Tag: statistics

J Perinat Med. 2022 Oct 3. doi: 10.1515/jpm-2022-0118. Online ahead of print.

ABSTRACT

OBJECTIVES: We conducted a systematic review and meta-analysis to quantitatively summarize the present data on the association of prenatally identified lateral placenta in singleton pregnancies with small for gestational age (SGA) neonates, preeclampsia and other perinatal outcomes.

METHODS: From inception to November 2021, we searched PubMed/Medline, Scopus and The Cochrane Library for papers comparing the risk of SGA and preeclampsia, as well as other perinatal outcomes in singleton pregnancies with a prenatally identified lateral placenta to those with non-lateral placentas. The revised Newcastle-Ottawa Scale was used to evaluate the quality of eligible papers. The I² test was employed to evaluate the heterogeneity of outcomes among the studies. To investigate the possibility of publication bias, funnel plots were constructed. Prospero RN: CRD42021251590.

RESULTS: The search yielded 5,420 articles, of which 16 were chosen, comprising of 15 cohort studies and one case control study with a total of 4,947 cases of lateral and 96,035 of non-lateral placenta (controls) reported. SGA neonates were more likely to be delivered in cases with a lateral placenta (OR: 1.74; 95% CI: 1.54-1.96; p<0.00001; I²=47%). Likewise, placental laterality was linked to a higher risk of fetal growth restriction (OR: 2.18; 95% CI: 1.54-3.06; p<0.00001; I2=0%), hypertensive disorders of pregnancy (OR: 2.39; 95% CI: 1.65-3.51; p=0.0001; I²=80%), preeclampsia (OR: 2.92; 95% CI: 1.92-4.44; p<0.0001; I²=82%) and preterm delivery (OR: 1.65; 95% CI: 1.46-1.87; p<0.00001; I²=0%).

CONCLUSIONS: The prenatal diagnosis of a lateral placenta appears to be associated with a higher incidence of preeclampsia, fetal growth restriction, preterm delivery and SGA. This may prove useful in screening for these conditions at the second trimester anomaly scan.

PMID:36174088 | DOI:10.1515/jpm-2022-0118

PLoS One. 2022 Sep 29;17(9):e0274581. doi: 10.1371/journal.pone.0274581. eCollection 2022.

ABSTRACT

BACKGROUND: Lumbo-sacral transitional vertebrae (LSTV) are one of the most common congenital variances of the spine. They are associated with an increased frequency of degeneration in the cranial adjacent segment. Hypermobility and concomitant increased loads are discussed as a possible reason for segmental degeneration. We therefore examined the lumbar and segmental motion distribution in patients with LSTV with flexion-extension radiographs.

METHODS: A retrospective study of 51 patients with osteochondrosis L5/S1 with flexion and extension radiographs was performed. Of these, 17 patients had LSTV and were matched 1:1 for age and sex with patients without LSTV out of the collective of the remaining 34 patients. The lumbar and segmental range of motion (RoM) by segmental lordosis angle and the segmental wedge angle were determined. Normal distribution of parameters was observed by Kolmogorov-Smirnov-test. Parametric data were compared by paired T-test. Non-parametric data were compared by Wilcoxon-rank-sum-test. Correlations were observed using Spearman’s Rank correlation coefficient. A p-value <0.05 was stated as statistically significant.

RESULTS: Patients with LSTV had mean age of 52.2±10.9, control group of 48.9±10.3. Both groups included 7 females and 10 males. Patients with LSTV presented with reduced RoM of the lumbar spine (LSTV 37.3°±19.2°, control 52.1°±20.5°, p = 0.065), however effects were statistically insignificant. LSTV significantly decreased segmental RoM in the transitional segment (LSTV 1.8°±2.7°, control 6.7°±6.0°, p = 0.003). Lumbar motion distribution differed significantly; while RoM was decreased in the transitional segment, (LSTV 5.7%, control 16.2%, p = 0.002), the distribution of lumbar motion to the cranial adjacent segment was increased (LSTV 30.7%, control 21.6%, p = 0.007).

CONCLUSION: Patients with LSTV show a reduced RoM in the transitional segment and a significantly increased motion distribution to the cranial adjacent segment in flexion-extension radiographs. The increased proportion of mobility in the cranial adjacent segment possibly explain the higher rates of degeneration within the segment.

PMID:36174065 | DOI:10.1371/journal.pone.0274581

PLoS One. 2022 Sep 29;17(9):e0274536. doi: 10.1371/journal.pone.0274536. eCollection 2022.

ABSTRACT

Attitudes toward aggression is a controversial phenomenon in psychiatry. This study examined and compared attitudes toward patient aggression in psychiatric hospitals from the perspectives of nurses, patients and informal caregivers and identified factors associated to these attitudes. A total of 2,424 participants completed a self-reported instrument regarding attitudes toward aggression (12-items Perception of Aggression Scale; POAS-S). We analysed data from nurses (n = 782), patients (n = 886), and informal caregivers (n = 765). Pearson’s r correlations were used to examine associations between variables. Differences between group scores were analysed using ANOVA/MANOVA with post-hoc Sheffe tests. Multivariate logistic regression models and logistic regression analysis were used to examine the effects of respondents’ characteristics on their attitudes toward aggression. Nurses had significantly more negative and less tolerant perceptions toward aggression (mean [SD] 47.1 [7.5], p<0.001) than the patients (mean [SD] 44.4 [8.2]) and the informal caregivers (mean [SD] 45.0 [6.9), according to the POAS-S total scores. The same trend was found with the dysfunction and function sub-scores (mean [SD] 25.3 [4.1] and 15.0 [3.6], respectively); the differences between the groups were statistically significant (p <0.001) when nurses’ scores were compared to those of both the patients (mean [SD] 23.7 [5.3] and 14.0 [4.1], respectively) and the informal caregivers (mean [SD] 24.4 [4.2] and 13.9 [3.5], respectively). The study offers new understanding of aggressive behavior in different treatment settings where attitudes toward patient behavior raises ethical and practical dilemmas. These results indicate a need for more targeted on-the-job training for nursing staff, aggression management rehabilitation programs for patients, and peer-support programs for informal caregivers focused on patient aggression.

PMID:36174064 | DOI:10.1371/journal.pone.0274536

PLoS One. 2022 Sep 29;17(9):e0275475. doi: 10.1371/journal.pone.0275475. eCollection 2022.

ABSTRACT

BACKGROUND: Globally, three fourth of neonatal deaths occur during the early neonatal period, this makes it a critical time to reduce the burden of neonatal death. The survival status of a newborn is determined by the individual (neonatal and maternal), and facility-level factors. Several studies were conducted in Ethiopia to assess early neonatal death; however, most of the studies had limited participants and did not well address the two main determinant factors covered in this study. In response to this gap, this study attempted to examine factors related to early neonatal death based on perinatal death surveillance data in consideration of all the possible determinants of early neonatal death.

METHODS: The national perinatal death surveillance data were used for this study. A total of 3814 reviewed perinatal deaths were included in the study. Bayesian multilevel parametric survival analysis was employed to identify factors affecting the survival of newborns during the early neonatal period. Adjusted time ratio (ATR) with 95% Bayesian credible intervals (CrI) was reported and log-likelihood was used for model comparison. Statistical significance was declared based on the non-inclusion of 1.0 in the 95% CrI.

RESULT: More than half (52.4%) of early neonatal deaths occurred within the first two days of birth. Per the final model, as gestational age increases by a week the risk of dying during the early neonatal period is reduced by 6% [ATR = 0.94,95%CrI:(0.93-0.96)]. There was an increased risk of death during the early neonatal period among neonates deceased due to birth injury as compared to neonates who died due to infection [ATR = 2.05,95%CrI:(1.30-3.32)]; however, perinates who died due to complication of an intrapartum event had a lower risk of death than perinates who died due to infection [ATR = 0.87,95%CrI:(0.83-0.90)]. As the score of delay one and delay three increases by one unit, the newborn’s likelihood of surviving during the early neonatal period is reduced by 4% [ATR = 1.04,95%CrI:(1.01-1.07)] and 21% [ATR = 1.21,95%CrI:(1.15-1.27)] respectively. Neonates born from mothers living in a rural area had a higher risk of dying during the early neonatal period than their counterparts living in an urban area [ATR = 3.53,95%CrI:(3.34-3.69)]. As compared to neonates treated in a primary health facility, being treated in secondary [ATR = 1.14,95%CrI:(1.02-1.27)] and tertiary level of care [ATR = 1.15,95%CrI:(1.04-1.25)] results in a higher risk of death during the early neonatal period.

CONCLUSION: The survival of a newborn during the early neonatal period is determined by both individual (gestational age, cause of death, and delay one) and facility (residence, type of health facility and delay three) level factors. Thus, to have a positive early neonatal outcome, a tailored intervention is needed for the three major causes of death (i.e Infection, birth injury, and complications of the intrapartum period). Furthermore, promoting maternal health, improving the health-seeking behaviour of mothers, strengthening facility readiness, and narrowing down inequalities in service provision are recommended to improve the newborn’s outcomes during the early neonatal period.

PMID:36174051 | DOI:10.1371/journal.pone.0275475

PLoS One. 2022 Sep 29;17(9):e0275260. doi: 10.1371/journal.pone.0275260. eCollection 2022.

ABSTRACT

Control charts are an amazing and essential statistical process control (SPC) instrument that is commonly used in monitoring systems to detect a specific defect in the procedure. The mixed Tukey modified exponentially weighted moving average – moving average control chart (MMEM-TCC) with motivation detection ability for fewer shifts in the process mean under symmetric and non-symmetric distributions is proposed in this paper. Average run length (ARL), standard deviation of run length (SDRL), and median run length (MRL) were used as efficiency criteria in the Monte Carlo simulation, and their efficiency was compared to existing control charts. Furthermore, the expected ARL (EARL) is a method for evaluating the performance of control charts beyond a specific range of shift sizes. The distinguishing feature of the proposed chart is that it performs efficiently in detecting small to moderate shifts. There are applications for PM 2.5 and PM 10 data that demonstrate the performance of the proposed chart.

PMID:36174049 | DOI:10.1371/journal.pone.0275260

PLoS One. 2022 Sep 29;17(9):e0275328. doi: 10.1371/journal.pone.0275328. eCollection 2022.

ABSTRACT

Despite the potential benefits of implicit measures over self-report measures, they are rarely used in real-world contexts to predict behavior. Two potential reasons are that (a) traditional implicit measures typically show low predictive validity and (b) the practical utility of implicit measures has hardly been investigated. The current studies test the practical utility of a new generation of implicit measures for predicting drunk driving. Study 1 (N = 290) examined whether an implicit measure of beliefs about past drunk driving (i.e., the Past Driving Under the Influence Implicit Association Test; P-DUI-IAT) retrospectively predicts drunk driving in driving school students, a population for which this measure could have applied value. Study 1 also explored whether P-DUI-IAT scores prospectively predicted drunk driving over six months. Due to the low number of offenders, however, Study 1 had low statistical power to test this latter question. In Study 2 (N = 228), we therefore examined the utility of the P-DUI-IAT and a new variant of this test (i.e., the Acceptability of Driving Under the Influence Implicit Association Test; A-DUI-IAT) to prospectively predict drunk driving in an online sample with a high number of offenders. Results from Study 1 show that the P-DUI-IAT predicts self-rated past drunk driving behavior in driving school students (ORs = 3.11-6.12, ps < .043, 95% CIs = [1.11, 37.69]). Results from Study 1 do not show evidence for utility of the P-DUI-IAT to prospectively predict self-rated drunk driving. Results from Study 2, on the other hand, show strong evidence for the utility of both implicit measures to prospectively predict self-rated drunk driving (ORs = 3.80-5.82, ps < .002, 95% CIs = [1.72, 14.47]). Although further applied research is necessary, the current results could provide a first step towards the application of implicit measures in real-world contexts.

PMID:36174048 | DOI:10.1371/journal.pone.0275328

PLoS One. 2022 Sep 29;17(9):e0274160. doi: 10.1371/journal.pone.0274160. eCollection 2022.

ABSTRACT

BACKGROUND AND OBJECTIVE: Use of insecticide treated nets (ITN), one of the most cost-effective malaria interventions contributes to malaria cases averted and reduction in child mortality. We explored the use of ITN in children under five (CU5) and children of school age to understand factors contributing to ITN use.

METHODS: A cross-sectional study analyzed 2018 Nigeria Demographic and Health Survey data. The outcome variable was CU5 or children of school age who slept under ITN the night before the survey. Independent variables include child sex, head of household’s sex, place of residence, state, household owning radio and television, number of household members, wealth quintile, years since ITN was obtained and level of malaria endemicity. Multi-level logistic regression model was used to access factors associated with ITN use among children.

RESULTS: In total, 32,087 CU5 and 54,692 children of school age were examined with 74.3% of CU5 and 57.8% of children of school age using ITN the night before the survey. While seven states had more than 80% of CU5 who used ITN, only one state had over 80% of school children who used ITN. ITN use in CU5 is associated with living in rural area (aOR = 1.20, 95% CI 1.14 to 1.26) and residing in meso endemic area (aOR = 3.1, 95% CI 2.89 to 3.54). While In children of school age, use of ITN was associated with female headed households (aOR = 1.14, 95% CI 1.09 to 1.19), meso (aOR = 3.17, 95% CI 2.89 to 3.47) and hyper (aOR = 14.9, 95% CI 12.99 to 17.07) endemic areas. Children residing in larger households were less likely to use ITN.

CONCLUSIONS: This study demonstrated increased use of ITN in CU5 from poor households and children living in rural and malaria endemic areas. Findings provide some policy recommendations for increasing ITN use in school children.

PMID:36174025 | DOI:10.1371/journal.pone.0274160

PLoS One. 2022 Sep 29;17(9):e0274573. doi: 10.1371/journal.pone.0274573. eCollection 2022.

ABSTRACT

BACKGROUND: Stillbirth and perinatal mortality issues continue to receive inadequate policy attention in Ghana despite government efforts maternal health care policy intervention over the years. The development has raised concerns as to whether Ghana can achieve the World Health Organization target of 12 per 1000 live births by the year 2030.

PURPOSE: In this study, we compared stillbirth and perinatal mortality between two groups of women who registered and benefitted from Ghana’s ‘free’ maternal health care policy and those who did not. We further explored the contextual factors of utilization of maternal health care under the ‘free’ policy to find explanation to the quantitative findings.

METHODS: The study adopted a mixed method approach, first using two rounds of Ghana Demographic and Health Survey data sets, 2008 and 2014 as baseline and end line respectively. We constructed outcome variables of stillbirth and perinatal mortality from the under 5 mortality variables (n = 487). We then analyzed for association using multiple logistics regression and checked for sensitivity and over dispersion using Poisson and negative binomial regression models, while adjusting for confounding. We also conducted 23 in-depth interviews and 8 focus group discussions for doctors, midwives and pregnant women and analyzed the contents of the transcripts thematically with verbatim quotes.

RESULTS: Stillbirth rate increased in 2014 by 2 per 1000 live births. On the other hand, perinatal mortality rate declined within the same period by 4 per 1000 live births. Newborns were 1.64 times more likely to be stillborn; aOR: 1.64; 95% [CI: 1.02, 2.65] and 2.04 times more likely to die before their 6th day of life; aOR: 2.04; 95% [CI: 1.28, 3.25] among the ‘free’ maternal health care policy group, compared to the no ‘free’ maternal health care policy group, and the differences were statistically significant, p< 0.041; p< 0.003, respectively. Routine medicines such as folic acid and multi-vitamins were intermittently in short supply forcing private purchase by pregnant women to augment their routine requirement. Also, pregnant women in labor took in local concoction as oxytocin, ostensibly to fast track the labor process and inadvertently leading to complications of uterine rapture thus, increasing the risk of stillbirths.

CONCLUSION: Even though perinatal mortality rate declined overall in 2014, the proportion of stillbirth and perinatal death is declining slowly despite the ‘free’ policy intervention. Shortage of medicine commodities, inadequate monitoring of labor process coupled with pregnant women intake of traditional herbs, perhaps explains the current rate of stillbirth and perinatal death.

PMID:36174023 | DOI:10.1371/journal.pone.0274573

PLoS One. 2022 Sep 29;17(9):e0273147. doi: 10.1371/journal.pone.0273147. eCollection 2022.

ABSTRACT

BACKGROUND: Ethiopia has low malaria prevalence compared to most other malaria-endemic countries in Africa. However, malaria is still a major public health problem in the country. The binary logistic regression model has been widely used to analyse malaria indicator survey (MIS) data. However, most MIS have a hierarchical structure which may result in dependent data. Since this model assumes that conditional on the covariates the malaria statuses of individuals are independent, it ignores potential intra-cluster correlation among observations within a cluster and may generate biased analysis results and conclusions. Therefore, the aim of this study was to quantify the variation in the prevalence of malaria between sample enumeration areas (SEAs) or clusters, the effects of cluster characteristics on the prevalence of malaria using the intra-class correlation coefficient as well as to identify significant factors that affect the prevalence of malaria using the multilevel logistic regression modelling in three major regions of Ethiopia, namely Amhara, Oromia and Southern Nations, Nationalities and Peoples’ (SNNP).

METHODS: Dataset for three regional states extracted from the 2011 Ethiopian National Malaria Indicator Surveys (EMIS) national representative samples was used in this study. It contains 9272 sample individuals selected from these regions. Various multilevel models with random sample SEA effects were applied taking into account the survey design weights. These weights are scaled to address unequal probabilities of selection within clusters. The spatial clustering of malaria prevalence was assessed applying Getis-Ord statistic to best linear unbiased prediction values of model random effects.

RESULTS: About 53.82 and 28.72 per cents of the sampled households in the study regions had no mosquito net and sprayed at least once within the last 12 months, respectively. The results of this study indicate that age, gender, household had mosquito nets, the dwelling has windows, source of drinking water, the two SEA-level variables, i.e. region and median altitude, were significantly related to the prevalence of malaria. After adjusting for these seven variables, about 45% of the residual variation in the prevalence of malaria in the study regions was due to systematic differences between SEAs, while the remaining 55% was due to unmeasured differences between persons or households. The estimated MOR, i.e. the unexplained SEA heterogeneity, was 4.784. This result suggests that there is high variation between SEAs in the prevalence of malaria. In addition, the 80% interval odds ratios (IORs) related to SEA-level variables contain one suggesting that the SEA variability is large in comparison with the effect of each of the variable.

CONCLUSIONS: The multilevel logistic regression with random effects model used in this paper identified five individual / household and two SEA-level risk factors of malaria infection. Therefore, the public health policy makers should pay attentions to those significant factors, such as improving the availability of pure drinking water. Further, the findings of spatial clustering provide information to health policymakers to plan geographically targeted interventions to control malaria transmission.

PMID:36174003 | DOI:10.1371/journal.pone.0273147

PLoS One. 2022 Sep 29;17(9):e0275472. doi: 10.1371/journal.pone.0275472. eCollection 2022.

ABSTRACT

Identifying differentially expressed genes is difficult because of the small number of available samples compared with the large number of genes. Conventional gene selection methods employing statistical tests have the critical problem of heavy dependence of P-values on sample size. Although the recently proposed principal component analysis (PCA) and tensor decomposition (TD)-based unsupervised feature extraction (FE) has often outperformed these statistical test-based methods, the reason why they worked so well is unclear. In this study, we aim to understand this reason in the context of projection pursuit (PP) that was proposed a long time ago to solve the problem of dimensions; we can relate the space spanned by singular value vectors with that spanned by the optimal cluster centroids obtained from K-means. Thus, the success of PCA- and TD-based unsupervised FE can be understood by this equivalence. In addition to this, empirical threshold adjusted P-values of 0.01 assuming the null hypothesis that singular value vectors attributed to genes obey the Gaussian distribution empirically corresponds to threshold-adjusted P-values of 0.1 when the null distribution is generated by gene order shuffling. For this purpose, we newly applied PP to the three data sets to which PCA and TD based unsupervised FE were previously applied; these data sets treated two topics, biomarker identification for kidney cancers (the first two) and the drug discovery for COVID-19 (the thrid one). Then we found the coincidence between PP and PCA or TD based unsupervised FE is pretty well. Shuffling procedures described above are also successfully applied to these three data sets. These findings thus rationalize the success of PCA- and TD-based unsupervised FE for the first time.

PMID:36173994 | DOI:10.1371/journal.pone.0275472