Nevin Manimala

Cad Saude Publica. 2022 Jan 7;38(1):e00037021. doi: 10.1590/0102-311X00037021. eCollection 2022.

ABSTRACT

The objective of this study was to analyze factors associated with cases of congenital anomalies from the perspective of social determinants of health in the State of Rio Grande do Sul, Brazil. This is a case-control study with all the pairs of mothers and liveborn infants from 2012 to 2015 in the state, based on the total number of liveborn infants with congenital anomalies (5,250) and a random sample of 21,000 without congenital anomalies, according to data on the live birth certificates. The statistical analyses included chi-square tests and logistic regression models with SPSS. The Dahlgren & Whitehead model was used as the basis for grouping and discussing the variables. In the multivariate model, all the variables that were significantly associated with the outcome were in the sense of increasing the odds of births with congenital anomalies: black women had 20% higher odds than white women (OR = 1.20; p-value = 0.013); age over 40 years increased the odds by 97% when compared to women 18 to 29 years of age; women with less than four years of schooling showed 50% higher odds when compared to women with 12 or more years of schooling (OR = 1.50; p-value = 0.001); women with no prenatal visits had 97% higher odds than women with seven or more prenatal visits (OR = 1.97; p-value = 0.001); and prior history of miscarriages/stillbirths increased the odds by 17% (OR = 1.17; p-value = 0.001). The results raise the issue of racial and social inequalities, related to health inequities.

PMID:35081200 | DOI:10.1590/0102-311X00037021

R I Med J (2013). 2022 Feb 1;105(1):37-41.

ABSTRACT

BACKGROUND: During the initial wave of the COVID-19, there was uncertainty related to whether the pandemic would affect pregnancy delivery outcomes. We sought to identify whether changes in hospital policies and provider practices, driven by COVID-19, would influence delivery outcomes in nulliparous, term, singleton, vertex (NTSV) pregnancies in Rhode Island.

OBJECTIVE: We compare the delivery outcomes and associated factors for NTSV deliveries during the first wave of the COVID-19 pandemic in Rhode Island compared to patients who delivered the year prior.

STUDY DESIGN: This is a retrospective cohort study of patients who presented to Women & Infants Hospital for NTSV deliveries during April 2019, pre-COVID-19, and April 2020, during COVID-19.

RESULTS: During COVID-19, patients were more likely to have abnormal electronic fetal monitoring (AEFM) as an indication for cesarean section (p<.02) and less likely to have an elective cesarean delivery (p<.01). Patients during COVID-19 were more likely to have a midwife involved in their care compared to pre-COVID-19 (p<.001). The cesarean section rate was not statistically different between the two time periods.

CONCLUSION: Those delivering during the pandemic were more likely to have AEFM as an indication for cesarean delivery and less likely to have elective cesareans. They were more likely to have a midwife involved in their care. Further investigation into factors associated with changes in NTSV cesarean rates is warranted.

PMID:35081187

PLoS One. 2022 Jan 26;17(1):e0263015. doi: 10.1371/journal.pone.0263015. eCollection 2022.

ABSTRACT

Problem-based learning (PBL) allows students to learn medical statistics through problem solving experience. The aim of this study was to assess the efficiency of PBL modules implemented in the blended learning courses in medical statistics through knowledge outcomes and student satisfaction. The pilot study was designed as a randomized controlled trial that included 53 medical students who had completed all course activities. The students were randomized in two groups: the group with access to PBL modules within the blended learning course (hPBL group) and the group without access to PBL modules-only blended learning course (BL group). There were no significant differences between the groups concerning socio-demographic characteristics, previous academic success and modality of access to course materials. Students from hPBL group had a significantly higher problem solving score (p = 0.012; effect size 0.69) and the total medical statistics score (p = 0,046; effect size 0.57). Multivariate regression analysis with problem solving as an outcome variable showed that problem solving was associated with being in hPBL group (p = 0.010) and having higher grade point average (p = 0.037). Multivariate regression analysis with the medical statistics score as an outcome variable showed the association between a higher score on medical statistics with access to PBL modules (p = 0.045) and a higher grade point average (p = 0.021). All students in hPBL group (100.0%) considered PBL modules useful for learning medical statistics. PBL modules can be easily implemented in the existing courses within medical statistics using the Moodle platform, they have high applicability and can complement, but not replace other forms of teaching. These modules were shown to be efficient in learning, to be well accepted among students and to be a potential missing link between teaching and learning medical statistics. The authors of this study are planning to create PBL modules for advanced courses in medical statistics and to conduct this study on other universities with a more representative study sample, with the aim to overcome the limitations of the existing study and confirm its results.

PMID:35081161 | DOI:10.1371/journal.pone.0263015

PLoS One. 2022 Jan 26;17(1):e0262387. doi: 10.1371/journal.pone.0262387. eCollection 2022.

ABSTRACT

OBJECTIVE: To evaluate the association between transvaginal ultrasound scan of cervix and Bishop’s score in predicting successful induction of labour, cut-off points and patients’ tolerability and acceptance for both procedures.

DESIGN: A comparative clinical trial.

SETTING: A tertiary hospital in Selangor, Malaysia.

PARTICIPANTS: 294 women planned for elective induction of labour for various indications were included. All women had transvaginal ultrasound to assess the cervical length and digital vaginal examination to assess the Bishop cervical scoring by separate investigators before induction of labour.

PRIMARY OUTCOME MEASURE: To evaluate the association of the cervical length by transvaginal ultrasound scan and Bishop score in predicting successful induction of labour.

SECONDARY OUTCOME MEASURE: Variables associated with successful induction of labour and patients’ tolerability and acceptance for transvaginal ultrasound scan of cervix.

RESULTS: There was no statistically significant difference among the vaginal and Caesarean delivery groups in terms of mean maternal age, height, weight, body mass index, ethnicity and gestational age at induction. Vaginal delivery occurred in 207 women (70.4%) and 87 women (29.6%) delivered via Caesarean section. There was a high degree of correlation between the cervical length and Bishop score (r-value 0.745; p <0.001). Sonographic assessment of cervical length demonstrated a comparable accuracy in comparison to Bishop score. Analysis using ROC curves noted an optimal cut-off value of ≤27mm for cervical length and Bishop score of ≥ 4, with a sensitivity of 69.1% vs 67%, specificity 60.9% vs 55%, and area under the curves (AUCs) of 0.672 and 0.643 respectively (p <0.001). Multivariate logistic regression analysis demonstrated that parity (OR 2.70), cervical length (OR 0.925), Bishop score (OR 1.272) and presence of funnelling (OR 3.292) were highly significant as independent predictors of success labour induction. Women also expressed significantly less discomfort with transvaginal ultrasound compared with digital vaginal examination.

CONCLUSION: Sonographic assessment of cervical measurement predicts the success of induction of labour with similar diagnostic accuracy with conventional Bishop score.

PMID:35081157 | DOI:10.1371/journal.pone.0262387

PLoS One. 2022 Jan 26;17(1):e0262908. doi: 10.1371/journal.pone.0262908. eCollection 2022.

ABSTRACT

OBJECTIVE: The aim of this retrospective observational study is to analyse clinical, serological and radiological predictors of outcome in patients with COVID-19 pneumonia treated with tocilizumab, providing clinical guidance to its use in real-life.

METHOD: This is a retrospective, monocentric observational cohort study. All consecutive patients hospitalized between February the 11th and April 14th 2020 for severe COVID-19 pneumonia at Reggio Emilia AUSL and treated with tocilizumab were enrolled. The patient’s clinical status was recorded every day using the WHO ordinal scale for clinical improvement. Response to treatment was defined as an improvement of one point (from the status at the beginning of tocilizumab treatment) during the follow-up on this scale. Bivariate association of main patients’ characteristics with outcomes was explored by descriptive statistics and Fisher or Kruskal Wallis tests (respectively for qualitative or quantitative variables). Each clinically significant predictor was checked by a loglikelihood ratio test (in univariate logistic models for each of the considered outcomes) against the null model.

RESULTS: A total of 173 patients were included. Only hypertension, the use of angiotensin-converting enzyme inhibitors, PaO2/FiO2, respiratory rate and C-reactive protein were selected for the multivariate analysis. In the multivariable model, none of them was significantly associated with response.

CONCLUSIONS: Evaluating a large number of clinical variables, our study did not find new predictors of outcome in COVID19 patients treated with tocilizumab. Further studies are needed to investigate the use of tocilizumab in COVID-19 and to better identify clinical phenotypes which could benefit from this treatment.

PMID:35081151 | DOI:10.1371/journal.pone.0262908

PLoS One. 2022 Jan 26;17(1):e0262607. doi: 10.1371/journal.pone.0262607. eCollection 2022.

ABSTRACT

Despite advancements in the study of brain maturation at different developmental epochs, no work has linked the significant neural changes occurring just after birth to the subtler refinements in the brain occurring in childhood and adolescence. We aimed to provide a comprehensive picture regarding foundational neurodevelopment and examine systematic differences by family income. Using a nationally representative longitudinal sample of 486 infants, children, and adolescents (age 5 months to 20 years) from the NIH MRI Study of Normal Brain Development and leveraging advances in statistical modeling, we mapped developmental trajectories for the four major cortical lobes and constructed charts that show the statistical distribution of gray matter and reveal the considerable variability in regional volumes and structural change, even among healthy, typically developing children. Further, the data reveal that significant structural differences in gray matter development for children living in or near poverty, first detected during childhood (age 2.5-6.5 years), evolve throughout adolescence.

PMID:35081147 | DOI:10.1371/journal.pone.0262607

PLoS One. 2022 Jan 26;17(1):e0262749. doi: 10.1371/journal.pone.0262749. eCollection 2022.

ABSTRACT

Falls are a major issue for bipeds. For elderly adults, falls can have a negative impact on their quality of life and lead to increased medical costs. Fortunately, interventional methods are effective at reducing falls assuming they are prescribed. For biped robots, falls prevent them from completing required tasks. Thus, it is important to understand what aspects of gait increase fall risk. Gait variability may be associated with increased fall risk; however, previous studies have not investigated the variation in the movement of the legs. The purpose of this study was to determine the effect of joint angle variability on falling to determine which component(s) of variability were statistically significant. In order to investigate joint angle variability, a physics-based simulation model that captured joint angle variability as a function of time through Fourier series was used. This allowed the magnitude, the frequency mean, and the frequency standard deviation of the variability to be altered. For the values tested, results indicated that the magnitude of the variability had the most significant impact on falling, and specifically that the stance knee flexion variability magnitude was the most significant factor. This suggests that increasing the joint variability magnitude may increase fall risk, particularly if the controller is not able to actively compensate. Altering the variability frequency had little to no effect on falling.

PMID:35081142 | DOI:10.1371/journal.pone.0262749

PLoS One. 2022 Jan 26;17(1):e0262055. doi: 10.1371/journal.pone.0262055. eCollection 2022.

ABSTRACT

Many methodologies are used to predict the genetic merit in animals and plants, but some of them require priori assumptions that may increase the complexity of the model. Artificial neural network (ANN) has advantage to not require priori assumptions about the relationships between inputs and the output allowing great flexibility to handle different types of complex non-additive effects, such as dominance and epistasis. Despite this advantage, the biological interpretability of ANNs is still limited. The aim of this research was to estimate the heritability and markers effects for two traits in Coffea canephora using an additive-dominance architecture ANN and to compare it with genomic best linear unbiased prediction (GBLUP). The data used consists of 51 clones of C. canephora varietal Conilon, 32 of varietal group Robusta and 82 intervarietal hybrids. From this, 165 phenotyped individuals were genotyped for 14,387 SNPs. Due to the high computational cost of ANNs, we used Bagging decision tree to reduce the dimensionality of the data, selecting the markers that accumulated 70% of the total importance. An ANN with three hidden layers was run, each varying from 1 to 40 neurons summing 64,000 neural networks. The network architectures with the best predictive ability were selected. The best architectures were composed by 4, 15, and 33 neurons in the first, second and third hidden layers, respectively, for yield, and by 13, 20, and 24 neurons, respectively for rust resistance. The predictive ability was greater when using ANN with three hidden layers than using one hidden layer and GBLUP, with 0.72 and 0.88 for yield and coffee leaf rust resistance, respectively. The concordance rate (CR) of the 10% larger markers effects among the methods varied between 10% and 13.8%, for additive effects and between 5.4% and 11.9% for dominance effects. The narrow-sense ([Formula: see text]) and dominance-only ([Formula: see text]) heritability estimates were 0.25 and 0.06, respectively, for yield, and 0.67 and 0.03, respectively for rust resistance. The ANN was able to estimate the heritabilities from an additive-dominance genomic architectures and the ANN with three hidden layers obtained best predictive ability when compared with those obtained from GBLUP and ANN with one hidden layer.

PMID:35081139 | DOI:10.1371/journal.pone.0262055

Se Pu. 2022 Feb 8;40(2):123-129. doi: 10.3724/SP.J.1123.2021.04016.

ABSTRACT

Osteonecrosis of the femoral head (ONFH) can lead to its collapse which requires total hip arthroplasty. Exosomes, which are important for intercellular communication are involved in a series of physiological and pathological processes, and therefore play a unique role in disease diagnosis and treatment. In this study, untargeted metabolomics was used to investigate the metabolic characteristics of lipids in exosomes of femoral head tissue with osteonecrosis and to explain the metabolic changes that occur in the body during this disease. Ultracentrifugation was used to separate and enrich exosomes from femoral head tissue with osteonecrosis. Exosomes were identified using dynamic light scattering (DLS), Western blotting, and transmission electron microscopy (TEM). Gradient elution was performed with ultrapure water and acetonitrile as mobile phases using a Kinetex XB-C18 column (100 mm×2.1 mm, 2.6 μm). The column oven temperature, flow rate of the mobile phase, and duration were 30 ℃, 300 μL/min, and 15 min, respectively. A triple TOF 4600 high resolution mass spectrometry system was used, and the mass scan range of m/z was set at 100 -1000. Other conditions were as follows: sheath gas, 380 kPa; auxiliary gas, 380 kPa; curtain gas, 170 kPa; and atomization temperature, 600 ℃. Ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) combined with multivariate statistical analysis was used to identify the lipid metabolic profile of ONFH-derived exosomes. The exosome metabolites were characterized in detail, which enables their identification and provided a reliable method for quality evaluation. After transforming the obtained original data using MarkView software, peak identification, peak alignment, subtraction of solvent peak, impurity peak, noise filtering, and other treatments, a three-dimensional matrix was obtained from the exported data table. Principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) in the SIMCA-P14.1 software were used for multivariate statistical analysis of differentially expressed exosome lipid metabolites. This strategy was validated using lipid metabolites from patients with ONFH and healthy controls. The correlation distribution was shown according to the point dispersion of the PCA score plot, and lipid metabolites from the same disease showed ideal clustering. This result indicates a small difference between the groups. A good clustering effect is also obtained using OPLS-DA, and the statistical model has high reliability. A total of 18 significantly altered lipid metabolites were detected in the exosomes, including acrylolipids, fatty acid esters, glycerides, and their derivatives. The pathway analysis was conducted with MetaboAnalyst (https://www.metaboanalyst.ca/) via database source including the HMDB (http://www.hmdb.ca/) and MMCD (http://mmcd.nmrfam.wisc.edu/) for confirming the impacted metabolic pathways and visualization. Metabolic pathway analysis showed that glycerophospholipid and sphingolipid metabolism were the most significantly altered in exosomes. An imbalance between sphingolipids and glycerophospholipids leads to lipotoxic damage, which is implicated in the pathophysiology of common metabolic diseases. Furthermore, glycerophospholipids are correlated with cell proliferation, differentiation, and apoptosis, and the change in glycerophospholipid ratio can reflect the disturbance in lipid metabolism. The metabolic changes in exosomes may reflect the metabolic changes in ONFH. In this study, lipid metabolomics analysis based on UPLC-MS/MS was used to determine metabolic differences between exosomes extracted from ONFN and femoral neck fracture (FNF). Metabolomic analysis of necrotic femoral head tissue-derived exosomes can help explore the most relevant pathways for assessing the changes in exosome metabolism that affect exosome metabolism in necrotic bone tissue.

PMID:35080158 | DOI:10.3724/SP.J.1123.2021.04016

Vet Med Sci. 2022 Jan 26. doi: 10.1002/vms3.740. Online ahead of print.

ABSTRACT

BACKGROUND: A cross-sectional survey study was conducted from September 2020 to April 2021. A total of 217 households were randomly selected. The data collection instruments were structured questionnaires: focus group discussion and key informant interviews. Data were coded, entered and analyzed using Statistical Package for the Social Sciences (SPSS) version 20 software. Ranking indexes as well as binary logistic regression analysis were used to look for the relationship between dependent and independent variables.

RESULT: The present study showed that season of calving, disease and parasite challenges, housing conditions and shortage of land for forage production with an index value of 0.180, 0.154, 0.153 and 0.126, respectively, were the most important constraints affecting milk production potential. Likewise, foot and mouth disease [adjusted odds ratio (AOR) = 0.001, 95% confidence interval (CI) = (0.000-0.016)], internal parasites [AOR = 0.003, 95% CI = (0.000-0.046)], shortage of grazing land [AOR = 0.017, 95% CI = (0.002-0.148)], summer season of calving [AOR = 0.012, 95% CI = (0.002-0.088)], overall cattle herd composition [AOR = 0.002, 95% CI = (0.000-0.025)], straw shed [AOR = 0.046, 95% CI = (0.006-0.327)] and open yard [AOR = 0.003, 95% CI = (0.000-0.183)] housing conditions were significantly associated with milk production status at p < 0.001 and p < 0.05.

CONCLUSION: The current study indicated that milk production status was poor. Therefore, suitable government policy support and provision of subsidies, genuine participation of dairy producers with governmental and non-governmental organizations are imperative to improve livestock productivity. Furthermore, future research and development actions should find solutions to decrease the bottlenecks so that the massive potentials of the area could be exploited to its maximum and could advance the livelihood of the community.

PMID:35080133 | DOI:10.1002/vms3.740