All rights reserved.

PMID:35146750 | DOI:10.1111/biom.13633

Int Marit Health. 2021;72(4):259-267. doi: 10.5603/IMH.2021.0050.

ABSTRACT

BACKGROUND: The primary aim of this study was to reveal whether the Gendarmerie Coast Guard Academy (GCGA) students caught and went through the coronavirus disease 2019 (COVID-19) according to their physical activity levels during the COVID-19 pandemic process.

MATERIALS AND METHODS: The research group of the study consisted of 332 volunteer male students studying at the GCGA. International Physical Activity Questionnaire-Short Form (IPAQ-SF) and personal information form were used as data collection tools in the study. The data obtained from the questionnaires were analysed in the Jamovi 1.8.2 statistical software programme with a 95% confidence interval and a 5% margin of error. In the analysis of data, non-parametric correlation test was used for pairwise comparisons and Multinomial and Binomial Logistic Regression test was used for comparisons of subcategories.

RESULTS: According to students’ body mass index scores, 73.49% of the students were of normal weight. The results of the analysis, showed that 29.82% of the GCGA students had COVID-19, and 70.18% of them did not have COVID-19. It was determined that 91.92% of those who had COVID-19 had mild illness and recovered at home. According to the metabolic equivalence classification of students, a negative and significant relationship between students’ physical activity levels (inactive < minimally active < very active) and the risk of getting the positive results for COVID-19 (yes < no) and the severity of COVID-19 (in intensive care < in the hospital < mildly at home) was found.

CONCLUSIONS: It could be said that increasing the physical activity level of students can reduce the possibility of having COVID-19 and also increase the probability of mild illness not requiring hospitalisation in those with positive COVID-19 test result.

PMID:35146742 | DOI:10.5603/IMH.2021.0050

Biol Trace Elem Res. 2022 Feb 11. doi: 10.1007/s12011-021-02892-y. Online ahead of print.

ABSTRACT

The level of heavy metals in vegetables grown in soil irrigated with various sources of water and the health risks associated with the consumption of these vegetables were assessed in this study. Samples of water, soil, and vegetables were collected from farmer fields. After digestion in acidic solution, analytical measurements were made using an atomic absorption spectrophotometer. The mean concentration of Pb, Cr, Cd, Cu, Zn, Ni, Fe, and Mn in the soil of two sampling area were in the range from 60.00 to 84.00 mg kg^-1, 68.00 to 98.00 mg kg^-1, 1.60 to 2.60 mg kg^-1, 26.10 to 33.20 mg kg^-1, 22.60 to 30.80 mg kg^-1, 50.10 to 78.30 mg kg^-1, 420.00 to 471.00 mg kg^-1, and 270.20 to 340.50 mg kg^-1, respectively. Heavy metals in soil varied significantly at (P ≤ 0.001) among sampling area. The nine heavy metals were divided into two clusters for wastewater and soil, according to cluster analysis. The number of variables was reduced using principal component analysis, which yielded three latent factors, one for wastewater and one for soil. Pb, Cr, Cd, Cu, Zn, Ni, Fe, and Mn concentrations were significantly higher at P ≤ 0.001 in nine vegetables grown on soil irrigated with untreated wastewater than in vegetables grown on fresh-tube well-water-irrigated soil. The health risks associated with metal intake were assessed using the estimated daily intake of metals (EDIM), hazard quotients (HQs), and hazard index (HI). The rates of metal transfer to vegetables have been determined. Except for Pb and Cd, all of the elements’ EDMI values were found to be lower than their RfD values. The corresponding HRI values of metals in the various vegetables were found to be below 1, implying that vegetable consumption in the studied region poses no carcinogenic risk. Constant determination of heavy metals in all fruits and vegetables is essential for the assessment of health risks associated with dietary metal exposure. The study has provided valuable information to the general public about the use of wastewater for irrigation of vegetables.

PMID:35146633 | DOI:10.1007/s12011-021-02892-y

J Digit Imaging. 2022 Feb 10. doi: 10.1007/s10278-022-00588-w. Online ahead of print.

ABSTRACT

Previous studies have demonstrated a frequent occurrence of screw/K-wire malpositioning during surgical fracture treatment under 2D fluoroscopy and a correspondingly high revision rate as a result of using intraoperative 3D imaging. In order to facilitate and accelerate the diagnosis of implant malpositioning in 3D data sets, this study investigates two versions of an implant detection software for mobile 3D C-arms in terms of their detection performance based on comparison with manual evaluation. The 3D data sets of patients who had received surgical fracture treatment at five anatomical regions were extracted from the research database. First, manual evaluation of the data sets was performed, and the number of implanted implants was assessed. For 25 data sets, the time required by four investigators to adjust each implant was monitored. Subsequently, the evaluation was performed using both software versions based on the following detection parameters: true-positive-rate, false-negative-rate, false-detection-rate and positive predictive value. Furthermore, the causes of false positive and false negative detected implants depending on the anatomical region were investigated. Two hundred fourteen data sets with overall 1767 implants were included. The detection parameters were significantly improved (p<.001) from version 1 to version 2 of the implant detection software. Automatic evaluation required an average of 4.1±0.4 s while manual evaluation was completed in 136.15±72.9 s (p<.001), with a statistically significant difference between experienced and inexperienced users (p=.005). In summary, version 2 of the implant detection software achieved significantly better results. The time saved by using the software could contribute to optimizing the intraoperative workflow.

PMID:35146612 | DOI:10.1007/s10278-022-00588-w

Pharm Res. 2022 Feb 10. doi: 10.1007/s11095-022-03175-4. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate a three-compartmental semi-physiological model for analysis of uptake clearance and efflux from brain tissue of the hydrophilic markers sucrose and mannitol, compared to non-compartmental techniques presuming unidirectional uptake.

METHODS: Stable isotope-labeled [¹³C]sucrose and [¹³C]mannitol (10 mg/kg each) were injected as IV bolus into the tail vein of awake young adult mice. Blood and brain samples were taken after different time intervals up to 8 h. Plasma and brain concentrations were quantified by UPLC-MS/MS. Brain uptake clearance (K_in) was analyzed using either the single-time point analysis, the multiple time point graphical method, or by fitting the parameters of a three-compartmental model that allows for symmetrical exchange across the blood-brain barrier and an additional brain efflux clearance.

RESULTS: The three-compartment model was able to describe the experimental data well, yielding estimates for K_in of sucrose and mannitol of 0.068 ± 0.005 and 0.146 ± 0.020 μl.min^-1.g^-1, respectively, which were significantly different (p < 0.01). The separate brain efflux clearance had values of 0.693 ± 0.106 (sucrose) and 0.881 ± 0.20 (mannitol) μl.min^-1.g^-1, which were not statistically different. K_in values obtained by single time point and multiple time point analyses were dependent on the terminal sampling time and showed declining values for later time points.

CONCLUSIONS: Using the three-compartment model allows determination of K_in for small molecule hydrophilic markers with low blood-brain barrier permeability. It also provides, for the first time, an estimate of brain efflux after systemic administration of a marker, which likely represents bulk flow clearance from brain tissue.

PMID:35146590 | DOI:10.1007/s11095-022-03175-4

Environ Monit Assess. 2022 Feb 10;194(3):168. doi: 10.1007/s10661-022-09843-7.

ABSTRACT

How and to which extent terrain factors affecting the drainage area threshold (DAT) are disputable. This paper uses principal component analysis (PCA) and correlation analysis to study the influence degree of terrain factors on DAT. Firstly, 22 watersheds, locating in the severe soil erosion region (SSER) of Loess Plateau of China, are picked out as the example areas. The purpose of the mean change point method (MCP) to detect the relationship between DAT and gully density (GD) is to get a reasonable DAT. Secondly, nine terrain factors are calculated, and their statistical values are compared and put in the matrix to clear the different effects on DAT. Finally, the effects of statistical eigenvalues of terrain factors on DAT are compared with PCA and the correlation analysis. According to the PCA, the nine terrain factors are summarized into three principal components, which are slope, height variation, and relief factor. By calculating the score weighted by each factor coefficient matrix and eigenvalue, the result states that slope (S), terrain curvatures (K), and surface roughness (SR) are the factors that have great influence on DAT. Meanwhile, the results of correlation analysis indicate that S, SR, and K have exerted a great influence on the DAT, and the significance level was above 0.05. Both the results of PCA and correlation analysis make clear that the slope is the most direct and influential factor affecting DAT, while other factors are more or less related to slope directly and indirectly. The result implies that the vertical variation of terrain has a strong correlation with the slope, and also has a great influence on DAT. This research not only would be of great significance to recognize the mechanism of gully development, but also able to provide a scientific reference for soil and water conservation in the Loess Plateau.

PMID:35146588 | DOI:10.1007/s10661-022-09843-7